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GOOD AFTERNOON, GOOD MORNING,

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GOOD EVENING WHEREVER YOU ARE

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WATCHING US FROM.

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THANK YOU SO MUCH FOR YOINS US

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FOR THIS SCIENTIFIC WORKFORCE

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DIVERSITY SEMINAR ON HOW DIVERSE

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PERSPECTIVES ENHANCED DATA

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SCIENCE OUTCOMES.

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I AM MARIE BERNARD NIH CHIEF

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SCIENTIFIC OFFICER FOR WORKFORCE

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DIVERSITY AND VERY HAPPY TO

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WELCOME YOU TO THIS EVENT.

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NEXT SLIDE ISSUES PLEASE.

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TODAY WE HAVE A STAR STUDDED

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CAST OF SPEAKERS, DR. JENNIFER

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COUCH, WHO'S THE CHIEF OF THE

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DIVISION OF CANCER BIOLOGY AT

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THE NATIONAL CANCER INSTITUTE.

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DR. SAMSON GEBREAB, PROGRAM

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LEGAL FOR THE AIM-AHEAD PROGRAM.

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AND DR. MANU PLATT, DIRECTOR FOR

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THE TRUSTEES FOR BIOMEDICAL

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ENGINEERING TECHNOLOGY

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ACCELERATION AND ASSOCIATION

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DIRECTOR FOR SCIENTIFIC

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DIVERSITY EQUITY AND INCLUSION

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AT THE NATIONAL INSTITUTE OF

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BIOMEDICAL IMAGES AND

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BIOENGINEERING.

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I WILL PROVIDE MORE ABOUT THEIR

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BACKGROUNDS LATER, BUT THEY ARE

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THE BEST PEOPLE TO PRESENT OUR

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VOW POINT ON THIS ISSUE.

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NEXT SLIDE.

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A FOURTH APPEARANCE HOUSEKEEPING

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ITEMS, QUESTIONS THAT OFTEN COME

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UP, DO YOU WANT A COPY OF THIS

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PRESENTATION?

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GO TO OUR WEBSITE

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DIVERSITY.NIH.GOV WHERE SPEAKER

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SLIDES ARE AVAILABLE AND 508

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COMPLIANT.

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DO YOU WANT A RECORDING OF THIS

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EVENT, IT WILL BE POSTED ON THE

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WEBSITE WITHIN THE NEXT FEW

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BUSINESS DAYS.

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AS YOU GO IN THERE, YOU WILL SEE

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THAT THERE ARE RECORDING FROM

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OTHER MULTIPLE SEMINARS AS WELL.

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DO YOU HAVE QUESTIONS IN YOU CAN

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LEVERAGE THE Q&A FEATURE IN
THE

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TOOL BAR TO SUBMIT YOUR

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QUESTIONS, SO IT'S A Q&A

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FEATURE, NOT THE CHAT FEATURE

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AND IF YOU HAVE A NEED FOR

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TECHNICAL SUPPORT, PLEASE E-MAIL

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ARYANA.GOINSAT AT ICFNEXT.COM.

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NEXT SLIDE.

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SO THIS IS THE START OF OUR

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25-26 SWDSS SEASON.

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THE 23-24 SEASON HAD 3 REALLY

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OUTSTANDING PRESENTATIONS, HOW

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TO RESEARCH ACTIVE INSTITUTIONS

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IMPACT THE DIVERSITY OF THE

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SCIENTIFIC WORKFORCE, HOW DOES

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DIVERSITY IMPACT INNOVATION IN

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TEAM SCIENCE, HOW ARE

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INSTITUTIONS TRANSFORMED TO

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FOSTER CULTURES OF INCLUSIVE

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EXCELLENCE?

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YOU CAN USE THE QR CODE IN THE

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CORNER HERE TO FIND THE

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RECORDINGS, SLIDES, PROCEEDINGS

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FOR ALL EXCEPT THE JUNE MEETING,

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PROCEEDINGS FOR THE JUNE MEETING

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WILL BE COMING SHORTLY AND AS I

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SAID, THIS IS -- WE'VE BEEN DO

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THANKSGIVING A BIT OF TIME NOW,

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THERE ARE A TOTAL OF 10 OF THESE

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SEMINARS OVER THE YEARS SO YOU

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MIGHT WANT TO LOOK BACK AND SEE

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SOME OF THE OTHERS, IF YOU UPON

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DON'T WANT TO USE THE QR CODE,

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YOU CAN GO TO DIVERSITY.NIH.GOV.

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NEXT SLIDE.

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AND COMING SOON AS PART OF THIS

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FISCAL YEAR 25 INITIATIVE, HOW

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CAN RESEARCH ACTIVE INSTITUTIONS

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ENHANCE THEIR RESEARCH CAPACITY?

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THAT'S SCHEDULED FEBRUARY 11th

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OF 2024 FROM 1:30-3:00 P.M.

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EASTERN TIME.

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AS A REGISTRANT OF THIS MEETING,

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WILL GET NOTIFICATION ONCE THAT

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REGISTRATION SITE IS OPEN, BUT

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PLEASE MARK IT ON YOUR

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CALENDARS.

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IT SHOULD BE AN EXCELLENT

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SEMINAR.

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NEXT SLIDE.

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SO BEFORE WE GET FULLY INTO

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THINGS WE WANTED TO GET A CHANCE

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TO KNOW YOU A LITTLE BITTER, SO

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WE HAVE A LITTLE POLL FOR YOU.

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CAN WE PUT THE POLL UP PLEASE

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EMPLOY.

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[MUSIC ]

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LITTLE POLL FOR YOU.

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CAN WE PUT THE POLL UP PLEASE.

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[MUSIC ]

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>> OKAY, LET'S SEE WHAT WE
FOUND

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OUT.

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SO THE MAJORITY OF YOU ARE

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COLLABORATING WITH DATA

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SCIENTISTS, 65% VERSUS 35%, IT

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LOOKS LIKE THE MAIORITY OF THAT

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RESPONDED, 66% ARE WORKING WITH

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QUALITATIVE DATA, 43% IN AREA OF

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HEALTH EQUITY, 27% IN ALGORITHMS

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AND DATA MODELS AND 18% IN

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OMICS.

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SO THAT'S REALLY HELPFUL TO

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KNOW, PARTICULARLY FOR OUR

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PRESENTERS TO KNOW WHO THEY'RE

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SPEAKING TO.

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BEFORE WE GET STARTED WITH OUR

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PRESENTERS HOWEVER, I HAVE A

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VERY IMPORTANT GUEST WHO WILL BE

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PROVIDING OPENING COMMENTS FOR

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US DR. MONICA BERTAGNOLLI,

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UNFORTUNATELY SHE WAS NOT ABLE

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TO BE HERE IN PERSON BUT BECAUSE

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THIS IS AN AREA THAT'S NEAR AND

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DEAR TO HER HEART, SHE AS THE

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NIH DIRECTOR HAS HAD HAS HAD 2

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MAJOR FOCI, 1 IS MAKING SURE

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THAT CARE IS PROVIDED TO ALL AND

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IN THE HELT CARE INITIATIVE,

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MAKING SURE THAT DATA IS

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APPLICABLE TO ALL.

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SHE'S VERY MUCH ENDORSING THE

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INITIATIVE THAT WE HAVE HERE.

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DR. BERTAGNOLLI, 17th DIRECTOR

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OF THE NATIONAL INSTITUTES

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HEALTH.

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SHE WAS NOMINATED BY PRESIDENT

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JOE BIDEN, MAY 2023, CONFIRMED

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BY THE SENATE OF NOVEMBER 2023,

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SO SHE'S JUST COMING UP ON HER

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ANNIVERSARY OF HAVING BEEN

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CONFIRMED.

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SHE'S A FIRST SURGEON AND SECOND

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WOMAN TO HOLD THE POSITION OF

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NIH DIRECTOR.

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SHE OVERSEES THE LARGEST CAMPUS

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OF RESEARCH IN THE WORLD.

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SHE PREVIOUSLY SERVED AS CANETH

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DIRECTOR OF THE NCI, -- HARVARD

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MEDICAL SCHOOL, SURGEON AND

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BRIGHAM AND WOMEN'S HOSPITAL AND

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A MEMBER OF THE GASTROINTESTINAL

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CANCER TREATMENT AND SARCOMA

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CENTERS AT DANA-FARBER INSTITUTE

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SO CLEARLY A HIGH QUALIFIED

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INDIVIDUAL IN THIS ROLE AND

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REALLY HAPPY SHE WILL BE ABLE TO

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GIVE US OPENING REMARKS.

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ROLL THE TAPE PLEASE.

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>> WELCOME, EVERYONE TO
THIS

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SESSION OF THE SCIENTIFIC

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WORKFORCE DIVERSITY SEMINAR

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SERIES.

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I AM SO GLAD THIS SEMINAR IS

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ADDRESSING DATA SCIENCE.

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WE'RE LIVING IN A TIME OF RAPID

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ADVANCEMENTS IN AREAS LIKE

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INFORMATION SCIENCE AND DATA

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ANALYTICS.

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IN ORDER TO MAKE AS MUCH

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PROGRESS AS POSSIBLE IN

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ADVANCING HEALTH, WE NEED TO

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MAKE SURE THAT THESE ANALYTERAL

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METHODS ARE APPLIED TO DATA THAT

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INCLUDES EVERYONE.

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AFTERALL AT THE NATIONAL

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INSTITUTES OF HEALTH, OUR

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MISSION IS TO SEEK FUNDMENTAL

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KNOWLEDGE AND TO USE THAT

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KNOWLEDGE TO ENHANCE THE HEALTH

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OF ALL.

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I GREW UP IN RURAL WYOMING, IN A

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PLACE WHERE THE NEAREST DOCTOR'S

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OFFICE IS A HUNDRED MILES AWAY.

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I KNOW FROM MY OWN EXPERIENCE

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HOW IMPORTANT IT IS TO INSURE

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THAT THE BENEFITS OF HEALTH

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RESEARCH REACH PEOPLE FROM ALL

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WALKS OF LIFE REGARDLESS OF

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INCOME OR ZIP CODE.

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SINCE BECOMING AN NIH DIRECTOR

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LAST NOVEMBER, I'VE TAKEN ON 2

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KEY PRIORITIES, THE FIRST IS TO

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MAKE CLINICAL RESEARCH MORE

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ACCESSIBLE SO THAT THEY REFLECT

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THE FULL DIVERSITY OF AMERICANS.

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AND SECOND, I WANT US TO EMBRACE

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NEW ANALYTIC TOOLS, MAKE THEM

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FAR MORE ACCESSIBLE AND INSURE

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THAT THEIR USE SERVES TO ADVANCE

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HEALTHCARE FOR ALL PEOPLE.

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IT IS WELL KNOWN THAT MACHINE

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LEARNING AND ARTIFICIAL

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INTELLIGENCE ARE PRONE TO BIAS.

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THEY PRODUCE WHAT THEY'VE

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LEARNED FROM THE DATA THEY'RE

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PROVIDED.

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PART OF THE PROBLEM IS THAT THE

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INFORMATION THESE METHODS BUILD

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ON CAN REFLECT BIASES IN OUR OWN

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CULTURE.

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ADDITIONAL BIAS STEMS FROM HOW

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PROBLEMS ARE APPROACHED, HOW

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CODE IS WRITTEN, AND HOW

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ALGORITHMS ARE IMPLEMENTED.

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THESE ARE DANGERS WE CAN

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MITIGATE BY MAKING SURE THAT

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DATA SCIENTISTS ARE THEMSELVES

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DIVERSE.

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WE KNOW THAT TEAMS WITH DIVERSE

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PERSPECTIVES CAN FILL OUT EACH

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OTHER'S BLIND SPOTS.

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IF WE DON'T ADDRESS BIAS WE RUN

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THE RISK OF CAUSING HARM AND

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EXACERBATING HARMFUL INIQUITIES

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IN OUR SOCIETY.

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FOR EXAMPLE, RESEARCHERS WHO

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PUBLISHED THEIR FINDINGS IN THE

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JOURNAL OF SCIENCE IN

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OCTOBER 2019 FOUND THAT A

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COMMERCIAL ALGORITHM WIDELY USED

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IN THE HEALTHCARE SYSTEM WAS

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BIASED TO OVERLOOK HEALTH RISKS

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IN BLACK PATIENTS COMPARED WITH

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WHITE PATIENTS.

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LEADING TO LESS NEEDED CARE FOR

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BLACK PATIENTS WITH UNCONTROLLED

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ILLNESSES.

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THE BIAS WAS ROOTED IN THE

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ALGORITHM'S MISTAKEN ASSUMPTIONS

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ABOUT HEALTHCARE COSTS, NOT

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TAKING INTO,A COUNT THAT THERE

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IS UNEQUAL ACCESS TO CARE

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MEANING THAT THE HEALTHCARE

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INDUSTRY SPENDS LESS MONEY

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CARING FOR BLACK PASHTS THAN

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WHITE PATIENTS.

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IN ANOTHER EXAMPLE PUBLISHED IN

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THE YOWRNAL OF NATURE MEDICINE

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IN DECEMBER 2024, AN AI IMAGING

260
00:09:42,818 --> 00:09:44,253
ALGORITHM TESTED AGAINST A LARGE

261
00:09:44,253 --> 00:09:45,788
DATA SET OF CHEST X-RAYS WAS

262
00:09:45,788 --> 00:09:50,826
FOUND TO BE MORE LIKELY TO MISS

263
00:09:50,826 --> 00:09:52,695
DISEASE DIAGNOSIS FOR

264
00:09:52,695 --> 00:09:53,762
UNDERSERVED POPULATIONS,

265
00:09:53,762 --> 00:09:55,631
INCLUDING FEMALE PATIENTS,

266
00:09:55,631 --> 00:09:57,166
PATIENTS UNDER 20 YEARS OF AGE,

267
00:09:57,166 --> 00:10:00,069
BLACK AND HISPANIC PATIENTS AND

268
00:10:00,069 --> 00:10:00,636
PATIENTS ON MEDICAID.

269
00:10:00,636 --> 00:10:03,439
WE HAVE TO BUILD INCLUSIVE

270
00:10:03,439 --> 00:10:04,840
ENVIRONMENTS AND DIVERSE

271
00:10:04,840 --> 00:10:07,142
PERSPECTIVES BOTH IN OUR DATA

272
00:10:07,142 --> 00:10:11,513
SES, AND AMONG DATA SCIENCE

273
00:10:11,513 --> 00:10:12,214
RESEARCHERS.

274
00:10:12,214 --> 00:10:13,449
HAVING DIVERSE PERSPECTIVES IS

275
00:10:13,449 --> 00:10:16,118
REQUIRED FOR US TO DEVELOP TOOLS

276
00:10:16,118 --> 00:10:18,320
AND PRODUCTS THAT MORE CLOSELY

277
00:10:18,320 --> 00:10:19,688
MEET PEOPLE'S NEEDS AND WILL

278
00:10:19,688 --> 00:10:21,590
HELP US ASK BETTER RESEARCH

279
00:10:21,590 --> 00:10:24,460
QUESTIONS IN MUCH BETTER WAYS.

280
00:10:24,460 --> 00:10:26,762
WITH OUR ADVANCING KNOWLEDGE AND

281
00:10:26,762 --> 00:10:28,464
TECHNOLOGY, THERE IS NO GOOD

282
00:10:28,464 --> 00:10:33,969
REASON FOR US NOT TO DELIVER

283
00:10:33,969 --> 00:10:36,038
EVIDENCE-BASED DATA-DRIVEN

284
00:10:36,038 --> 00:10:36,705
HEALTHCARE TO EVERYONE.

285
00:10:36,705 --> 00:10:39,575
THANK YOU ALL FOR ATTENDING

286
00:10:39,575 --> 00:10:40,309
TODAY'S SEMINAR.

287
00:10:40,309 --> 00:10:49,918
AS WE EMBRACE THE EFFORT TO WORK

288
00:10:49,918 --> 00:10:50,819
TOWARD THIS GOAL.

289
00:10:50,819 --> 00:10:55,257
>> SO YOU CAN SEE WHY WE
SO

290
00:10:55,257 --> 00:10:56,258
ENJOY DR. BERTAGNOLLI'S AS OUR

291
00:10:56,258 --> 00:10:56,759
LEADER.

292
00:10:56,759 --> 00:10:57,926
SHE IS FULLY LEADING US INTO THE

293
00:10:57,926 --> 00:11:00,329
THINGS WE WILL BE DISCUSSING, WE

294
00:11:00,329 --> 00:11:03,198
WILL FIRST TART WITH OUR

295
00:11:03,198 --> 00:11:08,070
PANELIST DR. JENNIFER COUCH,

296
00:11:08,070 --> 00:11:09,538
SHE'S WITH BIOEMERGENCYING AND

297
00:11:09,538 --> 00:11:10,239
COMPUTATIONAL SCIENCES, THERE

298
00:11:10,239 --> 00:11:11,540
SHE LEADS THE BRANCH BY

299
00:11:11,540 --> 00:11:12,675
SUPPORTING BASIC RESEARCH AND

300
00:11:12,675 --> 00:11:16,812
TECHNOLOGY DEVELOP AM AND

301
00:11:16,812 --> 00:11:18,347
MOLECULAR APPLICATIONS BY

302
00:11:18,347 --> 00:11:20,082
PHYSICAL BIOLOGY AND

303
00:11:20,082 --> 00:11:21,350
COMPUTATIONAL AND MATHEMATICAL

304
00:11:21,350 --> 00:11:21,617
METHODS.

305
00:11:21,617 --> 00:11:23,419
SHE MANAGES A PORTFOLIO OF

306
00:11:23,419 --> 00:11:27,923
GRANTS FOCUSED ON MULTISCALE

307
00:11:27,923 --> 00:11:28,490
MODELING, BIO-INFORMATICS

308
00:11:28,490 --> 00:11:29,958
CITIZEN SCIENCE AND DATA

309
00:11:29,958 --> 00:11:31,493
SCIENCE, ADDITIONALLY HER AREAS

310
00:11:31,493 --> 00:11:35,664
OF EXPERTISE INCLUDE ARTIFICIAL

311
00:11:35,664 --> 00:11:36,532
INTELLIGENCE, MOLECULAR

312
00:11:36,532 --> 00:11:38,400
APPLICATIONS, STRUCTURAL BIOLOGY

313
00:11:38,400 --> 00:11:39,001
AND BIOTECHNOLOGY.

314
00:11:39,001 --> 00:11:43,605
DR. COUCH, YOU HAVE THE FLOOR.

315
00:11:43,605 --> 00:11:44,139
>> GREAT.

316
00:11:44,139 --> 00:11:44,540
THANKS, EVERYBODY.

317
00:11:44,540 --> 00:11:52,848
JUST SHARE HERE QUICKLY.

318
00:11:52,848 --> 00:11:53,248
OKAY, ALL RIGHT.

319
00:11:53,248 --> 00:11:56,185
I ASSUME EVERYBODY'S SEEING THAT

320
00:11:56,185 --> 00:11:56,485
OKAY?

321
00:11:56,485 --> 00:12:00,089
SO I JUST WANT TO -- THAT'S A

322
00:12:00,089 --> 00:12:01,190
TOUGH ACT TO FOLLOW BOTH OF YOU

323
00:12:01,190 --> 00:12:03,325
SO I WILL TRY AND STAY QUICKLY

324
00:12:03,325 --> 00:12:05,394
ON TIME HERE SO THAT WE CAN GET

325
00:12:05,394 --> 00:12:06,929
TO THE REALLY EXCITING PANEL

326
00:12:06,929 --> 00:12:07,996
DISCUSSION AT THE END AND I WILL

327
00:12:07,996 --> 00:12:11,100
JUST TALK ABOUT A VARIETY OF

328
00:12:11,100 --> 00:12:12,501
QUICK VIGNETTES HERE ABOUT HOW

329
00:12:12,501 --> 00:12:15,070
WE'RE SUPPORTING BRINGING A

330
00:12:15,070 --> 00:12:16,605
BLUEDER PERSPECTIVE INTO CANCER

331
00:12:16,605 --> 00:12:19,174
DATA SCIENCE AND BIOMEDICAL DATA

332
00:12:19,174 --> 00:12:20,075
SCIENCE IN GENERAL.

333
00:12:20,075 --> 00:12:22,911
>> DR. COUCH WE CANNOT SEE
YOUR

334
00:12:22,911 --> 00:12:23,312
PRESENTATION.

335
00:12:23,312 --> 00:12:26,448
>> YOU CANNOT SEE MY

336
00:12:26,448 --> 00:12:32,554
PRESENTATION.

337
00:12:32,554 --> 00:12:32,988
OKAY, SORRY.

338
00:12:32,988 --> 00:12:34,556
OH BECAUSE I FAILED TO HIT THE

339
00:12:34,556 --> 00:12:35,424
LAST BUTTON.

340
00:12:35,424 --> 00:12:37,059
THERE WE GO.

341
00:12:37,059 --> 00:12:38,594
SORRY ABOUT THAT.

342
00:12:38,594 --> 00:12:39,928
ALL RIGHT.

343
00:12:39,928 --> 00:12:44,633
SO, I JUST WANT TO START HERE

344
00:12:44,633 --> 00:12:46,401
WITH A QUICK MENTION OF AI EVEN

345
00:12:46,401 --> 00:12:48,837
THOUGH I KNOW YOU WILL HEAR A

346
00:12:48,837 --> 00:12:51,173
LOT OF THAT LATER FROM SAMSON.

347
00:12:51,173 --> 00:12:53,175
SO AI IS EVERYWHERE IN CANCER

348
00:12:53,175 --> 00:12:54,610
RESEARCH AND AI AND DATA SCIENCE

349
00:12:54,610 --> 00:12:56,145
IN GENERAL RUN THROUGH THE WHOLE

350
00:12:56,145 --> 00:12:58,814
SPECTRUM OF CANCER RESEARCH AND

351
00:12:58,814 --> 00:13:00,883
CLINICAL PRACTICE INCLUDING

352
00:13:00,883 --> 00:13:02,050
SCREENING, DIAGNOSIS, DRUG

353
00:13:02,050 --> 00:13:04,153
DISCOVERY AND SURVEILLANCE AND

354
00:13:04,153 --> 00:13:06,288
HEALTHCARE DELIVERY, BUT ALSO IN

355
00:13:06,288 --> 00:13:10,125
THE AREA THAT I WORK IN THIS

356
00:13:10,125 --> 00:13:12,027
UNDERSTANDING THE BASIC

357
00:13:12,027 --> 00:13:14,296
FUNDAMENTAL BIOLOGICAL

358
00:13:14,296 --> 00:13:22,905
MECHANISMS THAT UNDERLIE CONSER

359
00:13:22,905 --> 00:13:24,673
INITIATION PROGRESSION.

360
00:13:24,673 --> 00:13:25,607
SORRY, HAVING TECHNICAL

361
00:13:25,607 --> 00:13:30,012
DIFFICULTIES HERE FOR A

362
00:13:30,012 --> 00:13:36,819
SECURITIZATION.

363
00:13:36,819 --> 00:13:37,719
APOLOGIES EVERYONE.

364
00:13:37,719 --> 00:13:39,955
ALL RIGHT, THERE WE GO.

365
00:13:39,955 --> 00:13:42,891
AI IS EVOLVING SO RAPID AND SO

366
00:13:42,891 --> 00:13:43,892
MUCH INTEREST IN IT, AND

367
00:13:43,892 --> 00:13:45,294
PATIENTS AND ALL OF US ARE

368
00:13:45,294 --> 00:13:46,728
BEGINNING TO ENGAGE WITH IT AND

369
00:13:46,728 --> 00:13:50,332
WORRY ABOUT THINGS THAT YOU

370
00:13:50,332 --> 00:13:53,802
HEARD DR. BERTAGNOLLI MENTION

371
00:13:53,802 --> 00:13:55,537
ABOUT BI AS AND APPLICABILITY

372
00:13:55,537 --> 00:13:56,638
AND A GENERAL DESIRE TO

373
00:13:56,638 --> 00:13:57,706
UNDERSTAND IT BETTER AND I

374
00:13:57,706 --> 00:13:59,241
WANTED TO HIGHLIGHT QUICKLY

375
00:13:59,241 --> 00:14:01,443
HERE, THE CANCER AI

376
00:14:01,443 --> 00:14:03,011
CONVERSATIONS THAT WE HAVE IN

377
00:14:03,011 --> 00:14:09,117
THE IN, CI, THIS IS A WHERE WE

378
00:14:09,117 --> 00:14:10,452
INVITE A SMALL GROUP OF EXPERTS

379
00:14:10,452 --> 00:14:12,221
TO FROM A VARIETY OF DIFFERENT

380
00:14:12,221 --> 00:14:13,889
PERSPECTIVES ON I SINGLE TOPIC

381
00:14:13,889 --> 00:14:16,425
TO PROVIDE QUICK TALKS AND MEN A

382
00:14:16,425 --> 00:14:17,526
MODERATED DISCUSSION AROUND A

383
00:14:17,526 --> 00:14:18,961
COUPLE OF TOPICS IN CANCER AI

384
00:14:18,961 --> 00:14:20,596
AND I FEATURED A COUPLE HERE

385
00:14:20,596 --> 00:14:23,332
THAT ARE IN HEALTH DISPARITIES

386
00:14:23,332 --> 00:14:25,667
AND GLOBAL ONCOLOGY BUT THERE'S

387
00:14:25,667 --> 00:14:26,735
A WHOLE SERIES OF THESE

388
00:14:26,735 --> 00:14:28,403
AVAILABLE ON THE WEBSITE, BOTH

389
00:14:28,403 --> 00:14:31,340
PAST AND FUTURE, SO, ALSO AT NCI

390
00:14:31,340 --> 00:14:32,507
AND THEN SPECIFICALLY IN THE

391
00:14:32,507 --> 00:14:33,575
DIVISION OF CANCER BIOLOGY WHERE

392
00:14:33,575 --> 00:14:36,945
I AM, WE SUPPORT A NUMBER OF

393
00:14:36,945 --> 00:14:38,580
DATA SCIENCE HEAVY PROGRAMS AND

394
00:14:38,580 --> 00:14:39,982
DATA SCIENCE SCATTERED

395
00:14:39,982 --> 00:14:41,583
THROUGHOUT THE INVESTIGATOR

396
00:14:41,583 --> 00:14:43,952
INITIATED POOL.

397
00:14:43,952 --> 00:14:45,754
AND COORDINATING ACROSS ALL

398
00:14:45,754 --> 00:14:46,622
THESE PROGRAMS AND SCIENCE AND

399
00:14:46,622 --> 00:14:48,957
HELPING TO BUILD THE NEXT

400
00:14:48,957 --> 00:14:49,524
TRANSDISCIPLINARY RESEARCH

401
00:14:49,524 --> 00:14:51,026
WORKFORCE IS A BIG CHALLENGE AND

402
00:14:51,026 --> 00:14:53,929
SO 1 OF THE WAYS THAT WE DO THAT

403
00:14:53,929 --> 00:14:57,099
IS THROUGH A COORDINATING STRAY

404
00:14:57,099 --> 00:14:58,033
JECTORY THAT COORDINATES ACROSS

405
00:14:58,033 --> 00:15:00,702
THESE THAT RELIES SO MUCH ON

406
00:15:00,702 --> 00:15:01,036
DATA SCIENCE.

407
00:15:01,036 --> 00:15:03,372
SO IN ALL OF THOSE PROGRAMS, ALL

408
00:15:03,372 --> 00:15:06,008
OF THOSE DATA SCIENCE HEAVY

409
00:15:06,008 --> 00:15:08,577
PROGRAMS, THEY'RE ALL

410
00:15:08,577 --> 00:15:09,111
MULTIDISCIPLINARY

411
00:15:09,111 --> 00:15:09,511
TRANSDISCIPLINARY,

412
00:15:09,511 --> 00:15:10,479
INTERDISCIPLINEAR EXPE THEY ALL

413
00:15:10,479 --> 00:15:12,714
RELY ON DATA, SCIENCE, MATH,

414
00:15:12,714 --> 00:15:13,849
EMERGENCYING AND WE WERE THE

415
00:15:13,849 --> 00:15:15,851
ISED A LOT OF THIS SCIENCE NOW

416
00:15:15,851 --> 00:15:17,686
FOR DECADES AND WHILE THE

417
00:15:17,686 --> 00:15:19,321
GRADUATE STUDENTS, POST DOCS AND

418
00:15:19,321 --> 00:15:20,155
EARLY CAREER RESEARCH IS

419
00:15:20,155 --> 00:15:22,391
SUPPORTED IN PART IN THESE

420
00:15:22,391 --> 00:15:24,559
PROGETHS MAKE UP -- MAKE UP

421
00:15:24,559 --> 00:15:27,996
THESE LARGE PROGRAMS ARE

422
00:15:27,996 --> 00:15:29,164
IMMERSED IN THESE

423
00:15:29,164 --> 00:15:30,098
INTERDISCIPLINARY RESEARCH SPACE

424
00:15:30,098 --> 00:15:31,500
AND TEAM SCIENCE, IT CAN BE

425
00:15:31,500 --> 00:15:32,834
DIFFICULT FOR THEM AS THEY MOVE

426
00:15:32,834 --> 00:15:34,903
ON FROM THOSE TEAMS INTO

427
00:15:34,903 --> 00:15:37,072
STARTING UP THEIR OWN RESEARCH

428
00:15:37,072 --> 00:15:39,207
AND BUILDING THEIR OWN TEAMS AND

429
00:15:39,207 --> 00:15:40,375
NEW INSTITUTIONS THAT PERHAPS

430
00:15:40,375 --> 00:15:43,378
DON'T HAVE THE FACILITIES OR

431
00:15:43,378 --> 00:15:44,880
MULTIDISCIPLINARY TEAMS ALREADY

432
00:15:44,880 --> 00:15:45,647
IN PLACE.

