GOOD AFTERNOON, GOOD MORNING,
GOOD EVENING WHEREVER YOU ARE
WATCHING US FROM.
THANK YOU SO MUCH FOR YOINS US
FOR THIS SCIENTIFIC WORKFORCE
DIVERSITY SEMINAR ON HOW DIVERSE
PERSPECTIVES ENHANCED DATA
SCIENCE OUTCOMES.
I AM MARIE BERNARD NIH CHIEF
SCIENTIFIC OFFICER FOR WORKFORCE
DIVERSITY AND VERY HAPPY TO
WELCOME YOU TO THIS EVENT.
NEXT SLIDE ISSUES PLEASE.
TODAY WE HAVE A STAR STUDDED
CAST OF SPEAKERS, DR. JENNIFER
COUCH, WHO'S THE CHIEF OF THE
DIVISION OF CANCER BIOLOGY AT
THE NATIONAL CANCER INSTITUTE.
DR. SAMSON GEBREAB, PROGRAM
LEGAL FOR THE AIM-AHEAD PROGRAM.
AND DR. MANU PLATT, DIRECTOR FOR
THE TRUSTEES FOR BIOMEDICAL
ENGINEERING TECHNOLOGY
ACCELERATION AND ASSOCIATION
DIRECTOR FOR SCIENTIFIC
DIVERSITY EQUITY AND INCLUSION
AT THE NATIONAL INSTITUTE OF
BIOMEDICAL IMAGES AND
BIOENGINEERING.
I WILL PROVIDE MORE ABOUT THEIR
BACKGROUNDS LATER, BUT THEY ARE
THE BEST PEOPLE TO PRESENT OUR
VOW POINT ON THIS ISSUE.
NEXT SLIDE.
A FOURTH APPEARANCE HOUSEKEEPING
ITEMS, QUESTIONS THAT OFTEN COME
UP, DO YOU WANT A COPY OF THIS
PRESENTATION?
GO TO OUR WEBSITE
DIVERSITY.NIH.GOV WHERE SPEAKER
SLIDES ARE AVAILABLE AND 508
COMPLIANT.
DO YOU WANT A RECORDING OF THIS
EVENT, IT WILL BE POSTED ON THE
WEBSITE WITHIN THE NEXT FEW
BUSINESS DAYS.
AS YOU GO IN THERE, YOU WILL SEE
THAT THERE ARE RECORDING FROM
OTHER MULTIPLE SEMINARS AS WELL.
DO YOU HAVE QUESTIONS IN YOU CAN
LEVERAGE THE Q&A FEATURE IN THE
TOOL BAR TO SUBMIT YOUR
QUESTIONS, SO IT'S A Q&A
FEATURE, NOT THE CHAT FEATURE
AND IF YOU HAVE A NEED FOR
TECHNICAL SUPPORT, PLEASE E-MAIL
ARYANA.GOINSAT AT ICFNEXT.COM.
NEXT SLIDE.
SO THIS IS THE START OF OUR
25-26 SWDSS SEASON.
THE 23-24 SEASON HAD 3 REALLY
OUTSTANDING PRESENTATIONS, HOW
TO RESEARCH ACTIVE INSTITUTIONS
IMPACT THE DIVERSITY OF THE
SCIENTIFIC WORKFORCE, HOW DOES
DIVERSITY IMPACT INNOVATION IN
TEAM SCIENCE, HOW ARE
INSTITUTIONS TRANSFORMED TO
FOSTER CULTURES OF INCLUSIVE
EXCELLENCE?
YOU CAN USE THE QR CODE IN THE
CORNER HERE TO FIND THE
RECORDINGS, SLIDES, PROCEEDINGS
FOR ALL EXCEPT THE JUNE MEETING,
PROCEEDINGS FOR THE JUNE MEETING
WILL BE COMING SHORTLY AND AS I
SAID, THIS IS -- WE'VE BEEN DO
THANKSGIVING A BIT OF TIME NOW,
THERE ARE A TOTAL OF 10 OF THESE
SEMINARS OVER THE YEARS SO YOU
MIGHT WANT TO LOOK BACK AND SEE
SOME OF THE OTHERS, IF YOU UPON
DON'T WANT TO USE THE QR CODE,
YOU CAN GO TO DIVERSITY.NIH.GOV.
NEXT SLIDE.
AND COMING SOON AS PART OF THIS
FISCAL YEAR 25 INITIATIVE, HOW
CAN RESEARCH ACTIVE INSTITUTIONS
ENHANCE THEIR RESEARCH CAPACITY?
THAT'S SCHEDULED FEBRUARY 11th
OF 2024 FROM 1:30-3:00 P.M.
EASTERN TIME.
AS A REGISTRANT OF THIS MEETING,
WILL GET NOTIFICATION ONCE THAT
REGISTRATION SITE IS OPEN, BUT
PLEASE MARK IT ON YOUR
CALENDARS.
IT SHOULD BE AN EXCELLENT
SEMINAR.
NEXT SLIDE.
SO BEFORE WE GET FULLY INTO
THINGS WE WANTED TO GET A CHANCE
TO KNOW YOU A LITTLE BITTER, SO
WE HAVE A LITTLE POLL FOR YOU.
CAN WE PUT THE POLL UP PLEASE
EMPLOY.
[MUSIC ]
LITTLE POLL FOR YOU.
CAN WE PUT THE POLL UP PLEASE.
[MUSIC ]
>> OKAY, LET'S SEE WHAT WE FOUND
OUT.
SO THE MAJORITY OF YOU ARE
COLLABORATING WITH DATA
SCIENTISTS, 65% VERSUS 35%, IT
LOOKS LIKE THE MAIORITY OF THAT
RESPONDED, 66% ARE WORKING WITH
QUALITATIVE DATA, 43% IN AREA OF
HEALTH EQUITY, 27% IN ALGORITHMS
AND DATA MODELS AND 18% IN
OMICS.
SO THAT'S REALLY HELPFUL TO
KNOW, PARTICULARLY FOR OUR
PRESENTERS TO KNOW WHO THEY'RE
SPEAKING TO.
BEFORE WE GET STARTED WITH OUR
PRESENTERS HOWEVER, I HAVE A
VERY IMPORTANT GUEST WHO WILL BE
PROVIDING OPENING COMMENTS FOR
US DR. MONICA BERTAGNOLLI,
UNFORTUNATELY SHE WAS NOT ABLE
TO BE HERE IN PERSON BUT BECAUSE
THIS IS AN AREA THAT'S NEAR AND
DEAR TO HER HEART, SHE AS THE
NIH DIRECTOR HAS HAD HAS HAD 2
MAJOR FOCI, 1 IS MAKING SURE
THAT CARE IS PROVIDED TO ALL AND
IN THE HELT CARE INITIATIVE,
MAKING SURE THAT DATA IS
APPLICABLE TO ALL.
SHE'S VERY MUCH ENDORSING THE
INITIATIVE THAT WE HAVE HERE.
DR. BERTAGNOLLI, 17th DIRECTOR
OF THE NATIONAL INSTITUTES
HEALTH.
SHE WAS NOMINATED BY PRESIDENT
JOE BIDEN, MAY 2023, CONFIRMED
BY THE SENATE OF NOVEMBER 2023,
SO SHE'S JUST COMING UP ON HER
ANNIVERSARY OF HAVING BEEN
CONFIRMED.
SHE'S A FIRST SURGEON AND SECOND
WOMAN TO HOLD THE POSITION OF
NIH DIRECTOR.
SHE OVERSEES THE LARGEST CAMPUS
OF RESEARCH IN THE WORLD.
SHE PREVIOUSLY SERVED AS CANETH
DIRECTOR OF THE NCI, -- HARVARD
MEDICAL SCHOOL, SURGEON AND
BRIGHAM AND WOMEN'S HOSPITAL AND
A MEMBER OF THE GASTROINTESTINAL
CANCER TREATMENT AND SARCOMA
CENTERS AT DANA-FARBER INSTITUTE
SO CLEARLY A HIGH QUALIFIED
INDIVIDUAL IN THIS ROLE AND
REALLY HAPPY SHE WILL BE ABLE TO
GIVE US OPENING REMARKS.
ROLL THE TAPE PLEASE.
>> WELCOME, EVERYONE TO THIS
SESSION OF THE SCIENTIFIC
WORKFORCE DIVERSITY SEMINAR
SERIES.
I AM SO GLAD THIS SEMINAR IS
ADDRESSING DATA SCIENCE.
WE'RE LIVING IN A TIME OF RAPID
ADVANCEMENTS IN AREAS LIKE
INFORMATION SCIENCE AND DATA
ANALYTICS.
IN ORDER TO MAKE AS MUCH
PROGRESS AS POSSIBLE IN
ADVANCING HEALTH, WE NEED TO
MAKE SURE THAT THESE ANALYTERAL
METHODS ARE APPLIED TO DATA THAT
INCLUDES EVERYONE.
AFTERALL AT THE NATIONAL
INSTITUTES OF HEALTH, OUR
MISSION IS TO SEEK FUNDMENTAL
KNOWLEDGE AND TO USE THAT
KNOWLEDGE TO ENHANCE THE HEALTH
OF ALL.
I GREW UP IN RURAL WYOMING, IN A
PLACE WHERE THE NEAREST DOCTOR'S
OFFICE IS A HUNDRED MILES AWAY.
I KNOW FROM MY OWN EXPERIENCE
HOW IMPORTANT IT IS TO INSURE
THAT THE BENEFITS OF HEALTH
RESEARCH REACH PEOPLE FROM ALL
WALKS OF LIFE REGARDLESS OF
INCOME OR ZIP CODE.
SINCE BECOMING AN NIH DIRECTOR
LAST NOVEMBER, I'VE TAKEN ON 2
KEY PRIORITIES, THE FIRST IS TO
MAKE CLINICAL RESEARCH MORE
ACCESSIBLE SO THAT THEY REFLECT
THE FULL DIVERSITY OF AMERICANS.
AND SECOND, I WANT US TO EMBRACE
NEW ANALYTIC TOOLS, MAKE THEM
FAR MORE ACCESSIBLE AND INSURE
THAT THEIR USE SERVES TO ADVANCE
HEALTHCARE FOR ALL PEOPLE.
IT IS WELL KNOWN THAT MACHINE
LEARNING AND ARTIFICIAL
INTELLIGENCE ARE PRONE TO BIAS.
THEY PRODUCE WHAT THEY'VE
LEARNED FROM THE DATA THEY'RE
PROVIDED.
PART OF THE PROBLEM IS THAT THE
INFORMATION THESE METHODS BUILD
ON CAN REFLECT BIASES IN OUR OWN
CULTURE.
ADDITIONAL BIAS STEMS FROM HOW
PROBLEMS ARE APPROACHED, HOW
CODE IS WRITTEN, AND HOW
ALGORITHMS ARE IMPLEMENTED.
THESE ARE DANGERS WE CAN
MITIGATE BY MAKING SURE THAT
DATA SCIENTISTS ARE THEMSELVES
DIVERSE.
WE KNOW THAT TEAMS WITH DIVERSE
PERSPECTIVES CAN FILL OUT EACH
OTHER'S BLIND SPOTS.
IF WE DON'T ADDRESS BIAS WE RUN
THE RISK OF CAUSING HARM AND
EXACERBATING HARMFUL INIQUITIES
IN OUR SOCIETY.
FOR EXAMPLE, RESEARCHERS WHO
PUBLISHED THEIR FINDINGS IN THE
JOURNAL OF SCIENCE IN
OCTOBER 2019 FOUND THAT A
COMMERCIAL ALGORITHM WIDELY USED
IN THE HEALTHCARE SYSTEM WAS
BIASED TO OVERLOOK HEALTH RISKS
IN BLACK PATIENTS COMPARED WITH
WHITE PATIENTS.
LEADING TO LESS NEEDED CARE FOR
BLACK PATIENTS WITH UNCONTROLLED
ILLNESSES.
THE BIAS WAS ROOTED IN THE
ALGORITHM'S MISTAKEN ASSUMPTIONS
ABOUT HEALTHCARE COSTS, NOT
TAKING INTO,A COUNT THAT THERE
IS UNEQUAL ACCESS TO CARE
MEANING THAT THE HEALTHCARE
INDUSTRY SPENDS LESS MONEY
CARING FOR BLACK PASHTS THAN
WHITE PATIENTS.
IN ANOTHER EXAMPLE PUBLISHED IN
THE YOWRNAL OF NATURE MEDICINE
IN DECEMBER 2024, AN AI IMAGING
ALGORITHM TESTED AGAINST A LARGE
DATA SET OF CHEST X-RAYS WAS
FOUND TO BE MORE LIKELY TO MISS
DISEASE DIAGNOSIS FOR
UNDERSERVED POPULATIONS,
INCLUDING FEMALE PATIENTS,
PATIENTS UNDER 20 YEARS OF AGE,
BLACK AND HISPANIC PATIENTS AND
PATIENTS ON MEDICAID.
WE HAVE TO BUILD INCLUSIVE
ENVIRONMENTS AND DIVERSE
PERSPECTIVES BOTH IN OUR DATA
SES, AND AMONG DATA SCIENCE
RESEARCHERS.
HAVING DIVERSE PERSPECTIVES IS
REQUIRED FOR US TO DEVELOP TOOLS
AND PRODUCTS THAT MORE CLOSELY
MEET PEOPLE'S NEEDS AND WILL
HELP US ASK BETTER RESEARCH
QUESTIONS IN MUCH BETTER WAYS.
WITH OUR ADVANCING KNOWLEDGE AND
TECHNOLOGY, THERE IS NO GOOD
REASON FOR US NOT TO DELIVER
EVIDENCE-BASED DATA-DRIVEN
HEALTHCARE TO EVERYONE.
THANK YOU ALL FOR ATTENDING
TODAY'S SEMINAR.
AS WE EMBRACE THE EFFORT TO WORK
TOWARD THIS GOAL.
>> SO YOU CAN SEE WHY WE SO
ENJOY DR. BERTAGNOLLI'S AS OUR
LEADER.
SHE IS FULLY LEADING US INTO THE
THINGS WE WILL BE DISCUSSING, WE
WILL FIRST TART WITH OUR
PANELIST DR. JENNIFER COUCH,
SHE'S WITH BIOEMERGENCYING AND
COMPUTATIONAL SCIENCES, THERE
SHE LEADS THE BRANCH BY
SUPPORTING BASIC RESEARCH AND
TECHNOLOGY DEVELOP AM AND
MOLECULAR APPLICATIONS BY
PHYSICAL BIOLOGY AND
COMPUTATIONAL AND MATHEMATICAL
METHODS.
SHE MANAGES A PORTFOLIO OF
GRANTS FOCUSED ON MULTISCALE
MODELING, BIO-INFORMATICS
CITIZEN SCIENCE AND DATA
SCIENCE, ADDITIONALLY HER AREAS
OF EXPERTISE INCLUDE ARTIFICIAL
INTELLIGENCE, MOLECULAR
APPLICATIONS, STRUCTURAL BIOLOGY
AND BIOTECHNOLOGY.
DR. COUCH, YOU HAVE THE FLOOR.
>> GREAT.
THANKS, EVERYBODY.
