||NLM Informatics Lecture Series
For 40 years, since Arthur C. Clarke and Marvin Minsky imagined HAL, and projected where Artificial Intelligence would be in 2001, we've had high hopes for computers amplifying our mental abilities. What's been holding AI up? The short answer is that while computers make fine idiot savants, they lack common sense: the millions of pieces of general knowledge we all share, and fall back on as needed, to cope with the rough edges of the real world. Decades later than expected, that shortcoming is being overcome through a long-term large-scale engineering effort. Since 1984, we have been developing software that combines a common sense knowledge base with a powerful reasoning engine and natural language interfaces. These applications have helped intelligence analysts cope with massive amounts of information and answer ad hoc terrorism-related queries. Two years ago, clinical researchers at the Cleveland Clinic began using this software to cope with massive amounts of patient data, to more directly ask cohort-level queries, and for other purposes. This presentation will discuss the evolution of AI work and will project a timetable, the path, and the remaining obstacles to finally realizing the promise of Artificial Intelligence in Medicine.
Douglas Lenat received his Ph.D. at Stanford in 1976; his thesis was a demonstration that certain kinds of creative discoveries in mathematics could be produced by a computer program (a theorem proposer, rather than a theorem prover). That work earned him the bi-annual IJCAI Computers and Thought Award in 1977, and sparked a renewed interest in machine learning. Dr. Lenat was a professor of computer science at Carnegie-Mellon University and at Stanford University. From 1984-1994 he was the Principal Scientist at MCC, the research consortium in Austin, from whence he launched the Cyc project, a large-scale effort to codify and axiomatize the millions of pieces of human consensus reality knowledge. A Fellow of the AAAI and AAAS, Dr. Lenat has authored three books (including Building Large Knowledge Based Systems) and approximately 100 journal articles. His interest and experience in national security has led him to regularly consult for several U.S. agencies and for the White House, and he is the only person to have served on the technical advisory boards of both Apple and Microsoft.
PowerPoint slides available here.