433
00:15:45,647 --> 00:15:47,549
SO AFTER LISTENING TO THEM FOR

434
00:15:47,549 --> 00:15:49,251
SOMETIME, 1 OF THE THINGS THAT

435
00:15:49,251 --> 00:15:51,320
WE'VE STARTED TO DO NOW FOR MANY

436
00:15:51,320 --> 00:15:53,455
YEARS IS SUPPORT AND WORK WITH

437
00:15:53,455 --> 00:15:57,492
THESE JUNIOR INVESTIGATORS SO

438
00:15:57,492 --> 00:15:58,226
THAT GRADUATE STUDENTS, POST

439
00:15:58,226 --> 00:16:02,230
DOCS AND EARLY CAREER PEOPLE BY

440
00:16:02,230 --> 00:16:03,665
RUNNING THESE THINGS WE CALL

441
00:16:03,665 --> 00:16:04,499
JUNIOR INVESTIGATOR MEETINGS, SO

442
00:16:04,499 --> 00:16:06,368
THESE ARE PLANNED BY AND RUN BY

443
00:16:06,368 --> 00:16:09,037
AND RUN FOR THE JR.

444
00:16:09,037 --> 00:16:10,739
INVESTIGATORS WITH OUR HELP AND

445
00:16:10,739 --> 00:16:12,607
MANAGE AM AND THERE THEY JUST

446
00:16:12,607 --> 00:16:14,109
EXCHANGE SCIENCE AND BUILD THEIR

447
00:16:14,109 --> 00:16:20,849
NETWORKS AND GET MENTORING AND

448
00:16:20,849 --> 00:16:21,183
CAREER ADVICE.

449
00:16:21,183 --> 00:16:22,384
SO WE ALSO KNOW THAT THE

450
00:16:22,384 --> 00:16:24,219
PIPELINE OF YOUNG SCIENTISTS CAN

451
00:16:24,219 --> 00:16:25,721
SOMETIMES BE NOT AS DIVERSE ASK

452
00:16:25,721 --> 00:16:26,822
INCLUSIVE AS WE WILL LIKE AND

453
00:16:26,822 --> 00:16:28,557
THAT'S FOR A LOT OF REASONS, 1

454
00:16:28,557 --> 00:16:31,626
OF WHICH IS THAT THE LACK OF

455
00:16:31,626 --> 00:16:32,894
EARLY EXPOSURE AND HANDS ON TO

456
00:16:32,894 --> 00:16:35,197
THIS KIND OF RESEARCH THAT

457
00:16:35,197 --> 00:16:36,365
ENTICES PEOPLE INTO THOSE

458
00:16:36,365 --> 00:16:37,332
CAREERS IN THE FIRST PLACE.

459
00:16:37,332 --> 00:16:40,035
AND 1 OF THE BARRIERS THAT THESE

460
00:16:40,035 --> 00:16:41,370
STUDENTINGS FACE SOMETIMES ARE

461
00:16:41,370 --> 00:16:43,038
JUST FINANCIAL.

462
00:16:43,038 --> 00:16:44,206
THEY NEED TRANSPORTATION, OR

463
00:16:44,206 --> 00:16:46,041
THEY MAY HAVE SUMMER JOBS TO

464
00:16:46,041 --> 00:16:47,476
SUPPORT THEMSELVES THROUGH THE

465
00:16:47,476 --> 00:16:50,312
SUMMER, AND THIS IS AN EXAMPLE

466
00:16:50,312 --> 00:16:56,151
HERE OF A PROGRAM RUN BY THE

467
00:16:56,151 --> 00:16:56,852
MOFET INTEGRATED MATHEMATICAL

468
00:16:56,852 --> 00:16:57,819
ONCOLOGY PROGRAM SUPPORTED IN

469
00:16:57,819 --> 00:16:59,888
PART BY THE CANCER SYSTEM SYSTEM

470
00:16:59,888 --> 00:17:00,822
BIOLOGY CONSORTIUM AND IT

471
00:17:00,822 --> 00:17:03,125
REACHES OUT TO LOCAL HIGH SCHOOL

472
00:17:03,125 --> 00:17:04,659
STUDENTS AND OFFERS A STIPEND SO

473
00:17:04,659 --> 00:17:06,762
THEY CAN JOIN DURING THEIR

474
00:17:06,762 --> 00:17:08,196
SUMMER BREAK, BUILD TEAMS, WORK

475
00:17:08,196 --> 00:17:10,332
ON PROGECS THAT ARE

476
00:17:10,332 --> 00:17:11,466
MULTIDISCIPLINARY, BRINGING

477
00:17:11,466 --> 00:17:12,234
TOGETHER BASIC AND CLINICAL

478
00:17:12,234 --> 00:17:13,435
RESEARCH WITH MATH AND COMPUTER

479
00:17:13,435 --> 00:17:16,371
SCIENCE AND THIS SLIDES SHOWS

480
00:17:16,371 --> 00:17:17,939
THE INAUGURAL SET OF STUDENTS

481
00:17:17,939 --> 00:17:19,307
BACK IN 2015 WHICH IS QUITE

482
00:17:19,307 --> 00:17:21,309
SMALL BUT NOW AFTER ALMOST 10

483
00:17:21,309 --> 00:17:23,278
YEARS, THE DEMAND HAS GROWN TO

484
00:17:23,278 --> 00:17:25,480
WHERE THEY HAVE 15 SPOTS

485
00:17:25,480 --> 00:17:26,114
AVAILABLE AND OVER 200

486
00:17:26,114 --> 00:17:36,625
APPLICANTS JUDGE UOF THE FROM

487
00:17:37,059 --> 00:17:37,826
THEIR LOCAL AREA.

488
00:17:37,826 --> 00:17:40,762
MOST OF THE TIEWPTS WHO COME

489
00:17:40,762 --> 00:17:42,497
INTO THIS DO SCIENCE AND MATH

490
00:17:42,497 --> 00:17:44,366
AND GO ON TO COLLEGE AFTER THIS

491
00:17:44,366 --> 00:17:44,633
PROGRAM.

492
00:17:44,633 --> 00:17:48,503
THEY BRING THAT

493
00:17:48,503 --> 00:17:50,172
MULTIDISCIPLINARY APPROACH AS

494
00:17:50,172 --> 00:17:52,574
THEY CONTINUE THEIR TRAINING AND

495
00:17:52,574 --> 00:17:53,608
CAREERS.

496
00:17:53,608 --> 00:17:54,276
ANOTHER EXPERIMENT THAT'S

497
00:17:54,276 --> 00:17:56,711
UNDERWAY NOW THROUGH OUR

498
00:17:56,711 --> 00:17:57,879
MULTICONSORTIUM TRAINING CENTER

499
00:17:57,879 --> 00:17:59,915
IS TRYING TO CONNECT DIVERSITY

500
00:17:59,915 --> 00:18:01,616
CANDIDATES WITH LABS THAT ARE

501
00:18:01,616 --> 00:18:03,985
ABLE TO HOST AND RECEIVE

502
00:18:03,985 --> 00:18:05,387
DIVERSITY SUPPLEMENTS AND MOST

503
00:18:05,387 --> 00:18:08,290
OF OUR RESEARCH AWARDS ARE

504
00:18:08,290 --> 00:18:09,591
ELIGIBLE TO RECEIVE DIVERSITY

505
00:18:09,591 --> 00:18:10,592
SUPPLEMENTS TO HOST DIVERSITY

506
00:18:10,592 --> 00:18:11,760
TRAINEES BUT IT CAN BE HARD TO

507
00:18:11,760 --> 00:18:12,928
MAKE THOSE MATCHES AND THIS

508
00:18:12,928 --> 00:18:15,197
PROGRAM SORT OF AIMS TO BRING

509
00:18:15,197 --> 00:18:17,666
TOGETHER A MATCH MAKING EVENT

510
00:18:17,666 --> 00:18:19,401
AND SEE IF BRINGING PEOPLE

511
00:18:19,401 --> 00:18:21,002
TOGETHER AND DOING SOME MATCH

512
00:18:21,002 --> 00:18:22,871
MAKING CAN HELP PEOPLE PASS THIS

513
00:18:22,871 --> 00:18:25,974
HURDLE, OF FINDING THE RIGHT

514
00:18:25,974 --> 00:18:29,244
HOST LAB AND THE RIGHT TRAINEE.

515
00:18:29,244 --> 00:18:30,879
SO I WANT TO JUST TALK HERE FOR

516
00:18:30,879 --> 00:18:33,448
THE LAST COUPLE OF MINUTES ABOUT

517
00:18:33,448 --> 00:18:34,816
ALTASD MATE WAYS OF ENGAGING

518
00:18:34,816 --> 00:18:36,685
PEOPLE, SORT OF REACHING THEM

519
00:18:36,685 --> 00:18:37,619
WHERE THEY'RE AT.

520
00:18:37,619 --> 00:18:39,788
SO USING THINGS LIKE GAMES OR

521
00:18:39,788 --> 00:18:41,356
CITIZEN SCIENCE OR COMMUNITY

522
00:18:41,356 --> 00:18:44,726
SCIENCE AND 1 WAY THAT PEOPLE

523
00:18:44,726 --> 00:18:46,161
ENGAGE IN DATA SCIENCE ALL THE

524
00:18:46,161 --> 00:18:48,029
TIME WITHOUT REALIZING IT IS

525
00:18:48,029 --> 00:18:49,598
GAMES, GAME USED SOPHISTICATED

526
00:18:49,598 --> 00:18:52,167
DATA SCIENCE TO HOE COMPLEXITY,

527
00:18:52,167 --> 00:18:54,636
DEAL WITH MULTIPLE SCALES ISSUES

528
00:18:54,636 --> 00:18:56,171
RENDER IMAGERY IN REALTIME, ALL

529
00:18:56,171 --> 00:18:59,841
THE THINGS WE DO AND NEED IN

530
00:18:59,841 --> 00:19:01,877
BIOMEDICAL RESEARCH, AND THEY

531
00:19:01,877 --> 00:19:03,044
ENABLE REALTIME COLLABORATIONS,

532
00:19:03,044 --> 00:19:04,079
SOMETIMES BETWEEN HUNDREDS OF

533
00:19:04,079 --> 00:19:06,515
PEOPLE FROM ACROSS THE WORLD AT

534
00:19:06,515 --> 00:19:08,517
ONCE AND THEY OFFER OPEN

535
00:19:08,517 --> 00:19:09,584
EXPLORATION AND DISCOVERY

536
00:19:09,584 --> 00:19:10,418
OPPORTUNITIES THAT IN SCIENCE I

537
00:19:10,418 --> 00:19:13,088
THINK CAN LEAD US TO THOSE

538
00:19:13,088 --> 00:19:14,689
AHA MOMENT WHEN IS WE SEE

539
00:19:14,689 --> 00:19:17,259
SOMETHING DIFFERENTLY IN OR IN A

540
00:19:17,259 --> 00:19:18,059
NEW WAY.

541
00:19:18,059 --> 00:19:19,327
SO COMMUNITY SCIENCE, THOSE ARE

542
00:19:19,327 --> 00:19:21,329
METHODS THAT TAP INTO THE

543
00:19:21,329 --> 00:19:22,731
CREATIVE COLLECTIVE OUT THERE,

544
00:19:22,731 --> 00:19:23,899
THE CREATIVITY AND INSIGHT AND

545
00:19:23,899 --> 00:19:25,667
INTEREST THAT WE KNOW ARE

546
00:19:25,667 --> 00:19:27,202
EVERYWHERE PATIENTS AND

547
00:19:27,202 --> 00:19:28,436
CAREGIVERS AND COMMUNITIES AND

548
00:19:28,436 --> 00:19:30,172
PEOPLE IN GENERAL WITH THEIR

549
00:19:30,172 --> 00:19:32,774
UNIQUE INSIGHT ANDS CONTEXT AND

550
00:19:32,774 --> 00:19:38,246
PERSPECTIVE AND JUST A GENUINE

551
00:19:38,246 --> 00:19:38,713
DESIRE TO CONTRIBUTE.

552
00:19:38,713 --> 00:19:40,282
SO, ENGAGING GAME DESIGNERS AND

553
00:19:40,282 --> 00:19:43,885
THINKING ABOUT GAMES IN SCIENCES

554
00:19:43,885 --> 00:19:44,352
IS NOT TRIVIAL.

555
00:19:44,352 --> 00:19:45,921
SO WE HAVE BEEN APPROACHING THIS

556
00:19:45,921 --> 00:19:47,422
FROM A VARIETY OF DIFFERENT WAYS

557
00:19:47,422 --> 00:19:48,056
ACROSS THE LAST SEVERAL YEARS

558
00:19:48,056 --> 00:19:51,393
AND WE SORT OF WITH THE SERIES

559
00:19:51,393 --> 00:19:52,494
OF CONVERSATIONS HERE BETWEEN

560
00:19:52,494 --> 00:19:54,362
GAME DESIGNERS OR USER

561
00:19:54,362 --> 00:19:57,232
EXPERIENCE EXPERTS AND THEN

562
00:19:57,232 --> 00:19:58,400
BIOMEDICAL RESEARCHERS, IN THIS

563
00:19:58,400 --> 00:20:00,435
CASE ALL CANCER RESEARCHERS

564
00:20:00,435 --> 00:20:01,903
THROUGH THE CANCER MOONSHOT AND

565
00:20:01,903 --> 00:20:04,306
WE RECORDED THOSE EXCHANGES AND

566
00:20:04,306 --> 00:20:05,874
THEN USE THAT AS INSPIRATION FOR

567
00:20:05,874 --> 00:20:09,244
OTHERS TO SORT OF THINK ABOUT

568
00:20:09,244 --> 00:20:09,844
HOW TO COLLABORATE.

569
00:20:09,844 --> 00:20:17,686
THIS IS A GAME DESIGNER WHO

570
00:20:17,686 --> 00:20:18,420
DESIGNS EX  PERIENTAL CAMPAIGNS

571
00:20:18,420 --> 00:20:20,422
WITH A RESEARCHER WHO RUNS A

572
00:20:20,422 --> 00:20:21,523
CANCER RESEARCH PROGRAMS USING

573
00:20:21,523 --> 00:20:25,860
THAT AS A WAY TOCCATAALIZE

574
00:20:25,860 --> 00:20:26,795
COLLABORATIONS BETWEEN OTHERS.

575
00:20:26,795 --> 00:20:28,296
AND I'M JUST GOING TO END HERE

576
00:20:28,296 --> 00:20:30,265
WITH 1 LAST EXAMPLE THAT

577
00:20:30,265 --> 00:20:33,301
SOMETIMES WHAT HOLDS UP NEW

578
00:20:33,301 --> 00:20:34,236
PARTNERSHIPS AND STOPS PEOPLE

579
00:20:34,236 --> 00:20:36,004
FROM VERY DIFFERENT FEELS FROM

580
00:20:36,004 --> 00:20:37,906
COMING TOGETHER IS THE INABILITY

581
00:20:37,906 --> 00:20:39,207
TO FIND PARTNERS, PEOPLE DON'T

582
00:20:39,207 --> 00:20:41,243
KNOW HOW TO MEET PEOPLE IN OTHER

583
00:20:41,243 --> 00:20:44,779
FIELDS, SOMETIMES AND SOEE RUN

584
00:20:44,779 --> 00:20:46,915
THESE INNOVATION IDEAS OR SAND

585
00:20:46,915 --> 00:20:48,450
PITS AS A WAY TO BRING IN

586
00:20:48,450 --> 00:20:49,217
INDIVIDUALS FROM DIFFERENT

587
00:20:49,217 --> 00:20:51,186
FIELDS AND DIFFERENT WORLDS,

588
00:20:51,186 --> 00:20:52,420
SOMETIMES PATIENT ADVOCATES OR

589
00:20:52,420 --> 00:20:54,089
OTHERS TOGETHER TO FIND NEW

590
00:20:54,089 --> 00:20:55,490
COLLABORATORS, TO MEET AND TO

591
00:20:55,490 --> 00:20:57,225
UNDERSTAND EACH OTHER'S FIELDS

592
00:20:57,225 --> 00:21:00,262
AND THEN TO PROPOSE IDEAS FOR

593
00:21:00,262 --> 00:21:01,196
PILOT PROJECTS, SOMETIMES WITH

594
00:21:01,196 --> 00:21:02,497
FUNDS AT THE END AND SOMETIMES

595
00:21:02,497 --> 00:21:04,299
NOT AND I'M JUST SHOWCASING THIS

596
00:21:04,299 --> 00:21:06,768
1 AS A DAILY BASIS THEA SCIENCE

597
00:21:06,768 --> 00:21:07,569
RELEVANT EXAMPLE THAT'S GOING TO

598
00:21:07,569 --> 00:21:09,471
TAKE PLACE IN A COUPLE OF MONTHS

599
00:21:09,471 --> 00:21:11,606
AND I THINK THAT LOOKS LIKE MY

600
00:21:11,606 --> 00:21:13,508
TIME IS UP. 

601
00:21:13,508 --> 00:21:13,875
>> THANK YOU.

602
00:21:13,875 --> 00:21:15,977
>> THANK YOU VERY MUCH.

603
00:21:15,977 --> 00:21:21,483
OUR NEXT SPEAKER IS DR. MANU

604
00:21:21,483 --> 00:21:24,352
PLATT, DIRECTOR OF CENTER FOR

605
00:21:24,352 --> 00:21:26,054
ENGINEERING BIOLOGY AND

606
00:21:26,054 --> 00:21:27,589
ASSOCIATE DIRECTOR FOR

607
00:21:27,589 --> 00:21:29,758
SCIENTIFIC DIVERSITY EQUITY AND

608
00:21:29,758 --> 00:21:32,394
INCLUSION AT THE NATIONAL

609
00:21:32,394 --> 00:21:34,462
INSTITUTE OF BIOMEDICAL

610
00:21:34,462 --> 00:21:35,330
ENGINEERING HIS RESEARCH FOCUSES

611
00:21:35,330 --> 00:21:37,432
ON MECHANISMS OF DEC,

612
00:21:37,432 --> 00:21:38,466
TRANSLATIONAL APPROACHES IN

613
00:21:38,466 --> 00:21:39,868
STROKES FOR PEOPLE AFFECTED WITH

614
00:21:39,868 --> 00:21:42,404
SICKLE CELL DISEASE AND

615
00:21:42,404 --> 00:21:43,238
HARNESSING PROTEOLYTIC SYSTEMS

616
00:21:43,238 --> 00:21:45,473
AND BIOLOGY TOOLS TO PREDICT

617
00:21:45,473 --> 00:21:47,709
DISEASE PROGRESSION.

618
00:21:47,709 --> 00:21:48,877
INTEGRATED RESEARCH AND

619
00:21:48,877 --> 00:21:49,711
MENTORING GOALS WILL CHANGE THE

620
00:21:49,711 --> 00:21:51,279
LOOK OF THE NEXT GENERATION OF

621
00:21:51,279 --> 00:21:52,580
SCIENTISTS THAT ENGINEERING

622
00:21:52,580 --> 00:21:53,748
THROUGH SUCCESSFUL DIVERSITY

623
00:21:53,748 --> 00:21:57,385
PROGRAMS HE HAS INITIATED.

624
00:21:57,385 --> 00:21:57,752
DR. PLATT.

625
00:21:57,752 --> 00:22:01,022
NTHANK YOU SO MUCH FOR THAT

626
00:22:01,022 --> 00:22:03,325
INTRODUCTION DR. BERNARD AND I

627
00:22:03,325 --> 00:22:08,897
FEEL LIKE OUR DIRECTOR

628
00:22:08,897 --> 00:22:09,431
DR. BERTAGNOLLI STOLE MY

629
00:22:09,431 --> 00:22:11,132
DISCUSSION BUT I WILL PUT SOME

630
00:22:11,132 --> 00:22:14,936
MEAT ON WHAT SHE WAS DISCUSSING.

631
00:22:14,936 --> 00:22:16,571
SO YOU KNOW MY TAKE HOME MESSAGE

632
00:22:16,571 --> 00:22:19,407
IS TO HIT IT UP FRONT, DIVERSIFY

633
00:22:19,407 --> 00:22:21,042
YOUR TEAM AND YOUR TEAM AT EARLY

634
00:22:21,042 --> 00:22:22,110
STAGES PARTICULARLY IN THE

635
00:22:22,110 --> 00:22:23,578
CONTEXT OF KNOWING ABOUT

636
00:22:23,578 --> 00:22:24,279
TWEPPING NEW TECHNOLOGIES, THEN

637
00:22:24,279 --> 00:22:26,014
I THINK IT'S IMPORTANT TO

638
00:22:26,014 --> 00:22:27,749
CONSIDER THE IMPACT OFIOURE

639
00:22:27,749 --> 00:22:29,284
TECHNOLOGY NEAR ALL HUMANS, AND

640
00:22:29,284 --> 00:22:30,719
WE WILL TALK ABOUT REASONS WHY,

641
00:22:30,719 --> 00:22:32,487
AND THEN AGAIN IF YOU NEED A

642
00:22:32,487 --> 00:22:34,022
MONEY REASON, THAT CAN HELP

643
00:22:34,022 --> 00:22:38,693
EXPAND THE MARKET AND THE IMPACT

644
00:22:38,693 --> 00:22:41,196
OF YOUR TECHNOLOGY AND SO THERE

645
00:22:41,196 --> 00:22:43,865
ARE CONSEQUENCES WHEN WE DON'T,

646
00:22:43,865 --> 00:22:46,067
DEVICE DESIGN, WILL LEAD TO

647
00:22:46,067 --> 00:22:48,536
AVOIDABLE UK COVID DEATHS,

648
00:22:48,536 --> 00:22:49,237
PULSEOX IMPEDIMENTSITTERS DID

649
00:22:49,237 --> 00:22:50,672
NOT WORK AS WELL FOR PEOPLE OF

650
00:22:50,672 --> 00:22:53,775
COLOR AND CAN HAVE TERRIBLE

651
00:22:53,775 --> 00:22:54,876
OUTCOMES FOR PEOPLE OF COLOR WHO

652
00:22:54,876 --> 00:22:58,646
ARE RELYING  ON THAT OXYGEN

653
00:22:58,646 --> 00:23:00,181
PERCENTAGE.

654
00:23:00,181 --> 00:23:04,986
SO THEN AS THE DR. BERTAGNOLLI,

655
00:23:04,986 --> 00:23:07,322
MENTIONED, THAT THERE WAS AN

656
00:23:07,322 --> 00:23:09,124
ALGORITHM TO AUTOMATICALLY ADD

657
00:23:09,124 --> 00:23:10,258
3-POINTS TO NONBLACK PATIENTS

658
00:23:10,258 --> 00:23:11,559
SCORES MAKING IT SEEM AS THOUGH

659
00:23:11,559 --> 00:23:13,661
BLACK PEOPLE WERE AT LOWER RISK

660
00:23:13,661 --> 00:23:15,864
OF DYING FROM HEART PROBLEMS

661
00:23:15,864 --> 00:23:17,399
SIMPLY BY VIRTUE OF RACE WHICH

662
00:23:17,399 --> 00:23:18,666
WASN'T TRUE AND AGAIN IT'S

663
00:23:18,666 --> 00:23:20,168
FORTUNATE REMEMBER THAT RACE IS

664
00:23:20,168 --> 00:23:22,070
A SOCIAL CONSTRUCT AND NOT A

665
00:23:22,070 --> 00:23:24,606
RELIABLE PROXY FOR GENETICS SO

666
00:23:24,606 --> 00:23:26,574
WE'RE SEEING THESE DESPERATE

667
00:23:26,574 --> 00:23:26,908
OUTCOMES.

668
00:23:26,908 --> 00:23:35,183
MANY HAVE HEARD ABOUT THE

669
00:23:35,183 --> 00:23:37,285
GLOMERULAR FILTRATION RATE WHICH

670
00:23:37,285 --> 00:23:39,154
WAS MISCALCULATED FOR KIDNEY

671
00:23:39,154 --> 00:23:42,157
FUNCTION IN BLACK AMERICANS AND

672
00:23:42,157 --> 00:23:48,730
INFLATED THE EGFR RESULT WHICH

673
00:23:48,730 --> 00:23:50,265
COVERED THE KIDNEY HEALTH.

674
00:23:50,265 --> 00:23:51,800
THERE WERE STILL SEEING THAT

675
00:23:51,800 --> 00:23:56,104
GREATER THAN 50% OF PATIENTS

676
00:23:56,104 --> 00:23:59,007
WAITING FOR KIDNEY TRANSPLANTS

677
00:23:59,007 --> 00:24:01,643
WERE ETHNIC MINORITIES AFRICAN

678
00:24:01,643 --> 00:24:03,144
AMERICANS CONSITUTING 32% OF

679
00:24:03,144 --> 00:24:03,945
THAT WAIT LIST, ALSO LEADING

680
00:24:03,945 --> 00:24:07,482
BACK TO THE LATER DIAGNOSIS OF

681
00:24:07,482 --> 00:24:08,516
THE KIDNEY DISFUNCTION, SO

682
00:24:08,516 --> 00:24:11,052
THAT'S WHY I THINK ABOUT DATA TO

683
00:24:11,052 --> 00:24:12,554
DEVELOP TO USE PHYSICIANS TO

684
00:24:12,554 --> 00:24:13,955
USE, WE MUST CONSIDER OTHER

685
00:24:13,955 --> 00:24:14,656
POPULATIONS.

686
00:24:14,656 --> 00:24:16,825
SO THIS HAS BEEN OVERTURNED

687
00:24:16,825 --> 00:24:19,427
RECENTLY WITH A LOT OF ADVOCACY

688
00:24:19,427 --> 00:24:20,962
IN THE COMMUNITY, AND THE NEW

689
00:24:20,962 --> 00:24:23,665
QUESTION IS HOW WILL THIS

690
00:24:23,665 --> 00:24:24,966
ELIMINATE CO EFFICIENTS THAT ARE

691
00:24:24,966 --> 00:24:26,534
AFFECTING BLACK PATIENTS AND IT

692
00:24:26,534 --> 00:24:28,336
WILL TAKE TIME FOR THOSE NUMBERS

693
00:24:28,336 --> 00:24:30,438
TO BE SHOWN SO WE CAN MAKE

694
00:24:30,438 --> 00:24:30,705
DECISIONS.

695
00:24:30,705 --> 00:24:32,540
BUT AGAIN AS JENNIFER LED OFF,

696
00:24:32,540 --> 00:24:36,010
THERE'S A LOT OF TALK OF THIS,

697
00:24:36,010 --> 00:24:39,514
BUT WE NEED TO BE CAREFUL OF

698
00:24:39,514 --> 00:24:40,715
COMPUTER BIAS BECAUSE PEOPLE DO

699
00:24:40,715 --> 00:24:42,750
PROVIDE THE INFORMATION AND WHO

700
00:24:42,750 --> 00:24:43,485
TRAINS THE ALGORITHM.

701
00:24:43,485 --> 00:24:44,786
I KNOW THESE THINGS ARE THINKING

702
00:24:44,786 --> 00:24:45,954
OF THINGS WE HAVEN'T BEFORE BUT

703
00:24:45,954 --> 00:24:48,256
THEY ARE DOING IT WITH THE

704
00:24:48,256 --> 00:24:50,225
INFORMATION WITH WHICH WE FEED

705
00:24:50,225 --> 00:24:51,459
THEM.

706
00:24:51,459 --> 00:24:53,394
SO GENDER, DIVERSITY, ETHNICITY,

707
00:24:53,394 --> 00:24:58,099
BODY TYPE, AGE, PREGNANCY, THESE

708
00:24:58,099 --> 00:25:00,235
ARE MAJOR, MAJOR TIMES OF RISKY

709
00:25:00,235 --> 00:25:02,670
HEALTH OUTCOMES, SO TO START

710
00:25:02,670 --> 00:25:03,838
THIS COMPUTATIONAL BIAS WE MUST

711
00:25:03,838 --> 00:25:14,382
MAKE A GREATER EFFORT TO RECRUIT

712
00:25:22,290 --> 00:25:22,924
FROM DIFFERENT POPULATIONS.

713
00:25:22,924 --> 00:25:25,493
THIS IS WHAT WE NEED TO OVERCOME

714
00:25:25,493 --> 00:25:26,561
SO WE CAN DIVERSIFY THESE

715
00:25:26,561 --> 00:25:28,029
WORKFORCES AND GET THESE BETTER

716
00:25:28,029 --> 00:25:28,429
THOUGHTS.

717
00:25:28,429 --> 00:25:30,498
I THINK BACK I TOOK A LOT OF

718
00:25:30,498 --> 00:25:31,499
COMPUTER SCIENCE COURSES IN MY

719
00:25:31,499 --> 00:25:33,034
EDUCATION AND I REMEMBER WHEN

720
00:25:33,034 --> 00:25:36,471
DOING CODING THERE WAS A SET OF

721
00:25:36,471 --> 00:25:37,572
NUMBERS YOU ALWAYS WANTED TO

722
00:25:37,572 --> 00:25:39,607
TEST, YOU WOULD DO LIKE 0, 1,

723
00:25:39,607 --> 00:25:41,676
NEGATIVE 1 AND THEN YOU DO A

724
00:25:41,676 --> 00:25:42,877
FRACTION OR DECIMAL TO THEN SEE

725
00:25:42,877 --> 00:25:46,114
IF IT WOULD BREAK YOUR CODE.