JUST SHARE HERE QUICKLY.
OKAY, ALL RIGHT.
I ASSUME EVERYBODY'S SEEING THAT
OKAY?
SO I JUST WANT TO -- THAT'S A
TOUGH ACT TO FOLLOW BOTH OF YOU
SO I WILL TRY AND STAY QUICKLY
ON TIME HERE SO THAT WE CAN GET
TO THE REALLY EXCITING PANEL
DISCUSSION AT THE END AND I WILL
JUST TALK ABOUT A VARIETY OF
QUICK VIGNETTES HERE ABOUT HOW
WE'RE SUPPORTING BRINGING A
BLUEDER PERSPECTIVE INTO CANCER
DATA SCIENCE AND BIOMEDICAL DATA
SCIENCE IN GENERAL.
>> DR. COUCH WE CANNOT SEE YOUR
PRESENTATION.
>> YOU CANNOT SEE MY
PRESENTATION.
OKAY, SORRY.
OH BECAUSE I FAILED TO HIT THE
LAST BUTTON.
THERE WE GO.
SORRY ABOUT THAT.
ALL RIGHT.
SO, I JUST WANT TO START HERE
WITH A QUICK MENTION OF AI EVEN
THOUGH I KNOW YOU WILL HEAR A
LOT OF THAT LATER FROM SAMSON.
SO AI IS EVERYWHERE IN CANCER
RESEARCH AND AI AND DATA SCIENCE
IN GENERAL RUN THROUGH THE WHOLE
SPECTRUM OF CANCER RESEARCH AND
CLINICAL PRACTICE INCLUDING
SCREENING, DIAGNOSIS, DRUG
DISCOVERY AND SURVEILLANCE AND
HEALTHCARE DELIVERY, BUT ALSO IN
THE AREA THAT I WORK IN THIS
UNDERSTANDING THE BASIC
FUNDAMENTAL BIOLOGICAL
MECHANISMS THAT UNDERLIE CONSER
INITIATION PROGRESSION.
SORRY, HAVING TECHNICAL
DIFFICULTIES HERE FOR A
SECURITIZATION.
APOLOGIES EVERYONE.
ALL RIGHT, THERE WE GO.
AI IS EVOLVING SO RAPID AND SO
MUCH INTEREST IN IT, AND
PATIENTS AND ALL OF US ARE
BEGINNING TO ENGAGE WITH IT AND
WORRY ABOUT THINGS THAT YOU
HEARD DR. BERTAGNOLLI MENTION
ABOUT BI AS AND APPLICABILITY
AND A GENERAL DESIRE TO
UNDERSTAND IT BETTER AND I
WANTED TO HIGHLIGHT QUICKLY
HERE, THE CANCER AI
CONVERSATIONS THAT WE HAVE IN
THE IN, CI, THIS IS A WHERE WE
INVITE A SMALL GROUP OF EXPERTS
TO FROM A VARIETY OF DIFFERENT
PERSPECTIVES ON I SINGLE TOPIC
TO PROVIDE QUICK TALKS AND MEN A
MODERATED DISCUSSION AROUND A
COUPLE OF TOPICS IN CANCER AI
AND I FEATURED A COUPLE HERE
THAT ARE IN HEALTH DISPARITIES
AND GLOBAL ONCOLOGY BUT THERE'S
A WHOLE SERIES OF THESE
AVAILABLE ON THE WEBSITE, BOTH
PAST AND FUTURE, SO, ALSO AT NCI
AND THEN SPECIFICALLY IN THE
DIVISION OF CANCER BIOLOGY WHERE
I AM, WE SUPPORT A NUMBER OF
DATA SCIENCE HEAVY PROGRAMS AND
DATA SCIENCE SCATTERED
THROUGHOUT THE INVESTIGATOR
INITIATED POOL.
AND COORDINATING ACROSS ALL
THESE PROGRAMS AND SCIENCE AND
HELPING TO BUILD THE NEXT
TRANSDISCIPLINARY RESEARCH
WORKFORCE IS A BIG CHALLENGE AND
SO 1 OF THE WAYS THAT WE DO THAT
IS THROUGH A COORDINATING STRAY
JECTORY THAT COORDINATES ACROSS
THESE THAT RELIES SO MUCH ON
DATA SCIENCE.
SO IN ALL OF THOSE PROGRAMS, ALL
OF THOSE DATA SCIENCE HEAVY
PROGRAMS, THEY'RE ALL
MULTIDISCIPLINARY
TRANSDISCIPLINARY,
INTERDISCIPLINEAR EXPE THEY ALL
RELY ON DATA, SCIENCE, MATH,
EMERGENCYING AND WE WERE THE
ISED A LOT OF THIS SCIENCE NOW
FOR DECADES AND WHILE THE
GRADUATE STUDENTS, POST DOCS AND
EARLY CAREER RESEARCH IS
SUPPORTED IN PART IN THESE
PROGETHS MAKE UP -- MAKE UP
THESE LARGE PROGRAMS ARE
IMMERSED IN THESE
INTERDISCIPLINARY RESEARCH SPACE
AND TEAM SCIENCE, IT CAN BE
DIFFICULT FOR THEM AS THEY MOVE
ON FROM THOSE TEAMS INTO
STARTING UP THEIR OWN RESEARCH
AND BUILDING THEIR OWN TEAMS AND
NEW INSTITUTIONS THAT PERHAPS
DON'T HAVE THE FACILITIES OR
MULTIDISCIPLINARY TEAMS ALREADY
IN PLACE.
SO AFTER LISTENING TO THEM FOR
SOMETIME, 1 OF THE THINGS THAT
WE'VE STARTED TO DO NOW FOR MANY
YEARS IS SUPPORT AND WORK WITH
THESE JUNIOR INVESTIGATORS SO
THAT GRADUATE STUDENTS, POST
DOCS AND EARLY CAREER PEOPLE BY
RUNNING THESE THINGS WE CALL
JUNIOR INVESTIGATOR MEETINGS, SO
THESE ARE PLANNED BY AND RUN BY
AND RUN FOR THE JR.
INVESTIGATORS WITH OUR HELP AND
MANAGE AM AND THERE THEY JUST
EXCHANGE SCIENCE AND BUILD THEIR
NETWORKS AND GET MENTORING AND
CAREER ADVICE.
SO WE ALSO KNOW THAT THE
PIPELINE OF YOUNG SCIENTISTS CAN
SOMETIMES BE NOT AS DIVERSE ASK
INCLUSIVE AS WE WILL LIKE AND
THAT'S FOR A LOT OF REASONS, 1
OF WHICH IS THAT THE LACK OF
EARLY EXPOSURE AND HANDS ON TO
THIS KIND OF RESEARCH THAT
ENTICES PEOPLE INTO THOSE
CAREERS IN THE FIRST PLACE.
AND 1 OF THE BARRIERS THAT THESE
STUDENTINGS FACE SOMETIMES ARE
JUST FINANCIAL.
THEY NEED TRANSPORTATION, OR
THEY MAY HAVE SUMMER JOBS TO
SUPPORT THEMSELVES THROUGH THE
SUMMER, AND THIS IS AN EXAMPLE
HERE OF A PROGRAM RUN BY THE
MOFET INTEGRATED MATHEMATICAL
ONCOLOGY PROGRAM SUPPORTED IN
PART BY THE CANCER SYSTEM SYSTEM
BIOLOGY CONSORTIUM AND IT
REACHES OUT TO LOCAL HIGH SCHOOL
STUDENTS AND OFFERS A STIPEND SO
THEY CAN JOIN DURING THEIR
SUMMER BREAK, BUILD TEAMS, WORK
ON PROGECS THAT ARE
MULTIDISCIPLINARY, BRINGING
TOGETHER BASIC AND CLINICAL
RESEARCH WITH MATH AND COMPUTER
SCIENCE AND THIS SLIDES SHOWS
THE INAUGURAL SET OF STUDENTS
BACK IN 2015 WHICH IS QUITE
SMALL BUT NOW AFTER ALMOST 10
YEARS, THE DEMAND HAS GROWN TO
WHERE THEY HAVE 15 SPOTS
AVAILABLE AND OVER 200
APPLICANTS JUDGE UOF THE FROM
THEIR LOCAL AREA.
MOST OF THE TIEWPTS WHO COME
INTO THIS DO SCIENCE AND MATH
AND GO ON TO COLLEGE AFTER THIS
PROGRAM.
THEY BRING THAT
MULTIDISCIPLINARY APPROACH AS
THEY CONTINUE THEIR TRAINING AND
CAREERS.
ANOTHER EXPERIMENT THAT'S
UNDERWAY NOW THROUGH OUR
MULTICONSORTIUM TRAINING CENTER
IS TRYING TO CONNECT DIVERSITY
CANDIDATES WITH LABS THAT ARE
ABLE TO HOST AND RECEIVE
DIVERSITY SUPPLEMENTS AND MOST
OF OUR RESEARCH AWARDS ARE
ELIGIBLE TO RECEIVE DIVERSITY
SUPPLEMENTS TO HOST DIVERSITY
TRAINEES BUT IT CAN BE HARD TO
MAKE THOSE MATCHES AND THIS
PROGRAM SORT OF AIMS TO BRING
TOGETHER A MATCH MAKING EVENT
AND SEE IF BRINGING PEOPLE
TOGETHER AND DOING SOME MATCH
MAKING CAN HELP PEOPLE PASS THIS
HURDLE, OF FINDING THE RIGHT
HOST LAB AND THE RIGHT TRAINEE.
SO I WANT TO JUST TALK HERE FOR
THE LAST COUPLE OF MINUTES ABOUT
ALTASD MATE WAYS OF ENGAGING
PEOPLE, SORT OF REACHING THEM
WHERE THEY'RE AT.
SO USING THINGS LIKE GAMES OR
CITIZEN SCIENCE OR COMMUNITY
SCIENCE AND 1 WAY THAT PEOPLE
ENGAGE IN DATA SCIENCE ALL THE
TIME WITHOUT REALIZING IT IS
GAMES, GAME USED SOPHISTICATED
DATA SCIENCE TO HOE COMPLEXITY,
DEAL WITH MULTIPLE SCALES ISSUES
RENDER IMAGERY IN REALTIME, ALL
THE THINGS WE DO AND NEED IN
BIOMEDICAL RESEARCH, AND THEY
ENABLE REALTIME COLLABORATIONS,
SOMETIMES BETWEEN HUNDREDS OF
PEOPLE FROM ACROSS THE WORLD AT
ONCE AND THEY OFFER OPEN
EXPLORATION AND DISCOVERY
OPPORTUNITIES THAT IN SCIENCE I
THINK CAN LEAD US TO THOSE
AHA MOMENT WHEN IS WE SEE
SOMETHING DIFFERENTLY IN OR IN A
NEW WAY.
SO COMMUNITY SCIENCE, THOSE ARE
METHODS THAT TAP INTO THE
CREATIVE COLLECTIVE OUT THERE,
THE CREATIVITY AND INSIGHT AND
INTEREST THAT WE KNOW ARE
EVERYWHERE PATIENTS AND
CAREGIVERS AND COMMUNITIES AND
PEOPLE IN GENERAL WITH THEIR
UNIQUE INSIGHT ANDS CONTEXT AND
PERSPECTIVE AND JUST A GENUINE
DESIRE TO CONTRIBUTE.
SO, ENGAGING GAME DESIGNERS AND
THINKING ABOUT GAMES IN SCIENCES
IS NOT TRIVIAL.
SO WE HAVE BEEN APPROACHING THIS
FROM A VARIETY OF DIFFERENT WAYS
ACROSS THE LAST SEVERAL YEARS
AND WE SORT OF WITH THE SERIES
OF CONVERSATIONS HERE BETWEEN
GAME DESIGNERS OR USER
EXPERIENCE EXPERTS AND THEN
BIOMEDICAL RESEARCHERS, IN THIS
CASE ALL CANCER RESEARCHERS
THROUGH THE CANCER MOONSHOT AND
WE RECORDED THOSE EXCHANGES AND
THEN USE THAT AS INSPIRATION FOR
OTHERS TO SORT OF THINK ABOUT
HOW TO COLLABORATE.
THIS IS A GAME DESIGNER WHO
DESIGNS EX PERIENTAL CAMPAIGNS
WITH A RESEARCHER WHO RUNS A
CANCER RESEARCH PROGRAMS USING
THAT AS A WAY TOCCATAALIZE
COLLABORATIONS BETWEEN OTHERS.
AND I'M JUST GOING TO END HERE
WITH 1 LAST EXAMPLE THAT
SOMETIMES WHAT HOLDS UP NEW
PARTNERSHIPS AND STOPS PEOPLE
FROM VERY DIFFERENT FEELS FROM
COMING TOGETHER IS THE INABILITY
TO FIND PARTNERS, PEOPLE DON'T
KNOW HOW TO MEET PEOPLE IN OTHER
FIELDS, SOMETIMES AND SOEE RUN
THESE INNOVATION IDEAS OR SAND
PITS AS A WAY TO BRING IN
INDIVIDUALS FROM DIFFERENT
FIELDS AND DIFFERENT WORLDS,
SOMETIMES PATIENT ADVOCATES OR
OTHERS TOGETHER TO FIND NEW
COLLABORATORS, TO MEET AND TO
UNDERSTAND EACH OTHER'S FIELDS
AND THEN TO PROPOSE IDEAS FOR
PILOT PROJECTS, SOMETIMES WITH
FUNDS AT THE END AND SOMETIMES
NOT AND I'M JUST SHOWCASING THIS
1 AS A DAILY BASIS THEA SCIENCE
RELEVANT EXAMPLE THAT'S GOING TO
TAKE PLACE IN A COUPLE OF MONTHS
AND I THINK THAT LOOKS LIKE MY
TIME IS UP.
>> THANK YOU.
>> THANK YOU VERY MUCH.
OUR NEXT SPEAKER IS DR. MANU
PLATT, DIRECTOR OF CENTER FOR
ENGINEERING BIOLOGY AND
ASSOCIATE DIRECTOR FOR
SCIENTIFIC DIVERSITY EQUITY AND
INCLUSION AT THE NATIONAL
INSTITUTE OF BIOMEDICAL
ENGINEERING HIS RESEARCH FOCUSES
ON MECHANISMS OF DEC,
TRANSLATIONAL APPROACHES IN
STROKES FOR PEOPLE AFFECTED WITH
SICKLE CELL DISEASE AND
HARNESSING PROTEOLYTIC SYSTEMS
AND BIOLOGY TOOLS TO PREDICT
DISEASE PROGRESSION.
INTEGRATED RESEARCH AND
MENTORING GOALS WILL CHANGE THE
LOOK OF THE NEXT GENERATION OF
SCIENTISTS THAT ENGINEERING
THROUGH SUCCESSFUL DIVERSITY
PROGRAMS HE HAS INITIATED.
DR. PLATT.
NTHANK YOU SO MUCH FOR THAT
INTRODUCTION DR. BERNARD AND I
FEEL LIKE OUR DIRECTOR
DR. BERTAGNOLLI STOLE MY
DISCUSSION BUT I WILL PUT SOME
MEAT ON WHAT SHE WAS DISCUSSING.
