What Do Knowledge Graphs Really Know?
Mark Musen (Stanford)
Since the earliest days of AI, there has been a struggle to define
what we really mean by knowledge and how to determine when a
computational agent displays intelligence. Allen Newell had
considerable influence in asking the AI community to think about
knowledge in behavioral terms. He argued that knowledge
representations do not manifest intelligence until some process comes
along and operates on them. In that perspective, knowledge graphs are
not intrinsically knowledgeable at all. We need agents to do
something with our graphs to cause intelligent actions. With all the
excitement about knowledge graphs, we’ve been focussing intently on
the graphs. In the next round of research, we need to be thinking
more about the knowledge. Knowledge graphs give us the ability to
represent unimaginable numbers of entities in the world and the
relationships among them. It’s time to apply the same kind of
principled thinking that has led us to the development of knowledge
graphs to the construction of intelligent agents that can demonstrate,
through their behaviors, what our graphs really know.
The slides are available here.
Mark Musen is Professor of Biomedical Informatics and of Biomedical
Data Science at Stanford University, where he is Director of the
Stanford Center for Biomedical Informatics Research. He conducts
research related to intelligent systems, computational ontologies,
open science, and biomedical decision support. His group developed
Protégé, the world’s most widely used technology for building and
managing terminologies and ontologies. He served as principal
investigator of the National Center for Biomedical Ontology, one of
the original National Centers for Biomedical Computing created by the
U.S. National Institutes of Heath. He directs the Center for Expanded
Data Annotation and Retrieval (CEDAR), founded under the NIH Big Data
to Knowledge Initiative. CEDAR develops semantic technology to ease
the authoring and management of biomedical experimental metadata. He
was the recipient of the Donald A. B. Lindberg Award for Innovation in
Informatics from the American Medical Informatics Association in 2006.
He has been elected to the American College of Medical Informatics,
the International Academy of Health Sciences Informatics, and the
National Academy of Medicine.