726
00:25:46,114 --> 00:25:47,649
SO IN THINKING ABOUT HOW WE MAKE

727
00:25:47,649 --> 00:25:49,884
SURE WE CAN DIVERSIFY THE TYPES

728
00:25:49,884 --> 00:25:51,786
OF GROUPS AND COMMUNITIES TO BE

729
00:25:51,786 --> 00:25:53,054
INCLUDED IN OUR HEALTHCARE

730
00:25:53,054 --> 00:25:54,856
SOLUTIONS, AGAIN IN THE EARLIEST

731
00:25:54,856 --> 00:25:56,190
PHASE OF DESIGN AND TECHNOLOGY,

732
00:25:56,190 --> 00:25:57,592
TOO BEING ME BACK TO A LOT OF

733
00:25:57,592 --> 00:25:59,494
WORK I USED TO DO IN THE

734
00:25:59,494 --> 00:26:00,562
HIV/AIDS WORLD WHERE THEY WERE

735
00:26:00,562 --> 00:26:01,596
THINKING ABOUT POPULATION SAYS

736
00:26:01,596 --> 00:26:02,931
THAT WERE BEING LEFT BEHIND

737
00:26:02,931 --> 00:26:06,301
WHICH MAKES IT SOLVING A PUBLIC

738
00:26:06,301 --> 00:26:07,702
HEALTH CRISIS A BIT HARDER.

739
00:26:07,702 --> 00:26:10,371
PERSON LIVING WITH HIV, YOUNG

740
00:26:10,371 --> 00:26:11,706
WOMAN, PRISON, I'M A MIRROR

741
00:26:11,706 --> 00:26:14,475
IMAGE GRANT, INYECTING DRUG

742
00:26:14,475 --> 00:26:16,277
USER, SEX WORKER, YOU CAN SEE

743
00:26:16,277 --> 00:26:17,011
THESE OTHER CATEGORIES ON THE

744
00:26:17,011 --> 00:26:19,147
BOTTOM THAT IT WE CAN DEVELOP

745
00:26:19,147 --> 00:26:20,782
CATEGORIES IF YOU'RE DEVELOPING

746
00:26:20,782 --> 00:26:21,950
USEABLE TECHNOLOGY, THESE ARE

747
00:26:21,950 --> 00:26:23,451
THE SLIGHTS OF INDIVIDUALS YOU

748
00:26:23,451 --> 00:26:24,652
SHOULD CONSIDER WHERE YOUR

749
00:26:24,652 --> 00:26:25,920
TECHNOLOGY WORK FORAND YOU DON'T

750
00:26:25,920 --> 00:26:28,122
EACH HAVE A DIVERSE TEAM TO PUSH

751
00:26:28,122 --> 00:26:28,590
YOU FOR THAT.

752
00:26:28,590 --> 00:26:31,025
I ALSO WANT TO DO PUSH MAJOR

753
00:26:31,025 --> 00:26:31,993
EFFORTS HAPPENING IN MY

754
00:26:31,993 --> 00:26:34,195
INSTITUTE ISSUES THE NATIONAL

755
00:26:34,195 --> 00:26:35,763
INTUITY OF BIOMEDICAL IMAGING

756
00:26:35,763 --> 00:26:36,731
AND ENGINEERING, IMAGING IS A

757
00:26:36,731 --> 00:26:38,967
BIG PART OF WHAT WE DO AND THEY

758
00:26:38,967 --> 00:26:40,134
DEVELOPED THIS MEDICAL IMAGING

759
00:26:40,134 --> 00:26:42,870
AND DATA RESOURCE CENTER,

760
00:26:42,870 --> 00:26:45,873
STARTED DOING COVID TO COLLECT

761
00:26:45,873 --> 00:26:47,408
X-RAY SCANS AND LOOK AT LUNG

762
00:26:47,408 --> 00:26:50,178
DAMAGE AND DEVELOP AI AND

763
00:26:50,178 --> 00:26:51,245
MACHINE LEARNING ALGORITHMS THAT

764
00:26:51,245 --> 00:26:52,947
COULD DIAGNOSE THESE SCANS BUT

765
00:26:52,947 --> 00:26:54,983
ALSO AT THE VERY EARLY DAYS

766
00:26:54,983 --> 00:26:57,051
WANTED TO BE SURE THEY COULD

767
00:26:57,051 --> 00:26:58,720
ADDRESS BIAS AND I DID VERSITY

768
00:26:58,720 --> 00:27:00,488
IN THESE DATA SETS SO THAT IT

769
00:27:00,488 --> 00:27:02,223
WOULD BE BROADLY APPLICABLE TO

770
00:27:02,223 --> 00:27:03,691
THE BROADEST SWATH OF THE HUMANS

771
00:27:03,691 --> 00:27:04,993
WITH THEIR CONDITIONS AND

772
00:27:04,993 --> 00:27:06,527
THEY'VE ACTUALLY PUBLISHED IN

773
00:27:06,527 --> 00:27:07,695
WORK AND DISSEMINATED IT SO IT'S

774
00:27:07,695 --> 00:27:09,364
AVAILABLE FOR ALL TO SEE, BUT

775
00:27:09,364 --> 00:27:11,566
AGAIN THINK BEING BIAS IN THE

776
00:27:11,566 --> 00:27:12,867
EARLIEST PHASES OF THEIR

777
00:27:12,867 --> 00:27:14,969
PROJECTS SUCH THAT THEN AS THEY

778
00:27:14,969 --> 00:27:16,037
DISSEMINATE TO OTHERS, THESE

779
00:27:16,037 --> 00:27:18,573
TOOLS TO ADDRESS OR IDENTIFY AI

780
00:27:18,573 --> 00:27:20,008
OR MACHINE LEARNING BIAS, CAN

781
00:27:20,008 --> 00:27:24,712
THEN BE USED TO REDUCE THOSE

782
00:27:24,712 --> 00:27:25,747
CONQUENCES WE SEE.

783
00:27:25,747 --> 00:27:27,415
SO IN MY LAST FEW MINUTES I WANT

784
00:27:27,415 --> 00:27:28,349
TO BUST A MYTH.

785
00:27:28,349 --> 00:27:29,684
WE DO NEED TO BUST THE MYTH THAT

786
00:27:29,684 --> 00:27:30,885
BLACK PEOPLE AND OTHER PEOPLE OF

787
00:27:30,885 --> 00:27:33,354
COLOR DO NOT WANT TO PARTICIPATE

788
00:27:33,354 --> 00:27:34,856
IN CLINICAL TRIALS.

789
00:27:34,856 --> 00:27:35,890
THERE'S GREAT RESHAPING AND

790
00:27:35,890 --> 00:27:37,892
FRAMING OF THIS, AND TO, IT'S

791
00:27:37,892 --> 00:27:39,494
REALLY ABOUT WHO IS BEING

792
00:27:39,494 --> 00:27:42,597
OFFERED THE OPPORTUNITY TO

793
00:27:42,597 --> 00:27:43,898
ACTUALLY PARTICIPATE, SO BIAS OF

794
00:27:43,898 --> 00:27:44,866
OTHER PATIENTS SAYING THEY WILL

795
00:27:44,866 --> 00:27:45,833
BE A DIFFICULT PATIENT, THEY

796
00:27:45,833 --> 00:27:47,869
WILL NOT WANT TO DO ALL THESE I

797
00:27:47,869 --> 00:27:48,836
THINK THISS, PRECLUDED

798
00:27:48,836 --> 00:27:50,004
CLINICIANS FROM EVEN OFFERING

799
00:27:50,004 --> 00:27:54,876
THESE INDIVIDUALS TO

800
00:27:54,876 --> 00:27:55,176
PARTICIPATE.

801
00:27:55,176 --> 00:27:55,977
SO A META-ANALYSIS OF THESE

802
00:27:55,977 --> 00:27:57,979
STUDIES HAVE SHOWN THAT WHEN

803
00:27:57,979 --> 00:28:00,715
ASKED, AT LEAST HALF

804
00:28:00,715 --> 00:28:01,249
PARTICIPANTS OFFER, WOULD

805
00:28:01,249 --> 00:28:04,452
PARTICIPANT IN A CANCER CLINICAL

806
00:28:04,452 --> 00:28:05,019
TRIAL.

807
00:28:05,019 --> 00:28:08,256
AND AGAIN, BLACK, HISPANIC AND

808
00:28:08,256 --> 00:28:09,357
ASIAN PARTIC PLAN TO ANALYZE BY

809
00:28:09,357 --> 00:28:11,926
AGES ENGAGED AT LEAST AS HIGH AS

810
00:28:11,926 --> 00:28:12,727
WHITE PATIENTS.

811
00:28:12,727 --> 00:28:14,595
SO WE TALK ABOUT ADDRESSING BIAS

812
00:28:14,595 --> 00:28:17,999
IN IT AND WE NEED TO HAVE THE

813
00:28:17,999 --> 00:28:19,967
POPULATION TO RECRUITED INTO THE

814
00:28:19,967 --> 00:28:21,269
STUDY FOR US TO TRAIN THE MODEL

815
00:28:21,269 --> 00:28:23,371
BUT WE NEED TO EVERYCOME THAT.

816
00:28:23,371 --> 00:28:25,907
ANOTHER BIG BARRIER WAS BEING

817
00:28:25,907 --> 00:28:27,442
RANDOMLY ASSIGNED IN THE CONTROL

818
00:28:27,442 --> 00:28:29,610
TRIAL, NOBODY WANTED TO THE

819
00:28:29,610 --> 00:28:32,246
PLACEBO, THEY WERE GOING TO DO

820
00:28:32,246 --> 00:28:34,248
THE GOOD DRUG, NOT THAT MY

821
00:28:34,248 --> 00:28:35,450
HEALTHCARE OF SUFFER WHILE I'M

822
00:28:35,450 --> 00:28:36,084
IN THIS STUDY.

823
00:28:36,084 --> 00:28:37,719
AND IF YOU LOOK AT THE NUMBERS

824
00:28:37,719 --> 00:28:39,454
HERE, THE PHYSICIANS MAY NOT

825
00:28:39,454 --> 00:28:40,555
OFFER THE TRIAL TO PATIENTS OUT

826
00:28:40,555 --> 00:28:42,123
OF CONCERN OF A NUMBER OF THINGS

827
00:28:42,123 --> 00:28:44,225
BUT THIS BECOMES A BARRIER IN

828
00:28:44,225 --> 00:28:44,926
RECRUITING THESE DIVERSE NUMBERS

829
00:28:44,926 --> 00:28:46,360
TO SHOW HOW THE CLINICAL TRIAL

830
00:28:46,360 --> 00:28:49,297
ON YOUR DRUG OR THERAPY COULD

831
00:28:49,297 --> 00:28:50,832
AFFECT THE GREATER SWATH OF

832
00:28:50,832 --> 00:28:52,100
HUMANITY AND JUST TO CLOSE OUT

833
00:28:52,100 --> 00:28:54,535
THIS GREAT QUOTE FROM THE NEW

834
00:28:54,535 --> 00:28:55,503
ENGLAND JOURNAL OF MEDICINE THAT

835
00:28:55,503 --> 00:28:57,004
ANOTHER THING WE NEED TO THINK

836
00:28:57,004 --> 00:28:58,506
ABOUT IS EQUALLY IMPORTANT

837
00:28:58,506 --> 00:29:00,575
MAKING MEDICINE A MORE

838
00:29:00,575 --> 00:29:01,876
ANTIRACIST FIELD THEN YOU CAN

839
00:29:01,876 --> 00:29:03,511
HAVE THOSE CLINICIANS THAT WILL

840
00:29:03,511 --> 00:29:04,545
APPROACH ALL THEIR PATIENTS TO

841
00:29:04,545 --> 00:29:07,348
TRY TO RECRUIT THEM AND AGAIN

842
00:29:07,348 --> 00:29:08,850
THIS INVOLVES REVISITING OW

843
00:29:08,850 --> 00:29:10,585
CLINICIAN SAYS CONCEPT ALLIZE

844
00:29:10,585 --> 00:29:11,419
RACE TO BEGIN WITH.

845
00:29:11,419 --> 00:29:12,854
I'M NOT A CLINICIAN BUT I WANT

846
00:29:12,854 --> 00:29:14,222
TO DROP THESE OUT THERE SO WE

847
00:29:14,222 --> 00:29:16,758
CAN GET THE MORE DIVERSE

848
00:29:16,758 --> 00:29:17,759
RESEARCH AND CLINICAL TEAMS TOO

849
00:29:17,759 --> 00:29:18,726
SPEAK TO ALL HUMANS.

850
00:29:18,726 --> 00:29:20,561
HOW DO YOU RECRUIT A TEAM?

851
00:29:20,561 --> 00:29:22,563
HAPPY TO TALK ABOUT THAT, I HAVE

852
00:29:22,563 --> 00:29:23,898
A FEW STRATEGIES I USED OVER MY

853
00:29:23,898 --> 00:29:25,133
CAREER BUT I LOOK FORWARD TO

854
00:29:25,133 --> 00:29:30,204
DISCUSS THAT WITH THE PANEL. 

855
00:29:30,204 --> 00:29:31,072
THANK YOU.

856
00:29:31,072 --> 00:29:35,276
>> THANK YOU SO MUCH DR.
PLATT.

857
00:29:35,276 --> 00:29:41,783
>> OUR LAST SPEAKER IS DR.
SAMS

858
00:29:41,783 --> 00:29:44,385
SON GABREAB, I ALWAYS PRONOUNCE

859
00:29:44,385 --> 00:29:48,389
IT WRONG, I APOLOGIZE. 

860
00:29:48,389 --> 00:29:50,391
PROGRAM LEAD DATA SCIENCE

861
00:29:50,391 --> 00:29:50,992
TECHNOLOGY.

862
00:29:50,992 --> 00:29:53,594
HE JOINED OBSSR AS ITS CALLED IN

863
00:29:53,594 --> 00:29:56,464
2022 TO LEAD NIH'S ARTIFICIAL

864
00:29:56,464 --> 00:29:58,166
INTELLIGENCE MACHINE LEARNING

865
00:29:58,166 --> 00:29:59,600
CONSORTIUM TO ADVANCE HEALTH

866
00:29:59,600 --> 00:30:01,469
EQUITY AND RESEARCH DIVERSITY

867
00:30:01,469 --> 00:30:03,604
FOR AIM AHEAD.

868
00:30:03,604 --> 00:30:04,672
IN THIS ROLE, HE'S RESPONSIBLE

869
00:30:04,672 --> 00:30:06,874
FOR THE OVERALL MANAGEMENT,

870
00:30:06,874 --> 00:30:09,043
OVERSIGHT, COORDINATION AND

871
00:30:09,043 --> 00:30:09,911
IMPLEMENTATION OF AIM-AHEAD

872
00:30:09,911 --> 00:30:10,978
PROGRAM AND INSURING THE

873
00:30:10,978 --> 00:30:13,281
BENEFITS OF BIG DATA AND

874
00:30:13,281 --> 00:30:17,351
ARTIFICIAL INTELIENCE AND

875
00:30:17,351 --> 00:30:18,052
MACHINE LEARNING TECHNOLOGIES

876
00:30:18,052 --> 00:30:28,563
REACH ACROSS ALL POPULATIONS. 

877
00:30:33,134 --> 00:30:33,868
DR. GABREAB.

878
00:30:33,868 --> 00:30:34,468
>> GOOD AFTERNOON,
EVERYONE.

879
00:30:34,468 --> 00:30:35,670
THANK YOU SO MUCH AND YOU SEE

880
00:30:35,670 --> 00:30:40,908
THE SLIDES VERY WELL?

881
00:30:40,908 --> 00:30:41,742
>> YES.

882
00:30:41,742 --> 00:30:42,977
>> YES, THANK YOU.

883
00:30:42,977 --> 00:30:43,477
>> THANK YOU.

884
00:30:43,477 --> 00:30:47,014
YES SO DR. BERTAGNOLLI, AND

885
00:30:47,014 --> 00:30:49,984
JENNIFER AND MANU HAS COVERED

886
00:30:49,984 --> 00:30:52,553
MOST OF MY TALK ACTUALLY BUT I

887
00:30:52,553 --> 00:30:53,487
WILL TRY MY BEST.

888
00:30:53,487 --> 00:31:03,965
IT'S A TOUGH ACT TO FOLLOW.

889
00:31:05,833 --> 00:31:08,769
SO AS YOU HAVE SEEN FROM THE

890
00:31:08,769 --> 00:31:10,738
TALK FROM  JENNIFER AND MANU,

891
00:31:10,738 --> 00:31:12,440
THAT IT'S WIDELY USED IN THE

892
00:31:12,440 --> 00:31:15,042
HEALTHCARE, BUT WE HAVE TO

893
00:31:15,042 --> 00:31:17,011
REMEMBER THAT YOU KNOW THE

894
00:31:17,011 --> 00:31:18,980
CURRENT AI SYSTEMS ARE

895
00:31:18,980 --> 00:31:22,383
VULNERABLE TO THE LONG STANDING

896
00:31:22,383 --> 00:31:28,189
SYSTEMIC SOCIAL AND HEALTH

897
00:31:28,189 --> 00:31:28,489
INIQUITIES.

898
00:31:28,489 --> 00:31:29,824
WITHOUT CONSIDERING EQUITY AND

899
00:31:29,824 --> 00:31:31,025
DIVERSITY AND INCLUSION, THE

900
00:31:31,025 --> 00:31:32,226
DEVELOPMENT AND THE DEPLOYMENT

901
00:31:32,226 --> 00:31:35,129
OF AI IN THE HEALTHCARE IS GOING

902
00:31:35,129 --> 00:31:38,199
TO BE   PERPETUATED GIVEN

903
00:31:38,199 --> 00:31:39,400
EXACERBATED AT A LARGE SCALE.

904
00:31:39,400 --> 00:31:45,973
AND YOU HAVE SEEN

905
00:31:45,973 --> 00:31:46,707
DR. BERTAGNOLLI MENTIONING THE

906
00:31:46,707 --> 00:31:49,310
SCIENCE RESEARCH WHICH WAS

907
00:31:49,310 --> 00:31:54,248
PUBLISHED BY DR. OPEN MIER WHO

908
00:31:54,248 --> 00:31:55,182
HIGHLIGHTS AN ALEGORITHMS USING

909
00:31:55,182 --> 00:31:58,286
IT AS A HEGHT CARE PROXY FOR

910
00:31:58,286 --> 00:32:00,488
HEGHT CARE NEEDS AND CONCLUDED

911
00:32:00,488 --> 00:32:06,060
PLAQUE PATIENTS ARE HEALTHIER

912
00:32:06,060 --> 00:32:07,261
COMPARED TO EQUALLY SEEK

913
00:32:07,261 --> 00:32:07,762
[INDISCERNIBLE].

914
00:32:07,762 --> 00:32:12,266
AS A RESULT THIS LED TO

915
00:32:12,266 --> 00:32:13,200
 FEWER

916
00:32:13,200 --> 00:32:14,235
RESOURCES AND LOWER QUALITY CARE

917
00:32:14,235 --> 00:32:15,970
TO BLACK PATIENTS WHICH

918
00:32:15,970 --> 00:32:17,972
COMPOUNDED THE EXISTING HEALTHY

919
00:32:17,972 --> 00:32:19,473
CARE RESOURCES NEEDED AND THIS

920
00:32:19,473 --> 00:32:22,143
IS THE KIND OF BIAS THAT WE ARE

921
00:32:22,143 --> 00:32:25,780
TALKING ABOUT IN TERMS OF MAKING

922
00:32:25,780 --> 00:32:28,182
SURE THAT TO MITIGATE BECAUSE

923
00:32:28,182 --> 00:32:30,685
THE CURRENT HEALTHCARE SYSTEM IS

924
00:32:30,685 --> 00:32:36,090
ALREADY, YOU KNOW BIASED AND HAS

925
00:32:36,090 --> 00:32:38,092
SYSTEMIC ISSUES.

926
00:32:38,092 --> 00:32:41,262
SO WHAT DO WE NEED, YOU KNOW IN

927
00:32:41,262 --> 00:32:42,997
ORDER TO MITIGATE THOSE BIAS.

928
00:32:42,997 --> 00:32:46,000
I WILL COVER SOME OF THE, YOU

929
00:32:46,000 --> 00:32:47,101
KNOW POTENTIAL BIAS OR DIFFERENT

930
00:32:47,101 --> 00:32:49,036
BIAS THAT ARE EXISTED WITHIN THE

931
00:32:49,036 --> 00:32:49,303
SYSTEM.

932
00:32:49,303 --> 00:32:51,372
SOME OF THEM COVERED BY MANU BUT

933
00:32:51,372 --> 00:32:55,009
1 OF IT IS THE

934
00:32:55,009 --> 00:32:55,710
UNDERREPRESENTATIVE CLINICAL

935
00:32:55,710 --> 00:32:57,044
CARE DATA AND WE HAVE ALSO LACK

936
00:32:57,044 --> 00:32:59,847
OF DIVERSITY IN THE AI

937
00:32:59,847 --> 00:33:01,949
WORKFORCE, AND ADOPTION OF AI

938
00:33:01,949 --> 00:33:03,451
TECHNOLOGY IN THE DIVERSE

939
00:33:03,451 --> 00:33:03,751
COMMUNITIES.

940
00:33:03,751 --> 00:33:05,086
ONE THINK THIS I WANT TO

941
00:33:05,086 --> 00:33:06,053
HIGHLIGHT SPECIFICALLY THAT WAS

942
00:33:06,053 --> 00:33:10,224
NOT HIGHLIGHTED IS THE LACK OF

943
00:33:10,224 --> 00:33:11,559
DATA IN LIVED EXPERIENCE

944
00:33:11,559 --> 00:33:12,994
ESPECIALLY IN SOCIAL

945
00:33:12,994 --> 00:33:14,028
DETERMINANTS OF HEALTH.

946
00:33:14,028 --> 00:33:17,198
FOR EXAMPLE IN JAMA, HIGHLIGHTED

947
00:33:17,198 --> 00:33:19,500
MISSION LEARNING MODULES THAT

948
00:33:19,500 --> 00:33:20,434
INCORPORATE SOCIAL DETERMINANTS

949
00:33:20,434 --> 00:33:23,504
OF HEALTH IMPROVED THE

950
00:33:23,504 --> 00:33:24,872
PREDICTION OF IN HOSPITAL

951
00:33:24,872 --> 00:33:26,640
MOTILITY AMONG PATIENTS WITH

952
00:33:26,640 --> 00:33:29,944
HEALTHCARE, PARTICULARLY BLACK

953
00:33:29,944 --> 00:33:31,245
PATIENTS, THIS HIGHLIGHTS THAT

954
00:33:31,245 --> 00:33:32,146
INTEGRATING SOCIAL DETERMINE

955
00:33:32,146 --> 00:33:33,748
NABTS OF HEALTH INTO THE AI

956
00:33:33,748 --> 00:33:36,283
MODEL TO MORE EFFECTIVE BUT ALSO

957
00:33:36,283 --> 00:33:38,919
EQUITABLE AND INCLUSIVE

958
00:33:38,919 --> 00:33:41,255
HEALTHCARE SOLUTION BUT THOSE

959
00:33:41,255 --> 00:33:43,991
SOCIAL DETERMINANTS ARE ARE

960
00:33:43,991 --> 00:33:45,393
MOSTLY CAPTURED IN OUR

961
00:33:45,393 --> 00:33:47,895
HEALTHCARE SYSTEM, AND MANU

962
00:33:47,895 --> 00:33:50,364
COVERED SOME OF THAT IN ADDITION

963
00:33:50,364 --> 00:33:52,066
TO THOSE SOME OF THAT BIAS ALSO

964
00:33:52,066 --> 00:33:55,803
COMES IN HOW WE ANALYZE, HOW WE

965
00:33:55,803 --> 00:33:58,773
INTERPRET ALSO, THE ALGORITHM OR

966
00:33:58,773 --> 00:34:02,376
THE IMPLEMENT IN HEALTHCARE

967
00:34:02,376 --> 00:34:03,110
SYSTEM AS WELL.

968
00:34:03,110 --> 00:34:06,013
SO WHAT IS NIH DOING IN THIS

969
00:34:06,013 --> 00:34:10,217
REGARD TO OTHERS, THE BIAS IN AI

970
00:34:10,217 --> 00:34:14,321
THAT ALSO MITIGATE THE HEALTH

971
00:34:14,321 --> 00:34:16,557
DISPARITY, IN JULY 2024, NIH

972
00:34:16,557 --> 00:34:18,192
LEADERSHIP HELD A RETIRED Y'ALL

973
00:34:18,192 --> 00:34:24,899
FORM BY BRINGING DIFFERENT 

974
00:34:24,899 --> 00:34:29,170
STAKEHOLDERS WITH ADDRESSING

975
00:34:29,170 --> 00:34:31,505
HEALTH DISPARITY AND MANY

976
00:34:31,505 --> 00:34:32,106
HISTORICALLY UNDERREPRESENTED

977
00:34:32,106 --> 00:34:34,175
COMMUNITIES AND RESEARCHERS HAVE

978
00:34:34,175 --> 00:34:39,747
NOT BEEN ENGAGED IN THE

979
00:34:39,747 --> 00:34:41,015
INFRASTRUCTURE OR DEVELOPMENT,

980
00:34:41,015 --> 00:34:43,918
AND RECOGNIZING THIS, THE NIH

981
00:34:43,918 --> 00:34:47,555
LAUNCHED A FLAGSHIP PROGRAM

982
00:34:47,555 --> 00:34:50,524
CALLED THE ARTIFICIAL

983
00:34:50,524 --> 00:34:51,959
INTELLIGENCE MACHINE LEARNING

984
00:34:51,959 --> 00:34:54,028
CONSORTIUM TO ADVANCE HEALTH

985
00:34:54,028 --> 00:34:57,431
EQUITY RESEARCHER DIVERSITY ALSO

986
00:34:57,431 --> 00:34:57,865
KNOWN AS AIM-AHEAD.

987
00:34:57,865 --> 00:35:00,234
US ON 3 AREAS ISSUES FIRST IS TO

988
00:35:00,234 --> 00:35:02,169
INCREASE PARTICIPATION AND

989
00:35:02,169 --> 00:35:04,638
REPRESENTATION OF RESEARCHERS

990
00:35:04,638 --> 00:35:05,172
AND COMMUNITIES CURENTDLY

991
00:35:05,172 --> 00:35:05,806
UNDERREPRESENTED IN THE

992
00:35:05,806 --> 00:35:07,208
DEVELOPMENT BUT ALSO IN THE USE

993
00:35:07,208 --> 00:35:07,842
OF AI.

994
00:35:07,842 --> 00:35:10,678
THE PROGRAM ALSO PROVIDES

995
00:35:10,678 --> 00:35:12,847
RESEARCH OPPORTUNITIES FOR

996
00:35:12,847 --> 00:35:14,849
INVESTIGATORS TO ADDRESS HEALTH

997
00:35:14,849 --> 00:35:16,817
DISPARITY BY REFERAGEING AI AND

998
00:35:16,817 --> 00:35:17,952
ALSO ELECTRONIC HEALTH RECORDS

999
00:35:17,952 --> 00:35:22,523
AND OTHER DATA SET LIKE SOCIAL

1000
00:35:22,523 --> 00:35:23,457
DETERMINANTS OF HEALTH.

1001
00:35:23,457 --> 00:35:26,994
ALSO IMPROVE THE CAPABILITIES

1002
00:35:26,994 --> 00:35:30,664
AND TECHNOLOGIES FOR COMMUNITIES

1003
00:35:30,664 --> 00:35:33,334
AND STATISTICIANS TO SHARE THE

1004
00:35:33,334 --> 00:35:36,137
EMERGING TECHNOLOGY AND USE OF

1005
00:35:36,137 --> 00:35:37,438
AI/ML IN HEALTH DISPARITY.

1006
00:35:37,438 --> 00:35:39,840
SO IN THE LAST 2 YEARS, THE

1007
00:35:39,840 --> 00:35:41,275
PROGRAM IS IN THE THIRD YEARS,

1008
00:35:41,275 --> 00:35:42,476
IN THE LAST YEARS WE ARE PROUD

1009
00:35:42,476 --> 00:35:46,780
TO SAY THAT THE PROGRAM HAS

1010
00:35:46,780 --> 00:35:48,949
SUPPORTED OVER 274 DIVERSE

1011
00:35:48,949 --> 00:35:50,351
RESEARCHERS AND INSTITUTIONS TO

1012
00:35:50,351 --> 00:35:51,852
OTHERS AND GAPS IN RESEARCH

1013
00:35:51,852 --> 00:35:53,721
DIVERSITY BUT ALSO ADDRESS BIAS

1014
00:35:53,721 --> 00:35:55,456
IN AI IN DATA AND ADVANCED

1015
00:35:55,456 --> 00:35:56,557
CANNED WHAT.

1016
00:35:56,557 --> 00:35:58,859
SOME OF THOSE ARE -- SOME OF

1017
00:35:58,859 --> 00:36:00,661
THOSE ARE IN 4 KEY AREAS, WE

1018
00:36:00,661 --> 00:36:03,797
HAVE 3 FELLOWSHIP PROGRAMS, THEY

1019
00:36:03,797 --> 00:36:05,633
ARE LEADERSHIP, FELLOWSHIP WHICH

1020
00:36:05,633 --> 00:36:07,701
TRIES TO TRAIN NEXT GENERATION

1021
00:36:07,701 --> 00:36:10,404
LEADERS TO CHAMPION AI ML IN

1022
00:36:10,404 --> 00:36:12,573
HEALTHCARE INSTITUTION AND

1023
00:36:12,573 --> 00:36:13,207
FEDERAL INSTITUTION BUT ALSO

1024
00:36:13,207 --> 00:36:17,077
SHAPE THE POLARIZED SIGHS AROUND

1025
00:36:17,077 --> 00:36:19,513
AI ML, AND THE ALSO RESEARCH

1026
00:36:19,513 --> 00:36:20,548
FELLOWSHIP WHICH TRIES TO TRAIN

1027
00:36:20,548 --> 00:36:22,650
THE NEXT GENERATION IN HELT CARE

1028
00:36:22,650 --> 00:36:24,185
RESEARCHERS IN USING

1029
00:36:24,185 --> 00:36:27,988
[INDISCERNIBLE] AND LEVERAGING

1030
00:36:27,988 --> 00:36:30,491
AI TO OTHERS [INDISCERNIBLE] AND

1031
00:36:30,491 --> 00:36:32,793
THEN RECENTLY WE ALSO LAUNCHED

1032
00:36:32,793 --> 00:36:37,865
THE CLINICIAN  FELLOWSHIP WHICH

1033
00:36:37,865 --> 00:36:38,465
IS TARGETING AND EMPOWERING

1034
00:36:38,465 --> 00:36:39,767
BROAD RANGE OF CLINICIANS IN THE

1035
00:36:39,767 --> 00:36:42,503
SPACE OF AI AND HEALTH

1036
00:36:42,503 --> 00:36:42,770
DISPARITY.