SO YOU KNOW MY TAKE HOME MESSAGE
IS TO HIT IT UP FRONT, DIVERSIFY
YOUR TEAM AND YOUR TEAM AT EARLY
STAGES PARTICULARLY IN THE
CONTEXT OF KNOWING ABOUT
TWEPPING NEW TECHNOLOGIES, THEN
I THINK IT'S IMPORTANT TO
CONSIDER THE IMPACT OFIOURE
TECHNOLOGY NEAR ALL HUMANS, AND
WE WILL TALK ABOUT REASONS WHY,
AND THEN AGAIN IF YOU NEED A
MONEY REASON, THAT CAN HELP
EXPAND THE MARKET AND THE IMPACT
OF YOUR TECHNOLOGY AND SO THERE
ARE CONSEQUENCES WHEN WE DON'T,
DEVICE DESIGN, WILL LEAD TO
AVOIDABLE UK COVID DEATHS,
PULSEOX IMPEDIMENTSITTERS DID
NOT WORK AS WELL FOR PEOPLE OF
COLOR AND CAN HAVE TERRIBLE
OUTCOMES FOR PEOPLE OF COLOR WHO
ARE RELYING ON THAT OXYGEN
PERCENTAGE.
SO THEN AS THE DR. BERTAGNOLLI,
MENTIONED, THAT THERE WAS AN
ALGORITHM TO AUTOMATICALLY ADD
3-POINTS TO NONBLACK PATIENTS
SCORES MAKING IT SEEM AS THOUGH
BLACK PEOPLE WERE AT LOWER RISK
OF DYING FROM HEART PROBLEMS
SIMPLY BY VIRTUE OF RACE WHICH
WASN'T TRUE AND AGAIN IT'S
FORTUNATE REMEMBER THAT RACE IS
A SOCIAL CONSTRUCT AND NOT A
RELIABLE PROXY FOR GENETICS SO
WE'RE SEEING THESE DESPERATE
OUTCOMES.
MANY HAVE HEARD ABOUT THE
GLOMERULAR FILTRATION RATE WHICH
WAS MISCALCULATED FOR KIDNEY
FUNCTION IN BLACK AMERICANS AND
INFLATED THE EGFR RESULT WHICH
COVERED THE KIDNEY HEALTH.
THERE WERE STILL SEEING THAT
GREATER THAN 50% OF PATIENTS
WAITING FOR KIDNEY TRANSPLANTS
WERE ETHNIC MINORITIES AFRICAN
AMERICANS CONSITUTING 32% OF
THAT WAIT LIST, ALSO LEADING
BACK TO THE LATER DIAGNOSIS OF
THE KIDNEY DISFUNCTION, SO
THAT'S WHY I THINK ABOUT DATA TO
DEVELOP TO USE PHYSICIANS TO
USE, WE MUST CONSIDER OTHER
POPULATIONS.
SO THIS HAS BEEN OVERTURNED
RECENTLY WITH A LOT OF ADVOCACY
IN THE COMMUNITY, AND THE NEW
QUESTION IS HOW WILL THIS
ELIMINATE CO EFFICIENTS THAT ARE
AFFECTING BLACK PATIENTS AND IT
WILL TAKE TIME FOR THOSE NUMBERS
TO BE SHOWN SO WE CAN MAKE
DECISIONS.
BUT AGAIN AS JENNIFER LED OFF,
THERE'S A LOT OF TALK OF THIS,
BUT WE NEED TO BE CAREFUL OF
COMPUTER BIAS BECAUSE PEOPLE DO
PROVIDE THE INFORMATION AND WHO
TRAINS THE ALGORITHM.
I KNOW THESE THINGS ARE THINKING
OF THINGS WE HAVEN'T BEFORE BUT
THEY ARE DOING IT WITH THE
INFORMATION WITH WHICH WE FEED
THEM.
SO GENDER, DIVERSITY, ETHNICITY,
BODY TYPE, AGE, PREGNANCY, THESE
ARE MAJOR, MAJOR TIMES OF RISKY
HEALTH OUTCOMES, SO TO START
THIS COMPUTATIONAL BIAS WE MUST
MAKE A GREATER EFFORT TO RECRUIT
FROM DIFFERENT POPULATIONS.
THIS IS WHAT WE NEED TO OVERCOME
SO WE CAN DIVERSIFY THESE
WORKFORCES AND GET THESE BETTER
THOUGHTS.
I THINK BACK I TOOK A LOT OF
COMPUTER SCIENCE COURSES IN MY
EDUCATION AND I REMEMBER WHEN
DOING CODING THERE WAS A SET OF
NUMBERS YOU ALWAYS WANTED TO
TEST, YOU WOULD DO LIKE 0, 1,
NEGATIVE 1 AND THEN YOU DO A
FRACTION OR DECIMAL TO THEN SEE
IF IT WOULD BREAK YOUR CODE.
SO IN THINKING ABOUT HOW WE MAKE
SURE WE CAN DIVERSIFY THE TYPES
OF GROUPS AND COMMUNITIES TO BE
INCLUDED IN OUR HEALTHCARE
SOLUTIONS, AGAIN IN THE EARLIEST
PHASE OF DESIGN AND TECHNOLOGY,
TOO BEING ME BACK TO A LOT OF
WORK I USED TO DO IN THE
HIV/AIDS WORLD WHERE THEY WERE
THINKING ABOUT POPULATION SAYS
THAT WERE BEING LEFT BEHIND
WHICH MAKES IT SOLVING A PUBLIC
HEALTH CRISIS A BIT HARDER.
PERSON LIVING WITH HIV, YOUNG
WOMAN, PRISON, I'M A MIRROR
IMAGE GRANT, INYECTING DRUG
USER, SEX WORKER, YOU CAN SEE
THESE OTHER CATEGORIES ON THE
BOTTOM THAT IT WE CAN DEVELOP
CATEGORIES IF YOU'RE DEVELOPING
USEABLE TECHNOLOGY, THESE ARE
THE SLIGHTS OF INDIVIDUALS YOU
SHOULD CONSIDER WHERE YOUR
TECHNOLOGY WORK FORAND YOU DON'T
EACH HAVE A DIVERSE TEAM TO PUSH
YOU FOR THAT.
I ALSO WANT TO DO PUSH MAJOR
EFFORTS HAPPENING IN MY
INSTITUTE ISSUES THE NATIONAL
INTUITY OF BIOMEDICAL IMAGING
AND ENGINEERING, IMAGING IS A
BIG PART OF WHAT WE DO AND THEY
DEVELOPED THIS MEDICAL IMAGING
AND DATA RESOURCE CENTER,
STARTED DOING COVID TO COLLECT
X-RAY SCANS AND LOOK AT LUNG
DAMAGE AND DEVELOP AI AND
MACHINE LEARNING ALGORITHMS THAT
COULD DIAGNOSE THESE SCANS BUT
ALSO AT THE VERY EARLY DAYS
WANTED TO BE SURE THEY COULD
ADDRESS BIAS AND I DID VERSITY
IN THESE DATA SETS SO THAT IT
WOULD BE BROADLY APPLICABLE TO
THE BROADEST SWATH OF THE HUMANS
WITH THEIR CONDITIONS AND
THEY'VE ACTUALLY PUBLISHED IN
WORK AND DISSEMINATED IT SO IT'S
AVAILABLE FOR ALL TO SEE, BUT
AGAIN THINK BEING BIAS IN THE
EARLIEST PHASES OF THEIR
PROJECTS SUCH THAT THEN AS THEY
DISSEMINATE TO OTHERS, THESE
TOOLS TO ADDRESS OR IDENTIFY AI
OR MACHINE LEARNING BIAS, CAN
THEN BE USED TO REDUCE THOSE
CONQUENCES WE SEE.
SO IN MY LAST FEW MINUTES I WANT
TO BUST A MYTH.
WE DO NEED TO BUST THE MYTH THAT
BLACK PEOPLE AND OTHER PEOPLE OF
COLOR DO NOT WANT TO PARTICIPATE
IN CLINICAL TRIALS.
THERE'S GREAT RESHAPING AND
FRAMING OF THIS, AND TO, IT'S
REALLY ABOUT WHO IS BEING
OFFERED THE OPPORTUNITY TO
ACTUALLY PARTICIPATE, SO BIAS OF
OTHER PATIENTS SAYING THEY WILL
BE A DIFFICULT PATIENT, THEY
WILL NOT WANT TO DO ALL THESE I
THINK THISS, PRECLUDED
CLINICIANS FROM EVEN OFFERING
THESE INDIVIDUALS TO
PARTICIPATE.
SO A META-ANALYSIS OF THESE
STUDIES HAVE SHOWN THAT WHEN
ASKED, AT LEAST HALF
PARTICIPANTS OFFER, WOULD
PARTICIPANT IN A CANCER CLINICAL
TRIAL.
AND AGAIN, BLACK, HISPANIC AND
ASIAN PARTIC PLAN TO ANALYZE BY
AGES ENGAGED AT LEAST AS HIGH AS
WHITE PATIENTS.
SO WE TALK ABOUT ADDRESSING BIAS
IN IT AND WE NEED TO HAVE THE
POPULATION TO RECRUITED INTO THE
STUDY FOR US TO TRAIN THE MODEL
BUT WE NEED TO EVERYCOME THAT.
ANOTHER BIG BARRIER WAS BEING
RANDOMLY ASSIGNED IN THE CONTROL
TRIAL, NOBODY WANTED TO THE
PLACEBO, THEY WERE GOING TO DO
THE GOOD DRUG, NOT THAT MY
HEALTHCARE OF SUFFER WHILE I'M
IN THIS STUDY.
AND IF YOU LOOK AT THE NUMBERS
HERE, THE PHYSICIANS MAY NOT
OFFER THE TRIAL TO PATIENTS OUT
OF CONCERN OF A NUMBER OF THINGS
BUT THIS BECOMES A BARRIER IN
RECRUITING THESE DIVERSE NUMBERS
TO SHOW HOW THE CLINICAL TRIAL
ON YOUR DRUG OR THERAPY COULD
AFFECT THE GREATER SWATH OF
HUMANITY AND JUST TO CLOSE OUT
THIS GREAT QUOTE FROM THE NEW
ENGLAND JOURNAL OF MEDICINE THAT
ANOTHER THING WE NEED TO THINK
ABOUT IS EQUALLY IMPORTANT
MAKING MEDICINE A MORE
ANTIRACIST FIELD THEN YOU CAN
HAVE THOSE CLINICIANS THAT WILL
APPROACH ALL THEIR PATIENTS TO
TRY TO RECRUIT THEM AND AGAIN
THIS INVOLVES REVISITING OW
CLINICIAN SAYS CONCEPT ALLIZE
RACE TO BEGIN WITH.
I'M NOT A CLINICIAN BUT I WANT
TO DROP THESE OUT THERE SO WE
CAN GET THE MORE DIVERSE
RESEARCH AND CLINICAL TEAMS TOO
SPEAK TO ALL HUMANS.
HOW DO YOU RECRUIT A TEAM?
HAPPY TO TALK ABOUT THAT, I HAVE
A FEW STRATEGIES I USED OVER MY
CAREER BUT I LOOK FORWARD TO
DISCUSS THAT WITH THE PANEL.
THANK YOU.
>> THANK YOU SO MUCH DR. PLATT.
>> OUR LAST SPEAKER IS DR. SAMS
SON GABREAB, I ALWAYS PRONOUNCE
IT WRONG, I APOLOGIZE.
PROGRAM LEAD DATA SCIENCE
TECHNOLOGY.
HE JOINED OBSSR AS ITS CALLED IN
2022 TO LEAD NIH'S ARTIFICIAL
INTELLIGENCE MACHINE LEARNING
CONSORTIUM TO ADVANCE HEALTH
EQUITY AND RESEARCH DIVERSITY
FOR AIM AHEAD.
IN THIS ROLE, HE'S RESPONSIBLE
FOR THE OVERALL MANAGEMENT,
OVERSIGHT, COORDINATION AND
IMPLEMENTATION OF AIM-AHEAD
PROGRAM AND INSURING THE
BENEFITS OF BIG DATA AND
ARTIFICIAL INTELIENCE AND
MACHINE LEARNING TECHNOLOGIES
REACH ACROSS ALL POPULATIONS.
DR. GABREAB.
>> GOOD AFTERNOON, EVERYONE.
THANK YOU SO MUCH AND YOU SEE
THE SLIDES VERY WELL?
>> YES.
>> YES, THANK YOU.
>> THANK YOU.
YES SO DR. BERTAGNOLLI, AND
JENNIFER AND MANU HAS COVERED
MOST OF MY TALK ACTUALLY BUT I
WILL TRY MY BEST.
IT'S A TOUGH ACT TO FOLLOW.
SO AS YOU HAVE SEEN FROM THE
TALK FROM JENNIFER AND MANU,
THAT IT'S WIDELY USED IN THE
HEALTHCARE, BUT WE HAVE TO
REMEMBER THAT YOU KNOW THE
CURRENT AI SYSTEMS ARE
VULNERABLE TO THE LONG STANDING
SYSTEMIC SOCIAL AND HEALTH
INIQUITIES.
WITHOUT CONSIDERING EQUITY AND
DIVERSITY AND INCLUSION, THE
DEVELOPMENT AND THE DEPLOYMENT
OF AI IN THE HEALTHCARE IS GOING
TO BE PERPETUATED GIVEN
EXACERBATED AT A LARGE SCALE.
AND YOU HAVE SEEN
DR. BERTAGNOLLI MENTIONING THE
SCIENCE RESEARCH WHICH WAS
PUBLISHED BY DR. OPEN MIER WHO
HIGHLIGHTS AN ALEGORITHMS USING
IT AS A HEGHT CARE PROXY FOR
HEGHT CARE NEEDS AND CONCLUDED
PLAQUE PATIENTS ARE HEALTHIER
COMPARED TO EQUALLY SEEK
[INDISCERNIBLE].
AS A RESULT THIS LED TO
FEWER
RESOURCES AND LOWER QUALITY CARE
TO BLACK PATIENTS WHICH
COMPOUNDED THE EXISTING HEALTHY
CARE RESOURCES NEEDED AND THIS
IS THE KIND OF BIAS THAT WE ARE
TALKING ABOUT IN TERMS OF MAKING
SURE THAT TO MITIGATE BECAUSE
THE CURRENT HEALTHCARE SYSTEM IS
ALREADY, YOU KNOW BIASED AND HAS
SYSTEMIC ISSUES.
SO WHAT DO WE NEED, YOU KNOW IN
ORDER TO MITIGATE THOSE BIAS.
I WILL COVER SOME OF THE, YOU
KNOW POTENTIAL BIAS OR DIFFERENT
BIAS THAT ARE EXISTED WITHIN THE
SYSTEM.
SOME OF THEM COVERED BY MANU BUT
1 OF IT IS THE
UNDERREPRESENTATIVE CLINICAL
CARE DATA AND WE HAVE ALSO LACK
OF DIVERSITY IN THE AI
WORKFORCE, AND ADOPTION OF AI
TECHNOLOGY IN THE DIVERSE
COMMUNITIES.
ONE THINK THIS I WANT TO
HIGHLIGHT SPECIFICALLY THAT WAS
NOT HIGHLIGHTED IS THE LACK OF
DATA IN LIVED EXPERIENCE
ESPECIALLY IN SOCIAL
DETERMINANTS OF HEALTH.
FOR EXAMPLE IN JAMA, HIGHLIGHTED
MISSION LEARNING MODULES THAT
INCORPORATE SOCIAL DETERMINANTS
OF HEALTH IMPROVED THE
PREDICTION OF IN HOSPITAL
MOTILITY AMONG PATIENTS WITH
HEALTHCARE, PARTICULARLY BLACK
PATIENTS, THIS HIGHLIGHTS THAT
INTEGRATING SOCIAL DETERMINE
NABTS OF HEALTH INTO THE AI
MODEL TO MORE EFFECTIVE BUT ALSO
EQUITABLE AND INCLUSIVE
HEALTHCARE SOLUTION BUT THOSE
SOCIAL DETERMINANTS ARE ARE
MOSTLY CAPTURED IN OUR
HEALTHCARE SYSTEM, AND MANU
COVERED SOME OF THAT IN ADDITION
TO THOSE SOME OF THAT BIAS ALSO
COMES IN HOW WE ANALYZE, HOW WE
INTERPRET ALSO, THE ALGORITHM OR
THE IMPLEMENT IN HEALTHCARE
SYSTEM AS WELL.
SO WHAT IS NIH DOING IN THIS
REGARD TO OTHERS, THE BIAS IN AI
THAT ALSO MITIGATE THE HEALTH
DISPARITY, IN JULY 2024, NIH
LEADERSHIP HELD A RETIRED Y'ALL
FORM BY BRINGING DIFFERENT
STAKEHOLDERS WITH ADDRESSING
HEALTH DISPARITY AND MANY
HISTORICALLY UNDERREPRESENTED
COMMUNITIES AND RESEARCHERS HAVE
NOT BEEN ENGAGED IN THE
INFRASTRUCTURE OR DEVELOPMENT,
AND RECOGNIZING THIS, THE NIH
LAUNCHED A FLAGSHIP PROGRAM
CALLED THE ARTIFICIAL
INTELLIGENCE MACHINE LEARNING
CONSORTIUM TO ADVANCE HEALTH
EQUITY RESEARCHER DIVERSITY ALSO
KNOWN AS AIM-AHEAD.
US ON 3 AREAS ISSUES FIRST IS TO
INCREASE PARTICIPATION AND
REPRESENTATION OF RESEARCHERS
AND COMMUNITIES CURENTDLY
UNDERREPRESENTED IN THE
DEVELOPMENT BUT ALSO IN THE USE
OF AI.
THE PROGRAM ALSO PROVIDES
RESEARCH OPPORTUNITIES FOR
INVESTIGATORS TO ADDRESS HEALTH
DISPARITY BY REFERAGEING AI AND
ALSO ELECTRONIC HEALTH RECORDS
AND OTHER DATA SET LIKE SOCIAL
DETERMINANTS OF HEALTH.
ALSO IMPROVE THE CAPABILITIES
AND TECHNOLOGIES FOR COMMUNITIES
AND STATISTICIANS TO SHARE THE
EMERGING TECHNOLOGY AND USE OF
AI/ML IN HEALTH DISPARITY.
SO IN THE LAST 2 YEARS, THE
PROGRAM IS IN THE THIRD YEARS,
IN THE LAST YEARS WE ARE PROUD
TO SAY THAT THE PROGRAM HAS
SUPPORTED OVER 274 DIVERSE
RESEARCHERS AND INSTITUTIONS TO
OTHERS AND GAPS IN RESEARCH
DIVERSITY BUT ALSO ADDRESS BIAS
IN AI IN DATA AND ADVANCED
CANNED WHAT.
SOME OF THOSE ARE -- SOME OF
THOSE ARE IN 4 KEY AREAS, WE
HAVE 3 FELLOWSHIP PROGRAMS, THEY
ARE LEADERSHIP, FELLOWSHIP WHICH
TRIES TO TRAIN NEXT GENERATION
LEADERS TO CHAMPION AI ML IN
HEALTHCARE INSTITUTION AND
FEDERAL INSTITUTION BUT ALSO
SHAPE THE POLARIZED SIGHS AROUND
AI ML, AND THE ALSO RESEARCH
FELLOWSHIP WHICH TRIES TO TRAIN
THE NEXT GENERATION IN HELT CARE
RESEARCHERS IN USING
[INDISCERNIBLE] AND LEVERAGING
AI TO OTHERS [INDISCERNIBLE] AND
THEN RECENTLY WE ALSO LAUNCHED
THE CLINICIAN FELLOWSHIP WHICH
IS TARGETING AND EMPOWERING
BROAD RANGE OF CLINICIANS IN THE
SPACE OF AI AND HEALTH
DISPARITY.
WE ALSO THINK IN ENGAGING THE
COMMUNITY IS ESSENTIAL TO
DEVELOPING AI APPLICATION THAT
ADVANCED DID THAT ALSO INCLUSIVE
SO WE ENGAGE THROUGH HUB
SPECIFIC PILOT PROGECS AND WE
ALSO HAVE A LARGE CONSORTIUM
PROJECT THAT ARE
MULTIDISCIPLINARY THAT BRINGS
COLLABORATIVE INVESTIGATOR FROM
DIFFERENT DISCIPLINE TO ADVANCE
IN THE HEALTH DISPARITIES BUT
ALSO ADVANCE, WE HAVE ALSO SOME
PROGRAMS LIKE THE BUILDING FOR
EXAMPLE, THE PROGRAM FOR
[INDISCERNIBLE], WHICH TRY TO
[INDISCERNIBLE] LOWER RESOURCE
INSTITUTION BY PROVIDING
FUNDING, TRAINING, GRANT
WRITING, COLLABORATION, TO HOST
TEAMS FOR THIS PROJECT AND FOR
GRANTS AS WELL.
IN ADDITION, WE HAVE ALSO
LAUNCHED A COLLABORATION WITH
THE NIH PROGRAMS LIKE ALL OF US
AND NCATS, TO INCREASE
RESEARCHERS DIVERSITY BY
LEVERAGING DATA SET THAT WAS,
YOU KNOW CAPTURED BY US AND ALSO
BY LIBERATING THE INFRASTRUCTURE
AND TRAINING COMPONENT AND ALSO
THE PROGRAM HAS THIS CALLED
[INDISCERNIBLE] PLATFORM THAT
TRIED TO CONNECT MENTORS AND
MENTEES SO THAT TO INTERACT AND
DISCUSS IN THE SPACE OF AI
HEALTH DISPARITY AND THE PROGRAM
HAS OVER CLOSE TO 5000 TOTAL
MEMBERS.
OUT OF THIS ARE OVER 2600 ARE
MENTEES, OVER 1430 OR MENTORS
AND THEN THEY ARE ACROSS THE
1700 INSTITUTIONS.
THE PROGRAM IS HIGHLY VISIBLE
AND IN FACT IT WAS ESSENTIALLY
MENINGED BY THE PRESIDENT JOE
BIDEN EXECUTIVE ORDER ON THE
SAFE SECURE AND TRUSTWORTHY
DEVELOPMENT OF USE OF ARTIFICIAL
INTELLIGENCE WHICH SPECIFICALLY
CALLS THE PROGRAM TO ACCELERATE
GRANTS, BUT ALSO TO SHOWCASE
ACTIVITIES IN UNDERSERVED
COMMUNITIES.
SO AS I MENTIONED IT, THE
INCLUSIVE COMMUNITIES FROM UNDER
REPRESENTED VERY IMPORTANT IN
ORDER TO MITIGATE THE BIAS AND
THE HEALTH DISPARITY THAT WE
HAVE BEEN SHOWING EARLIER, AND 1
EXAMPLE THAT I WANT TO HIGHLIGHT
IS THAT THE PROGRAM IS ENGAGING
OR WORKING IN PARTNERSHIP WITH
LOCAL COMPANY, A CLINIC TRYING
TO EMPOWER AND ENGAGE THE
COMMUNITIES FROM BERMING HAM
ALABAMA AND THIS ENGAGEMENT, THE
[INDISCERNIBLE] IDEAS FOR AIML
COULD BE USED TO HELP IMPACT
TOPICS OF THEIR CHOICE.
YOU CAN CLICK IT IN THE VIDEO ON
THESE SLIDES WHICH WILL BE
AVAILABLE TO YOU AND YOU WILL
SEE THAT YOU WILL BE INSPIRED BY
THE COMMUNITY'S PARTICIPATION
AND TRYING TO EMPOWER THEMSELVES
AND IDENTIFY AND ASK WHERE THEY
CAN SEE THE POTENTIAL BENEFIT
FOR THEIR HEALTH.
WE HAVE ALSO ANOTHER COMMUNITY
ENGAGEMENT WITH --
>> MAY I ASK, DO YOU HAVE MANY
MORE SLIDES AFTER THIS?
>> I HAVE 1 SLIDE AFTER THAT.
>> ONE SLIDE, OKAY, THANK YOU.
>> WE HAVE A SMALL BUSINESS PART
MERSHIP, AND PARTNERSHIP WITH
SMALL BUSINESS CLINIC TRYING
DEVELOP A CHAT BOT THAT USES
LEARNING AND WITH SCHEDULES AND
BEHAVIOR THAT WILL POSITIVELY
AFFECT THOSE COMMUNITIES AS WELL
AND 1 OF THE PROBLEM THAT WE SEE
IN THE LOWER RESOURCE
INSTITUTION IS THAT THERE IS A
DIGITAL DIVIDE AND THE PROGRAM
IS TRYING TO [INDISCERNIBLE]
ACCESS TO DATA AND ESPECIALLY
COLLABORATING WITH NIH SPONSORED
PROGRAMS LIKE SCHARE, BRIDGE 2
AI AND ALL OF US, AND ACCESS
THOSE RESOURCES BUT ALSO TO
CONDUCT NOBLE RESEARCH AT THE
INTERSECTION OF AI ML THROUGH
TRAINING MENTORSHIP AND SERVICE.
SO TO CLOSING THOUGHTS, DIVERSE
AND INCLUSIVE AI ARE VERY
CRUCIAL BECAUSE IT AVOID HARM TO
THE MARGINALIZED AND
UNDERREPRESENTED COMMUNITIES BUT
ALSO NECESSARY STEP TO INCREASE
TRUST.
SO I'M GOING TO CLOSE THAT, YOU
KNOW FOR AI TO BE BENEFICIAL TO
THE ALL COMMUNITY SLIDE, THE
DOCTOR MENTIONED IT TO ALL THE
INITIATIVE, INCLIEWTIONZ OF
PEOPLE WITH DIVERSE ATTRIBUTES
AND PERSPECTIVE, ESPECIALLY IN
DATA COLLECTION USED PROCESS
SYSTEM AND GOVERNMENTS ACROSS
THE LIFE CYCLE OF THAT IS VERY
IMPORTANT.
THANK YOU.
IF YOU WANT TO KNOW MORE ABOUT
THE AI/ML PROGRAM, FEEL FREE TO
CONTACT ME AND I ENCOURAGE YOU
TO SUBSCRIBE TO THESE PROGRAMS.
>> THANK YOU SO MUCH, SO WE'RE
NOW GOING TO GO TO OUR Q&A, WE
HAVE QUESTIONS THAT CAME TO
PEOPLE THAT REGISTERED FOR THE
MEETING, WE HAVE SOME QUESTIONS
DURING THE PRESENTATIONS, I HOPE
WE WILL BE ABLE TO GET THROUGH A
FEW OF THEM BECAUSE I WILL ASK
EACH OF YOU AS SPEAKERS TO BE AS
CONCISE AS YOU CAN, BUT AS
COMPLETE AS POSSIBLE AS WELL, SO
WE WILL TART OFF WITH A QUESTION
FOR ALL 3 OF YOU AND I THINK I
WILL GO IN THE ORDER IN WHICH
YOU PRESENTED FOR THOSE
RESPONSES, JUST TO LET THE
AUDIENCE KNOW, WE'RE SWITCHING
TO GOING BY FIRST NAMES RATHER
THAN LAST NAME OR TITLE.
NOT BEING DISRESPECT OFFUL,
WE'RE BEING COLLEGIAL HERE
EMPLOY CAN YOU DESCRIBE ABOUT
HOW TO THINK ABOUT DATA SCIENCE
MEASUREMENTS AND OUTCOMES, HOW
DOES HAVING DIVERSE PERSPECTIVES
HELP CREATE BETTER OUTCOMES, SO
JENNIFER, THEN MANU, THEN
SAMSON.
JENNIFER?
>> YOU KNOW I ALMOST THINK IT'S
IN THE TITLE, THE TITLE OF THIS
WAS HOW CAN OR DO DIVERSE
PERPECTIVES ENHANCE DATA
SCIENCE, I THINK THEY DO ENHANCE
IT, AND THEY DO IT IN A VARIETY
OF WAYS BUT NOT THE LEAST OF
WHICH IS WHEN PEOPLE COLLABORATE
ACROSS FIELDS WITH DIFFERENT
EXPERIENCE, DIFFERENT LIVED
EXPERIENCE, DIFFERENT EXPERTISE,
ALL OF THAT, SO THEY CHALLENGE
EACH OTHER'S ASSUMPTIONS AND
EXPLAIN THINGS IN WAYS THEY
WOULDN'T NORMALLY DO, AND IN
DOING THAT, I THINK YOU GET AT
SOME OF THE THINGS THAT WOULD
TRAVEL ON THROUGH DATA SCIENCE
OUTCOMES WHEN PEOPLE WORK ALONE
OR DON'T CHALLENGE THE ORIGINAL
ASSUMPTIONS.
>> WE LIKE THE NUMBERS, THE
NUMBERS TELL US THE TRUTH, AND
WHEN I LEARN ABOUT SOCIAL
DETERMINANTS OF HEALTH AND THESE
OTHER DRIVING FACTORS THAT CAN
CAUSE A HEALTHCARE OUTCOME THAT
IF YOU WERE NOT LOOKING AT THE
NUMBER, YOU MIGHT NOT KNOW WHAT
1 WAS NEEDED TO INVESTIGATE THAT
WAS DRIVING AN OUTCOME.
SO THAT'S 1 EXAMPLE OF HOW
DIVERSITY OR THOSE TEAMS HELP
YOU THINK ABOUT WHAT'S HAPPENING
WITH REAL PEOPLE VERSUS JUST
WHAT THE NUMBER SAY BECAUSE THEY
WILL SAY WHAT YOU WANT THEM TO
SAY, DEPENDING ON THE CONFINE
THAT YOU PUT AROUND THEM, SO
OTHER PEOPLE TO CHALLENGE THOSE
THOUGHTS AND HOW THEY ARRIVE
THERE I THINK IS WHAT THEN MAKE
ITS A ROBUST FINDING.
>> YEAH, JUST WANT TO ADD THAT I
THINK TO ME, THE MOST IMPORTANT
IS DIVERSITY ASK INCLUSION
ACROSS THE BOARD IS VERY
IMPORTANT.
WHEN I SAY ACROSS THE BOARD, OF
THE LIFE CYCLE OF AI, BUT
INCLUDING THE PEOPLE.