1037
00:36:42,770 --> 00:36:44,939
WE ALSO THINK IN ENGAGING THE

1038
00:36:44,939 --> 00:36:46,807
COMMUNITY IS ESSENTIAL TO

1039
00:36:46,807 --> 00:36:49,910
DEVELOPING AI APPLICATION THAT

1040
00:36:49,910 --> 00:36:52,846
ADVANCED DID THAT ALSO INCLUSIVE

1041
00:36:52,846 --> 00:36:55,849
SO WE ENGAGE THROUGH HUB

1042
00:36:55,849 --> 00:36:57,017
SPECIFIC PILOT PROGECS AND WE

1043
00:36:57,017 --> 00:36:59,320
ALSO HAVE A LARGE CONSORTIUM

1044
00:36:59,320 --> 00:37:02,489
PROJECT THAT ARE

1045
00:37:02,489 --> 00:37:03,624
MULTIDISCIPLINARY THAT BRINGS

1046
00:37:03,624 --> 00:37:07,261
COLLABORATIVE INVESTIGATOR FROM

1047
00:37:07,261 --> 00:37:08,095
DIFFERENT DISCIPLINE TO ADVANCE

1048
00:37:08,095 --> 00:37:09,964
IN THE HEALTH DISPARITIES BUT

1049
00:37:09,964 --> 00:37:13,400
ALSO ADVANCE, WE HAVE ALSO SOME

1050
00:37:13,400 --> 00:37:16,837
PROGRAMS LIKE THE BUILDING FOR

1051
00:37:16,837 --> 00:37:19,907
EXAMPLE, THE PROGRAM FOR

1052
00:37:19,907 --> 00:37:21,342
[INDISCERNIBLE], WHICH TRY TO

1053
00:37:21,342 --> 00:37:22,543
[INDISCERNIBLE] LOWER RESOURCE

1054
00:37:22,543 --> 00:37:25,012
INSTITUTION BY PROVIDING

1055
00:37:25,012 --> 00:37:29,516
FUNDING, TRAINING, GRANT

1056
00:37:29,516 --> 00:37:30,584
WRITING, COLLABORATION, TO HOST

1057
00:37:30,584 --> 00:37:32,386
TEAMS FOR THIS PROJECT AND FOR

1058
00:37:32,386 --> 00:37:33,887
GRANTS AS WELL.

1059
00:37:33,887 --> 00:37:36,290
IN ADDITION, WE HAVE ALSO

1060
00:37:36,290 --> 00:37:39,026
LAUNCHED A COLLABORATION WITH

1061
00:37:39,026 --> 00:37:43,631
THE NIH PROGRAMS LIKE ALL OF US

1062
00:37:43,631 --> 00:37:46,100
AND NCATS, TO INCREASE

1063
00:37:46,100 --> 00:37:46,934
RESEARCHERS DIVERSITY BY

1064
00:37:46,934 --> 00:37:49,703
LEVERAGING DATA SET THAT WAS,

1065
00:37:49,703 --> 00:37:54,074
YOU KNOW CAPTURED BY US AND ALSO

1066
00:37:54,074 --> 00:37:55,943
BY LIBERATING THE INFRASTRUCTURE

1067
00:37:55,943 --> 00:37:58,445
AND TRAINING COMPONENT AND ALSO

1068
00:37:58,445 --> 00:38:03,250
THE PROGRAM HAS THIS CALLED

1069
00:38:03,250 --> 00:38:04,485
[INDISCERNIBLE] PLATFORM THAT

1070
00:38:04,485 --> 00:38:06,120
TRIED TO CONNECT MENTORS AND

1071
00:38:06,120 --> 00:38:09,623
MENTEES SO THAT TO INTERACT AND

1072
00:38:09,623 --> 00:38:11,592
DISCUSS IN THE SPACE OF AI

1073
00:38:11,592 --> 00:38:12,559
HEALTH DISPARITY AND THE PROGRAM

1074
00:38:12,559 --> 00:38:16,096
HAS OVER CLOSE TO 5000 TOTAL

1075
00:38:16,096 --> 00:38:16,530
MEMBERS.

1076
00:38:16,530 --> 00:38:21,969
OUT OF THIS ARE OVER 2600 ARE

1077
00:38:21,969 --> 00:38:24,938
MENTEES, OVER 1430 OR MENTORS

1078
00:38:24,938 --> 00:38:29,810
AND THEN THEY ARE ACROSS THE

1079
00:38:29,810 --> 00:38:30,444
1700 INSTITUTIONS.

1080
00:38:30,444 --> 00:38:31,945
THE PROGRAM IS HIGHLY VISIBLE

1081
00:38:31,945 --> 00:38:34,381
AND IN FACT IT WAS ESSENTIALLY

1082
00:38:34,381 --> 00:38:35,949
MENINGED BY THE PRESIDENT JOE

1083
00:38:35,949 --> 00:38:37,985
BIDEN EXECUTIVE ORDER ON THE

1084
00:38:37,985 --> 00:38:40,621
SAFE SECURE AND TRUSTWORTHY

1085
00:38:40,621 --> 00:38:42,923
DEVELOPMENT OF USE OF ARTIFICIAL

1086
00:38:42,923 --> 00:38:44,325
INTELLIGENCE WHICH SPECIFICALLY

1087
00:38:44,325 --> 00:38:46,327
CALLS THE PROGRAM TO ACCELERATE

1088
00:38:46,327 --> 00:38:49,930
GRANTS, BUT ALSO TO SHOWCASE

1089
00:38:49,930 --> 00:38:57,671
ACTIVITIES IN UNDERSERVED

1090
00:38:57,671 --> 00:38:57,971
COMMUNITIES.

1091
00:38:57,971 --> 00:39:01,208
SO AS I MENTIONED IT, THE

1092
00:39:01,208 --> 00:39:04,078
INCLUSIVE COMMUNITIES FROM UNDER

1093
00:39:04,078 --> 00:39:05,579
REPRESENTED VERY IMPORTANT IN

1094
00:39:05,579 --> 00:39:07,815
ORDER TO MITIGATE THE BIAS AND

1095
00:39:07,815 --> 00:39:09,783
THE HEALTH DISPARITY THAT WE

1096
00:39:09,783 --> 00:39:12,353
HAVE BEEN SHOWING EARLIER, AND 1

1097
00:39:12,353 --> 00:39:13,687
EXAMPLE THAT I WANT TO HIGHLIGHT

1098
00:39:13,687 --> 00:39:16,990
IS THAT THE PROGRAM IS ENGAGING

1099
00:39:16,990 --> 00:39:19,626
OR WORKING IN PARTNERSHIP WITH

1100
00:39:19,626 --> 00:39:21,261
LOCAL COMPANY, A CLINIC TRYING

1101
00:39:21,261 --> 00:39:25,833
TO EMPOWER AND ENGAGE THE

1102
00:39:25,833 --> 00:39:27,668
COMMUNITIES FROM BERMING HAM

1103
00:39:27,668 --> 00:39:34,241
ALABAMA AND THIS ENGAGEMENT, THE

1104
00:39:34,241 --> 00:39:35,542
[INDISCERNIBLE] IDEAS FOR AIML

1105
00:39:35,542 --> 00:39:38,379
COULD BE USED TO HELP IMPACT

1106
00:39:38,379 --> 00:39:39,380
TOPICS OF THEIR CHOICE.

1107
00:39:39,380 --> 00:39:41,949
YOU CAN CLICK IT IN THE VIDEO ON

1108
00:39:41,949 --> 00:39:43,450
THESE SLIDES WHICH WILL BE

1109
00:39:43,450 --> 00:39:44,284
AVAILABLE TO YOU AND YOU WILL

1110
00:39:44,284 --> 00:39:48,422
SEE THAT YOU WILL BE INSPIRED BY

1111
00:39:48,422 --> 00:39:49,923
THE COMMUNITY'S PARTICIPATION

1112
00:39:49,923 --> 00:39:54,928
AND TRYING TO EMPOWER THEMSELVES

1113
00:39:54,928 --> 00:39:56,697
AND IDENTIFY AND ASK WHERE THEY

1114
00:39:56,697 --> 00:40:02,269
CAN SEE THE POTENTIAL BENEFIT

1115
00:40:02,269 --> 00:40:04,304
FOR THEIR HEALTH.

1116
00:40:04,304 --> 00:40:07,841
WE HAVE ALSO ANOTHER COMMUNITY

1117
00:40:07,841 --> 00:40:09,143
ENGAGEMENT WITH --

1118
00:40:09,143 --> 00:40:10,878
>> MAY I ASK, DO YOU HAVE
MANY

1119
00:40:10,878 --> 00:40:12,880
MORE SLIDES AFTER THIS?

1120
00:40:12,880 --> 00:40:14,281
>> I HAVE 1 SLIDE AFTER
THAT.

1121
00:40:14,281 --> 00:40:16,383
>> I HAVE 1 SLIDE AFTER
THAT.

1122
00:40:16,383 --> 00:40:17,785
>> ONE SLIDE, OKAY, THANK
YOU.

1123
00:40:17,785 --> 00:40:20,988
>> WE HAVE A SMALL
BUSINESS PART

1124
00:40:20,988 --> 00:40:23,857
MERSHIP, AND PARTNERSHIP WITH

1125
00:40:23,857 --> 00:40:27,428
SMALL BUSINESS CLINIC TRYING

1126
00:40:27,428 --> 00:40:37,671
DEVELOP A CHAT BOT THAT USES

1127
00:40:37,671 --> 00:40:39,773
LEARNING AND WITH SCHEDULES AND

1128
00:40:39,773 --> 00:40:41,074
BEHAVIOR THAT WILL POSITIVELY

1129
00:40:41,074 --> 00:40:41,909
AFFECT THOSE COMMUNITIES AS WELL

1130
00:40:41,909 --> 00:40:43,877
AND 1 OF THE PROBLEM THAT WE SEE

1131
00:40:43,877 --> 00:40:44,745
IN THE LOWER RESOURCE

1132
00:40:44,745 --> 00:40:47,381
INSTITUTION IS THAT THERE IS A

1133
00:40:47,381 --> 00:40:50,284
DIGITAL DIVIDE AND THE PROGRAM

1134
00:40:50,284 --> 00:40:52,686
IS TRYING TO [INDISCERNIBLE]

1135
00:40:52,686 --> 00:40:55,656
ACCESS TO DATA AND ESPECIALLY

1136
00:40:55,656 --> 00:41:02,296
COLLABORATING WITH NIH SPONSORED

1137
00:41:02,296 --> 00:41:04,565
PROGRAMS LIKE SCHARE, BRIDGE 2

1138
00:41:04,565 --> 00:41:06,500
AI AND ALL OF US, AND ACCESS

1139
00:41:06,500 --> 00:41:08,235
THOSE RESOURCES BUT ALSO TO

1140
00:41:08,235 --> 00:41:10,671
CONDUCT NOBLE RESEARCH AT THE

1141
00:41:10,671 --> 00:41:14,675
INTERSECTION OF AI ML THROUGH

1142
00:41:14,675 --> 00:41:18,111
TRAINING MENTORSHIP AND SERVICE.

1143
00:41:18,111 --> 00:41:19,880
SO TO CLOSING THOUGHTS, DIVERSE

1144
00:41:19,880 --> 00:41:22,716
AND INCLUSIVE AI ARE VERY

1145
00:41:22,716 --> 00:41:25,752
CRUCIAL BECAUSE IT AVOID HARM TO

1146
00:41:25,752 --> 00:41:27,154
THE MARGINALIZED AND

1147
00:41:27,154 --> 00:41:28,722
UNDERREPRESENTED COMMUNITIES BUT

1148
00:41:28,722 --> 00:41:30,691
ALSO NECESSARY STEP TO INCREASE

1149
00:41:30,691 --> 00:41:30,891
TRUST.

1150
00:41:30,891 --> 00:41:33,360
SO I'M GOING TO CLOSE THAT, YOU

1151
00:41:33,360 --> 00:41:36,763
KNOW FOR AI TO BE BENEFICIAL TO

1152
00:41:36,763 --> 00:41:38,866
THE ALL COMMUNITY SLIDE, THE

1153
00:41:38,866 --> 00:41:41,068
DOCTOR MENTIONED IT TO ALL THE

1154
00:41:41,068 --> 00:41:42,569
INITIATIVE, INCLIEWTIONZ OF

1155
00:41:42,569 --> 00:41:44,905
PEOPLE WITH DIVERSE ATTRIBUTES

1156
00:41:44,905 --> 00:41:46,874
AND PERSPECTIVE, ESPECIALLY IN

1157
00:41:46,874 --> 00:41:49,843
DATA COLLECTION USED PROCESS

1158
00:41:49,843 --> 00:41:51,345
SYSTEM AND GOVERNMENTS ACROSS

1159
00:41:51,345 --> 00:41:56,850
THE LIFE CYCLE OF THAT IS VERY

1160
00:41:56,850 --> 00:41:57,117
IMPORTANT.

1161
00:41:57,117 --> 00:41:57,384
THANK YOU.

1162
00:41:57,384 --> 00:42:00,420
IF YOU WANT TO KNOW MORE ABOUT

1163
00:42:00,420 --> 00:42:02,055
THE AI/ML PROGRAM, FEEL FREE TO

1164
00:42:02,055 --> 00:42:04,691
CONTACT ME AND I ENCOURAGE YOU

1165
00:42:04,691 --> 00:42:06,393
TO SUBSCRIBE TO THESE PROGRAMS.

1166
00:42:06,393 --> 00:42:08,128
>> THANK YOU SO MUCH, SO
WE'RE

1167
00:42:08,128 --> 00:42:12,966
NOW GOING TO GO TO OUR Q&A,
WE

1168
00:42:12,966 --> 00:42:16,003
HAVE QUESTIONS THAT CAME TO

1169
00:42:16,003 --> 00:42:17,404
PEOPLE THAT REGISTERED FOR THE

1170
00:42:17,404 --> 00:42:19,439
MEETING, WE HAVE SOME QUESTIONS

1171
00:42:19,439 --> 00:42:20,474
DURING THE PRESENTATIONS, I HOPE

1172
00:42:20,474 --> 00:42:21,909
WE WILL BE ABLE TO GET THROUGH A

1173
00:42:21,909 --> 00:42:23,310
FEW OF THEM BECAUSE I WILL ASK

1174
00:42:23,310 --> 00:42:25,679
EACH OF YOU AS SPEAKERS TO BE AS

1175
00:42:25,679 --> 00:42:29,316
CONCISE AS YOU CAN, BUT AS

1176
00:42:29,316 --> 00:42:31,485
COMPLETE AS POSSIBLE AS WELL, SO

1177
00:42:31,485 --> 00:42:33,153
WE WILL TART OFF WITH A QUESTION

1178
00:42:33,153 --> 00:42:35,222
FOR ALL 3 OF YOU AND I THINK I

1179
00:42:35,222 --> 00:42:37,291
WILL GO IN THE ORDER IN WHICH

1180
00:42:37,291 --> 00:42:39,493
YOU PRESENTED FOR THOSE

1181
00:42:39,493 --> 00:42:40,994
RESPONSES, JUST TO LET THE

1182
00:42:40,994 --> 00:42:42,062
AUDIENCE KNOW, WE'RE SWITCHING

1183
00:42:42,062 --> 00:42:44,231
TO GOING BY FIRST NAMES RATHER

1184
00:42:44,231 --> 00:42:47,267
THAN LAST NAME OR TITLE.

1185
00:42:47,267 --> 00:42:50,370
NOT BEING DISRESPECT OFFUL,

1186
00:42:50,370 --> 00:42:51,371
WE'RE BEING COLLEGIAL HERE

1187
00:42:51,371 --> 00:42:52,306
EMPLOY CAN YOU DESCRIBE ABOUT

1188
00:42:52,306 --> 00:42:54,308
HOW TO THINK ABOUT DATA SCIENCE

1189
00:42:54,308 --> 00:42:55,842
MEASUREMENTS AND OUTCOMES, HOW

1190
00:42:55,842 --> 00:42:57,945
DOES HAVING DIVERSE PERSPECTIVES

1191
00:42:57,945 --> 00:43:01,381
HELP CREATE BETTER OUTCOMES, SO

1192
00:43:01,381 --> 00:43:06,453
JENNIFER, THEN MANU, THEN

1193
00:43:06,453 --> 00:43:07,354
SAMSON.

1194
00:43:07,354 --> 00:43:07,621
JENNIFER?

1195
00:43:07,621 --> 00:43:09,189
>> YOU KNOW I ALMOST THINK
IT'S

1196
00:43:09,189 --> 00:43:13,160
IN THE TITLE, THE  TITLE OF THIS

1197
00:43:13,160 --> 00:43:16,396
WAS HOW CAN OR DO DIVERSE  

1198
00:43:16,396 --> 00:43:17,097
PERPECTIVES ENHANCE DATA

1199
00:43:17,097 --> 00:43:18,231
SCIENCE, I THINK THEY DO ENHANCE

1200
00:43:18,231 --> 00:43:20,334
IT, AND THEY DO IT IN A VARIETY

1201
00:43:20,334 --> 00:43:22,169
OF WAYS BUT NOT THE LEAST OF

1202
00:43:22,169 --> 00:43:23,470
WHICH IS WHEN PEOPLE COLLABORATE

1203
00:43:23,470 --> 00:43:24,972
ACROSS FIELDS WITH DIFFERENT

1204
00:43:24,972 --> 00:43:26,807
EXPERIENCE, DIFFERENT LIVED

1205
00:43:26,807 --> 00:43:27,841
EXPERIENCE, DIFFERENT EXPERTISE,

1206
00:43:27,841 --> 00:43:31,645
ALL OF THAT, SO THEY CHALLENGE

1207
00:43:31,645 --> 00:43:32,479
EACH OTHER'S ASSUMPTIONS AND

1208
00:43:32,479 --> 00:43:34,548
EXPLAIN THINGS IN WAYS THEY

1209
00:43:34,548 --> 00:43:35,649
WOULDN'T NORMALLY DO, AND IN

1210
00:43:35,649 --> 00:43:38,452
DOING THAT, I THINK YOU GET AT

1211
00:43:38,452 --> 00:43:42,189
SOME OF THE THINGS THAT WOULD

1212
00:43:42,189 --> 00:43:45,158
TRAVEL ON THROUGH DATA SCIENCE

1213
00:43:45,158 --> 00:43:48,328
OUTCOMES WHEN PEOPLE WORK ALONE

1214
00:43:48,328 --> 00:43:58,872
OR DON'T CHALLENGE THE ORIGINAL

1215
00:44:00,407 --> 00:44:00,741
ASSUMPTIONS.

1216
00:44:00,741 --> 00:44:02,976
>> WE LIKE THE NUMBERS,
THE

1217
00:44:02,976 --> 00:44:05,512
NUMBERS TELL US THE TRUTH, AND

1218
00:44:05,512 --> 00:44:07,481
WHEN I LEARN ABOUT SOCIAL

1219
00:44:07,481 --> 00:44:08,915
DETERMINANTS OF HEALTH AND THESE

1220
00:44:08,915 --> 00:44:12,953
OTHER DRIVING FACTORS THAT CAN

1221
00:44:12,953 --> 00:44:14,121
CAUSE A HEALTHCARE OUTCOME THAT

1222
00:44:14,121 --> 00:44:16,323
IF YOU WERE NOT LOOKING AT THE

1223
00:44:16,323 --> 00:44:17,958
NUMBER, YOU MIGHT NOT KNOW WHAT

1224
00:44:17,958 --> 00:44:21,528
1 WAS NEEDED TO INVESTIGATE THAT

1225
00:44:21,528 --> 00:44:23,096
WAS DRIVING AN OUTCOME.

1226
00:44:23,096 --> 00:44:24,665
SO THAT'S 1 EXAMPLE OF HOW

1227
00:44:24,665 --> 00:44:26,166
DIVERSITY OR THOSE TEAMS HELP

1228
00:44:26,166 --> 00:44:27,467
YOU THINK ABOUT WHAT'S HAPPENING

1229
00:44:27,467 --> 00:44:29,069
WITH REAL PEOPLE VERSUS JUST

1230
00:44:29,069 --> 00:44:30,137
WHAT THE NUMBER SAY BECAUSE THEY

1231
00:44:30,137 --> 00:44:32,806
WILL SAY WHAT YOU WANT THEM TO

1232
00:44:32,806 --> 00:44:34,207
SAY, DEPENDING ON THE CONFINE

1233
00:44:34,207 --> 00:44:36,410
THAT YOU PUT AROUND THEM, SO

1234
00:44:36,410 --> 00:44:37,377
OTHER PEOPLE TO CHALLENGE THOSE

1235
00:44:37,377 --> 00:44:38,545
THOUGHTS AND HOW THEY ARRIVE

1236
00:44:38,545 --> 00:44:40,847
THERE I THINK IS WHAT THEN MAKE

1237
00:44:40,847 --> 00:44:44,484
ITS A ROBUST FINDING.

1238
00:44:44,484 --> 00:44:46,019
>> YEAH, JUST WANT TO ADD
THAT I

1239
00:44:46,019 --> 00:44:49,089
THINK TO ME, THE MOST IMPORTANT

1240
00:44:49,089 --> 00:44:51,291
IS DIVERSITY ASK INCLUSION

1241
00:44:51,291 --> 00:44:52,526
ACROSS THE BOARD IS VERY

1242
00:44:52,526 --> 00:44:52,826
IMPORTANT.

1243
00:44:52,826 --> 00:44:55,829
WHEN I SAY ACROSS THE BOARD, OF

1244
00:44:55,829 --> 00:45:01,001
THE LIFE CYCLE OF AI, BUT

1245
00:45:01,001 --> 00:45:01,568
INCLUDING THE PEOPLE.

1246
00:45:01,568 --> 00:45:02,769
WHEN I SAY PEOPLE FOR EXAMPLE,

1247
00:45:02,769 --> 00:45:05,972
YOU KNOW IF WE WANT TO CREATE A

1248
00:45:05,972 --> 00:45:07,207
TECHNOAND SOCIAL AI ML, WE NEED

1249
00:45:07,207 --> 00:45:10,243
TO INCLUDE PEOPLE NOT ONLY

1250
00:45:10,243 --> 00:45:11,378
TECHNICAL OR MATHEMATICALLY,

1251
00:45:11,378 --> 00:45:13,113
VERSUS PEOPLE BUT ALSO PEOPLE

1252
00:45:13,113 --> 00:45:16,416
FROM BEHAVIORIAL AND SOCIAL AND

1253
00:45:16,416 --> 00:45:17,250
EVEN HISTORY ANTHROPOLOGISTS

1254
00:45:17,250 --> 00:45:20,487
MAINLY TO BE THERE TO PROVIDE A

1255
00:45:20,487 --> 00:45:21,121
DIFFERENT DIMENSION, DIFFERENT

1256
00:45:21,121 --> 00:45:22,155
PERSPECTIVE ALSO AND TO THE

1257
00:45:22,155 --> 00:45:24,224
OTHER HING IS A LIVED EXPERIENCE

1258
00:45:24,224 --> 00:45:25,692
ALSO VERY IMPORTANT.

1259
00:45:25,692 --> 00:45:28,095
PEOPLE BRING THEIR DIFFERENT

1260
00:45:28,095 --> 00:45:29,996
BACKGROUND, DIFFERENT

1261
00:45:29,996 --> 00:45:30,964
PERSPECTIVE AND CULTURE AND TRY

1262
00:45:30,964 --> 00:45:33,366
TO SOLVE A PROBLEM, SO

1263
00:45:33,366 --> 00:45:34,401
DIVERSITY'S INCLUSION IS VERY

1264
00:45:34,401 --> 00:45:36,136
IMPORTANT AND IT'S VERY

1265
00:45:36,136 --> 00:45:39,106
IMPORTANT AND WE SHOULD

1266
00:45:39,106 --> 00:45:40,640
EMPHASIZE, LOCATION, LOCATION,

1267
00:45:40,640 --> 00:45:41,575
DIVERSITY, DIVERSITY AND

1268
00:45:41,575 --> 00:45:42,743
INCLUSION IS VERY IMPORTANT.

1269
00:45:42,743 --> 00:45:47,614
NTHANK 

1270
00:45:47,614 --> 00:45:47,748
-

1271
00:45:47,748 --> 00:45:50,317
>> THANK YOU VERY MUCH.

1272
00:45:50,317 --> 00:45:52,185
SO JENNIFER, DO THE SAND PITS

1273
00:45:52,185 --> 00:45:54,054
FOCUS ON A SPECIFIC PROBLEM?

1274
00:45:54,054 --> 00:45:56,656
HOW DOES THE NCI INSURE THE DATA

1275
00:45:56,656 --> 00:45:58,258
PRIVACY AND SECURITY CONCERNS

1276
00:45:58,258 --> 00:46:03,663
ARE ATTENDED TO AND OF COURSE

1277
00:46:03,663 --> 00:46:06,399
THE SCIENCE SCIENCE VERIFICATION

1278
00:46:06,399 --> 00:46:06,767
EFFORTS?

1279
00:46:06,767 --> 00:46:08,568
>> A LOT BUNDLED INTO THAT

1280
00:46:08,568 --> 00:46:09,269
QUESTION.

1281
00:46:09,269 --> 00:46:10,470
THE SAND PITS ADDRESS AN AREA OF

1282
00:46:10,470 --> 00:46:11,671
SCIENCE AND WHAT THEY'RE REALLY

1283
00:46:11,671 --> 00:46:14,407
DESIGNED TO DO IS BRING PEOPLE

1284
00:46:14,407 --> 00:46:15,509
FROM DIFFERENT DISCIPLINES

1285
00:46:15,509 --> 00:46:17,644
TOGETHER AROUND A SORT OF SHARED

1286
00:46:17,644 --> 00:46:19,079
INTEREST SO THE 1 I SHOWED IS

1287
00:46:19,079 --> 00:46:20,247
ACTUALLY SPONSORED BY THE OFFICE

1288
00:46:20,247 --> 00:46:22,382
OF DATA SCIENCE HERE AT THE NIH

1289
00:46:22,382 --> 00:46:27,254
AND RUN TOGETHER WITH THE NCI

1290
00:46:27,254 --> 00:46:29,689
AROUND QUANTUM COMPUTING AND

1291
00:46:29,689 --> 00:46:30,757
COMPLICATED RESEARCH QUESTIONS,

1292
00:46:30,757 --> 00:46:30,957
RIGHT?

1293
00:46:30,957 --> 00:46:35,495
BUT THEY CAN BE AROUND ANY SORT

1294
00:46:35,495 --> 00:46:36,596
OF SCIENCE, SCOPING THEM IS

1295
00:46:36,596 --> 00:46:37,864
REALLY TRICK EXPE I THINK THE

1296
00:46:37,864 --> 00:46:43,103
SECOND PART OF THAT QUESTION IS

1297
00:46:43,103 --> 00:46:45,071
AROUND PROTECTING PROTECTING

1298
00:46:45,071 --> 00:46:46,106
PRIVATE PRIVACY AND CITIZEN

1299
00:46:46,106 --> 00:46:47,941
SCIENCE AND COMMUNITY SCIENCE.

1300
00:46:47,941 --> 00:46:48,341
>> YES.

1301
00:46:48,341 --> 00:46:49,309
>> AND THAT'S A TRICKY 1
AND I

1302
00:46:49,309 --> 00:46:54,114
THINK IN A VARIETY OF DIFFERENT

1303
00:46:54,114 --> 00:46:54,381
WAYS.

1304
00:46:54,381 --> 00:46:56,183
BUT IN THE SAME WAY PRIVACY IS

1305
00:46:56,183 --> 00:46:57,384
PROECTOMYOSIN ITED AND HOPEFULLY

1306
00:46:57,384 --> 00:46:58,218
MAYBE SOMEBODY IN THE AUDIENCE

1307
00:46:58,218 --> 00:46:59,820
HERE IS FROM ALL OF US AND CAN

1308
00:46:59,820 --> 00:47:01,555
ANSWER THAT QUESTION BETTER THAN

1309
00:47:01,555 --> 00:47:03,790
I CAN, BUT IN BIG PROGRAMS LIKE

1310
00:47:03,790 --> 00:47:06,693
THAT, THEY HAVE METHODS TO DEAL

1311
00:47:06,693 --> 00:47:07,761
WITH THE PRIVACY CONCERNS BUT

1312
00:47:07,761 --> 00:47:09,629
WHAT I WAS ALLUDED TO ALSO IS

1313
00:47:09,629 --> 00:47:13,066
THAT IT DOESN'T JUST ABOUT DATA

1314
00:47:13,066 --> 00:47:15,569
COLLECTION, IT'S AROUND THE

1315
00:47:15,569 --> 00:47:18,972
CREATIVITY AND CAPABILITIES THAT

1316
00:47:18,972 --> 00:47:21,241
PEOPLE, THE PUBLIC COMMUNITIES,

1317
00:47:21,241 --> 00:47:22,442
PATIENTS WHOEVER HAVE WHEN THEY

1318
00:47:22,442 --> 00:47:23,510
THINK ABOUT ADDRESSING PROBLEMS,

1319
00:47:23,510 --> 00:47:25,912
SO THAT CAN BE EITHER AN

1320
00:47:25,912 --> 00:47:27,881
IDENTIFYING QUESTIONS OR HELPING

1321
00:47:27,881 --> 00:47:30,116
WITH ANALYSIS, OR PROVIDING

1322
00:47:30,116 --> 00:47:33,787
CONTEXT AS WELLsA PROVIDING

1323
00:47:33,787 --> 00:47:34,054
DATA.

1324
00:47:34,054 --> 00:47:37,691
-- AS WELL AS PROVIDING DATA.

1325
00:47:37,691 --> 00:47:40,093
>> SO MANU, DO YOU HAVE
PRACTICE

1326
00:47:40,093 --> 00:47:41,294
EXAMPLES TO SHARE INVOLVING

1327
00:47:41,294 --> 00:47:43,029
PERSONS WITH LIVED EXPERIENCE,

1328
00:47:43,029 --> 00:47:45,265
CLINICIANS AND OTHER

1329
00:47:45,265 --> 00:47:46,132
STAKEHOLDERS IN ACTIVITIES

1330
00:47:46,132 --> 00:47:48,969
DESIGNED TO ENHANCE USE OF

1331
00:47:48,969 --> 00:47:50,136
REPRESENTATIVE DATA, INCLUSION

1332
00:47:50,136 --> 00:47:52,138
AND CLINICAL TRIALS AND IN

1333
00:47:52,138 --> 00:47:54,207
DETECTING AND ADDRESSING MODEL

1334
00:47:54,207 --> 00:47:55,242
BIASES, PARTICULARLY WITH

1335
00:47:55,242 --> 00:47:57,210
AFFECTED GROUPS WHO HAVE LESS

1336
00:47:57,210 --> 00:48:00,647
STATISTICAL OR DATA LITERACY?

1337
00:48:00,647 --> 00:48:02,949
>> SO I HAVEN'T AN EXAMPLE
THAT

1338
00:48:02,949 --> 00:48:04,484
IS NOT AS MUCH OF THE BIG DATA

1339
00:48:04,484 --> 00:48:05,552
COLLECTION PART BUT I THINK IT

1340
00:48:05,552 --> 00:48:07,988
DOES GIVE AN EXAMPLE OF HOW YOU

1341
00:48:07,988 --> 00:48:08,622
INCLUDE EFFECTIVE POPULATIONS

1342
00:48:08,622 --> 00:48:10,023
INTO THE WORK YOU DO.

1343
00:48:10,023 --> 00:48:12,092
AGAIN, I REALLY HAVE A LOT ON

1344
00:48:12,092 --> 00:48:12,959
HIV/AIDS BUT I REALLY WANT TO

1345
00:48:12,959 --> 00:48:15,395
TALK ABOUT MY TIME IN GEORGIA,

1346
00:48:15,395 --> 00:48:17,264
SICKLE CELL DISEASE IS A MAJOR

1347
00:48:17,264 --> 00:48:18,698
AREA OF RESEARCH OF ME AND I

1348
00:48:18,698 --> 00:48:20,800
BEGAN A PARTNER OF THE SICKLE

1349
00:48:20,800 --> 00:48:22,068
CELL FOUNDATION OF GEORGIA,

1350
00:48:22,068 --> 00:48:23,136
NUMBER 1 RECRUITING AND

1351
00:48:23,136 --> 00:48:25,105
SUPPLYING BLOOD TO US BUT AGAIN

1352
00:48:25,105 --> 00:48:26,406
IT IS BREAKING OUT OF THE

1353
00:48:26,406 --> 00:48:27,340
SCIENTIFIC QUESTION THAT WE WILL

1354
00:48:27,340 --> 00:48:29,276
NEED THE BLOOD TO DO OUR

1355
00:48:29,276 --> 00:48:31,278
ANALYSIS BACK HOME AND GET

1356
00:48:31,278 --> 00:48:32,412
NUMBERS VERSUS REALLY STARTING

1357
00:48:32,412 --> 00:48:33,747
TO TALK TO THE PEOPLE LIVING

1358
00:48:33,747 --> 00:48:34,881
WITH SICK ELITE EXECUTIVE IS

1359
00:48:34,881 --> 00:48:36,216
DISEASE AND WHAT'S INTERESTING

1360
00:48:36,216 --> 00:48:38,585
TO FIND OUT IS HOW MUCH THEY RUN

1361
00:48:38,585 --> 00:48:39,719
THEIR OWN TESTS ON THEMSELVES

1362
00:48:39,719 --> 00:48:41,955
AND TRY TO GET BETTER AND

1363
00:48:41,955 --> 00:48:42,722
THEY'RE TRACKING THEIR OWN

1364
00:48:42,722 --> 00:48:44,891
PERSONAL HEALTH, EATING WHAT THE

1365
00:48:44,891 --> 00:48:46,026
WEATHER PATTERNINGS LOOK LIKE

1366
00:48:46,026 --> 00:48:47,761
AND SEVERAL OTHER THINGS THAT

1367
00:48:47,761 --> 00:48:48,962
THEY'RE COLLECTING TO FIND OUT

1368
00:48:48,962 --> 00:48:49,996
WHAT WORKS BEST FOR THEM.

1369
00:48:49,996 --> 00:48:51,798
SO I THINK ABOUT THAT IN THE

1370
00:48:51,798 --> 00:48:52,465
SPACE OF PERSONALIZED MEDICINE

1371
00:48:52,465 --> 00:48:54,634
AND THINKING ABOUT PATES WITH

1372
00:48:54,634 --> 00:48:56,069
RANGES IN DISEASE SEVERITY,

1373
00:48:56,069 --> 00:48:57,570
BRINGING THEM ONLINE GAVE US NEW

1374
00:48:57,570 --> 00:48:59,739
THINGS THAT WE WANTED TO MEASURE

1375
00:48:59,739 --> 00:49:01,975
AND OUR BLOOD SAMPLES OR IN OUR

1376
00:49:01,975 --> 00:49:03,176
MOUSE MODELS BECAUSE SOME OF THE

1377
00:49:03,176 --> 00:49:05,278
THINGS WE WERE IDENTIFYING WERE

1378
00:49:05,278 --> 00:49:07,013
CRITICAL POINTS AGAIN IN L OWN

1379
00:49:07,013 --> 00:49:09,182
SMALLER NUMBERS THEY WERE

1380
00:49:09,182 --> 00:49:10,450
COLLECTING REALLY BEGAN TO DRIVE

1381
00:49:10,450 --> 00:49:11,718
INTERESTING QUESTIONS FOR US,

1382
00:49:11,718 --> 00:49:13,253
BUT ON THE FLIP SIDE, ALSO

1383
00:49:13,253 --> 00:49:15,188
SPEAKING WITH THEM ABOUT HOW

1384
00:49:15,188 --> 00:49:16,957
COMFORTABLE WERE THEY IN SHARING

1385
00:49:16,957 --> 00:49:18,591
OTHER DATA WE MIGHT WANT TO

1386
00:49:18,591 --> 00:49:19,993
COLLECT PARTICULARLY WHEN IF GOT

1387
00:49:19,993 --> 00:49:21,995
TO DOWN TO GENOME SEQUENCING OR

1388
00:49:21,995 --> 00:49:23,430
OTHER THINGS WHICH AGAIN IF YOU

1389
00:49:23,430 --> 00:49:25,165
SAY, WHAT, OF COURSE, THEY

1390
00:49:25,165 --> 00:49:26,066
BELIEVE IN SCIENCE, THEY WILL

1391
00:49:26,066 --> 00:49:28,034
GIVE US THIS INFORMATION, DEVOID

1392
00:49:28,034 --> 00:49:29,369
OF ACTUALLY HAVING TO TALK TO

1393
00:49:29,369 --> 00:49:31,404
THE HUMANS THAT IT IMPACTS THAT

1394
00:49:31,404 --> 00:49:32,839
IT ACTUALLY CAN CHANGE ABOUT HOW

1395
00:49:32,839 --> 00:49:34,174
IT APPROACHES NEW RECRUITS OR

1396
00:49:34,174 --> 00:49:36,142
JUST WHAT DATA DO YOU ACTUALLY

1397
00:49:36,142 --> 00:49:37,877
NEED THAT YOU COULD GET A

1398
00:49:37,877 --> 00:49:39,079
BROADER AMOUNT FROM THIS

1399
00:49:39,079 --> 00:49:39,980
COMMUNITY THAT'S AFFECTED AND

1400
00:49:39,980 --> 00:49:41,348
THAT COULD THEN DRIVE THE

1401
00:49:41,348 --> 00:49:42,983
SCIENCE FURTHER.

1402
00:49:42,983 --> 00:49:44,317
SO AGAIN, IT ALWAYS SHOCKS ME

1403
00:49:44,317 --> 00:49:46,219
AGAIN AS A Ph.D., I LEARN

1404
00:49:46,219 --> 00:49:47,420
THINGS AND TALK TO CLINICIANS

1405
00:49:47,420 --> 00:49:51,791
BUT I LEARN MORE WHEN I TALK TO

1406
00:49:51,791 --> 00:49:52,692
THE AFFECTED POPULATIONS ABOUT

1407
00:49:52,692 --> 00:49:55,462
HOW THEY COULD HELPED AND THE

1408
00:49:55,462 --> 00:49:56,997
NUMBERS GENERATED AGAINST THEM

1409
00:49:56,997 --> 00:49:57,998
OR FOR THEM.

1410
00:49:57,998 --> 00:49:58,565
>> GREAT.

1411
00:49:58,565 --> 00:50:01,468
SO THIS NEXT QUESTION WAS

1412
00:50:01,468 --> 00:50:02,635
ADDRESSED TO YOU SAMSON BUT MANU

1413
00:50:02,635 --> 00:50:05,271
YOU MAY WANT TO WEIGH IN ON THIS

1414
00:50:05,271 --> 00:50:06,573
1 AS WELL, GIVEN YOUR RESPONSE

1415
00:50:06,573 --> 00:50:08,641
TO THE QUESTION JUST ASKED,

1416
00:50:08,641 --> 00:50:10,043
THERE'S UNDERSTANDABLY BEEN A

1417
00:50:10,043 --> 00:50:13,046
LOT OF DISCUSSION OF BIAS AND

1418
00:50:13,046 --> 00:50:14,848
ALGORITHMS AND DATA SETS,

1419
00:50:14,848 --> 00:50:16,049
HOWEVER, INDIVIDUAL RESEARCHERS

1420
00:50:16,049 --> 00:50:17,751
PHYSICIANS, ET CETERA HAVE THEIR

1421
00:50:17,751 --> 00:50:18,218
OWN BIASES.

1422
00:50:18,218 --> 00:50:20,787
ARE THERE WAYS THAT AI TOOLS CAN

1423
00:50:20,787 --> 00:50:22,622
ACTUALLY BE USED TO OVERCOME

1424
00:50:22,622 --> 00:50:23,923
BIAS IN RESEARCH OR CLINICAL

1425
00:50:23,923 --> 00:50:24,224
PRACTICE.

1426
00:50:24,224 --> 00:50:28,795
I WILL ASK YOU TO START SAMSON,

1427
00:50:28,795 --> 00:50:30,530
AND THEN MANU, AND THEN YOU

1428
00:50:30,530 --> 00:50:30,930
JENNIFER.

1429
00:50:30,930 --> 00:50:31,965
I WOULD LIKE ALL 3 OF YOU TO

1430
00:50:31,965 --> 00:50:34,401
WEIGH IN ON THAT.

1431
00:50:34,401 --> 00:50:40,340
>> YEAH, SO I THINK THERE
ARE 2

1432
00:50:40,340 --> 00:50:42,308
KINDS OF 1S, MANU MENTIONED IT,

1433
00:50:42,308 --> 00:50:47,047
ALSO THERE IS THE HEMABIAS, I

1434
00:50:47,047 --> 00:50:49,215
SOCIAL BIAS AS WELL AND I DON'T

1435
00:50:49,215 --> 00:50:53,453
KNOW IF WE CAN YOU KNOW AT THAT

1436
00:50:53,453 --> 00:50:54,120
TIMISTICALLY OR MATHEMATICALLY

1437
00:50:54,120 --> 00:50:55,488
SOLVE ALL THE BIASES AND SOME OF

1438
00:50:55,488 --> 00:50:58,758
THE BIASES THAT WE NEED TO BRING

1439
00:50:58,758 --> 00:51:01,061
A DIFFERENT KIND OF PEOPLE,

1440
00:51:01,061 --> 00:51:04,130
LIKE, YOU KNOW DIVERSE PEOPLE

1441
00:51:04,130 --> 00:51:06,332
WITH DIVERSE DISCIPLINE, AND

1442
00:51:06,332 --> 00:51:09,569
DIVERSE PERSPECTIVE TO, YOU KNOW

1443
00:51:09,569 --> 00:51:13,673
ADDRESS SOME OF THAT, YOU KNOW

1444
00:51:13,673 --> 00:51:15,708
UNCONSCIOUS BIAS [INDISCERNIBLE]

1445
00:51:15,708 --> 00:51:18,445
IN THE DEVELOPMENT OF AI AND

1446
00:51:18,445 --> 00:51:20,947
DESIGN AND IN DEVELOPMENT OF AI

1447
00:51:20,947 --> 00:51:21,347
AS WELL.

1448
00:51:21,347 --> 00:51:24,717
SO WE NEED TO HAVE LIKE A

1449
00:51:24,717 --> 00:51:25,985
PERSPECTIVE, YOU KNOW AND

1450
00:51:25,985 --> 00:51:27,087
INCLUSIVE AND DIVERSE PEOPLE,

1451
00:51:27,087 --> 00:51:29,022
BUT ALSO SOME OF THAT BIAS IS

1452
00:51:29,022 --> 00:51:32,158
DUE TO GET US AT, YOU KNOW FOR

1453
00:51:32,158 --> 00:51:33,960
EXAMPLE, THE SOCIAL

1454
00:51:33,960 --> 00:51:34,928
DETERMINANTS, MAY NOT BE

1455
00:51:34,928 --> 00:51:36,129
CAPTURED THERE AND IF WE DON'T

1456
00:51:36,129 --> 00:51:37,530
INCLUDE THEM IN THE AI MODEL

1457
00:51:37,530 --> 00:51:39,866
THEY MAY NOT BE EQUITABLE EVEN

1458
00:51:39,866 --> 00:51:41,835
THOUGH THE ALGORITHM ITSELF IS

1459
00:51:41,835 --> 00:51:44,304
WELL BUILT AND WELL DESIGNED

1460
00:51:44,304 --> 00:51:48,508
BECAUSE IT WASN'T INCLUDING THE

1461
00:51:48,508 --> 00:51:49,542
[INDISCERNIBLE], SOMETIMES IT

1462
00:51:49,542 --> 00:51:52,979
MAY NOT BE EQUITABLE, IT MAY NOT

1463
00:51:52,979 --> 00:51:56,015
BE BENEFICIAL TO THE PEOPLE YOU

1464
00:51:56,015 --> 00:51:56,749
ARE TRYING TO HELP.

1465
00:51:56,749 --> 00:51:59,419
SO WE HAVE TO LOOK AT IN TERMS

1466
00:51:59,419 --> 00:52:02,122
OF STATISTICAL BUT ALSO IN TERMS

1467
00:52:02,122 --> 00:52:03,523
OF THE SOCIAL BIAS POINT.

1468
00:52:03,523 --> 00:52:08,928
>> MANU WOULD YOU LIKE TO
ADD TO

1469
00:52:08,928 --> 00:52:11,698
THAT? YOU'VE ON MUTE.

1470
00:52:11,698 --> 00:52:12,499
>> JUST REALIZED THAT.

1471
00:52:12,499 --> 00:52:16,803
YEAH, I HAVE TO TAKE A SECOND.

1472
00:52:16,803 --> 00:52:18,171
UNCONSCIOUS BIAS AS WE KNOW IS

1473
00:52:18,171 --> 00:52:19,806
IMEAN WITH THE HUMAN AND PERSON

1474
00:52:19,806 --> 00:52:23,009
WHO'S PUTTING IT IN.

1475
00:52:23,009 --> 00:52:24,777
I DON'T HAVE A GREAT ANSWER FOR

1476
00:52:24,777 --> 00:52:26,346
YOU BUT 1 THING YOU NEED ON THIS

1477
00:52:26,346 --> 00:52:28,681
TEAM IS YOU NEED A SKEPTIC WITH

1478
00:52:28,681 --> 00:52:29,616
THE TRUE BELIEVER BECAUSE YOU DO

1479
00:52:29,616 --> 00:52:31,684
WANT A TRUE BELIEVER TO BELIEVE

1480
00:52:31,684 --> 00:52:34,187
IN THE TECHNOLOGY TO PUSH IT TO

1481
00:52:34,187 --> 00:52:35,955
ITS LIMITED AND SHOW ALL THE

1482
00:52:35,955 --> 00:52:37,123
OPPORTUNITIES FOR IT, BUT YOU

1483
00:52:37,123 --> 00:52:39,092
NEED A KEPTIC TO KIND OF BLUNT

1484
00:52:39,092 --> 00:52:43,129
THAT TO WHAT IS ACTUALLY

1485
00:52:43,129 --> 00:52:49,569
BELIEVABLE THAT WE COULD CELS

1486
00:52:49,569 --> 00:52:53,806
AND 1 THING THAT'S USEFUL THERE

1487
00:52:53,806 --> 00:52:54,674
CONGRESSALLY MEDICAL DIRECTED

1488
00:52:54,674 --> 00:52:56,576
RESEARCH PROGRAM FUNDED THROUGH

1489
00:52:56,576 --> 00:52:57,877
D.O.D., IN THEIR REVIEW PANELS

1490
00:52:57,877 --> 00:52:59,512
THEY HAVE A PEASHT ADVOCATE FOR

1491
00:52:59,512 --> 00:53:01,014
EACH OF THE DIFFERENT DISEASES

1492
00:53:01,014 --> 00:53:02,315
WHICH CAN CUT THROUGH WHAT THE

1493
00:53:02,315 --> 00:53:03,683
RESEARCHER MAY HAVE AND IT'S A

1494
00:53:03,683 --> 00:53:05,251
GREAT IDEA AND THEY'RE LIKE,

1495
00:53:05,251 --> 00:53:07,153
OKAY, BUT WAIT, WHO'S GOING TO

1496
00:53:07,153 --> 00:53:07,954
BUY THAT, RIGHT?

1497
00:53:07,954 --> 00:53:09,455
AND THEY WANT OBVIOUSLY THE

1498
00:53:09,455 --> 00:53:11,057
CURES AND THE TECHNOLOGY TO MOVE

1499
00:53:11,057 --> 00:53:13,092
FORWARD BECAUSE THEY HAVE BEEN A

1500
00:53:13,092 --> 00:53:14,894
SURVIVOR OF THAT ILLNESS, BUT

1501
00:53:14,894 --> 00:53:16,996
LET'S BE REAL ABOUT WHAT IT CAN

1502
00:53:16,996 --> 00:53:17,163
DO.

1503
00:53:17,163 --> 00:53:19,265
SO I THINK THAT'S WHERE YOU NEED

1504
00:53:19,265 --> 00:53:20,533
TO HAVE THOSE DYNAMIC TEAMS

1505
00:53:20,533 --> 00:53:22,635
WHERE YOU BELIEVE IT,

1506
00:53:22,635 --> 00:53:23,703
DEVELOPMENT MATH AND ALGORITHM

1507
00:53:23,703 --> 00:53:25,171
THAT PUSH IT FURTHER AND

1508
00:53:25,171 --> 00:53:26,573
SOMEBODY TO STEP BACK, AND 1

1509
00:53:26,573 --> 00:53:29,075
OTHER PIECE I WOULD LIKE TO ADD

1510
00:53:29,075 --> 00:53:29,676
HERE.

1511
00:53:29,676 --> 00:53:30,977
IN THAT SKEPTICISM OR

1512
00:53:30,977 --> 00:53:32,178
CHALLENGING OPINIONS I THINK

1513
00:53:32,178 --> 00:53:33,680
ABOUT BIG DATA AND THESE STUDIES

1514
00:53:33,680 --> 00:53:35,215
YOU NEED MORE PATIENT SAMPLES,

1515
00:53:35,215 --> 00:53:37,083
YOU NEED MORE PATIENT NUMBERS

1516
00:53:37,083 --> 00:53:39,252
BUT THE CLINICIANS, SEES 1

1517
00:53:39,252 --> 00:53:42,855
PERSON, 1 PATIENT, SO THAT WHOLE

1518
00:53:42,855 --> 00:53:45,558
IN OF 1 AS THAT BEIMAN TO GO,

1519
00:53:45,558 --> 00:53:46,859
THE LARGE MODELS MIGHT HELP

1520
00:53:46,859 --> 00:53:49,329
GUIDE IT BUT IF I'M THE OUTLIER,

1521
00:53:49,329 --> 00:53:52,298
I JUST NEED TO KNOW YOU YOU ARE

1522
00:53:52,298 --> 00:53:54,100
THINKING OF ME AND DIDN'T JUST

1523
00:53:54,100 --> 00:53:54,601
LOOK AT 10,000 PEOPLE.

1524
00:53:54,601 --> 00:53:57,804
SO I THINK IT'S A BALANCING ACT

1525
00:53:57,804 --> 00:53:59,472
ON HOW GETTING MORE DATA WILL,A

1526
00:53:59,472 --> 00:54:01,241
PLIE TO ME UNLESS I'M 1 OF THOSE

1527
00:54:01,241 --> 00:54:01,841
IN THE MIX.

1528
00:54:01,841 --> 00:54:05,778
SO THOSE ARE COMPLICATED ANSWERS

1529
00:54:05,778 --> 00:54:08,181
TO YOUR QUESTION BUT THE WAY OF

1530
00:54:08,181 --> 00:54:09,182
BIAS FOR 1 EMPLOY.

1531
00:54:09,182 --> 00:54:11,150
>> AS A FORMER CLINICIAN,
THAT

1532
00:54:11,150 --> 00:54:13,453
IS A BIG CHALLENGE, HOW DO ALL

1533
00:54:13,453 --> 00:54:17,991
THESE DATA, PLIE TO THIS 1

1534
00:54:17,991 --> 00:54:19,192
INDIVIDUAL.

1535
00:54:19,192 --> 00:54:19,692
JENNIFER?

1536
00:54:19,692 --> 00:54:21,261
>> AS USUAL, I THINK
MANU'S

1537
00:54:21,261 --> 00:54:23,363
THOUGHTS BRING UP A WHOLE LOT OF

1538
00:54:23,363 --> 00:54:24,230
ADDITIONAL THOUGHTS AND

1539
00:54:24,230 --> 00:54:26,065
QUESTIONS, YOU KNOW THIS GETS AT

1540
00:54:26,065 --> 00:54:29,502
THE ROOT OF A LOT OF DIFFICULTY

1541
00:54:29,502 --> 00:54:30,570
OUT THERE, RIGHT WHICH IS PART

1542
00:54:30,570 --> 00:54:32,705
OF IT IS THIS SORT OF HOW DOES

1543
00:54:32,705 --> 00:54:33,640
THE POPULATION SCALE TRANSLATE

1544
00:54:33,640 --> 00:54:36,075
TO THE 1, BUT ALSO, BIAS IS

1545
00:54:36,075 --> 00:54:37,277
EVERYWHERE, IT'S IN THE DATA,

1546
00:54:37,277 --> 00:54:38,778
IT'S IN OUR CURRENT PRACTICE,

1547
00:54:38,778 --> 00:54:42,115
IT'S IN ALL OF US AND THAT SORT

1548
00:54:42,115 --> 00:54:42,715
OF THING.

1549
00:54:42,715 --> 00:54:44,517
THERE WAS MCATS DID AN

1550
00:54:44,517 --> 00:54:46,452
INTERESTING SERIES OF CHALLENGES

1551
00:54:46,452 --> 00:54:49,922
AROUND USING AI PER FOR BIAS

1552
00:54:49,922 --> 00:54:52,025
MITIGATION, IN OTHER WORDS TO

1553
00:54:52,025 --> 00:54:55,428
DETECT BIAS AND THE  ALGORITHMS

1554
00:54:55,428 --> 00:55:01,000
AND THAT SORT OF THING, THERE'S

1555
00:55:01,000 --> 00:55:03,136
OTHER AGENCIES LIKEANIST AROUND

1556
00:55:03,136 --> 00:55:04,604
THEIR FRAMEWORK FOR TRUSTWORTHY

1557
00:55:04,604 --> 00:55:05,872
AI, I AM TRYING TO THINK OF THE

1558
00:55:05,872 --> 00:55:07,540
NAME OF IT, BUT THERE'S A LOT OF

1559
00:55:07,540 --> 00:55:08,641
GUIDANCE OUT THERE TO UPON HAD

1560
00:55:08,641 --> 00:55:10,143
PEOPLE SORT OF THROUGH SOME OF

1561
00:55:10,143 --> 00:55:13,146
THESE, BUT JUST TO GO BACK TO

1562
00:55:13,146 --> 00:55:15,048
SOMETHING I THINK BOTH SAMSON

1563
00:55:15,048 --> 00:55:17,517
AND MANU HAVE SAID, A LOT OF IT

1564
00:55:17,517 --> 00:55:21,521
HAS TO DO WITH WORKING IN TEAMS,

1565
00:55:21,521 --> 00:55:22,255
CHALLENGING ASSUMPTIONS,

1566
00:55:22,255 --> 00:55:23,623
THINKING IT THROUGH FROM A

1567
00:55:23,623 --> 00:55:25,224
VARIETY OF DIFFERENT

1568
00:55:25,224 --> 00:55:25,992
PERSPECTIVES INCLUDING IN THOSE

1569
00:55:25,992 --> 00:55:27,527
CASES WHERE IT'S GOING TO GO

1570
00:55:27,527 --> 00:55:30,330
INTO THE CLINIC, INCLUDING

1571
00:55:30,330 --> 00:55:30,997
PRACTICES THE PATIENT EXPERIENCE

1572
00:55:30,997 --> 00:55:32,165
AND I THINK THAT'S WHY WE'RE

1573
00:55:32,165 --> 00:55:33,599
SEEING MORE AND MORE OF THESE

1574
00:55:33,599 --> 00:55:35,401
CONFERENCES AND SESSIONS AND

1575
00:55:35,401 --> 00:55:37,270
THINGS ON THE WAY THAT PATIENTS

1576
00:55:37,270 --> 00:55:38,671
ARE ALREADY USING AI FOR

1577
00:55:38,671 --> 00:55:40,073
THEMSELVES AND THE WAY THAT

1578
00:55:40,073 --> 00:55:41,808
THEY'RE THINKING ABOUT THEIR OWN

1579
00:55:41,808 --> 00:55:43,443
DATA AND COLLECTING THEIR OWN

1580
00:55:43,443 --> 00:55:45,478
DATA SO THAT'S A REALLY

1581
00:55:45,478 --> 00:55:48,781
INTERESTING AND RAPIDLY EVOLVING

1582
00:55:48,781 --> 00:55:49,449
SPACE, ALSO.

1583
00:55:49,449 --> 00:55:50,950
>> SO THE NEXT QUESTION IS
FOR

1584
00:55:50,950 --> 00:55:53,386
ALL 3 OF YOU, I WILL START WITH

1585
00:55:53,386 --> 00:55:55,021
YOU MANU AND THEN YOU SAM SON

1586
00:55:55,021 --> 00:56:05,565
AND JENNIFER, I JUST GO AROUND. 

1587
00:56:10,236 --> 00:56:13,873
THIS QUESTION IS, --

1588
00:56:13,873 --> 00:56:15,508
>> I THINK 1 THING I'VE
SEEN IN

1589
00:56:15,508 --> 00:56:18,711
OOH H DO, I WAS ON THE OUTSIDE

1590
00:56:18,711 --> 00:56:20,012
18 MONTHS AGO, 19 MONTHS AGO AND

1591
00:56:20,012 --> 00:56:21,781
NOW I'M ON THE INSIDE BUT WHAT

1592
00:56:21,781 --> 00:56:24,217
DOES AMRI BROADLY IS NIH HAS

1593
00:56:24,217 --> 00:56:25,418
BEEN SHARING THEIR DATA

1594
00:56:25,418 --> 00:56:26,686
PRACTICES AND POLICIES BECAUSE 1

1595
00:56:26,686 --> 00:56:28,688
THING I SEE IS LET'S TALL IT

1596
00:56:28,688 --> 00:56:30,890
LET'S SAY AN OUTCOME OF THESE

1597
00:56:30,890 --> 00:56:32,558
PUSHES TO COLLECT LARGER AMOUNTS

1598
00:56:32,558 --> 00:56:35,795
OF DATA WHETHER THEY'RE IN RNA

1599
00:56:35,795 --> 00:56:37,263
SEQ, OR SEQUENCING OR WHATEVER

1600
00:56:37,263 --> 00:56:38,297
WE'RE DOING, 1 RESEARCHER IS

1601
00:56:38,297 --> 00:56:39,832
USING A SMALL PIECE OF THAT DATA

1602
00:56:39,832 --> 00:56:41,467
FOR THEIR GUIDANCE AND STUDIES

1603
00:56:41,467 --> 00:56:44,070
THAT SOMEONE'S COLLECTING A

1604
00:56:44,070 --> 00:56:45,037
REPOSITORY MAYBE DOING

1605
00:56:45,037 --> 00:56:46,205
META-ANALYSIS, BUT THERE IS THAT

1606
00:56:46,205 --> 00:56:49,409
BENEFIT OF MAKING THAT DATA

1607
00:56:49,409 --> 00:56:50,443
AVAILABLE BECAUSE IT PROVIDES

1608
00:56:50,443 --> 00:56:52,311
SOME KIND OF DEMOCRATIZATION OF

1609
00:56:52,311 --> 00:56:54,280
DOING THESE ARTIFICIAL

1610
00:56:54,280 --> 00:56:54,914
IBT--INTEGRATE TELEIGENCE

1611
00:56:54,914 --> 00:56:56,249
ANALYSIS TO SMALLER

1612
00:56:56,249 --> 00:56:58,384
INSTITUTIONS, PLACES THAT CAN

1613
00:56:58,384 --> 00:56:59,285
BUY COMPUTERS AND MAYBE THEY

1614
00:56:59,285 --> 00:57:02,155
CAN'T -- DON'T HAVE THE RESEARCH

1615
00:57:02,155 --> 00:57:02,955
INFRASTRUCTURE TO COLLECT THAT

1616
00:57:02,955 --> 00:57:05,358
DATA BUT WHEN IT ALL BECOMES

1617
00:57:05,358 --> 00:57:07,326
AVAILABLE, WHAT I HEARD A RECENT

1618
00:57:07,326 --> 00:57:08,828
ORCHSHOP I WAS AT.