WHEN I SAY PEOPLE FOR EXAMPLE,
YOU KNOW IF WE WANT TO CREATE A
TECHNOAND SOCIAL AI ML, WE NEED
TO INCLUDE PEOPLE NOT ONLY
TECHNICAL OR MATHEMATICALLY,
VERSUS PEOPLE BUT ALSO PEOPLE
FROM BEHAVIORIAL AND SOCIAL AND
EVEN HISTORY ANTHROPOLOGISTS
MAINLY TO BE THERE TO PROVIDE A
DIFFERENT DIMENSION, DIFFERENT
PERSPECTIVE ALSO AND TO THE
OTHER HING IS A LIVED EXPERIENCE
ALSO VERY IMPORTANT.
PEOPLE BRING THEIR DIFFERENT
BACKGROUND, DIFFERENT
PERSPECTIVE AND CULTURE AND TRY
TO SOLVE A PROBLEM, SO
DIVERSITY'S INCLUSION IS VERY
IMPORTANT AND IT'S VERY
IMPORTANT AND WE SHOULD
EMPHASIZE, LOCATION, LOCATION,
DIVERSITY, DIVERSITY AND
INCLUSION IS VERY IMPORTANT.
NTHANK
-
>> THANK YOU VERY MUCH.
SO JENNIFER, DO THE SAND PITS
FOCUS ON A SPECIFIC PROBLEM?
HOW DOES THE NCI INSURE THE DATA
PRIVACY AND SECURITY CONCERNS
ARE ATTENDED TO AND OF COURSE
THE SCIENCE SCIENCE VERIFICATION
EFFORTS?
>> A LOT BUNDLED INTO THAT
QUESTION.
THE SAND PITS ADDRESS AN AREA OF
SCIENCE AND WHAT THEY'RE REALLY
DESIGNED TO DO IS BRING PEOPLE
FROM DIFFERENT DISCIPLINES
TOGETHER AROUND A SORT OF SHARED
INTEREST SO THE 1 I SHOWED IS
ACTUALLY SPONSORED BY THE OFFICE
OF DATA SCIENCE HERE AT THE NIH
AND RUN TOGETHER WITH THE NCI
AROUND QUANTUM COMPUTING AND
COMPLICATED RESEARCH QUESTIONS,
RIGHT?
BUT THEY CAN BE AROUND ANY SORT
OF SCIENCE, SCOPING THEM IS
REALLY TRICK EXPE I THINK THE
SECOND PART OF THAT QUESTION IS
AROUND PROTECTING PROTECTING
PRIVATE PRIVACY AND CITIZEN
SCIENCE AND COMMUNITY SCIENCE.
>> YES.
>> AND THAT'S A TRICKY 1 AND I
THINK IN A VARIETY OF DIFFERENT
WAYS.
BUT IN THE SAME WAY PRIVACY IS
PROECTOMYOSIN ITED AND HOPEFULLY
MAYBE SOMEBODY IN THE AUDIENCE
HERE IS FROM ALL OF US AND CAN
ANSWER THAT QUESTION BETTER THAN
I CAN, BUT IN BIG PROGRAMS LIKE
THAT, THEY HAVE METHODS TO DEAL
WITH THE PRIVACY CONCERNS BUT
WHAT I WAS ALLUDED TO ALSO IS
THAT IT DOESN'T JUST ABOUT DATA
COLLECTION, IT'S AROUND THE
CREATIVITY AND CAPABILITIES THAT
PEOPLE, THE PUBLIC COMMUNITIES,
PATIENTS WHOEVER HAVE WHEN THEY
THINK ABOUT ADDRESSING PROBLEMS,
SO THAT CAN BE EITHER AN
IDENTIFYING QUESTIONS OR HELPING
WITH ANALYSIS, OR PROVIDING
CONTEXT AS WELLsA PROVIDING
DATA.
-- AS WELL AS PROVIDING DATA.
>> SO MANU, DO YOU HAVE PRACTICE
EXAMPLES TO SHARE INVOLVING
PERSONS WITH LIVED EXPERIENCE,
CLINICIANS AND OTHER
STAKEHOLDERS IN ACTIVITIES
DESIGNED TO ENHANCE USE OF
REPRESENTATIVE DATA, INCLUSION
AND CLINICAL TRIALS AND IN
DETECTING AND ADDRESSING MODEL
BIASES, PARTICULARLY WITH
AFFECTED GROUPS WHO HAVE LESS
STATISTICAL OR DATA LITERACY?
>> SO I HAVEN'T AN EXAMPLE THAT
IS NOT AS MUCH OF THE BIG DATA
COLLECTION PART BUT I THINK IT
DOES GIVE AN EXAMPLE OF HOW YOU
INCLUDE EFFECTIVE POPULATIONS
INTO THE WORK YOU DO.
AGAIN, I REALLY HAVE A LOT ON
HIV/AIDS BUT I REALLY WANT TO
TALK ABOUT MY TIME IN GEORGIA,
SICKLE CELL DISEASE IS A MAJOR
AREA OF RESEARCH OF ME AND I
BEGAN A PARTNER OF THE SICKLE
CELL FOUNDATION OF GEORGIA,
NUMBER 1 RECRUITING AND
SUPPLYING BLOOD TO US BUT AGAIN
IT IS BREAKING OUT OF THE
SCIENTIFIC QUESTION THAT WE WILL
NEED THE BLOOD TO DO OUR
ANALYSIS BACK HOME AND GET
NUMBERS VERSUS REALLY STARTING
TO TALK TO THE PEOPLE LIVING
WITH SICK ELITE EXECUTIVE IS
DISEASE AND WHAT'S INTERESTING
TO FIND OUT IS HOW MUCH THEY RUN
THEIR OWN TESTS ON THEMSELVES
AND TRY TO GET BETTER AND
THEY'RE TRACKING THEIR OWN
PERSONAL HEALTH, EATING WHAT THE
WEATHER PATTERNINGS LOOK LIKE
AND SEVERAL OTHER THINGS THAT
THEY'RE COLLECTING TO FIND OUT
WHAT WORKS BEST FOR THEM.
SO I THINK ABOUT THAT IN THE
SPACE OF PERSONALIZED MEDICINE
AND THINKING ABOUT PATES WITH
RANGES IN DISEASE SEVERITY,
BRINGING THEM ONLINE GAVE US NEW
THINGS THAT WE WANTED TO MEASURE
AND OUR BLOOD SAMPLES OR IN OUR
MOUSE MODELS BECAUSE SOME OF THE
THINGS WE WERE IDENTIFYING WERE
CRITICAL POINTS AGAIN IN L OWN
SMALLER NUMBERS THEY WERE
COLLECTING REALLY BEGAN TO DRIVE
INTERESTING QUESTIONS FOR US,
BUT ON THE FLIP SIDE, ALSO
SPEAKING WITH THEM ABOUT HOW
COMFORTABLE WERE THEY IN SHARING
OTHER DATA WE MIGHT WANT TO
COLLECT PARTICULARLY WHEN IF GOT
TO DOWN TO GENOME SEQUENCING OR
OTHER THINGS WHICH AGAIN IF YOU
SAY, WHAT, OF COURSE, THEY
BELIEVE IN SCIENCE, THEY WILL
GIVE US THIS INFORMATION, DEVOID
OF ACTUALLY HAVING TO TALK TO
THE HUMANS THAT IT IMPACTS THAT
IT ACTUALLY CAN CHANGE ABOUT HOW
IT APPROACHES NEW RECRUITS OR
JUST WHAT DATA DO YOU ACTUALLY
NEED THAT YOU COULD GET A
BROADER AMOUNT FROM THIS
COMMUNITY THAT'S AFFECTED AND
THAT COULD THEN DRIVE THE
SCIENCE FURTHER.
SO AGAIN, IT ALWAYS SHOCKS ME
AGAIN AS A Ph.D., I LEARN
THINGS AND TALK TO CLINICIANS
BUT I LEARN MORE WHEN I TALK TO
THE AFFECTED POPULATIONS ABOUT
HOW THEY COULD HELPED AND THE
NUMBERS GENERATED AGAINST THEM
OR FOR THEM.
>> GREAT.
SO THIS NEXT QUESTION WAS
ADDRESSED TO YOU SAMSON BUT MANU
YOU MAY WANT TO WEIGH IN ON THIS
1 AS WELL, GIVEN YOUR RESPONSE
TO THE QUESTION JUST ASKED,
THERE'S UNDERSTANDABLY BEEN A
LOT OF DISCUSSION OF BIAS AND
ALGORITHMS AND DATA SETS,
HOWEVER, INDIVIDUAL RESEARCHERS
PHYSICIANS, ET CETERA HAVE THEIR
OWN BIASES.
ARE THERE WAYS THAT AI TOOLS CAN
ACTUALLY BE USED TO OVERCOME
BIAS IN RESEARCH OR CLINICAL
PRACTICE.
I WILL ASK YOU TO START SAMSON,
AND THEN MANU, AND THEN YOU
JENNIFER.
I WOULD LIKE ALL 3 OF YOU TO
WEIGH IN ON THAT.
>> YEAH, SO I THINK THERE ARE 2
KINDS OF 1S, MANU MENTIONED IT,
ALSO THERE IS THE HEMABIAS, I
SOCIAL BIAS AS WELL AND I DON'T
KNOW IF WE CAN YOU KNOW AT THAT
TIMISTICALLY OR MATHEMATICALLY
SOLVE ALL THE BIASES AND SOME OF
THE BIASES THAT WE NEED TO BRING
A DIFFERENT KIND OF PEOPLE,
LIKE, YOU KNOW DIVERSE PEOPLE
WITH DIVERSE DISCIPLINE, AND
DIVERSE PERSPECTIVE TO, YOU KNOW
ADDRESS SOME OF THAT, YOU KNOW
UNCONSCIOUS BIAS [INDISCERNIBLE]
IN THE DEVELOPMENT OF AI AND
DESIGN AND IN DEVELOPMENT OF AI
AS WELL.
SO WE NEED TO HAVE LIKE A
PERSPECTIVE, YOU KNOW AND
INCLUSIVE AND DIVERSE PEOPLE,
BUT ALSO SOME OF THAT BIAS IS
DUE TO GET US AT, YOU KNOW FOR
EXAMPLE, THE SOCIAL
DETERMINANTS, MAY NOT BE
CAPTURED THERE AND IF WE DON'T
INCLUDE THEM IN THE AI MODEL
THEY MAY NOT BE EQUITABLE EVEN
THOUGH THE ALGORITHM ITSELF IS
WELL BUILT AND WELL DESIGNED
BECAUSE IT WASN'T INCLUDING THE
[INDISCERNIBLE], SOMETIMES IT
MAY NOT BE EQUITABLE, IT MAY NOT
BE BENEFICIAL TO THE PEOPLE YOU
ARE TRYING TO HELP.
SO WE HAVE TO LOOK AT IN TERMS
OF STATISTICAL BUT ALSO IN TERMS
OF THE SOCIAL BIAS POINT.
>> MANU WOULD YOU LIKE TO ADD TO
THAT? YOU'VE ON MUTE.
>> JUST REALIZED THAT.
YEAH, I HAVE TO TAKE A SECOND.
UNCONSCIOUS BIAS AS WE KNOW IS
IMEAN WITH THE HUMAN AND PERSON
WHO'S PUTTING IT IN.
I DON'T HAVE A GREAT ANSWER FOR
YOU BUT 1 THING YOU NEED ON THIS
TEAM IS YOU NEED A SKEPTIC WITH
THE TRUE BELIEVER BECAUSE YOU DO
WANT A TRUE BELIEVER TO BELIEVE
IN THE TECHNOLOGY TO PUSH IT TO
ITS LIMITED AND SHOW ALL THE
OPPORTUNITIES FOR IT, BUT YOU
NEED A KEPTIC TO KIND OF BLUNT
THAT TO WHAT IS ACTUALLY
BELIEVABLE THAT WE COULD CELS
AND 1 THING THAT'S USEFUL THERE
CONGRESSALLY MEDICAL DIRECTED
RESEARCH PROGRAM FUNDED THROUGH
D.O.D., IN THEIR REVIEW PANELS
THEY HAVE A PEASHT ADVOCATE FOR
EACH OF THE DIFFERENT DISEASES
WHICH CAN CUT THROUGH WHAT THE
RESEARCHER MAY HAVE AND IT'S A
GREAT IDEA AND THEY'RE LIKE,
OKAY, BUT WAIT, WHO'S GOING TO
BUY THAT, RIGHT?
AND THEY WANT OBVIOUSLY THE
CURES AND THE TECHNOLOGY TO MOVE
FORWARD BECAUSE THEY HAVE BEEN A
SURVIVOR OF THAT ILLNESS, BUT
LET'S BE REAL ABOUT WHAT IT CAN
DO.
SO I THINK THAT'S WHERE YOU NEED
TO HAVE THOSE DYNAMIC TEAMS
WHERE YOU BELIEVE IT,
DEVELOPMENT MATH AND ALGORITHM
THAT PUSH IT FURTHER AND
SOMEBODY TO STEP BACK, AND 1
OTHER PIECE I WOULD LIKE TO ADD
HERE.
IN THAT SKEPTICISM OR
CHALLENGING OPINIONS I THINK
ABOUT BIG DATA AND THESE STUDIES
YOU NEED MORE PATIENT SAMPLES,
YOU NEED MORE PATIENT NUMBERS
BUT THE CLINICIANS, SEES 1
PERSON, 1 PATIENT, SO THAT WHOLE
IN OF 1 AS THAT BEIMAN TO GO,
THE LARGE MODELS MIGHT HELP
GUIDE IT BUT IF I'M THE OUTLIER,
I JUST NEED TO KNOW YOU YOU ARE
THINKING OF ME AND DIDN'T JUST
LOOK AT 10,000 PEOPLE.
SO I THINK IT'S A BALANCING ACT
ON HOW GETTING MORE DATA WILL,A
PLIE TO ME UNLESS I'M 1 OF THOSE
IN THE MIX.
SO THOSE ARE COMPLICATED ANSWERS
TO YOUR QUESTION BUT THE WAY OF
BIAS FOR 1 EMPLOY.
>> AS A FORMER CLINICIAN, THAT
IS A BIG CHALLENGE, HOW DO ALL
THESE DATA, PLIE TO THIS 1
INDIVIDUAL.
JENNIFER?
>> AS USUAL, I THINK MANU'S
THOUGHTS BRING UP A WHOLE LOT OF
ADDITIONAL THOUGHTS AND
QUESTIONS, YOU KNOW THIS GETS AT
THE ROOT OF A LOT OF DIFFICULTY
OUT THERE, RIGHT WHICH IS PART
OF IT IS THIS SORT OF HOW DOES
THE POPULATION SCALE TRANSLATE
TO THE 1, BUT ALSO, BIAS IS
EVERYWHERE, IT'S IN THE DATA,
IT'S IN OUR CURRENT PRACTICE,
IT'S IN ALL OF US AND THAT SORT
OF THING.