1619
00:57:08,828 --> 00:57:09,695
AT THE AMERICAN INDIAN SOCIETY

1620
00:57:09,695 --> 00:57:12,131
OR SOMEWHERE ELSE, WHERE THEY

1621
00:57:12,131 --> 00:57:13,199
WANTED DATAAN OITATED BETTER SO

1622
00:57:13,199 --> 00:57:15,701
THAT OTHERS CAN USE IT, AND THEY

1623
00:57:15,701 --> 00:57:17,403
KNOW, SOME OF THE NUANCES THAT

1624
00:57:17,403 --> 00:57:20,606
WERE IN THE POPULATION OR

1625
00:57:20,606 --> 00:57:21,073
TREATMENT POPULATION.

1626
00:57:21,073 --> 00:57:22,241
THE CHALLENGE OF COURSE IS

1627
00:57:22,241 --> 00:57:24,977
PRIVACY BUT IF THEY'RE A WAY TO

1628
00:57:24,977 --> 00:57:25,878
DEIDENTIFIED THAT THEN PEOPLE

1629
00:57:25,878 --> 00:57:27,146
WHO DON'T HAVE TO DO THE

1630
00:57:27,146 --> 00:57:28,381
EXPERIMENT CAN STILL HAVE ACCESS

1631
00:57:28,381 --> 00:57:30,183
TO THAT DATA, I KNOW THAT'S SOME

1632
00:57:30,183 --> 00:57:32,018
OF THE GOALS OF ALL OF US AND

1633
00:57:32,018 --> 00:57:35,855
AIM AHEAD, BUT I'M REALLY FOR

1634
00:57:35,855 --> 00:57:36,923
THAT DEMOCRATIZATION THAN

1635
00:57:36,923 --> 00:57:38,524
TRAYING NEW USERS TO ACCESS THAT

1636
00:57:38,524 --> 00:57:41,727
DAT IN A CHEAPER WAY BECAUSE

1637
00:57:41,727 --> 00:57:44,430
IT'S THE PROCESSING SPEED OPPOSE

1638
00:57:44,430 --> 00:57:46,132
TO THE WET LAB STUFF.

1639
00:57:46,132 --> 00:57:48,334
IT'S 1 WAY TO TOUCH ON IT BUT

1640
00:57:48,334 --> 00:57:53,339
IT'S 1 WAY I THINK ABOUT THAT.

1641
00:57:53,339 --> 00:57:56,709
>> I AGREE WITH MANU, AND
DATA

1642
00:57:56,709 --> 00:57:56,943
SHARING.

1643
00:57:56,943 --> 00:58:00,847
I THINK 1 THING IS THAT HAVING

1644
00:58:00,847 --> 00:58:04,317
DATA  TRANSPARENCY IS VERY

1645
00:58:04,317 --> 00:58:04,717
IMPORTANT.

1646
00:58:04,717 --> 00:58:06,953
SOMETIMES WE DON'T KNOW WHAT

1647
00:58:06,953 --> 00:58:10,590
DATA WE V. RIGHT NOW WE HAVE

1648
00:58:10,590 --> 00:58:13,993
SOME DATA, NCATS, RHETORIC AND

1649
00:58:13,993 --> 00:58:17,029
OTHERS AND HAVING IT IN

1650
00:58:17,029 --> 00:58:18,664
TRANSPARENCY, YOU KNOW

1651
00:58:18,664 --> 00:58:21,534
STANDARDIZED WAY OF SHOWING THAT

1652
00:58:21,534 --> 00:58:24,303
DATA AND AVAILABLE AND ACCESS IT

1653
00:58:24,303 --> 00:58:25,037
TO DIVERSITY RESEARCHERS

1654
00:58:25,037 --> 00:58:27,006
INCLUDING FROM THE LOWER

1655
00:58:27,006 --> 00:58:28,140
RESEARCHERS IS VERY IMPORTANT

1656
00:58:28,140 --> 00:58:30,009
AND ANOTHER THING IS CLOUD

1657
00:58:30,009 --> 00:58:31,777
COMPUTING IS A VERY GREAT

1658
00:58:31,777 --> 00:58:33,980
EQUALIZER IN TERMS OF

1659
00:58:33,980 --> 00:58:35,014
DEMOCRATIZING ACCESS BUT WE NEED

1660
00:58:35,014 --> 00:58:37,850
TO GIVE THAT ACCESS TO THE LOWER

1661
00:58:37,850 --> 00:58:38,985
RESOURCE INSTITUTION AND ALSO

1662
00:58:38,985 --> 00:58:41,554
RESEARCHERS FROM THOSE

1663
00:58:41,554 --> 00:58:42,255
INSTITUTIONS STILL TRAINING.

1664
00:58:42,255 --> 00:58:45,858
IT'S NOT ENOUGH TO SAY THAT, YOU

1665
00:58:45,858 --> 00:58:48,861
KNOW WE HAVE, YOU KNOW WE HAVE

1666
00:58:48,861 --> 00:58:50,496
ACCESS, IT'S HERE, THEY'RE USING

1667
00:58:50,496 --> 00:58:52,365
IT AND IT'S ACCESSIBLE TO YOU.

1668
00:58:52,365 --> 00:58:56,569
BUT WE HAVE TO ALSO SUPPLEMENT

1669
00:58:56,569 --> 00:58:59,739
THESE MENTORSHIP AND ENHANCE

1670
00:58:59,739 --> 00:59:02,375
TRAIN AND ALSO CONSERVE AS WELL,

1671
00:59:02,375 --> 00:59:09,582
FOR THOSE PEOPLE TO BE ABLE TO

1672
00:59:09,582 --> 00:59:17,323
ADDRESS THE ISSUES NOW.

1673
00:59:17,323 --> 00:59:18,291
>> JENNIFER IN.

1674
00:59:18,291 --> 00:59:19,725
>> YEAH, SO 1 THING TO
THINK

1675
00:59:19,725 --> 00:59:22,428
ABOUT IS THAT NOT ALL DATA IS

1676
00:59:22,428 --> 00:59:23,663
PATIENT DATA OR CLINICAL DAT

1677
00:59:23,663 --> 00:59:25,831
RIGHT IN THERE, THERE'S ENORMOUS

1678
00:59:25,831 --> 00:59:26,866
AMOUNT OF DAILY BASIS THEA THAT

1679
00:59:26,866 --> 00:59:27,700
IS GENERATED THROUGH THE COURSE

1680
00:59:27,700 --> 00:59:29,435
OF WORK THAT THE NIH SUPPORTS

1681
00:59:29,435 --> 00:59:31,270
THAT IS OUT THERE IN A VARIETY

1682
00:59:31,270 --> 00:59:33,239
OF DIFFERENT WAY ANDS IS USED BY

1683
00:59:33,239 --> 00:59:36,242
PEOPLE HA DO AI OR OTHER FORMS

1684
00:59:36,242 --> 00:59:38,444
OF DATA SCIENCE TO LAY DOWN SOME

1685
00:59:38,444 --> 00:59:39,178
FOUNDATIONAL KNOWLEDGE AND THAT

1686
00:59:39,178 --> 00:59:40,580
SORT OF THING SO THAT'S A

1687
00:59:40,580 --> 00:59:42,448
DIFFERENT AREA BUT THERE IS A

1688
00:59:42,448 --> 00:59:47,186
LOT OF GUIDANCE AROUND BEING

1689
00:59:47,186 --> 00:59:48,354
DEVELOPED AROUND TRUSTWORTHY AI

1690
00:59:48,354 --> 00:59:50,690
AND THESE SORTS OF THINGS WHEN 1

1691
00:59:50,690 --> 00:59:51,991
IS USING PATIENT DATA AND HOW TO

1692
00:59:51,991 --> 00:59:54,727
SHARE AND HOW TO DO LEARNING

1693
00:59:54,727 --> 00:59:56,729
ACROSS DIFFERENT SITES IN A WAY

1694
00:59:56,729 --> 00:59:57,663
THAT PROTECTS PRIVACY IS ALL

1695
00:59:57,663 --> 00:59:59,432
THAT SORT OF THING SO ALL THAT

1696
00:59:59,432 --> 01:00:01,167
IS SUPPORTED I THINK ACROSS THE

1697
01:00:01,167 --> 01:00:03,502
NIH AND THERE'S LOTS OF DEFINITE

1698
01:00:03,502 --> 01:00:06,038
PUBLICATIONS OUT THERE ON THAT.

1699
01:00:06,038 --> 01:00:10,209
I WILL SAY, TOO, WE THINK A LOT

1700
01:00:10,209 --> 01:00:11,477
ABOUT TRAINING THE NEXT

1701
01:00:11,477 --> 01:00:12,912
GENERATION WORKFORCE BUT THERE'S

1702
01:00:12,912 --> 01:00:16,782
ALSO KIND OF THE ENABLING THE

1703
01:00:16,782 --> 01:00:18,618
CURRENT GENERATION, OF

1704
01:00:18,618 --> 01:00:20,386
WORKFORCE, YOU KNOW TO BE BETTER

1705
01:00:20,386 --> 01:00:22,455
USERS AND MORE THOUGHTFUL USERS

1706
01:00:22,455 --> 01:00:24,624
AND MORE THOUGHTFUL

1707
01:00:24,624 --> 01:00:25,491
COLLABORATORS WITH DATA

1708
01:00:25,491 --> 01:00:27,393
SCIENTISTS AND AI TOOLS IN

1709
01:00:27,393 --> 01:00:30,329
GENERAL, RIGHT IN SO SORT OF

1710
01:00:30,329 --> 01:00:32,031
THINKING THROUGH HOW TO BE

1711
01:00:32,031 --> 01:00:33,566
EFFECTIVE USERS AND

1712
01:00:33,566 --> 01:00:35,701
COLLABORATORS AROUND THIS SPACE

1713
01:00:35,701 --> 01:00:38,037
WILL BE JUST AS USEFUL AND

1714
01:00:38,037 --> 01:00:39,005
PROVIDING REALLY SOLID DATA SETS

1715
01:00:39,005 --> 01:00:42,775
FOR PEOPLE TO WORK ON.

1716
01:00:42,775 --> 01:00:44,276
>> OKAY, THIS IS AN EASY

1717
01:00:44,276 --> 01:00:44,577
QUESTION.

1718
01:00:44,577 --> 01:00:47,413
I WILL START WITH YOU SAMSON,

1719
01:00:47,413 --> 01:00:50,316
AND THEN YOU JENNIFER AND THENUE

1720
01:00:50,316 --> 01:00:50,983
MANU.

1721
01:00:50,983 --> 01:00:52,652
MANU IS SMILING BECAUSE HE KNOWS

1722
01:00:52,652 --> 01:00:53,886
IT IS NOT.

1723
01:00:53,886 --> 01:00:56,088
>> HOW DO WE UNITE
DIFFERENT

1724
01:00:56,088 --> 01:00:57,323
STEM RESEARCH DISCIPLINES

1725
01:00:57,323 --> 01:00:58,791
INCLUDING SOCIAL MAJOR SCIENCES

1726
01:00:58,791 --> 01:01:06,032
SUCH AS ECONOMICS AND

1727
01:01:06,032 --> 01:01:06,632
EPIDEMIOLOGY, PSYCHOLOGY AND

1728
01:01:06,632 --> 01:01:13,806
SOCIOLOGY ON THE FRONTIERS OF

1729
01:01:13,806 --> 01:01:15,975
TODAY'S METHODS?

1730
01:01:15,975 --> 01:01:17,710
SAMSON, SOFTBALL TO YOU?

1731
01:01:17,710 --> 01:01:19,311
>> THIS WE ARE ALREADY
DOING

1732
01:01:19,311 --> 01:01:19,578
THAT.

1733
01:01:19,578 --> 01:01:22,381
WE HAVE FOR EXAMPLE,

1734
01:01:22,381 --> 01:01:23,716
COLLABORATING WITH NCATS, YOU

1735
01:01:23,716 --> 01:01:25,685
KNOW TRAINING TO USE THE NCATS

1736
01:01:25,685 --> 01:01:27,453
DATA, THIS IS THE REAL WORLD

1737
01:01:27,453 --> 01:01:35,194
DATA SET THAT'S BEEN COLLECTING

1738
01:01:35,194 --> 01:01:36,495
THROUGH THE COVID-19 PANDEMIC.

1739
01:01:36,495 --> 01:01:37,563
IT'S VERY HUGE AND WHAT WE'RE

1740
01:01:37,563 --> 01:01:39,632
DOING RIGHT NOW IS WE ARE

1741
01:01:39,632 --> 01:01:43,069
CREATING THIS TEAM SCIENCE

1742
01:01:43,069 --> 01:01:44,136
TRAINING, WE'RE BRINGING DATA

1743
01:01:44,136 --> 01:01:46,138
SCIENCE AND CLINICIANS FROM, AND

1744
01:01:46,138 --> 01:01:47,373
ALSO BIOMEDICAL RESEARCHERS FROM

1745
01:01:47,373 --> 01:01:53,112
STEM, YOU KNOW TOGETHER WORKING

1746
01:01:53,112 --> 01:01:55,081
TO ADDRESS, YOU KNOW, AND

1747
01:01:55,081 --> 01:01:56,916
ADDRESS RESEARCH QUESTIONS OR

1748
01:01:56,916 --> 01:01:59,752
HYPOTHESIS TOGETHER AS A TEAM

1749
01:01:59,752 --> 01:02:01,987
AND YOU KNOW THAT ARE RELATED TO

1750
01:02:01,987 --> 01:02:04,156
HEALTH DISPARITY, SO, YOU KNOW,

1751
01:02:04,156 --> 01:02:07,927
THE FIRST THING THAT WE NEED IS

1752
01:02:07,927 --> 01:02:10,362
TO CREATE THIS COLLABORATIVE OR

1753
01:02:10,362 --> 01:02:13,432
TEAM SCIENCE PROGRAMS AND THAT'S

1754
01:02:13,432 --> 01:02:14,700
WHAT WE'RE WANTING TO DO.

1755
01:02:14,700 --> 01:02:19,038
THE OTHER ALSO WE NEED TO BRING,

1756
01:02:19,038 --> 01:02:24,009
TEACH OUR DIFFERENT DISCIPLINES

1757
01:02:24,009 --> 01:02:24,744
ABOUT COMMUNITY ENGAGEMENT, SO

1758
01:02:24,744 --> 01:02:28,013
THAT AT A CAN LEARN FROM EACH

1759
01:02:28,013 --> 01:02:29,515
OTHER AND START SPEAKING THE

1760
01:02:29,515 --> 01:02:30,483
SAME LANGUAGE AS WELL, SO I

1761
01:02:30,483 --> 01:02:33,919
THINK WE ARE DOING THAT IN THE

1762
01:02:33,919 --> 01:02:35,888
MI PROGRAM, I THINK THE ONLY WAY

1763
01:02:35,888 --> 01:02:39,625
TO DO IT IS TO BRING THEM NOT

1764
01:02:39,625 --> 01:02:41,260
SOLO, BUT BRING OTHER TEAM IN

1765
01:02:41,260 --> 01:02:42,895
AND COLLABORATE WITH TEAM

1766
01:02:42,895 --> 01:02:43,696
SCIENCE.

1767
01:02:43,696 --> 01:02:45,030
>> I'M HAPPY TO HEAR
YOU'RE

1768
01:02:45,030 --> 01:02:46,265
SEEING IT IS EASY.

1769
01:02:46,265 --> 01:02:47,900
I WOULDN'T EXPECT IT TO BE EASY

1770
01:02:47,900 --> 01:02:50,336
TO ACCOMPLISH BUT JENNIFER?

1771
01:02:50,336 --> 01:02:51,637
>> YEAH, YOU GUYS DON'T
LOW BALL

1772
01:02:51,637 --> 01:02:52,938
THE QUESTIONS HERE, DO YOU.

1773
01:02:52,938 --> 01:02:55,341
SO IF THE QUESTION IS HOW DO WE

1774
01:02:55,341 --> 01:02:57,076
UNITE STEM FIELDS AND PULL FROM

1775
01:02:57,076 --> 01:02:58,978
ALL THESE OTHER DISCIPLINES INTO

1776
01:02:58,978 --> 01:02:59,945
BIOMEDICAL RESEARCH, YOU KNOW

1777
01:02:59,945 --> 01:03:01,680
LOTS OF DIFFERENT WAYS, RIGHT IN

1778
01:03:01,680 --> 01:03:02,948
AND I THINK BIOMEDICAL RESEARCH

1779
01:03:02,948 --> 01:03:06,185
HAS LONG KIND OF BROUGHT OTHER

1780
01:03:06,185 --> 01:03:08,687
DISCIPLINES IN, SORT OF AS

1781
01:03:08,687 --> 01:03:09,989
NEEDED FOR METHODS AND

1782
01:03:09,989 --> 01:03:11,090
APPROACHES AND THINKING AND TEAM

1783
01:03:11,090 --> 01:03:13,025
SCIENCE AND THAT SORT OF THING.

1784
01:03:13,025 --> 01:03:14,794
ONE KEY THING IS THINKING ABOUT

1785
01:03:14,794 --> 01:03:16,328
WHAT'S STOPPING IT FROM

1786
01:03:16,328 --> 01:03:16,762
HAPPENING ALREADY.

1787
01:03:16,762 --> 01:03:18,998
SO IF IT'S AN AREA LIKE,

1788
01:03:18,998 --> 01:03:20,232
ECONOMICS AND THE MATH THAT THEY

1789
01:03:20,232 --> 01:03:23,469
USE AND HOW THAT MATH CAN BE

1790
01:03:23,469 --> 01:03:25,437
USED IN MODELING HEALTHCARE

1791
01:03:25,437 --> 01:03:27,373
OUTCOMES OR SOMETHING LIKE THAT,

1792
01:03:27,373 --> 01:03:29,275
YOU KNOW SORT OF MAYBE 1 OF THE

1793
01:03:29,275 --> 01:03:30,976
THINGS TO DO IS TO BRING THEM

1794
01:03:30,976 --> 01:03:34,413
TOGETHER AND OFFER UP TEAM

1795
01:03:34,413 --> 01:03:35,047
SCIENCE, FUNDING OPPORTUNITIES

1796
01:03:35,047 --> 01:03:36,782
AND IF THE PROBLEM IS SORT OF

1797
01:03:36,782 --> 01:03:37,750
EARLIER THAN THAT, IF WHATEVER

1798
01:03:37,750 --> 01:03:40,019
THE FIELD IS, THAT WE'RE

1799
01:03:40,019 --> 01:03:42,655
INTERESTED IN, IS NOT THINKING

1800
01:03:42,655 --> 01:03:45,124
ABOUT BIOMEDICAL RESEARCH AT ALL

1801
01:03:45,124 --> 01:03:46,759
OR DOESN'T REALIZE THAT THEIR

1802
01:03:46,759 --> 01:03:48,093
DISCIPLINE MAY BE INTERSECTS OUR

1803
01:03:48,093 --> 01:03:50,396
DISCIPLINES IN SOME WAY, THAT'S

1804
01:03:50,396 --> 01:03:52,231
WHERE THESE INNOVATIONS LABS AND

1805
01:03:52,231 --> 01:03:53,465
IDEAS LABS COME IN HANDY.

1806
01:03:53,465 --> 01:03:56,068
WE REACH OUT TO VERY DIVERSE

1807
01:03:56,068 --> 01:03:58,003
COMMUNITIES, AND BRING IN

1808
01:03:58,003 --> 01:03:58,504
INDIVIDUALS, RIGHT?

1809
01:03:58,504 --> 01:04:00,172
THEY DON'T HAVE TO COME IN WITH

1810
01:04:00,172 --> 01:04:02,107
TEAMS AND PARTNERS AND THEY COME

1811
01:04:02,107 --> 01:04:03,876
IN AS INDIVIDUALS AND FIND THOSE

1812
01:04:03,876 --> 01:04:05,711
TEAMS AND PARTNERS AND LEARN HOW

1813
01:04:05,711 --> 01:04:07,613
TO TALK ACROSS THOSE SPACES, I

1814
01:04:07,613 --> 01:04:09,548
THINK SOME OF IT'S EASY AND SOME

1815
01:04:09,548 --> 01:04:15,087
OF IT'S REALLY HARD AND

1816
01:04:15,087 --> 01:04:15,387
LONG-TERM.

1817
01:04:15,387 --> 01:04:17,089
>> MARIE, YOU KNOW I LIKE
TO

1818
01:04:17,089 --> 01:04:19,458
KEEP IT REAL.

1819
01:04:19,458 --> 01:04:21,227
>> SO I THINK -- I THINK
SOME OF

1820
01:04:21,227 --> 01:04:23,295
THE BARRIERS OF INCLUDING THOSE

1821
01:04:23,295 --> 01:04:25,297
OTHER GROUPS, IS ENGINEERS AND

1822
01:04:25,297 --> 01:04:27,700
SCIENCES ARE A LITTLE SNOOTY,

1823
01:04:27,700 --> 01:04:28,033
RIGHT?

1824
01:04:28,033 --> 01:04:30,569
AND CLINICIANS HAVE A DIFFERENT

1825
01:04:30,569 --> 01:04:33,973
LEVEL OF EGO, AND THAT I SAID

1826
01:04:33,973 --> 01:04:35,574
THIS RECENTLY, YOU KNOW WHEN I

1827
01:04:35,574 --> 01:04:39,044
CAME, I WENT TO LIBERAL ARTS

1828
01:04:39,044 --> 01:04:42,047
EDUCATION, WENT TO MOOREHOUSE

1829
01:04:42,047 --> 01:04:45,618
EDUCATION, I'M OVER HERE DOING

1830
01:04:45,618 --> 01:04:46,318
CALCULUS AND PHYSICS, AND THEN

1831
01:04:46,318 --> 01:04:47,753
WHEN I DID THAT HIV/AIDS

1832
01:04:47,753 --> 01:04:49,154
RESEARCH AND THEY WANTED TO GET

1833
01:04:49,154 --> 01:04:51,056
IT INTO CERTAIN COMMUNITIES THE

1834
01:04:51,056 --> 01:04:53,292
PEOPLE WHO UNDERSTOOD CULTURE,

1835
01:04:53,292 --> 01:04:55,027
THE ANTHROPOLOGISTS, THE

1836
01:04:55,027 --> 01:04:56,195
LINGUISTS WERE MASSIVELY

1837
01:04:56,195 --> 01:04:57,496
IMPORTANT TO GETTING WHATEVER

1838
01:04:57,496 --> 01:05:00,666
TECHNOLOGY WE HAD TO THE PEOPLE.

1839
01:05:00,666 --> 01:05:03,302
SO THE SCIENCE IS YOU CAN HAVE

1840
01:05:03,302 --> 01:05:04,603
THE BEST SMALL MOLECULE BUT IF

1841
01:05:04,603 --> 01:05:06,705
IT'S NOT TAKEN UP BY THE

1842
01:05:06,705 --> 01:05:08,107
COMMUNITY, WHO CARES, RIGHT IN

1843
01:05:08,107 --> 01:05:10,409
SO THERE'S TIME ON THAT SIDE TO

1844
01:05:10,409 --> 01:05:11,911
DROP YOUR GUARD, YOU MAY BE GOOD

1845
01:05:11,911 --> 01:05:13,445
AT WHAT YOU DO BUT THAT WON'T

1846
01:05:13,445 --> 01:05:16,081
SOLVE THE PROBLEM AND MOST

1847
01:05:16,081 --> 01:05:18,050
SCIENTISTS I KNOW DO WANT TO

1848
01:05:18,050 --> 01:05:19,985
HAVE IMPACT, WHEN YOU EXPLAIN

1849
01:05:19,985 --> 01:05:22,788
IT'S A BARRIER TO START TO WORK

1850
01:05:22,788 --> 01:05:24,189
WITH THOSE COMMUNITIES AND I'VE

1851
01:05:24,189 --> 01:05:24,990
SEEN, GREAT, AGAIN HAVE GREAT

1852
01:05:24,990 --> 01:05:26,325
IDEA WHEN IS YOU BEGIN TO THINK

1853
01:05:26,325 --> 01:05:27,893
ABOUT THEM AND AGAIN ON THE

1854
01:05:27,893 --> 01:05:29,194
EARLIER PHASES OF TECHNOLOGY, IT

1855
01:05:29,194 --> 01:05:30,829
CAN REALLY HELP ROLL THAT OUT.

1856
01:05:30,829 --> 01:05:33,032
BUT I THINK 1 EXCELLENT EXAMPLE

1857
01:05:33,032 --> 01:05:34,566
OF THAT IS [INDISCERNIBLE] WHO

1858
01:05:34,566 --> 01:05:37,202
WAS AT THE WHITE HOUSE OFFICE OF

1859
01:05:37,202 --> 01:05:38,070
SCIENCE AND TECHNOLOGY POLICY IS

1860
01:05:38,070 --> 01:05:40,072
NOW A LEADER IN AI AND HOW WE

1861
01:05:40,072 --> 01:05:41,674
THINK ABOUT AI, BUT SHE WAS DEAN

1862
01:05:41,674 --> 01:05:45,144
OF THE SOCIAL SCIENCES AT

1863
01:05:45,144 --> 01:05:46,912
PRINCETON OR COLUMBI AMAYBE BOTH

1864
01:05:46,912 --> 01:05:49,148
BUT NOW SHE'S A LEADER IN,A I

1865
01:05:49,148 --> 01:05:50,683
AND THINK ABOUT HOW HUMANS AND

1866
01:05:50,683 --> 01:05:51,750
USE IT AND ROLL IT OUT.

1867
01:05:51,750 --> 01:05:54,186
AND I WANT TO END WITH THESE

1868
01:05:54,186 --> 01:05:56,388
OTHER WAYS TO INCLUDE THOSE

1869
01:05:56,388 --> 01:05:56,689
COMMUNITIES.

1870
01:05:56,689 --> 01:05:58,691
MY Ph.D. ADVISOR USED TO

1871
01:05:58,691 --> 01:06:00,192
ALWAYS TELL US, BE ABLE TO

1872
01:06:00,192 --> 01:06:02,494
EXPLAIN YOUR SCIENCE TO ME AS AN

1873
01:06:02,494 --> 01:06:03,796
EXPERT IN THE FIELD AND I ALSO

1874
01:06:03,796 --> 01:06:05,798
NEED YOU TO EXPLAIN IT TO YOUR

1875
01:06:05,798 --> 01:06:06,432
GRANDMOTHER, THEN YOU REALLY

1876
01:06:06,432 --> 01:06:07,599
KNOW WHAT YOU ARE TALKING ABOUT

1877
01:06:07,599 --> 01:06:12,004
IF YOU CAN EXPLAIN IT TO YOUR

1878
01:06:12,004 --> 01:06:12,338
GRANDMOTHER.

1879
01:06:12,338 --> 01:06:14,173
SHE

1880
01:06:14,173 --> 01:06:15,708
-- HE WAS JUST SAYING.

1881
01:06:15,708 --> 01:06:16,976
SO THATTAY HOW WE COMMUNICATE TO

1882
01:06:16,976 --> 01:06:18,844
OTHERS IN THE BUBBLE TO SEE WHAT

1883
01:06:18,844 --> 01:06:20,279
THE SKILL IS AND THAT'S WHAT WE

1884
01:06:20,279 --> 01:06:23,349
NEED TO LEARN TO HELPS THEM FEEL

1885
01:06:23,349 --> 01:06:26,885
BROUGHT INTO THE WORK WE'RE

1886
01:06:26,885 --> 01:06:30,689
DOING.

1887
01:06:30,689 --> 01:06:35,928
>> FABULOUS, SO, IT'S A
GREAT

1888
01:06:35,928 --> 01:06:37,463
SEGUE INTO WHERE WE'RE GOING.

1889
01:06:37,463 --> 01:06:42,401
I WILL GO JENNIFER -- LET'S GO

1890
01:06:42,401 --> 01:06:43,669
JENNIFER MANU SAMSON, IS THERE A

1891
01:06:43,669 --> 01:06:45,204
PLACE WHERE INVESTIGATORS FROM

1892
01:06:45,204 --> 01:06:48,540
SMALLER LESS RESOURCED

1893
01:06:48,540 --> 01:06:49,742
INSTITUTIONS R2s, MSIs,

1894
01:06:49,742 --> 01:06:50,976
REGIONALS IN THIS AREA OF

1895
01:06:50,976 --> 01:06:54,179
RESEARCH, IF SO WHAT CAN WE DO

1896
01:06:54,179 --> 01:07:00,219
TO GET THEM ENGAGED.

1897
01:07:00,219 --> 01:07:02,721
>> I'M ASSUMING BY THIS
AREA OF

1898
01:07:02,721 --> 01:07:05,824
RESEARCH WE MEAN SORT OF DATA

1899
01:07:05,824 --> 01:07:06,625
SCIENCE GENERALLY.

1900
01:07:06,625 --> 01:07:09,628
YOU KNOW DATA SCIENCE AND IS 1

1901
01:07:09,628 --> 01:07:11,964
OF THOSE THINGS THAT CAN BE DONE

1902
01:07:11,964 --> 01:07:13,132
FROM ANYWHERE, BUT AGAIN, SORT

1903
01:07:13,132 --> 01:07:15,801
OF A LOT OF THIS IS IN KNOWING

1904
01:07:15,801 --> 01:07:18,303
WHAT THE RIGHT QUESTIONS ARE TO

1905
01:07:18,303 --> 01:07:19,605
ASK, FINDING THE RIGHT

1906
01:07:19,605 --> 01:07:21,006
COLLABORATOR ANDS THAT SORT OF

1907
01:07:21,006 --> 01:07:24,410
THING AND SO, I THINK SOME OF

1908
01:07:24,410 --> 01:07:26,078
THE PROGRAMS THAT ENABLE THESE

1909
01:07:26,078 --> 01:07:26,912
PARTNERSHIP BUILDING AND THINGS

1910
01:07:26,912 --> 01:07:30,182
CAN BE USEFUL TO THESE FOLKS IN

1911
01:07:30,182 --> 01:07:32,918
SMALLER INSTITUTIONS BUT I THINK

1912
01:07:32,918 --> 01:07:34,219
AT LEAST FOR, WELL I'M GOING TO

1913
01:07:34,219 --> 01:07:36,155
GO AHEAD AND SAY TI THINK FOR

1914
01:07:36,155 --> 01:07:37,289
ALL OF NIH, DAILY BASIS THEA

1915
01:07:37,289 --> 01:07:40,259
SCIENCE CAN COME IN ON ANY SIZE

1916
01:07:40,259 --> 01:07:42,127
GRANT MECHANISM AND GO THROUGH

1917
01:07:42,127 --> 01:07:43,529
PEER REVIEW, SO ALL THE

1918
01:07:43,529 --> 01:07:45,431
MECHANISMS WE USE FOR SMALLER

1919
01:07:45,431 --> 01:07:46,432
INSTITUTIONS, THERE ARE NIQUE

1920
01:07:46,432 --> 01:07:50,736
THINGS ABOUT SMALLER

1921
01:07:50,736 --> 01:07:51,670
INSTITUTIONS, AND UNDERSERVED

1922
01:07:51,670 --> 01:07:52,571
INSTITUTIONS AND CERTAIN

1923
01:07:52,571 --> 01:07:54,673
INSTITUTIONS AND CERTAIN AREAS,

1924
01:07:54,673 --> 01:07:55,841
AND NONPROFIT INSTITUTIONS AND

1925
01:07:55,841 --> 01:07:59,745
ALL THE OTHER THINGS THAT WE

1926
01:07:59,745 --> 01:08:02,381
ENGAGE OUT THERE AND SO I THINK

1927
01:08:02,381 --> 01:08:05,350
SORT OF MY ADVICE TO THOSE FOLK

1928
01:08:05,350 --> 01:08:07,286
WOULD BE ON BRING THEIR OWN

1929
01:08:07,286 --> 01:08:09,955
STRENGTH TO THAT EQUATION AND

1930
01:08:09,955 --> 01:08:11,490
FIND PARTNERS WHERE THEY DON'T

1931
01:08:11,490 --> 01:08:14,293
HAVE THEM ALREADY.

1932
01:08:14,293 --> 01:08:17,529
>> YEAH, JUST TO CO SIGN
THAT, I

1933
01:08:17,529 --> 01:08:17,863
AGREE.

1934
01:08:17,863 --> 01:08:19,832
AGAIN THINGS CAN BE DONE WITH A

1935
01:08:19,832 --> 01:08:21,166
LAPTOP WITHOUT HAVING SUPER

1936
01:08:21,166 --> 01:08:22,668
COMPUTERS DOING ALL THE

1937
01:08:22,668 --> 01:08:25,737
PROCESSING BUT OF COURSE IF

1938
01:08:25,737 --> 01:08:27,739
THERE WERE FUNDS TO ALLOW FOR

1939
01:08:27,739 --> 01:08:28,807
THOSE ACCESSES AND THAT WOULD BE

1940
01:08:28,807 --> 01:08:29,041
GREAT.

1941
01:08:29,041 --> 01:08:31,310
IF YOU THINK ABOUT IT, I USED TO

1942
01:08:31,310 --> 01:08:32,578
BE SUPER IMPRESSED WITH THE

1943
01:08:32,578 --> 01:08:34,413
TOOLS THAT THE NATIONAL LIBRARY

1944
01:08:34,413 --> 01:08:36,181
HAD AVAILABLE, ONCE I START MID

1945
01:08:36,181 --> 01:08:37,950
Ph.D. AND POINTED THEM OUT TO

1946
01:08:37,950 --> 01:08:40,018
YOU, ALL THESE GWAS STUDIES ARE

1947
01:08:40,018 --> 01:08:41,320
SITTING AT THERE COMPUTE XER

1948
01:08:41,320 --> 01:08:42,087
SYRUPING THINGS.

1949
01:08:42,087 --> 01:08:44,490
BLASTS WHERE WE USED TO HAVE TO

1950
01:08:44,490 --> 01:08:45,991
DESIGN A PC ON PRIMER SEQUENCE

1951
01:08:45,991 --> 01:08:48,460
AND YOU DO BLAST AGAINST THESE

1952
01:08:48,460 --> 01:08:49,294
GENOME SEQUENCES ALL THESE I

1953
01:08:49,294 --> 01:08:51,463
THINKS THAT IF YOU WRITE SCRIPTS

1954
01:08:51,463 --> 01:08:53,198
AND CODES CAN BE AUTOMATED SO

1955
01:08:53,198 --> 01:08:55,200
THERE IS THIS MASSIVE DATA THAT

1956
01:08:55,200 --> 01:08:56,368
IS BEING AVAILABLE AND I THINK 1

1957
01:08:56,368 --> 01:08:58,137
WAY YOU CAN BRING IN SOME OF

1958
01:08:58,137 --> 01:08:58,871
THESE OTHER COMMUNITIES, AGAIN

1959
01:08:58,871 --> 01:08:59,838
THINKING ABOUT IT EARLIER IS

1960
01:08:59,838 --> 01:09:02,941
BRING IT INTO THE EDUCATIONAL

1961
01:09:02,941 --> 01:09:04,877
CLASSROOM, LIKE, IF YOU'RE

1962
01:09:04,877 --> 01:09:06,645
TAKING EVEN A FRESHMAN YEAR

1963
01:09:06,645 --> 01:09:08,914
GENERAL BIOLOGY COURSE, I THINK

1964
01:09:08,914 --> 01:09:10,315
BIOLOGY IS BECOMING MORE

1965
01:09:10,315 --> 01:09:11,416
QUAWBTITATIVE, HAVE PEOPLE DO

1966
01:09:11,416 --> 01:09:13,519
THOSE COURSES, USE SOME OF THESE

1967
01:09:13,519 --> 01:09:16,355
DATABASES ONLINE TO BEGIN TO DIP

1968
01:09:16,355 --> 01:09:18,657
THEIR TOE IN WHAT DATA IS

1969
01:09:18,657 --> 01:09:20,659
AVAILABLE AND HOW THAT CAN GAIN

1970
01:09:20,659 --> 01:09:22,060
ACCESS AND LOOK THROUGH IT, SO

1971
01:09:22,060 --> 01:09:25,097
THEN BY THEIR SENIOR YEAR, THEY

1972
01:09:25,097 --> 01:09:27,499
COMBINE PROJECTS OF STUDYING

1973
01:09:27,499 --> 01:09:30,335
THEIR OWN WAYS, BECAUSE AT MY

1974
01:09:30,335 --> 01:09:31,737
EARLIER COMMENT, THERE'S SO MUCH

1975
01:09:31,737 --> 01:09:33,105
DATA WE'RE GATHERING BUT AN

1976
01:09:33,105 --> 01:09:37,376
INVESTIGATOR USING A SMALL PIECE

1977
01:09:37,376 --> 01:09:39,378
AND SOMEONE CAN STILL COME IN

1978
01:09:39,378 --> 01:09:41,180
AND PULL A LOT OF INFORMATION

1979
01:09:41,180 --> 01:09:42,915
AND IN MY HEAD IT'S CHEAPER THAN

1980
01:09:42,915 --> 01:09:46,018
DOING THE WET LOB AND SPRMS.

1981
01:09:46,018 --> 01:09:48,320
I THINK MAKING THAT

1982
01:09:48,320 --> 01:09:50,088
DEMOCRATIZATION BETTER COULD

1983
01:09:50,088 --> 01:09:55,294
BRING IN MULTIPLE

1984
01:09:55,294 --> 01:09:55,761
 COMMUNITIES.

1985
01:09:55,761 --> 01:09:57,396
>> SO MY ANSWER IS IN MY
HEAD,

1986
01:09:57,396 --> 01:09:59,932
IT'S A PROGRAM DESIGNED FOR

1987
01:09:59,932 --> 01:10:01,200
LOWURE RESOURCE INSTITUTION AND

1988
01:10:01,200 --> 01:10:04,870
COMMUNITIES THAT ARE

1989
01:10:04,870 --> 01:10:05,571
UNDERREPRESENTED AND UNDERSERVED

1990
01:10:05,571 --> 01:10:07,306
COMMUNITIESAs WELL AND WE HAVE

1991
01:10:07,306 --> 01:10:13,045
SO MANY PROGRAMS IN THERE THAT

1992
01:10:13,045 --> 01:10:16,348
YOU CAN A DIFFERENT TRAINING,

1993
01:10:16,348 --> 01:10:18,217
INSTITUTIONAL LEVEL, BUT ALSO WE

1994
01:10:18,217 --> 01:10:19,851
HAVE PROJECTS THAT YOU CAN

1995
01:10:19,851 --> 01:10:22,254
UTILIZE YOUR OWN DATA AND WE CAN

1996
01:10:22,254 --> 01:10:24,489
PROVIDE YOU FUNDING AND ALSO

1997
01:10:24,489 --> 01:10:32,898
RESOURCES AND COMPUTING RESOURCE

1998
01:10:32,898 --> 01:10:33,765
AS WELL.

1999
01:10:33,765 --> 01:10:36,401
BUT TO THE POINT ALSO OF

2000
01:10:36,401 --> 01:10:37,336
JENNIFER, THERE ARE ALSO

2001
01:10:37,336 --> 01:10:40,939
PROGRAMS THAT SUPPORT LOWER

2002
01:10:40,939 --> 01:10:42,374
PHYSICIANS AND LIKE R25, CAN YOU

2003
01:10:42,374 --> 01:10:45,244
APPLY TO THOSE AND THERE IS ALSO

2004
01:10:45,244 --> 01:10:47,179
INDIVIDUAL ON THE DIVERSE

2005
01:10:47,179 --> 01:10:50,816
SUBLIMIT IF YOU FIND A SPONSOR

2006
01:10:50,816 --> 01:10:53,585
YOU CAN ENTER IN IT SPACE OF AI

2007
01:10:53,585 --> 01:10:55,487
AND DATA SCIENCE AND GENOMICS

2008
01:10:55,487 --> 01:10:57,723
AND YOU CAN [INDISCERNIBLE] AND

2009
01:10:57,723 --> 01:11:01,827
THIS DIVERSE SUPPLEMENT IS

2010
01:11:01,827 --> 01:11:04,730
ACROSS NIH, SPECIFIC TO EACH IC,

2011
01:11:04,730 --> 01:11:05,897
DEPENDING ON THE DISEASE

2012
01:11:05,897 --> 01:11:07,733
CONDITION YOU ARE STUDYING, YOU

2013
01:11:07,733 --> 01:11:08,700
CAN APPLY TO THOSE.

2014
01:11:08,700 --> 01:11:12,704
IF YOU YOU'RE INTERESTED TO

2015
01:11:12,704 --> 01:11:15,307
ENGAGE WITHIN MY PROGRAM, PLEASE

2016
01:11:15,307 --> 01:11:17,509
SUBSCRIBE THROUGH MY CONNECT OR

2017
01:11:17,509 --> 01:11:20,045
CONTACT ME VIA MY E-MAIL.

2018
01:11:20,045 --> 01:11:21,780
>> OH CAN I THROW OUT 1
PROGRAM

2019
01:11:21,780 --> 01:11:24,816
WE HAVE AT NIBIB, THANK YOU

2020
01:11:24,816 --> 01:11:27,286
SAMSON I'M LEARNING HOW TO DO

2021
01:11:27,286 --> 01:11:29,254
THIS, NIBIB ALSO STARTED THIS

2022
01:11:29,254 --> 01:11:30,789
HBCU BETA PROGRAM WHERE WE

2023
01:11:30,789 --> 01:11:32,758
ACTUALLY HAVE A GRANT MECHANISM

2024
01:11:32,758 --> 01:11:35,093
TO HELP BUILD INFRASTRUCTURE TO

2025
01:11:35,093 --> 01:11:37,162
DEVELOP BIOENGINEERING AT

2026
01:11:37,162 --> 01:11:38,030
HBCUs AT THE COUNTRY, SO I

2027
01:11:38,030 --> 01:11:40,699
WANT TO SAY THE CALL IS OUT.

2028
01:11:40,699 --> 01:11:41,533
THEY ANNOUNCED THE FIRST SCHOOL,

2029
01:11:41,533 --> 01:11:44,436
I THINK THE CALL IS, IT JUST

2030
01:11:44,436 --> 01:11:46,271
RECENTLY CLOSED BUT PUT YOUR EYE

2031
01:11:46,271 --> 01:11:50,976
ON IT FOR NEXT YEAR'S CALL, WAYS

2032
01:11:50,976 --> 01:11:52,377
FOR BUILDING MINORITY

2033
01:11:52,377 --> 01:11:53,745
INFRASTRUCTURE AT AN INSTITUTION

2034
01:11:53,745 --> 01:11:55,647
SUPPORTING THIS WORK.

2035
01:11:55,647 --> 01:11:57,716
>> SO BECAUSE OF THE TEAM
ON

2036
01:11:57,716 --> 01:11:59,751
BEHALF OF NIH, LED A REPORT THAT

2037
01:11:59,751 --> 01:12:01,753
BECAME A SET OF RECOMMENDATIONS

2038
01:12:01,753 --> 01:12:04,690
THROUGH THE ADVISORY COMMITTEE

2039
01:12:04,690 --> 01:12:07,225
TO THE DIRECTOR ON BROADER

2040
01:12:07,225 --> 01:12:12,564
PARTICIPATION OF INDIVIDUALS

2041
01:12:12,564 --> 01:12:13,432
WITH DISABILITIES IN RESEARCH

2042
01:12:13,432 --> 01:12:15,634
AND GETTING MORE SCIENTISTS WITH

2043
01:12:15,634 --> 01:12:16,535
DISABILITIES INVOLVED WITH

2044
01:12:16,535 --> 01:12:16,868
RESEARCH.

2045
01:12:16,868 --> 01:12:18,303
HOW DOES THAT FIT WITH ALL OF

2046
01:12:18,303 --> 01:12:20,972
THIS YOU'VE BEEN DISCUSSING WITH

2047
01:12:20,972 --> 01:12:23,241
REGARDS TO AI, MACHINE LEARNING,

2048
01:12:23,241 --> 01:12:23,775
ET CETERA.

2049
01:12:23,775 --> 01:12:25,177
WHERE DO HAVES WITH DISABILITIES

2050
01:12:25,177 --> 01:12:28,480
FIT INTO ALL THIS?

2051
01:12:28,480 --> 01:12:31,216
WHO WOULD LIKE TO JUMP IN FIRST?

2052
01:12:31,216 --> 01:12:32,284
>> I WOULD SAY THEY'VE
ALWAYS

2053
01:12:32,284 --> 01:12:33,752
FIT INTO THIS, RIGHT?

2054
01:12:33,752 --> 01:12:35,921
AND THEY SHOULD BE INCLUDED IN

2055
01:12:35,921 --> 01:12:36,154
THIS.

2056
01:12:36,154 --> 01:12:38,023
FOR ALL THE REASONS THAT WE

2057
01:12:38,023 --> 01:12:39,558
TALKED ABOUT INCLUDING

2058
01:12:39,558 --> 01:12:40,492
UNDERREPRESENTED MINORITIES IN

2059
01:12:40,492 --> 01:12:41,526
EVERY OTHER SPACE, RIGHT?

2060
01:12:41,526 --> 01:12:42,961
THE WAY THEY MIGHT APPROACH A

2061
01:12:42,961 --> 01:12:44,996
SOLUTION TO A PROBLEM, WOULD BE

2062
01:12:44,996 --> 01:12:46,498
REALLY DIFFERENT THAN SOMEONE

2063
01:12:46,498 --> 01:12:48,700
ELSE, BECAUSE SOMEONE ELSE IS

2064
01:12:48,700 --> 01:12:50,202
RELYING ON WHATEVER FACULTIES

2065
01:12:50,202 --> 01:12:51,169
THAT THIS OTHER PERSON DIDN'T

2066
01:12:51,169 --> 01:12:58,377
HAVE WORKING AT THE SAME LEVEL.

2067
01:12:58,377 --> 01:13:00,345
I'VE BEEN HOSTING STUDENTS IN MY

2068
01:13:00,345 --> 01:13:02,180
LAB WITH DISABILITIES OVER THE

2069
01:13:02,180 --> 01:13:04,049
LAST FEW YEARS AND IT CHANGES

2070
01:13:04,049 --> 01:13:06,151
THE WAY WE DO THINGS OF REGULAR

2071
01:13:06,151 --> 01:13:07,819
THINGS WE DO IN THE LABS, SO

2072
01:13:07,819 --> 01:13:09,621
WHENY WOO SEE THIS DATA SET,

2073
01:13:09,621 --> 01:13:11,456
THERE'S A BLIND SPOT AND

2074
01:13:11,456 --> 01:13:13,325
HOPEFULLY THAT'S NOT A

2075
01:13:13,325 --> 01:13:14,626
DISRESPECTFUL TERM BUT THERE'S A

2076
01:13:14,626 --> 01:13:15,460
LIVED EXPERIENCE YOU CAN'T

2077
01:13:15,460 --> 01:13:18,630
UNDERSTAND BECAUSE YOU NEVER HAD

2078
01:13:18,630 --> 01:13:20,565
IT CROSS YOUR DOME SO IT'S NOT

2079
01:13:20,565 --> 01:13:26,204
EVEN IN YOUR REALM OF

2080
01:13:26,204 --> 01:13:27,506
VISUALIZATION, UNTIL YOU HAVE A

2081
01:13:27,506 --> 01:13:30,242
TEAM OR LIVING WITH IT AND HAVE

2082
01:13:30,242 --> 01:13:32,177
SOMEONE SAY YOU KNOW WHAT NONE

2083
01:13:32,177 --> 01:13:34,379
OF YOU KNOW ABOUT?

2084
01:13:34,379 --> 01:13:36,581
XOR Y, AND THAT'S WHAT WE NEED

2085
01:13:36,581 --> 01:13:38,216
TO THINK ABOUT IN INTERFACING

2086
01:13:38,216 --> 01:13:40,419
DESIGN, BUT ALSO WHAT I'M MORE

2087
01:13:40,419 --> 01:13:41,720
INTERESTED IS AGAIN, THEY DON'T

2088
01:13:41,720 --> 01:13:42,687
HAVE THE SAME DISABILITY, SO

2089
01:13:42,687 --> 01:13:44,089
WHEN YOU WANT TO DO SOMETHING

2090
01:13:44,089 --> 01:13:45,924
FOR THOSE THAT ARE DEAF OR HARD

2091
01:13:45,924 --> 01:13:47,325
OF HEARING, DOES THAT LEAVE OUT

2092
01:13:47,325 --> 01:13:49,161
PEOPLE WHO ARE VISUAL IMPAIR

2093
01:13:49,161 --> 01:13:51,329
EXCLUDE THOSE WITH DIFFERENT

2094
01:13:51,329 --> 01:13:54,132
PHYSICAL DISABILITIES THAN THOSE

2095
01:13:54,132 --> 01:13:55,534
WITH THE NONVISIBLE DISABILITIES

2096
01:13:55,534 --> 01:13:57,536
SO EVEN THE DIVERSITY OF

2097
01:13:57,536 --> 01:13:58,403
DISABILITIES ARE THOSE THINGS WE

2098
01:13:58,403 --> 01:14:00,272
WANT TO TRY TO ENCLUED WHICH IS

2099
01:14:00,272 --> 01:14:01,306
CHALLENGING WHERE WE ARE NOW

2100
01:14:01,306 --> 01:14:03,408
BECAUSE OF THE WAY OUR WORKFORCE

2101
01:14:03,408 --> 01:14:04,676
AND WORK PRACTICES ARE SET UP

2102
01:14:04,676 --> 01:14:06,211
BUT THOSE ARE THE OTHER WAYS WE

2103
01:14:06,211 --> 01:14:08,713
CAN THINK ABOUT TO INCLUDE THOSE

2104
01:14:08,713 --> 01:14:10,682
GROUPS IN OUR RESEARCH TEAM IN

2105
01:14:10,682 --> 01:14:16,154
CHANGING HOW OUR WORKPLACE IS

2106
01:14:16,154 --> 01:14:16,688
MANDATED.

2107
01:14:16,688 --> 01:14:18,857
>> SO, THE AI ML PROGRAM
IS

2108
01:14:18,857 --> 01:14:21,326
INCLUSIVE IN TERMS OF SPECIALLY

2109
01:14:21,326 --> 01:14:22,561
DESIGNED FOR UNDERREPRESENTED

2110
01:14:22,561 --> 01:14:24,763
GROUPS INCLUDING PEOPLE WITH

2111
01:14:24,763 --> 01:14:25,931
DISABILITY ARE PART OF THIS

2112
01:14:25,931 --> 01:14:28,900
PROGRAM AND WE HAVE SO MANY

2113
01:14:28,900 --> 01:14:30,335
INDIVIDUALS WITH DISABILITIES TO

2114
01:14:30,335 --> 01:14:33,205
HAVE BEEN SUPPORTED BY THIS

2115
01:14:33,205 --> 01:14:34,573
PROGRAM TO DO RESEARCH BUT ALSO

2116
01:14:34,573 --> 01:14:36,808
SOME OF THEM ARE TRAINEES AS

2117
01:14:36,808 --> 01:14:40,879
WELL, IN THE SPACE OF AI ML.

2118
01:14:40,879 --> 01:14:43,515
SO SOME OF THOSE RESEARCHERS

2119
01:14:43,515 --> 01:14:47,185
THEY FOCUS ON PARTICULARLY ON

2120
01:14:47,185 --> 01:14:48,420
DISABILITY ISSUES THAT DEPENDING

2121
01:14:48,420 --> 01:14:50,155
ON YOUR RESEARCH INTEREST,

2122
01:14:50,155 --> 01:14:52,924
YOU'RE WELCOME TO APPLY TO

2123
01:14:52,924 --> 01:14:54,659
PROGRAMS OF THE -- YOU KNOW

2124
01:14:54,659 --> 01:14:57,863
WITHIN THE AI PROGRAMMING,

2125
01:14:57,863 --> 01:14:58,864
EITHER TRAINING, RESEARCH

2126
01:14:58,864 --> 01:15:02,334
PROGRAMS OR CAPACITY BUILDING

2127
01:15:02,334 --> 01:15:06,004
ATTEMPTS TO BE AS WELL,

2128
01:15:06,004 --> 01:15:06,872
INCLUDING COMMUNITY ENGAGEMENT.

2129
01:15:06,872 --> 01:15:08,773
>> YOU KNOW I WANT TO
RETURN TO

2130
01:15:08,773 --> 01:15:09,941
SOMETHING THAT MANU SAID BECAUSE

2131
01:15:09,941 --> 01:15:11,810
I THINK IT'S REALLY CRITICAL

2132
01:15:11,810 --> 01:15:13,678
HERE WHICH IS THAT I THINK

2133
01:15:13,678 --> 01:15:15,580
PEOPLE DESIGN WITH THE BEST OF

2134
01:15:15,580 --> 01:15:17,415
INTENTIONS BUT IF THEY DON'T

2135
01:15:17,415 --> 01:15:19,017
KNOW WHAT, YOU KNOW WHAT TO LOOK

2136
01:15:19,017 --> 01:15:22,120
OUT FOR WHEN THEY'RE -- WHEN

2137
01:15:22,120 --> 01:15:24,823
THEY'RE COLLABORATING WITH OR

2138
01:15:24,823 --> 01:15:26,224
DESIGNING FOR PEOPLE WITH ANY

2139
01:15:26,224 --> 01:15:28,493
KIND OF DISABILITY OR ANY KIND

2140
01:15:28,493 --> 01:15:30,929
OF SPECIFIC KIND OF PERSPECTIVE,

2141
01:15:30,929 --> 01:15:32,898
THEY DON'T KNOW, RIGHT IN SO THE

2142
01:15:32,898 --> 01:15:36,101
BEST WAY AROUND THAT IS INCREASE

2143
01:15:36,101 --> 01:15:40,071
SORT OF OPENNESS AND EXPOSURE

2144
01:15:40,071 --> 01:15:41,673
AND COLLABORATION WITH THE FOLKS

2145
01:15:41,673 --> 01:15:44,109
THAT YOU'RE DESIGNING FOR

2146
01:15:44,109 --> 01:15:45,810
TECHNOLOGY CAN BE A GREAT

2147
01:15:45,810 --> 01:15:47,112
LEVELER, BUT WE'VE ALSO SEEN A

2148
01:15:47,112 --> 01:15:48,680
LOT OF EXAMPLES WHERE TECHNOLOGY

2149
01:15:48,680 --> 01:15:50,482
HAS BEEN DESIGNED POORLY BY

2150
01:15:50,482 --> 01:15:51,449
PEOPLE THAT DIDN'T REALIZE

2151
01:15:51,449 --> 01:15:56,321
EXACTLY WHAT THEY WERE DESIGNING

2152
01:15:56,321 --> 01:15:56,488
FOR.

2153
01:15:56,488 --> 01:15:58,857
SO I'M SORT OF THINKING BACK TO

2154
01:15:58,857 --> 01:16:00,158
AN EARLIER COMMENT ABOUT HOW WE

2155
01:16:00,158 --> 01:16:02,227
THINK ABOUT TRAINING THE UP AND

2156
01:16:02,227 --> 01:16:03,061
COMING GENERATION AND 1 OF THE

2157
01:16:03,061 --> 01:16:04,763
THINGS THAT WE DO IN A LOT OF

2158
01:16:04,763 --> 01:16:05,730
OUR PROGRAMS NOW, BECAUSE IT

2159
01:16:05,730 --> 01:16:08,033
WORKS WELL, IS HAVE THE

2160
01:16:08,033 --> 01:16:09,734
TRAINEES, THE GRADUATE STUDENTS

2161
01:16:09,734 --> 01:16:12,337
AND POST DOCS PRESENT THEIR

2162
01:16:12,337 --> 01:16:13,572
TALKS AND POSTERS TO POSTER

2163
01:16:13,572 --> 01:16:16,875
JUDGES AND THINGS THAT ARE --A

2164
01:16:16,875 --> 01:16:18,276
THAT INCLUDE THE PATIENT

2165
01:16:18,276 --> 01:16:18,977
ADVOCATE VERY OFTEN AND THE

2166
01:16:18,977 --> 01:16:20,478
REASON FOR THAT IS PERSPECTIVE,

2167
01:16:20,478 --> 01:16:22,480
YOU KNOW IF THEY CAN LEARN TO

2168
01:16:22,480 --> 01:16:26,184
PRESENT TO A BROADER AUDIENCE,

2169
01:16:26,184 --> 01:16:27,619
MANU'S GRANDMOTHER, THEN THEY

2170
01:16:27,619 --> 01:16:29,154
CAN PRESENT TO ANYBODY AND THEY

2171
01:16:29,154 --> 01:16:30,622
CAN HAVE THAT INTERACTION WITH

2172
01:16:30,622 --> 01:16:31,823
ANYBODY AND BE MORE SORT OF OPEN

2173
01:16:31,823 --> 01:16:35,360
TO THE WAY THAT THEY'RE THINKING

2174
01:16:35,360 --> 01:16:36,561
ABOUT THEIR STUDIES AND

2175
01:16:36,561 --> 01:16:38,029
DESIGNING PRODUCTS IF THAT'S THE

2176
01:16:38,029 --> 01:16:41,132
DIRECTION THEY GO WITH THEIR

2177
01:16:41,132 --> 01:16:41,800
DATA SCIENCE.

2178
01:16:41,800 --> 01:16:42,200
>> THANK YOU.

2179
01:16:42,200 --> 01:16:45,370
SO THIS NEXT QUESTION, REMINDS

2180
01:16:45,370 --> 01:16:47,138
ME OF, YOU KNOW, IT'S CLEARLY

2181
01:16:47,138 --> 01:16:48,206
FROM A DATA PERSON.

2182
01:16:48,206 --> 01:16:53,244
I'M 1 OF THOSE PEOPLE WITH

2183
01:16:53,244 --> 01:16:55,146
COLLEGE CALCULUS AND THE

2184
01:16:55,146 --> 01:16:57,449
PROFESSOR SAID IT'S INTUITIVELY

2185
01:16:57,449 --> 01:16:58,550
EVIDENT AND I DIDN'T UNDERSTAND

2186
01:16:58,550 --> 01:16:59,584
ANYTHING AFTER THAT BUT I THINK

2187
01:16:59,584 --> 01:17:01,486
I GET THE POINT OF THIS

2188
01:17:01,486 --> 01:17:01,820
QUESTION.