THERE WAS MCATS DID AN
INTERESTING SERIES OF CHALLENGES
AROUND USING AI PER FOR BIAS
MITIGATION, IN OTHER WORDS TO
DETECT BIAS AND THE ALGORITHMS
AND THAT SORT OF THING, THERE'S
OTHER AGENCIES LIKEANIST AROUND
THEIR FRAMEWORK FOR TRUSTWORTHY
AI, I AM TRYING TO THINK OF THE
NAME OF IT, BUT THERE'S A LOT OF
GUIDANCE OUT THERE TO UPON HAD
PEOPLE SORT OF THROUGH SOME OF
THESE, BUT JUST TO GO BACK TO
SOMETHING I THINK BOTH SAMSON
AND MANU HAVE SAID, A LOT OF IT
HAS TO DO WITH WORKING IN TEAMS,
CHALLENGING ASSUMPTIONS,
THINKING IT THROUGH FROM A
VARIETY OF DIFFERENT
PERSPECTIVES INCLUDING IN THOSE
CASES WHERE IT'S GOING TO GO
INTO THE CLINIC, INCLUDING
PRACTICES THE PATIENT EXPERIENCE
AND I THINK THAT'S WHY WE'RE
SEEING MORE AND MORE OF THESE
CONFERENCES AND SESSIONS AND
THINGS ON THE WAY THAT PATIENTS
ARE ALREADY USING AI FOR
THEMSELVES AND THE WAY THAT
THEY'RE THINKING ABOUT THEIR OWN
DATA AND COLLECTING THEIR OWN
DATA SO THAT'S A REALLY
INTERESTING AND RAPIDLY EVOLVING
SPACE, ALSO.
>> SO THE NEXT QUESTION IS FOR
ALL 3 OF YOU, I WILL START WITH
YOU MANU AND THEN YOU SAM SON
AND JENNIFER, I JUST GO AROUND.
THIS QUESTION IS, --
>> I THINK 1 THING I'VE SEEN IN
OOH H DO, I WAS ON THE OUTSIDE
18 MONTHS AGO, 19 MONTHS AGO AND
NOW I'M ON THE INSIDE BUT WHAT
DOES AMRI BROADLY IS NIH HAS
BEEN SHARING THEIR DATA
PRACTICES AND POLICIES BECAUSE 1
THING I SEE IS LET'S TALL IT
LET'S SAY AN OUTCOME OF THESE
PUSHES TO COLLECT LARGER AMOUNTS
OF DATA WHETHER THEY'RE IN RNA
SEQ, OR SEQUENCING OR WHATEVER
WE'RE DOING, 1 RESEARCHER IS
USING A SMALL PIECE OF THAT DATA
FOR THEIR GUIDANCE AND STUDIES
THAT SOMEONE'S COLLECTING A
REPOSITORY MAYBE DOING
META-ANALYSIS, BUT THERE IS THAT
BENEFIT OF MAKING THAT DATA
AVAILABLE BECAUSE IT PROVIDES
SOME KIND OF DEMOCRATIZATION OF
DOING THESE ARTIFICIAL
IBT--INTEGRATE TELEIGENCE
ANALYSIS TO SMALLER
INSTITUTIONS, PLACES THAT CAN
BUY COMPUTERS AND MAYBE THEY
CAN'T -- DON'T HAVE THE RESEARCH
INFRASTRUCTURE TO COLLECT THAT
DATA BUT WHEN IT ALL BECOMES
AVAILABLE, WHAT I HEARD A RECENT
ORCHSHOP I WAS AT.
AT THE AMERICAN INDIAN SOCIETY
OR SOMEWHERE ELSE, WHERE THEY
WANTED DATAAN OITATED BETTER SO
THAT OTHERS CAN USE IT, AND THEY
KNOW, SOME OF THE NUANCES THAT
WERE IN THE POPULATION OR
TREATMENT POPULATION.
THE CHALLENGE OF COURSE IS
PRIVACY BUT IF THEY'RE A WAY TO
DEIDENTIFIED THAT THEN PEOPLE
WHO DON'T HAVE TO DO THE
EXPERIMENT CAN STILL HAVE ACCESS
TO THAT DATA, I KNOW THAT'S SOME
OF THE GOALS OF ALL OF US AND
AIM AHEAD, BUT I'M REALLY FOR
THAT DEMOCRATIZATION THAN
TRAYING NEW USERS TO ACCESS THAT
DAT IN A CHEAPER WAY BECAUSE
IT'S THE PROCESSING SPEED OPPOSE
TO THE WET LAB STUFF.
IT'S 1 WAY TO TOUCH ON IT BUT
IT'S 1 WAY I THINK ABOUT THAT.
>> I AGREE WITH MANU, AND DATA
SHARING.
I THINK 1 THING IS THAT HAVING
DATA TRANSPARENCY IS VERY
IMPORTANT.
SOMETIMES WE DON'T KNOW WHAT
DATA WE V. RIGHT NOW WE HAVE
SOME DATA, NCATS, RHETORIC AND
OTHERS AND HAVING IT IN
TRANSPARENCY, YOU KNOW
STANDARDIZED WAY OF SHOWING THAT
DATA AND AVAILABLE AND ACCESS IT
TO DIVERSITY RESEARCHERS
INCLUDING FROM THE LOWER
RESEARCHERS IS VERY IMPORTANT
AND ANOTHER THING IS CLOUD
COMPUTING IS A VERY GREAT
EQUALIZER IN TERMS OF
DEMOCRATIZING ACCESS BUT WE NEED
TO GIVE THAT ACCESS TO THE LOWER
RESOURCE INSTITUTION AND ALSO
RESEARCHERS FROM THOSE
INSTITUTIONS STILL TRAINING.
IT'S NOT ENOUGH TO SAY THAT, YOU
KNOW WE HAVE, YOU KNOW WE HAVE
ACCESS, IT'S HERE, THEY'RE USING
IT AND IT'S ACCESSIBLE TO YOU.
BUT WE HAVE TO ALSO SUPPLEMENT
THESE MENTORSHIP AND ENHANCE
TRAIN AND ALSO CONSERVE AS WELL,
FOR THOSE PEOPLE TO BE ABLE TO
ADDRESS THE ISSUES NOW.
>> JENNIFER IN.
>> YEAH, SO 1 THING TO THINK
ABOUT IS THAT NOT ALL DATA IS
PATIENT DATA OR CLINICAL DAT
RIGHT IN THERE, THERE'S ENORMOUS
AMOUNT OF DAILY BASIS THEA THAT
IS GENERATED THROUGH THE COURSE
OF WORK THAT THE NIH SUPPORTS
THAT IS OUT THERE IN A VARIETY
OF DIFFERENT WAY ANDS IS USED BY
PEOPLE HA DO AI OR OTHER FORMS
OF DATA SCIENCE TO LAY DOWN SOME
FOUNDATIONAL KNOWLEDGE AND THAT
SORT OF THING SO THAT'S A
DIFFERENT AREA BUT THERE IS A
LOT OF GUIDANCE AROUND BEING
DEVELOPED AROUND TRUSTWORTHY AI
AND THESE SORTS OF THINGS WHEN 1
IS USING PATIENT DATA AND HOW TO
SHARE AND HOW TO DO LEARNING
ACROSS DIFFERENT SITES IN A WAY
THAT PROTECTS PRIVACY IS ALL
THAT SORT OF THING SO ALL THAT
IS SUPPORTED I THINK ACROSS THE
NIH AND THERE'S LOTS OF DEFINITE
PUBLICATIONS OUT THERE ON THAT.
I WILL SAY, TOO, WE THINK A LOT
ABOUT TRAINING THE NEXT
GENERATION WORKFORCE BUT THERE'S
ALSO KIND OF THE ENABLING THE
CURRENT GENERATION, OF
WORKFORCE, YOU KNOW TO BE BETTER
USERS AND MORE THOUGHTFUL USERS
AND MORE THOUGHTFUL
COLLABORATORS WITH DATA
SCIENTISTS AND AI TOOLS IN
GENERAL, RIGHT IN SO SORT OF
THINKING THROUGH HOW TO BE
EFFECTIVE USERS AND
COLLABORATORS AROUND THIS SPACE
WILL BE JUST AS USEFUL AND
PROVIDING REALLY SOLID DATA SETS
FOR PEOPLE TO WORK ON.
>> OKAY, THIS IS AN EASY
QUESTION.
I WILL START WITH YOU SAMSON,
AND THEN YOU JENNIFER AND THENUE
MANU.
MANU IS SMILING BECAUSE HE KNOWS
IT IS NOT.
>> HOW DO WE UNITE DIFFERENT
STEM RESEARCH DISCIPLINES
INCLUDING SOCIAL MAJOR SCIENCES
SUCH AS ECONOMICS AND
EPIDEMIOLOGY, PSYCHOLOGY AND
SOCIOLOGY ON THE FRONTIERS OF
TODAY'S METHODS?
SAMSON, SOFTBALL TO YOU?
>> THIS WE ARE ALREADY DOING
THAT.
WE HAVE FOR EXAMPLE,
COLLABORATING WITH NCATS, YOU
KNOW TRAINING TO USE THE NCATS
DATA, THIS IS THE REAL WORLD
DATA SET THAT'S BEEN COLLECTING
THROUGH THE COVID-19 PANDEMIC.
IT'S VERY HUGE AND WHAT WE'RE
DOING RIGHT NOW IS WE ARE
CREATING THIS TEAM SCIENCE
TRAINING, WE'RE BRINGING DATA
SCIENCE AND CLINICIANS FROM, AND
ALSO BIOMEDICAL RESEARCHERS FROM
STEM, YOU KNOW TOGETHER WORKING
TO ADDRESS, YOU KNOW, AND
ADDRESS RESEARCH QUESTIONS OR
HYPOTHESIS TOGETHER AS A TEAM
AND YOU KNOW THAT ARE RELATED TO
HEALTH DISPARITY, SO, YOU KNOW,
THE FIRST THING THAT WE NEED IS
TO CREATE THIS COLLABORATIVE OR
TEAM SCIENCE PROGRAMS AND THAT'S
WHAT WE'RE WANTING TO DO.
THE OTHER ALSO WE NEED TO BRING,
TEACH OUR DIFFERENT DISCIPLINES
ABOUT COMMUNITY ENGAGEMENT, SO
THAT AT A CAN LEARN FROM EACH
OTHER AND START SPEAKING THE
SAME LANGUAGE AS WELL, SO I
THINK WE ARE DOING THAT IN THE
MI PROGRAM, I THINK THE ONLY WAY
TO DO IT IS TO BRING THEM NOT
SOLO, BUT BRING OTHER TEAM IN
AND COLLABORATE WITH TEAM
SCIENCE.
>> I'M HAPPY TO HEAR YOU'RE
SEEING IT IS EASY.
I WOULDN'T EXPECT IT TO BE EASY
TO ACCOMPLISH BUT JENNIFER?
>> YEAH, YOU GUYS DON'T LOW BALL
THE QUESTIONS HERE, DO YOU.
SO IF THE QUESTION IS HOW DO WE
UNITE STEM FIELDS AND PULL FROM
ALL THESE OTHER DISCIPLINES INTO
BIOMEDICAL RESEARCH, YOU KNOW
LOTS OF DIFFERENT WAYS, RIGHT IN
AND I THINK BIOMEDICAL RESEARCH
HAS LONG KIND OF BROUGHT OTHER
DISCIPLINES IN, SORT OF AS
NEEDED FOR METHODS AND
APPROACHES AND THINKING AND TEAM
SCIENCE AND THAT SORT OF THING.
ONE KEY THING IS THINKING ABOUT
WHAT'S STOPPING IT FROM
HAPPENING ALREADY.
SO IF IT'S AN AREA LIKE,
ECONOMICS AND THE MATH THAT THEY
USE AND HOW THAT MATH CAN BE
USED IN MODELING HEALTHCARE
OUTCOMES OR SOMETHING LIKE THAT,
YOU KNOW SORT OF MAYBE 1 OF THE
THINGS TO DO IS TO BRING THEM
TOGETHER AND OFFER UP TEAM
SCIENCE, FUNDING OPPORTUNITIES
AND IF THE PROBLEM IS SORT OF
EARLIER THAN THAT, IF WHATEVER
THE FIELD IS, THAT WE'RE
INTERESTED IN, IS NOT THINKING
ABOUT BIOMEDICAL RESEARCH AT ALL
OR DOESN'T REALIZE THAT THEIR
DISCIPLINE MAY BE INTERSECTS OUR
DISCIPLINES IN SOME WAY, THAT'S
WHERE THESE INNOVATIONS LABS AND
IDEAS LABS COME IN HANDY.
WE REACH OUT TO VERY DIVERSE
COMMUNITIES, AND BRING IN
INDIVIDUALS, RIGHT?
THEY DON'T HAVE TO COME IN WITH
TEAMS AND PARTNERS AND THEY COME
IN AS INDIVIDUALS AND FIND THOSE
TEAMS AND PARTNERS AND LEARN HOW
TO TALK ACROSS THOSE SPACES, I
THINK SOME OF IT'S EASY AND SOME
OF IT'S REALLY HARD AND
LONG-TERM.
>> MARIE, YOU KNOW I LIKE TO
KEEP IT REAL.
>> SO I THINK -- I THINK SOME OF
THE BARRIERS OF INCLUDING THOSE
OTHER GROUPS, IS ENGINEERS AND
SCIENCES ARE A LITTLE SNOOTY,
RIGHT?
AND CLINICIANS HAVE A DIFFERENT
LEVEL OF EGO, AND THAT I SAID
THIS RECENTLY, YOU KNOW WHEN I
CAME, I WENT TO LIBERAL ARTS
EDUCATION, WENT TO MOOREHOUSE
EDUCATION, I'M OVER HERE DOING
CALCULUS AND PHYSICS, AND THEN
WHEN I DID THAT HIV/AIDS
RESEARCH AND THEY WANTED TO GET
IT INTO CERTAIN COMMUNITIES THE
PEOPLE WHO UNDERSTOOD CULTURE,
THE ANTHROPOLOGISTS, THE
LINGUISTS WERE MASSIVELY
IMPORTANT TO GETTING WHATEVER
TECHNOLOGY WE HAD TO THE PEOPLE.
SO THE SCIENCE IS YOU CAN HAVE
THE BEST SMALL MOLECULE BUT IF
IT'S NOT TAKEN UP BY THE
COMMUNITY, WHO CARES, RIGHT IN
SO THERE'S TIME ON THAT SIDE TO
DROP YOUR GUARD, YOU MAY BE GOOD
AT WHAT YOU DO BUT THAT WON'T
SOLVE THE PROBLEM AND MOST
SCIENTISTS I KNOW DO WANT TO
HAVE IMPACT, WHEN YOU EXPLAIN
IT'S A BARRIER TO START TO WORK
WITH THOSE COMMUNITIES AND I'VE
SEEN, GREAT, AGAIN HAVE GREAT
IDEA WHEN IS YOU BEGIN TO THINK
ABOUT THEM AND AGAIN ON THE
EARLIER PHASES OF TECHNOLOGY, IT
CAN REALLY HELP ROLL THAT OUT.