2189
01:17:01,820 --> 01:17:04,589
IT SAYS IN TAFTICS BIAS AND

2190
01:17:04,589 --> 01:17:07,826
REDUCED BY APPLYING NOVEL MODELS

2191
01:17:07,826 --> 01:17:09,361
THAT MORE ACCURATELY CAPTURE

2192
01:17:09,361 --> 01:17:10,428
UNDERLYING PHENOMENA.

2193
01:17:10,428 --> 01:17:12,897
FOR INSTANCE MEASUREMENT ERROR

2194
01:17:12,897 --> 01:17:14,933
CAN RESULT IN SIGNIFICANT BIAS

2195
01:17:14,933 --> 01:17:15,934
IN THE RESULTS.

2196
01:17:15,934 --> 01:17:18,136
HAS SCIENTISTS WORK WITH MODELS

2197
01:17:18,136 --> 01:17:20,372
HOW DO THEY COLLABORATE TO

2198
01:17:20,372 --> 01:17:21,840
ADDRESS THESE ISSUES?

2199
01:17:21,840 --> 01:17:22,440
WHAT DOES EACH DISCIPLINE

2200
01:17:22,440 --> 01:17:30,982
CONTRIBUTE IN WHO WOULD LIKE TO

2201
01:17:30,982 --> 01:17:32,150
TAKE THAT?

2202
01:17:32,150 --> 01:17:32,651
COME ON.

2203
01:17:32,651 --> 01:17:34,519
YOU ALL DIDN'T HAVE THAT --

2204
01:17:34,519 --> 01:17:37,722
>> I WILL GIVE YOU SORT OF
A

2205
01:17:37,722 --> 01:17:38,556
NONANSWER TO THAT.

2206
01:17:38,556 --> 01:17:39,691
IT'S A VERY SPECIFIC QUESTION

2207
01:17:39,691 --> 01:17:43,094
AND I THINK THE ANSWER IS IT

2208
01:17:43,094 --> 01:17:45,363
DEPENDS ON WHAT IT IS THEY'RE

2209
01:17:45,363 --> 01:17:45,764
COLLABORATING ON.

2210
01:17:45,764 --> 01:17:47,799
AND I WILL THROW IN THERE, IT'S

2211
01:17:47,799 --> 01:17:51,302
NOT JUST COMPUTER SCIENTISTS AND

2212
01:17:51,302 --> 01:17:51,870
STATISTICIANS, IT'S

2213
01:17:51,870 --> 01:17:52,404
MATHEMATICIANS, ALSO AND

2214
01:17:52,404 --> 01:17:53,304
ENGINEERING AND ALL THE OTHER

2215
01:17:53,304 --> 01:17:56,041
PEOPLE THAT THINK IN THAT WAY.

2216
01:17:56,041 --> 01:17:58,710
AND WHEN WE BUILD MODELS TO

2217
01:17:58,710 --> 01:18:00,211
EXPLAIN DISEASE OR TO MAKE

2218
01:18:00,211 --> 01:18:05,417
PREDICTIONS OR TO MAKE DECISIONS

2219
01:18:05,417 --> 01:18:06,951
THEY'RE OFTEN COMBINATIONS OF

2220
01:18:06,951 --> 01:18:07,952
APPROACHES AND THOSE

2221
01:18:07,952 --> 01:18:09,320
COMBINATIONS OF APPROACHES CAN

2222
01:18:09,320 --> 01:18:12,590
BE STATISTICS OR MATH OR AI OR

2223
01:18:12,590 --> 01:18:13,425
ANY COMBINATION OF THEM.

2224
01:18:13,425 --> 01:18:15,727
AND SO WE SEE, WE SEE, I THINK

2225
01:18:15,727 --> 01:18:18,063
EVERY VERSION OF THAT

2226
01:18:18,063 --> 01:18:18,730
COLLABORATION JUST DEPENDING ON

2227
01:18:18,730 --> 01:18:23,768
WHAT THE QUESTION IS.

2228
01:18:23,768 --> 01:18:27,405
>> WITH THAT, AND THAT'S
WHY

2229
01:18:27,405 --> 01:18:31,476
THE, YOU KNOW, INCLUSIVE AND

2230
01:18:31,476 --> 01:18:32,544
TEAM SCIENCE AND

2231
01:18:32,544 --> 01:18:34,846
MULTIDISCIPLINARY TEAM SCIENCE

2232
01:18:34,846 --> 01:18:37,582
APPROACH IS VERY IMPORTANT AND

2233
01:18:37,582 --> 01:18:42,387
THE STATISTICIAN AND PROGRAMMERS

2234
01:18:42,387 --> 01:18:43,655
AND EPIDEMIOLOGISTS ARE WORKING

2235
01:18:43,655 --> 01:18:46,324
TOGETHER TO SOLVE, ALSO TO

2236
01:18:46,324 --> 01:18:48,226
[INDISCERNIBLE] METRICS TO

2237
01:18:48,226 --> 01:18:50,361
MEASURE THE ACCURACY AND

2238
01:18:50,361 --> 01:18:51,896
PERFORMANCE OF THE AI MODEL AND

2239
01:18:51,896 --> 01:18:54,099
THIS IS A NEW AREA, AND THERE

2240
01:18:54,099 --> 01:18:59,170
ARE A LOT OF METHODS THAT NEED

2241
01:18:59,170 --> 01:19:01,639
TO BE DEVELOPED, HOW TO GREATLY

2242
01:19:01,639 --> 01:19:03,808
MEASURE AND ALSO IDENTIFY AND

2243
01:19:03,808 --> 01:19:07,212
CHARACTERIZE THE DIFFERENT BIAS

2244
01:19:07,212 --> 01:19:09,447
THAT IS THE DATA SET AND ALSO,

2245
01:19:09,447 --> 01:19:13,218
HOW THE AI LIFE CYCLE, SO THE

2246
01:19:13,218 --> 01:19:14,886
SHORT ANSWER IS THAT, YOU KNOW

2247
01:19:14,886 --> 01:19:16,988
THE OLD DAYS THAT YOU KNOW

2248
01:19:16,988 --> 01:19:20,959
DIFFERENT DISCIPLINE, THEY

2249
01:19:20,959 --> 01:19:22,327
COLLABORATE ON OTHERS, I ISSUE I

2250
01:19:22,327 --> 01:19:24,329
HAVE SEEN IN MY GRADUATE

2251
01:19:24,329 --> 01:19:25,830
OPPORTUNITY OR POST DOCS AT THE

2252
01:19:25,830 --> 01:19:29,400
UNIVERSITY OF MICHIGAN THAT

2253
01:19:29,400 --> 01:19:31,369
PEOPLE FROM SOCIOLOGY AND

2254
01:19:31,369 --> 01:19:32,637
PSYCHOLOGY AND EPIDEMIOLOGY AND

2255
01:19:32,637 --> 01:19:35,974
YOU KNOW PHYSICIANS, THEY WORK

2256
01:19:35,974 --> 01:19:37,909
TOGETHER AND BIOSTATISTICIANS AS

2257
01:19:37,909 --> 01:19:38,977
WELL TO ADDRESS CERTAIN HEALTH

2258
01:19:38,977 --> 01:19:41,379
ISSUE FROM A DIFFERENT

2259
01:19:41,379 --> 01:19:41,980
PERSPECTIVE.

2260
01:19:41,980 --> 01:19:44,249
SO, I THINK TEAM SCIENCE

2261
01:19:44,249 --> 01:19:47,385
APPROACH IS THE 1 TO GO TO

2262
01:19:47,385 --> 01:19:48,720
ADDRESS THOSE [INDISCERNIBLE].

2263
01:19:48,720 --> 01:19:50,922
>> I DO THINK BOTH ARE
REALLY

2264
01:19:50,922 --> 01:19:51,990
HELPFUL BUT I ALSO THINK YOU

2265
01:19:51,990 --> 01:19:53,324
NEED TO UNDERSTAND THE TRAINING

2266
01:19:53,324 --> 01:19:54,692
OR PREPARATION THAT THEY ARE

2267
01:19:54,692 --> 01:19:56,928
COMING TO FOR THAT PROBLEM.

2268
01:19:56,928 --> 01:19:59,297
LIKE THAT HAPPENED WHEN YOU RUN

2269
01:19:59,297 --> 01:20:00,932
ACROSS MULTIPLE FIELDS ISSUES

2270
01:20:00,932 --> 01:20:04,068
EVEN CHEMISTS THINK DIFFERENTLY

2271
01:20:04,068 --> 01:20:04,936
THAN BIOCHEMISTS, AND TOW ME

2272
01:20:04,936 --> 01:20:07,472
THEY'RE ALL THE SAME BUT --I

2273
01:20:07,472 --> 01:20:09,774
KNOW THEY'RE VERY, VERY

2274
01:20:09,774 --> 01:20:10,408
DIFFERENT.

2275
01:20:10,408 --> 01:20:13,745
BUT WHAT THAT REALLY MEANS IS 95

2276
01:20:13,745 --> 01:20:15,513
TIMES OUT OF A HUNDRED YOU GET

2277
01:20:15,513 --> 01:20:16,781
THAT RESULT AND 5 TIMES YOU

2278
01:20:16,781 --> 01:20:18,783
DON'T SO IN THAT DEFINITION OF

2279
01:20:18,783 --> 01:20:20,552
TRUTH, RIGHT, IT ACTUALLY IS

2280
01:20:20,552 --> 01:20:22,754
CHANGED FOR THAT 5 THAN THE

2281
01:20:22,754 --> 01:20:23,788
REST, THE STATISTICIAN SAYS

2282
01:20:23,788 --> 01:20:27,091
WELL, NO IT'S TRUE OR NOT TRUE.

2283
01:20:27,091 --> 01:20:28,793
BUT THEN HAVE YOU AN ENGINEER

2284
01:20:28,793 --> 01:20:30,795
WHO WAS GIIVE A DESIGN GOAL,

2285
01:20:30,795 --> 01:20:34,265
MAKE THIS MODEL, GET TO BE

2286
01:20:34,265 --> 01:20:35,433
PREDICTIVE FOR 95% OF OUTCOMES

2287
01:20:35,433 --> 01:20:37,335
AND I GET TO 90%S ARE WE'RE

2288
01:20:37,335 --> 01:20:38,403
DOING WAY BETTER THAN WHAT WE

2289
01:20:38,403 --> 01:20:40,605
WERE ABLE ON DO BEFORE BUT

2290
01:20:40,605 --> 01:20:42,574
STATISTICALLY BUT IT'S NOT FULLY

2291
01:20:42,574 --> 01:20:44,309
WHAT WE WANT SO I THINK IT'S

2292
01:20:44,309 --> 01:20:45,944
GOING TO TAKE CONTEXT BUT I

2293
01:20:45,944 --> 01:20:47,979
THINK AGAIN IT'S THAT NATURAL

2294
01:20:47,979 --> 01:20:50,181
SKEPTICISM THAT BOTH FIELDS WILL

2295
01:20:50,181 --> 01:20:51,850
BRING TO IT THAT HOPEFULLY MAKE

2296
01:20:51,850 --> 01:20:53,017
IT A BETTER OUTCOME AND

2297
01:20:53,017 --> 01:20:54,719
SOMEONE'S GOING TO SAY, WELL

2298
01:20:54,719 --> 01:20:59,657
LET'S USE IT BEFORE WE GET TO

2299
01:20:59,657 --> 01:21:01,259
PERFECTION, I THINK.

2300
01:21:01,259 --> 01:21:02,760
OOH OKAY, WE'RE DOWN TO OUR LAST

2301
01:21:02,760 --> 01:21:04,295
7 MINUTES AND I WILL NEED AT

2302
01:21:04,295 --> 01:21:06,998
LEAST A COUPLE MINUTES BEFORE WE

2303
01:21:06,998 --> 01:21:07,665
COMPLETELY CLOSE OUT.

2304
01:21:07,665 --> 01:21:10,168
AND THERE WAS 1 QUESTION I

2305
01:21:10,168 --> 01:21:11,469
DIDN'T GET TO IT'S NOT FAIR TO

2306
01:21:11,469 --> 01:21:13,705
GIVE YOU NOT MUCH TIME FOR IT,

2307
01:21:13,705 --> 01:21:15,340
BUT WHAT IS YOUR WORST CASE

2308
01:21:15,340 --> 01:21:18,009
SCENARIO IN TERMS OF THE USE OF

2309
01:21:18,009 --> 01:21:18,676
AI AND DATA.

2310
01:21:18,676 --> 01:21:20,111
AND WHAT DO YOU REALLY WANT

2311
01:21:20,111 --> 01:21:21,613
PEOPLE TO TAKE AWAY FROM THIS

2312
01:21:21,613 --> 01:21:23,882
SESSION THAT CAME FROM YOU?

2313
01:21:23,882 --> 01:21:25,550
SO I SEE PEOPLE LAUGHING AT THAT

2314
01:21:25,550 --> 01:21:28,486
QUESTION BUT IT'S OUT THERE.

2315
01:21:28,486 --> 01:21:30,822
SO I'LL START WITH YOU JENNIFER

2316
01:21:30,822 --> 01:21:34,692
AND THEN YOU SAMSON AND MANU YOU

2317
01:21:34,692 --> 01:21:37,428
WILL GET THE LAST WORD SO

2318
01:21:37,428 --> 01:21:38,596
JENNIFER, 1 MINUTE EACH.

2319
01:21:38,596 --> 01:21:40,965
>> FANTASTIC THIS IS THE 1
I

2320
01:21:40,965 --> 01:21:44,035
WANTED TO GO FIRST ON, WORST

2321
01:21:44,035 --> 01:21:46,137
CASE SCENARIO, MY FEELING IS WE

2322
01:21:46,137 --> 01:21:47,639
CAN'T PREDICT THE WORST CASE

2323
01:21:47,639 --> 01:21:48,940
SCENARIO AND WE NEED TO FOCUS ON

2324
01:21:48,940 --> 01:21:50,842
WHAT ARE THE THINGS ARE WE CAN

2325
01:21:50,842 --> 01:21:53,711
CONTROL AND HOW CAN WE THINK

2326
01:21:53,711 --> 01:21:55,413
ABOUT FRAMING ETHICAL AND

2327
01:21:55,413 --> 01:21:56,814
RESPONSIBLY USE AND LEARNING

2328
01:21:56,814 --> 01:21:58,783
FROM WHAT'S ALREADY OUT THERE.

2329
01:21:58,783 --> 01:22:00,418
I THINK, YOU KNOW TECHNOLOGY IS

2330
01:22:00,418 --> 01:22:03,254
OUT THERE, AND IT IS IN USE AND

2331
01:22:03,254 --> 01:22:05,223
THE MORE WE UNDERSTAND IT AND

2332
01:22:05,223 --> 01:22:07,959
THE MORE WE PROVIDE PEOPLE WITH

2333
01:22:07,959 --> 01:22:09,694
TOOLS AND FRAMEWORKS AND

2334
01:22:09,694 --> 01:22:13,498
GUIDANCE AROUND HOW TO USE IT

2335
01:22:13,498 --> 01:22:14,098
EFFECTIVELY THE BETTER.

2336
01:22:14,098 --> 01:22:15,099
ONE THING YOU WANT PEOPLE TO

2337
01:22:15,099 --> 01:22:18,069
REMEMBER ABOUT WHAT YOU SAID

2338
01:22:18,069 --> 01:22:22,173
TODAY, IS THAT IT?

2339
01:22:22,173 --> 01:22:23,408
>> SEPARATE QUESTION.

2340
01:22:23,408 --> 01:22:25,343
THINK COLLABORATION, THINK CROSS

2341
01:22:25,343 --> 01:22:25,643
DISCIPLINE.

2342
01:22:25,643 --> 01:22:29,280
JUST LEAVE IT AT THAT.

2343
01:22:29,280 --> 01:22:33,584
>> OKAY, SAMSON, A MINUTE.

2344
01:22:33,584 --> 01:22:35,019
>> SO MY WORST SCENARIO IS
THAT

2345
01:22:35,019 --> 01:22:36,654
AI WILL BE HERE, IT'S ALREADY

2346
01:22:36,654 --> 01:22:38,222
THERE, IT'S BEING USED IN

2347
01:22:38,222 --> 01:22:39,624
HEALTHCARE, IT'S GOING TO BE THE

2348
01:22:39,624 --> 01:22:43,561
DRIVING FORCE FOR FUTURE

2349
01:22:43,561 --> 01:22:43,861
HEALTHCARE.

2350
01:22:43,861 --> 01:22:51,135
BUT I AM WORRIED THAT IT DOESN'T

2351
01:22:51,135 --> 01:22:54,739
  PERPETUATE SYSTEMIC IN THIS

2352
01:22:54,739 --> 01:22:56,240
MAKING IT LARGER IN A

2353
01:22:56,240 --> 01:22:57,675
COMPOUNDING SCALE AND THAT'S MY

2354
01:22:57,675 --> 01:22:59,143
WORRY BECAUSE YOU'RE USING

2355
01:22:59,143 --> 01:23:00,111
ALREADY THE EXISTING BIAS DATA

2356
01:23:00,111 --> 01:23:02,213
SET AND WE ARE NOT REQUIRED

2357
01:23:02,213 --> 01:23:04,682
THERE IN TERMS OF BRINGING

2358
01:23:04,682 --> 01:23:06,284
DIFFERENT PEOPLE, SO WE NEED TO

2359
01:23:06,284 --> 01:23:07,685
DO THAT, A BET ARE YOB CORPS

2360
01:23:07,685 --> 01:23:09,287
THAT THAT AND THE PEOPLE THAT I

2361
01:23:09,287 --> 01:23:11,689
WANT TO REMEMBER, HERE, IS THAT

2362
01:23:11,689 --> 01:23:14,058
IF AI IS GOING TO BE A GOOD

2363
01:23:14,058 --> 01:23:16,227
FORCE, YOU KNOW WE HAVE TO

2364
01:23:16,227 --> 01:23:19,764
DESIGN IT AND DEVELOP IT WITH

2365
01:23:19,764 --> 01:23:23,735
EQUITY AND INCLUSIVE IN MIND.

2366
01:23:23,735 --> 01:23:26,838
SO THAT TO,A VOID THIS SORT OF

2367
01:23:26,838 --> 01:23:27,638
DISCRIMINATION AND WORSE OUTCOME

2368
01:23:27,638 --> 01:23:30,575
THAT WE HAVE SEEN IN TUSKEGEE

2369
01:23:30,575 --> 01:23:33,978
AND OTHERS THAT COULD COULD

2370
01:23:33,978 --> 01:23:36,147
HAPPEN AGAIN WITH AI EVEN AT

2371
01:23:36,147 --> 01:23:37,615
LARGER SCALE IN DIFFERENT

2372
01:23:37,615 --> 01:23:42,120
HEALTHCARE ORGANIZATIONS THAT,

2373
01:23:42,120 --> 01:23:42,620
IS MY WORRY.

2374
01:23:42,620 --> 01:23:43,755
>> AND THE THING YOU WANT
PEOPLE

2375
01:23:43,755 --> 01:23:45,523
TO TAKE AWAY FROM YOUR

2376
01:23:45,523 --> 01:23:47,759
PRESENTATION TODAY?

2377
01:23:47,759 --> 01:23:51,262
>> I THINK INCLUSIVE IS
VERY

2378
01:23:51,262 --> 01:23:53,998
IMPORTANT, DIVERSITY IS NOT LIKE

2379
01:23:53,998 --> 01:23:57,135
A WORD, IT'S VERY IMPORTANT FOR

2380
01:23:57,135 --> 01:23:58,503
AI DEVELOPMENT ESPECIALLY HAVING

2381
01:23:58,503 --> 01:24:01,706
TEAM SCIENCE, BUT WHEN WE

2382
01:24:01,706 --> 01:24:04,008
DEVELOP IT, AI HAVE TO DEVELOP

2383
01:24:04,008 --> 01:24:07,111
WITH EQUITY IN MIND AS WELL.

2384
01:24:07,111 --> 01:24:07,378
>> MANU?

2385
01:24:07,378 --> 01:24:10,114
>> NOT TO SCARE ANYONE,
NO, MY

2386
01:24:10,114 --> 01:24:11,516
WORST FEAR, AGAIN I GREW UP

2387
01:24:11,516 --> 01:24:12,950
BLACK IN AMERICA, I HAVE A BLACK

2388
01:24:12,950 --> 01:24:15,053
FAMILY IS THAT THE CONSPIRACY

2389
01:24:15,053 --> 01:24:16,487
THEORIES WILL TAKE OVER OR THAT

2390
01:24:16,487 --> 01:24:18,656
THE MODELS WILL BE TRAINED ON

2391
01:24:18,656 --> 01:24:20,191
BAD DATA AND PEOPLE WILL SAY,

2392
01:24:20,191 --> 01:24:22,627
LOOK, I RAN MY OWN ANALYSIS

2393
01:24:22,627 --> 01:24:25,596
USING AI, IT SAID THIS.

2394
01:24:25,596 --> 01:24:27,198
ALMOST LIKE WE WOULD GET WITH

2395
01:24:27,198 --> 01:24:28,633
WEBMD BACK IN THE DAY WHEN

2396
01:24:28,633 --> 01:24:30,268
EVERYBODY LOOKS UP THEIR OWN

2397
01:24:30,268 --> 01:24:32,003
SYMPTOMS EXCEPT HERE THEY COULD

2398
01:24:32,003 --> 01:24:33,571
SAY HEY, I HAVE DATA I USED THE

2399
01:24:33,571 --> 01:24:34,972
COMPUTER AND IT TOLD ME THIS, SO

2400
01:24:34,972 --> 01:24:36,841
I DON'T NEED TO DO ALL OF THOSE

2401
01:24:36,841 --> 01:24:38,242
OTHER THINGS THAT YOU ALL THINK

2402
01:24:38,242 --> 01:24:40,912
OR MY DOCTOR THINKS, THAT'S MY

2403
01:24:40,912 --> 01:24:41,979
BIGGEST FEAR ABOUT PUTTING THAT

2404
01:24:41,979 --> 01:24:44,015
TRUST IN WHAT IT MIGHT BE THE

2405
01:24:44,015 --> 01:24:45,616
OUTPUT AND CLAIMING, I HAVE

2406
01:24:45,616 --> 01:24:48,052
EVIDENCE OF WHY THIS IS BEST.

2407
01:24:48,052 --> 01:24:49,420
THE MESSAGE I THINK PEOPLE

2408
01:24:49,420 --> 01:24:52,657
SHOULD TAKE HOME FROM ME TALKING

2409
01:24:52,657 --> 01:24:54,826
HERE IS HUMANS ARE SMARTER THAN

2410
01:24:54,826 --> 01:24:56,828
CO AM PEWTERS, I KNOW THAT SEEMS

2411
01:24:56,828 --> 01:24:58,563
COUNTER TO EVERYTHING WE WANT TO

2412
01:24:58,563 --> 01:24:59,964
SAY, BUT THE COMPUTERS ARE

2413
01:24:59,964 --> 01:25:01,399
LEARNING FROM WHAT HUMANS HAVE

2414
01:25:01,399 --> 01:25:03,267
DONE, AND THE HUMANS AT THIS

2415
01:25:03,267 --> 01:25:05,503
STAGE IN OUR TECHNOLOGY ARE

2416
01:25:05,503 --> 01:25:06,137
SMARTER THAN COMPUTERS.

2417
01:25:06,137 --> 01:25:07,939
WE HAVEN'T HAD THE SENTIENT

2418
01:25:07,939 --> 01:25:09,006
BREAK THROUGH YET BUT I THINK

2419
01:25:09,006 --> 01:25:10,308
THAT MATTERS, AND I THINK THE

2420
01:25:10,308 --> 01:25:11,476
OTHER REASON IT MATTERS IS

2421
01:25:11,476 --> 01:25:13,111
AGAIN, I WORK WITH A LOT OF

2422
01:25:13,111 --> 01:25:15,079
DIVERSE COMMUNITIES IS PEOPLE

2423
01:25:15,079 --> 01:25:17,482
HAVE A WAY OF KNOWING IS A WAY

2424
01:25:17,482 --> 01:25:18,783
OF LEARNING KNOWLEDGE AND

2425
01:25:18,783 --> 01:25:20,017
DIFFERENT CULTURE AND INDIGENOUS

2426
01:25:20,017 --> 01:25:22,120
CULTURE AND HAVE WAYS OF KNOWING

2427
01:25:22,120 --> 01:25:23,554
THINGS THAT ARE BASED ON HUMAN

2428
01:25:23,554 --> 01:25:24,722
EXPERIENCES, THAT YES, WE WANT

2429
01:25:24,722 --> 01:25:26,491
THE DATA, WE WANT TO MODERNIZE

2430
01:25:26,491 --> 01:25:28,726
AND ADVANCE HOW WE THINK ABOUT

2431
01:25:28,726 --> 01:25:32,296
IT BUT HUMANS, AT LEAST TODAY,

2432
01:25:32,296 --> 01:25:33,598
ARE STILL SMARTER THAN

2433
01:25:33,598 --> 01:25:33,865
COMPUTERS.

2434
01:25:33,865 --> 01:25:36,701
SO I WILL LEAVE THAT.

2435
01:25:36,701 --> 01:25:40,138
>> WELL, THANK YOU ALL 3
SO VERY

2436
01:25:40,138 --> 01:25:40,471
MUCH AND MANU.

2437
01:25:40,471 --> 01:25:41,439
YOU WILL HAVE TO TELL ME WHEN

2438
01:25:41,439 --> 01:25:43,808
THE DAY COMES THAT WE'RE NOT

2439
01:25:43,808 --> 01:25:47,645
SMARTER THAN COMPUTERS.

2440
01:25:47,645 --> 01:25:50,181
[LAUGHTER]

2441
01:25:50,181 --> 01:25:50,815
REALLY WONDERFUL PANEL,

2442
01:25:50,815 --> 01:25:51,249
WONDERFUL INSIGHTS.

2443
01:25:51,249 --> 01:25:52,483
I THINK THERE ARE SLIDES I NEED

2444
01:25:52,483 --> 01:25:55,486
TO SHARE AS WE ARE CLOSING THIS

2445
01:25:55,486 --> 01:25:55,653
OUT.

2446
01:25:55,653 --> 01:25:57,455
YEAH, THE FIRST THING I WOULD

2447
01:25:57,455 --> 01:25:59,891
LIKE WOULD BE TO ASK YOU ALL TO

2448
01:25:59,891 --> 01:26:02,260
TAKE A MEMORY CLONE TONIGHT

2449
01:26:02,260 --> 01:26:06,330
SHARE YOUR FEEDBACK ABOUT THE

2450
01:26:06,330 --> 01:26:06,564
SEMINAR.

2451
01:26:06,564 --> 01:26:08,299
I THINK YOU WILL GET THIS

2452
01:26:08,299 --> 01:26:10,701
IMMEDIATELY UPON OUR CLOSING

2453
01:26:10,701 --> 01:26:13,471
OUT, OR ARE THEY GETTING THIS

2454
01:26:13,471 --> 01:26:14,338
NOW?

2455
01:26:14,338 --> 01:26:16,741
CAN SOMEONE TELL ME, ARE THEY

2456
01:26:16,741 --> 01:26:17,742
GETTING IT NOW?

2457
01:26:17,742 --> 01:26:19,744
>> THELING WAS DROPPED IN
THE

2458
01:26:19,744 --> 01:26:20,178
CHAT.

2459
01:26:20,178 --> 01:26:20,912
>> IT'S BEING DROPPED INTO
THE

2460
01:26:20,912 --> 01:26:24,215
CHAT SO TAKE A MEMORY

2461
01:26:24,215 --> 01:26:25,116
RESPONSENT.

2462
01:26:25,116 --> 01:26:26,617
IT'S JUST A QUICK SCALE SO WE

2463
01:26:26,617 --> 01:26:29,353
CAN GET A SENSE OF HOW THIS WENT

2464
01:26:29,353 --> 01:26:34,659
FROM YOUR PERSPECTIVE. 

2465
01:26:34,659 --> 01:26:35,493
NEXT SLIDE, PLEASE.

2466
01:26:35,493 --> 01:26:36,794
AND PLEASE DO KEEP IN CONTACT

2467
01:26:36,794 --> 01:26:37,595
WITH US.

2468
01:26:37,595 --> 01:26:39,530
HERE'S OUR QR CODE, WE HAVE A

2469
01:26:39,530 --> 01:26:41,866
BLOG, WE HAVE A NEWS LETTER, WE

2470
01:26:41,866 --> 01:26:43,968
HAVE AN E-MAIL BOX, WE HAVE A

2471
01:26:43,968 --> 01:26:45,503
LINKED IN SIGHT, WE LOVE TO HEAR

2472
01:26:45,503 --> 01:26:48,372
FROM YOU, IT HELPS IN OUR

2473
01:26:48,372 --> 01:26:51,275
PLANNING FOR FUTURE SWDSS'S, OUR

2474
01:26:51,275 --> 01:26:53,344
NEXT 1 IS FEBRUARY 11th OF

2475
01:26:53,344 --> 01:26:54,478
2025.

2476
01:26:54,478 --> 01:26:56,280
AND YOU WILL RECEIVE AN E-MAIL

2477
01:26:56,280 --> 01:26:57,782
NOTIFICATION WHEN THAT

2478
01:26:57,782 --> 01:26:58,950
REGISTRATION SITE OPENS.

2479
01:26:58,950 --> 01:27:02,687
SO THANK YOU ALL SO VERY MUCH

2480
01:27:02,687 --> 01:27:08,092
PARTICULARLY DR. COUCH,

2481
01:27:08,092 --> 01:27:10,294
DR. GEBREAB, AND DR. PLATT.

2482
01:27:10,294 --> 01:27:11,929
IT WAS A WONDERFUL SEMINAR.

2483
01:27:11,929 --> 01:27:21,929
THANK YOU.