BUT I THINK 1 EXCELLENT EXAMPLE
OF THAT IS [INDISCERNIBLE] WHO
WAS AT THE WHITE HOUSE OFFICE OF
SCIENCE AND TECHNOLOGY POLICY IS
NOW A LEADER IN AI AND HOW WE
THINK ABOUT AI, BUT SHE WAS DEAN
OF THE SOCIAL SCIENCES AT
PRINCETON OR COLUMBI AMAYBE BOTH
BUT NOW SHE'S A LEADER IN,A I
AND THINK ABOUT HOW HUMANS AND
USE IT AND ROLL IT OUT.
AND I WANT TO END WITH THESE
OTHER WAYS TO INCLUDE THOSE
COMMUNITIES.
MY Ph.D. ADVISOR USED TO
ALWAYS TELL US, BE ABLE TO
EXPLAIN YOUR SCIENCE TO ME AS AN
EXPERT IN THE FIELD AND I ALSO
NEED YOU TO EXPLAIN IT TO YOUR
GRANDMOTHER, THEN YOU REALLY
KNOW WHAT YOU ARE TALKING ABOUT
IF YOU CAN EXPLAIN IT TO YOUR
GRANDMOTHER.
SHE
-- HE WAS JUST SAYING.
SO THATTAY HOW WE COMMUNICATE TO
OTHERS IN THE BUBBLE TO SEE WHAT
THE SKILL IS AND THAT'S WHAT WE
NEED TO LEARN TO HELPS THEM FEEL
BROUGHT INTO THE WORK WE'RE
DOING.
>> FABULOUS, SO, IT'S A GREAT
SEGUE INTO WHERE WE'RE GOING.
I WILL GO JENNIFER -- LET'S GO
JENNIFER MANU SAMSON, IS THERE A
PLACE WHERE INVESTIGATORS FROM
SMALLER LESS RESOURCED
INSTITUTIONS R2s, MSIs,
REGIONALS IN THIS AREA OF
RESEARCH, IF SO WHAT CAN WE DO
TO GET THEM ENGAGED.
>> I'M ASSUMING BY THIS AREA OF
RESEARCH WE MEAN SORT OF DATA
SCIENCE GENERALLY.
YOU KNOW DATA SCIENCE AND IS 1
OF THOSE THINGS THAT CAN BE DONE
FROM ANYWHERE, BUT AGAIN, SORT
OF A LOT OF THIS IS IN KNOWING
WHAT THE RIGHT QUESTIONS ARE TO
ASK, FINDING THE RIGHT
COLLABORATOR ANDS THAT SORT OF
THING AND SO, I THINK SOME OF
THE PROGRAMS THAT ENABLE THESE
PARTNERSHIP BUILDING AND THINGS
CAN BE USEFUL TO THESE FOLKS IN
SMALLER INSTITUTIONS BUT I THINK
AT LEAST FOR, WELL I'M GOING TO
GO AHEAD AND SAY TI THINK FOR
ALL OF NIH, DAILY BASIS THEA
SCIENCE CAN COME IN ON ANY SIZE
GRANT MECHANISM AND GO THROUGH
PEER REVIEW, SO ALL THE
MECHANISMS WE USE FOR SMALLER
INSTITUTIONS, THERE ARE NIQUE
THINGS ABOUT SMALLER
INSTITUTIONS, AND UNDERSERVED
INSTITUTIONS AND CERTAIN
INSTITUTIONS AND CERTAIN AREAS,
AND NONPROFIT INSTITUTIONS AND
ALL THE OTHER THINGS THAT WE
ENGAGE OUT THERE AND SO I THINK
SORT OF MY ADVICE TO THOSE FOLK
WOULD BE ON BRING THEIR OWN
STRENGTH TO THAT EQUATION AND
FIND PARTNERS WHERE THEY DON'T
HAVE THEM ALREADY.
>> YEAH, JUST TO CO SIGN THAT, I
AGREE.
AGAIN THINGS CAN BE DONE WITH A
LAPTOP WITHOUT HAVING SUPER
COMPUTERS DOING ALL THE
PROCESSING BUT OF COURSE IF
THERE WERE FUNDS TO ALLOW FOR
THOSE ACCESSES AND THAT WOULD BE
GREAT.
IF YOU THINK ABOUT IT, I USED TO
BE SUPER IMPRESSED WITH THE
TOOLS THAT THE NATIONAL LIBRARY
HAD AVAILABLE, ONCE I START MID
Ph.D. AND POINTED THEM OUT TO
YOU, ALL THESE GWAS STUDIES ARE
SITTING AT THERE COMPUTE XER
SYRUPING THINGS.
BLASTS WHERE WE USED TO HAVE TO
DESIGN A PC ON PRIMER SEQUENCE
AND YOU DO BLAST AGAINST THESE
GENOME SEQUENCES ALL THESE I
THINKS THAT IF YOU WRITE SCRIPTS
AND CODES CAN BE AUTOMATED SO
THERE IS THIS MASSIVE DATA THAT
IS BEING AVAILABLE AND I THINK 1
WAY YOU CAN BRING IN SOME OF
THESE OTHER COMMUNITIES, AGAIN
THINKING ABOUT IT EARLIER IS
BRING IT INTO THE EDUCATIONAL
CLASSROOM, LIKE, IF YOU'RE
TAKING EVEN A FRESHMAN YEAR
GENERAL BIOLOGY COURSE, I THINK
BIOLOGY IS BECOMING MORE
QUAWBTITATIVE, HAVE PEOPLE DO
THOSE COURSES, USE SOME OF THESE
DATABASES ONLINE TO BEGIN TO DIP
THEIR TOE IN WHAT DATA IS
AVAILABLE AND HOW THAT CAN GAIN
ACCESS AND LOOK THROUGH IT, SO
THEN BY THEIR SENIOR YEAR, THEY
COMBINE PROJECTS OF STUDYING
THEIR OWN WAYS, BECAUSE AT MY
EARLIER COMMENT, THERE'S SO MUCH
DATA WE'RE GATHERING BUT AN
INVESTIGATOR USING A SMALL PIECE
AND SOMEONE CAN STILL COME IN
AND PULL A LOT OF INFORMATION
AND IN MY HEAD IT'S CHEAPER THAN
DOING THE WET LOB AND SPRMS.
I THINK MAKING THAT
DEMOCRATIZATION BETTER COULD
BRING IN MULTIPLE
COMMUNITIES.
>> SO MY ANSWER IS IN MY HEAD,
IT'S A PROGRAM DESIGNED FOR
LOWURE RESOURCE INSTITUTION AND
COMMUNITIES THAT ARE
UNDERREPRESENTED AND UNDERSERVED
COMMUNITIESAs WELL AND WE HAVE
SO MANY PROGRAMS IN THERE THAT
YOU CAN A DIFFERENT TRAINING,
INSTITUTIONAL LEVEL, BUT ALSO WE
HAVE PROJECTS THAT YOU CAN
UTILIZE YOUR OWN DATA AND WE CAN
PROVIDE YOU FUNDING AND ALSO
RESOURCES AND COMPUTING RESOURCE
AS WELL.
BUT TO THE POINT ALSO OF
JENNIFER, THERE ARE ALSO
PROGRAMS THAT SUPPORT LOWER
PHYSICIANS AND LIKE R25, CAN YOU
APPLY TO THOSE AND THERE IS ALSO
INDIVIDUAL ON THE DIVERSE
SUBLIMIT IF YOU FIND A SPONSOR
YOU CAN ENTER IN IT SPACE OF AI
AND DATA SCIENCE AND GENOMICS
AND YOU CAN [INDISCERNIBLE] AND
THIS DIVERSE SUPPLEMENT IS
ACROSS NIH, SPECIFIC TO EACH IC,
DEPENDING ON THE DISEASE
CONDITION YOU ARE STUDYING, YOU
CAN APPLY TO THOSE.
IF YOU YOU'RE INTERESTED TO
ENGAGE WITHIN MY PROGRAM, PLEASE
SUBSCRIBE THROUGH MY CONNECT OR
CONTACT ME VIA MY E-MAIL.
>> OH CAN I THROW OUT 1 PROGRAM
WE HAVE AT NIBIB, THANK YOU
SAMSON I'M LEARNING HOW TO DO
THIS, NIBIB ALSO STARTED THIS
HBCU BETA PROGRAM WHERE WE
ACTUALLY HAVE A GRANT MECHANISM
TO HELP BUILD INFRASTRUCTURE TO
DEVELOP BIOENGINEERING AT
HBCUs AT THE COUNTRY, SO I
WANT TO SAY THE CALL IS OUT.
THEY ANNOUNCED THE FIRST SCHOOL,
I THINK THE CALL IS, IT JUST
RECENTLY CLOSED BUT PUT YOUR EYE
ON IT FOR NEXT YEAR'S CALL, WAYS
FOR BUILDING MINORITY
INFRASTRUCTURE AT AN INSTITUTION
SUPPORTING THIS WORK.
>> SO BECAUSE OF THE TEAM ON
BEHALF OF NIH, LED A REPORT THAT
BECAME A SET OF RECOMMENDATIONS
THROUGH THE ADVISORY COMMITTEE
TO THE DIRECTOR ON BROADER
PARTICIPATION OF INDIVIDUALS
WITH DISABILITIES IN RESEARCH
AND GETTING MORE SCIENTISTS WITH
DISABILITIES INVOLVED WITH
RESEARCH.
HOW DOES THAT FIT WITH ALL OF
THIS YOU'VE BEEN DISCUSSING WITH
REGARDS TO AI, MACHINE LEARNING,
ET CETERA.
WHERE DO HAVES WITH DISABILITIES
FIT INTO ALL THIS?
WHO WOULD LIKE TO JUMP IN FIRST?
>> I WOULD SAY THEY'VE ALWAYS
FIT INTO THIS, RIGHT?
AND THEY SHOULD BE INCLUDED IN
THIS.
FOR ALL THE REASONS THAT WE
TALKED ABOUT INCLUDING
UNDERREPRESENTED MINORITIES IN
EVERY OTHER SPACE, RIGHT?
THE WAY THEY MIGHT APPROACH A
SOLUTION TO A PROBLEM, WOULD BE
REALLY DIFFERENT THAN SOMEONE
ELSE, BECAUSE SOMEONE ELSE IS
RELYING ON WHATEVER FACULTIES
THAT THIS OTHER PERSON DIDN'T
HAVE WORKING AT THE SAME LEVEL.
I'VE BEEN HOSTING STUDENTS IN MY
LAB WITH DISABILITIES OVER THE
LAST FEW YEARS AND IT CHANGES
THE WAY WE DO THINGS OF REGULAR
THINGS WE DO IN THE LABS, SO
WHENY WOO SEE THIS DATA SET,
THERE'S A BLIND SPOT AND
HOPEFULLY THAT'S NOT A
DISRESPECTFUL TERM BUT THERE'S A
LIVED EXPERIENCE YOU CAN'T
UNDERSTAND BECAUSE YOU NEVER HAD
IT CROSS YOUR DOME SO IT'S NOT
EVEN IN YOUR REALM OF
VISUALIZATION, UNTIL YOU HAVE A
TEAM OR LIVING WITH IT AND HAVE
SOMEONE SAY YOU KNOW WHAT NONE
OF YOU KNOW ABOUT?
XOR Y, AND THAT'S WHAT WE NEED
TO THINK ABOUT IN INTERFACING
DESIGN, BUT ALSO WHAT I'M MORE
INTERESTED IS AGAIN, THEY DON'T
HAVE THE SAME DISABILITY, SO
WHEN YOU WANT TO DO SOMETHING
FOR THOSE THAT ARE DEAF OR HARD
OF HEARING, DOES THAT LEAVE OUT
PEOPLE WHO ARE VISUAL IMPAIR
EXCLUDE THOSE WITH DIFFERENT
PHYSICAL DISABILITIES THAN THOSE
WITH THE NONVISIBLE DISABILITIES
SO EVEN THE DIVERSITY OF
DISABILITIES ARE THOSE THINGS WE
WANT TO TRY TO ENCLUED WHICH IS
CHALLENGING WHERE WE ARE NOW
BECAUSE OF THE WAY OUR WORKFORCE
AND WORK PRACTICES ARE SET UP
BUT THOSE ARE THE OTHER WAYS WE
CAN THINK ABOUT TO INCLUDE THOSE
GROUPS IN OUR RESEARCH TEAM IN
CHANGING HOW OUR WORKPLACE IS
MANDATED.
>> SO, THE AI ML PROGRAM IS
INCLUSIVE IN TERMS OF SPECIALLY
DESIGNED FOR UNDERREPRESENTED
GROUPS INCLUDING PEOPLE WITH
DISABILITY ARE PART OF THIS
PROGRAM AND WE HAVE SO MANY
INDIVIDUALS WITH DISABILITIES TO
HAVE BEEN SUPPORTED BY THIS
PROGRAM TO DO RESEARCH BUT ALSO
SOME OF THEM ARE TRAINEES AS
WELL, IN THE SPACE OF AI ML.
SO SOME OF THOSE RESEARCHERS
THEY FOCUS ON PARTICULARLY ON
DISABILITY ISSUES THAT DEPENDING
ON YOUR RESEARCH INTEREST,
YOU'RE WELCOME TO APPLY TO
PROGRAMS OF THE -- YOU KNOW
WITHIN THE AI PROGRAMMING,
EITHER TRAINING, RESEARCH
PROGRAMS OR CAPACITY BUILDING
ATTEMPTS TO BE AS WELL,
INCLUDING COMMUNITY ENGAGEMENT.
>> YOU KNOW I WANT TO RETURN TO
SOMETHING THAT MANU SAID BECAUSE
I THINK IT'S REALLY CRITICAL
HERE WHICH IS THAT I THINK
PEOPLE DESIGN WITH THE BEST OF
INTENTIONS BUT IF THEY DON'T
KNOW WHAT, YOU KNOW WHAT TO LOOK
OUT FOR WHEN THEY'RE -- WHEN
THEY'RE COLLABORATING WITH OR
DESIGNING FOR PEOPLE WITH ANY
KIND OF DISABILITY OR ANY KIND
OF SPECIFIC KIND OF PERSPECTIVE,
THEY DON'T KNOW, RIGHT IN SO THE
BEST WAY AROUND THAT IS INCREASE
SORT OF OPENNESS AND EXPOSURE
AND COLLABORATION WITH THE FOLKS
THAT YOU'RE DESIGNING FOR
TECHNOLOGY CAN BE A GREAT
LEVELER, BUT WE'VE ALSO SEEN A
LOT OF EXAMPLES WHERE TECHNOLOGY
HAS BEEN DESIGNED POORLY BY
PEOPLE THAT DIDN'T REALIZE
EXACTLY WHAT THEY WERE DESIGNING
FOR.
SO I'M SORT OF THINKING BACK TO
AN EARLIER COMMENT ABOUT HOW WE
THINK ABOUT TRAINING THE UP AND
COMING GENERATION AND 1 OF THE
THINGS THAT WE DO IN A LOT OF
OUR PROGRAMS NOW, BECAUSE IT
WORKS WELL, IS HAVE THE
TRAINEES, THE GRADUATE STUDENTS
AND POST DOCS PRESENT THEIR
TALKS AND POSTERS TO POSTER
JUDGES AND THINGS THAT ARE --A
THAT INCLUDE THE PATIENT
ADVOCATE VERY OFTEN AND THE
REASON FOR THAT IS PERSPECTIVE,
YOU KNOW IF THEY CAN LEARN TO
PRESENT TO A BROADER AUDIENCE,
MANU'S GRANDMOTHER, THEN THEY
CAN PRESENT TO ANYBODY AND THEY
CAN HAVE THAT INTERACTION WITH
ANYBODY AND BE MORE SORT OF OPEN
TO THE WAY THAT THEY'RE THINKING
ABOUT THEIR STUDIES AND
DESIGNING PRODUCTS IF THAT'S THE
DIRECTION THEY GO WITH THEIR
DATA SCIENCE.
>> THANK YOU.
SO THIS NEXT QUESTION, REMINDS
ME OF, YOU KNOW, IT'S CLEARLY
FROM A DATA PERSON.
I'M 1 OF THOSE PEOPLE WITH
COLLEGE CALCULUS AND THE
PROFESSOR SAID IT'S INTUITIVELY
EVIDENT AND I DIDN'T UNDERSTAND
ANYTHING AFTER THAT BUT I THINK
I GET THE POINT OF THIS
QUESTION.
IT SAYS IN TAFTICS BIAS AND
REDUCED BY APPLYING NOVEL MODELS
THAT MORE ACCURATELY CAPTURE
UNDERLYING PHENOMENA.
FOR INSTANCE MEASUREMENT ERROR
CAN RESULT IN SIGNIFICANT BIAS
IN THE RESULTS.
HAS SCIENTISTS WORK WITH MODELS
HOW DO THEY COLLABORATE TO
ADDRESS THESE ISSUES?
WHAT DOES EACH DISCIPLINE
CONTRIBUTE IN WHO WOULD LIKE TO
TAKE THAT?
COME ON.
YOU ALL DIDN'T HAVE THAT --
>> I WILL GIVE YOU SORT OF A
NONANSWER TO THAT.
IT'S A VERY SPECIFIC QUESTION
AND I THINK THE ANSWER IS IT
DEPENDS ON WHAT IT IS THEY'RE
COLLABORATING ON.
AND I WILL THROW IN THERE, IT'S
NOT JUST COMPUTER SCIENTISTS AND
STATISTICIANS, IT'S
MATHEMATICIANS, ALSO AND
ENGINEERING AND ALL THE OTHER
PEOPLE THAT THINK IN THAT WAY.
AND WHEN WE BUILD MODELS TO
EXPLAIN DISEASE OR TO MAKE
PREDICTIONS OR TO MAKE DECISIONS
THEY'RE OFTEN COMBINATIONS OF
APPROACHES AND THOSE
COMBINATIONS OF APPROACHES CAN
BE STATISTICS OR MATH OR AI OR
ANY COMBINATION OF THEM.
AND SO WE SEE, WE SEE, I THINK
EVERY VERSION OF THAT
COLLABORATION JUST DEPENDING ON
WHAT THE QUESTION IS.
>> WITH THAT, AND THAT'S WHY
THE, YOU KNOW, INCLUSIVE AND
TEAM SCIENCE AND
MULTIDISCIPLINARY TEAM SCIENCE
APPROACH IS VERY IMPORTANT AND
THE STATISTICIAN AND PROGRAMMERS
AND EPIDEMIOLOGISTS ARE WORKING
TOGETHER TO SOLVE, ALSO TO
[INDISCERNIBLE] METRICS TO
MEASURE THE ACCURACY AND
PERFORMANCE OF THE AI MODEL AND
THIS IS A NEW AREA, AND THERE
ARE A LOT OF METHODS THAT NEED
TO BE DEVELOPED, HOW TO GREATLY
MEASURE AND ALSO IDENTIFY AND
CHARACTERIZE THE DIFFERENT BIAS
THAT IS THE DATA SET AND ALSO,
HOW THE AI LIFE CYCLE, SO THE
SHORT ANSWER IS THAT, YOU KNOW
THE OLD DAYS THAT YOU KNOW
DIFFERENT DISCIPLINE, THEY
COLLABORATE ON OTHERS, I ISSUE I
HAVE SEEN IN MY GRADUATE
OPPORTUNITY OR POST DOCS AT THE
UNIVERSITY OF MICHIGAN THAT
PEOPLE FROM SOCIOLOGY AND
PSYCHOLOGY AND EPIDEMIOLOGY AND
YOU KNOW PHYSICIANS, THEY WORK
TOGETHER AND BIOSTATISTICIANS AS
WELL TO ADDRESS CERTAIN HEALTH
ISSUE FROM A DIFFERENT
PERSPECTIVE.
SO, I THINK TEAM SCIENCE
APPROACH IS THE 1 TO GO TO
ADDRESS THOSE [INDISCERNIBLE].
>> I DO THINK BOTH ARE REALLY
HELPFUL BUT I ALSO THINK YOU
NEED TO UNDERSTAND THE TRAINING
OR PREPARATION THAT THEY ARE
COMING TO FOR THAT PROBLEM.
LIKE THAT HAPPENED WHEN YOU RUN
ACROSS MULTIPLE FIELDS ISSUES
EVEN CHEMISTS THINK DIFFERENTLY
THAN BIOCHEMISTS, AND TOW ME
THEY'RE ALL THE SAME BUT --I
KNOW THEY'RE VERY, VERY
DIFFERENT.
BUT WHAT THAT REALLY MEANS IS 95
TIMES OUT OF A HUNDRED YOU GET
THAT RESULT AND 5 TIMES YOU
DON'T SO IN THAT DEFINITION OF
TRUTH, RIGHT, IT ACTUALLY IS
CHANGED FOR THAT 5 THAN THE
REST, THE STATISTICIAN SAYS
WELL, NO IT'S TRUE OR NOT TRUE.
BUT THEN HAVE YOU AN ENGINEER
WHO WAS GIIVE A DESIGN GOAL,
MAKE THIS MODEL, GET TO BE
PREDICTIVE FOR 95% OF OUTCOMES
AND I GET TO 90%S ARE WE'RE
DOING WAY BETTER THAN WHAT WE
WERE ABLE ON DO BEFORE BUT
STATISTICALLY BUT IT'S NOT FULLY
WHAT WE WANT SO I THINK IT'S
GOING TO TAKE CONTEXT BUT I
THINK AGAIN IT'S THAT NATURAL
SKEPTICISM THAT BOTH FIELDS WILL
BRING TO IT THAT HOPEFULLY MAKE
IT A BETTER OUTCOME AND
SOMEONE'S GOING TO SAY, WELL
LET'S USE IT BEFORE WE GET TO
PERFECTION, I THINK.
OOH OKAY, WE'RE DOWN TO OUR LAST
7 MINUTES AND I WILL NEED AT
LEAST A COUPLE MINUTES BEFORE WE
COMPLETELY CLOSE OUT.
AND THERE WAS 1 QUESTION I
DIDN'T GET TO IT'S NOT FAIR TO
GIVE YOU NOT MUCH TIME FOR IT,
BUT WHAT IS YOUR WORST CASE
SCENARIO IN TERMS OF THE USE OF
AI AND DATA.
AND WHAT DO YOU REALLY WANT
PEOPLE TO TAKE AWAY FROM THIS
SESSION THAT CAME FROM YOU?
SO I SEE PEOPLE LAUGHING AT THAT
QUESTION BUT IT'S OUT THERE.
SO I'LL START WITH YOU JENNIFER
AND THEN YOU SAMSON AND MANU YOU
WILL GET THE LAST WORD SO
JENNIFER, 1 MINUTE EACH.
>> FANTASTIC THIS IS THE 1 I
WANTED TO GO FIRST ON, WORST
CASE SCENARIO, MY FEELING IS WE
CAN'T PREDICT THE WORST CASE
SCENARIO AND WE NEED TO FOCUS ON
WHAT ARE THE THINGS ARE WE CAN
CONTROL AND HOW CAN WE THINK
ABOUT FRAMING ETHICAL AND
RESPONSIBLY USE AND LEARNING
FROM WHAT'S ALREADY OUT THERE.
I THINK, YOU KNOW TECHNOLOGY IS
OUT THERE, AND IT IS IN USE AND
THE MORE WE UNDERSTAND IT AND
THE MORE WE PROVIDE PEOPLE WITH
TOOLS AND FRAMEWORKS AND
GUIDANCE AROUND HOW TO USE IT
EFFECTIVELY THE BETTER.
ONE THING YOU WANT PEOPLE TO
REMEMBER ABOUT WHAT YOU SAID
TODAY, IS THAT IT?
>> SEPARATE QUESTION.
THINK COLLABORATION, THINK CROSS
DISCIPLINE.
JUST LEAVE IT AT THAT.
>> OKAY, SAMSON, A MINUTE.
>> SO MY WORST SCENARIO IS THAT
AI WILL BE HERE, IT'S ALREADY
THERE, IT'S BEING USED IN
HEALTHCARE, IT'S GOING TO BE THE
DRIVING FORCE FOR FUTURE
HEALTHCARE.
BUT I AM WORRIED THAT IT DOESN'T
PERPETUATE SYSTEMIC IN THIS
MAKING IT LARGER IN A
COMPOUNDING SCALE AND THAT'S MY
WORRY BECAUSE YOU'RE USING
ALREADY THE EXISTING BIAS DATA
SET AND WE ARE NOT REQUIRED
THERE IN TERMS OF BRINGING
DIFFERENT PEOPLE, SO WE NEED TO
DO THAT, A BET ARE YOB CORPS
THAT THAT AND THE PEOPLE THAT I
WANT TO REMEMBER, HERE, IS THAT
IF AI IS GOING TO BE A GOOD
FORCE, YOU KNOW WE HAVE TO
DESIGN IT AND DEVELOP IT WITH
EQUITY AND INCLUSIVE IN MIND.
SO THAT TO,A VOID THIS SORT OF
DISCRIMINATION AND WORSE OUTCOME
THAT WE HAVE SEEN IN TUSKEGEE
AND OTHERS THAT COULD COULD
HAPPEN AGAIN WITH AI EVEN AT
LARGER SCALE IN DIFFERENT
HEALTHCARE ORGANIZATIONS THAT,
IS MY WORRY.
>> AND THE THING YOU WANT PEOPLE
TO TAKE AWAY FROM YOUR
PRESENTATION TODAY?
>> I THINK INCLUSIVE IS VERY
IMPORTANT, DIVERSITY IS NOT LIKE
A WORD, IT'S VERY IMPORTANT FOR
AI DEVELOPMENT ESPECIALLY HAVING
TEAM SCIENCE, BUT WHEN WE
DEVELOP IT, AI HAVE TO DEVELOP
WITH EQUITY IN MIND AS WELL.
>> MANU?
>> NOT TO SCARE ANYONE, NO, MY
WORST FEAR, AGAIN I GREW UP
BLACK IN AMERICA, I HAVE A BLACK
FAMILY IS THAT THE CONSPIRACY
THEORIES WILL TAKE OVER OR THAT
THE MODELS WILL BE TRAINED ON
BAD DATA AND PEOPLE WILL SAY,
LOOK, I RAN MY OWN ANALYSIS
USING AI, IT SAID THIS.
ALMOST LIKE WE WOULD GET WITH
WEBMD BACK IN THE DAY WHEN
EVERYBODY LOOKS UP THEIR OWN
SYMPTOMS EXCEPT HERE THEY COULD
SAY HEY, I HAVE DATA I USED THE
COMPUTER AND IT TOLD ME THIS, SO
I DON'T NEED TO DO ALL OF THOSE
OTHER THINGS THAT YOU ALL THINK
OR MY DOCTOR THINKS, THAT'S MY
BIGGEST FEAR ABOUT PUTTING THAT
TRUST IN WHAT IT MIGHT BE THE
OUTPUT AND CLAIMING, I HAVE
EVIDENCE OF WHY THIS IS BEST.
THE MESSAGE I THINK PEOPLE
SHOULD TAKE HOME FROM ME TALKING
HERE IS HUMANS ARE SMARTER THAN
CO AM PEWTERS, I KNOW THAT SEEMS
COUNTER TO EVERYTHING WE WANT TO
SAY, BUT THE COMPUTERS ARE
LEARNING FROM WHAT HUMANS HAVE
DONE, AND THE HUMANS AT THIS
STAGE IN OUR TECHNOLOGY ARE
SMARTER THAN COMPUTERS.
WE HAVEN'T HAD THE SENTIENT
BREAK THROUGH YET BUT I THINK
THAT MATTERS, AND I THINK THE
OTHER REASON IT MATTERS IS
AGAIN, I WORK WITH A LOT OF
DIVERSE COMMUNITIES IS PEOPLE
HAVE A WAY OF KNOWING IS A WAY
OF LEARNING KNOWLEDGE AND
DIFFERENT CULTURE AND INDIGENOUS
CULTURE AND HAVE WAYS OF KNOWING
THINGS THAT ARE BASED ON HUMAN
EXPERIENCES, THAT YES, WE WANT
THE DATA, WE WANT TO MODERNIZE
AND ADVANCE HOW WE THINK ABOUT
IT BUT HUMANS, AT LEAST TODAY,
ARE STILL SMARTER THAN
COMPUTERS.
SO I WILL LEAVE THAT.
>> WELL, THANK YOU ALL 3 SO VERY
MUCH AND MANU.
YOU WILL HAVE TO TELL ME WHEN
THE DAY COMES THAT WE'RE NOT
SMARTER THAN COMPUTERS.
[LAUGHTER]
REALLY WONDERFUL PANEL,
WONDERFUL INSIGHTS.
I THINK THERE ARE SLIDES I NEED
TO SHARE AS WE ARE CLOSING THIS
OUT.
YEAH, THE FIRST THING I WOULD
LIKE WOULD BE TO ASK YOU ALL TO
TAKE A MEMORY CLONE TONIGHT
SHARE YOUR FEEDBACK ABOUT THE
SEMINAR.
I THINK YOU WILL GET THIS
IMMEDIATELY UPON OUR CLOSING
OUT, OR ARE THEY GETTING THIS
NOW?
CAN SOMEONE TELL ME, ARE THEY
GETTING IT NOW?
>> THELING WAS DROPPED IN THE
CHAT.
>> IT'S BEING DROPPED INTO THE
CHAT SO TAKE A MEMORY
RESPONSENT.
IT'S JUST A QUICK SCALE SO WE
CAN GET A SENSE OF HOW THIS WENT
FROM YOUR PERSPECTIVE.
NEXT SLIDE, PLEASE.
AND PLEASE DO KEEP IN CONTACT
WITH US.
HERE'S OUR QR CODE, WE HAVE A
BLOG, WE HAVE A NEWS LETTER, WE
HAVE AN E-MAIL BOX, WE HAVE A
LINKED IN SIGHT, WE LOVE TO HEAR
FROM YOU, IT HELPS IN OUR
PLANNING FOR FUTURE SWDSS'S, OUR
NEXT 1 IS FEBRUARY 11th OF
2025.
AND YOU WILL RECEIVE AN E-MAIL
NOTIFICATION WHEN THAT
REGISTRATION SITE OPENS.
SO THANK YOU ALL SO VERY MUCH
PARTICULARLY DR. COUCH,
DR. GEBREAB, AND DR. PLATT.
IT WAS A WONDERFUL SEMINAR.
THANK YOU.