[CMU AI Seminar] May 11 at 12pm (Zoom) -- Jon Kleinberg (Cornell) -- Aligning Superhuman AI with Human Behavior: Chess as a Model System -- AI Seminar sponsored by Fortive

[Shaojie Bai]

Dear all,

We look forward to seeing you *next Tuesday (5/11)* from *1**2:00-1:00 PM
(U.S. Eastern time)* for the next talk of our *CMU AI seminar*, sponsored
by Fortive <https://careers.fortive.com/>.

To learn more about the seminar series or see the future schedule, please
visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.
<http://www.cs.cmu.edu/~aiseminar/>

On 5/11, the Winner of 2007 ACM Prize in Computing *Jon Kleinberg* (Cornell
University) will be giving a talk on "*Aligning Superhuman AI with Human
Behavior: Chess as a Model System*".

*Title*: Aligning Superhuman AI with Human Behavior: Chess as a Model System

*Talk Abstract*: In domains where AI systems have achieved superhuman
performance, there is an opportunity to study the similarities and
contrasts between human and AI behaviors at the level of granular actions,
not just aggregate performance. Such an analysis can yield several
potential sources of insight. First, by studying expert-level human
performance through the lens of systems that far surpass this performance,
we can try to characterize the settings in which human errors are most
likely to occur. Second, we can try to adapt high-performing AI systems to
match human behavior as closely as possible at an action-by-action level,

We pursue these goals in a domain with a long history in AI: chess. For our
purposes, chess provides a domain with many different levels of human
expertise, together with data from hundreds of millions of online games
that each record a specific decision together with its context. However,
applying existing chess engines to this data, including an open-source
implementation of AlphaZero, we find that they do not predict human moves
well.

We develop new methods for predicting human decisions at a move-by-move
level much more accurately than existing engines, and in a way that is
tunable to fine-grained differences in human skill. From this, we discover
aspects of chess positions that serve as predictors of human error, as well
as algorithms that are able to operate in this domain in a more
"human-like" way. One of our algorithms, the Maia chess engine, can be
tried at lichess.org (https://lichess.org/@/maia1), where it has played
over 300,000 games to date with users of the platform.

*Speaker Bio*: Jon Kleinberg is the Tisch University Professor in the
Departments of Computer Science and Information Science at Cornell
University. His research focuses on the interaction of algorithms and
networks, the roles they play in large-scale social and information
systems, and their broader societal implications. He is a member of the
National Academy of Sciences and the National Academy of Engineering, and
the recipient of MacArthur, Packard, Simons, Sloan, and Vannevar Bush
research fellowships, as well awards including the Harvey Prize, the
Nevanlinna Prize, and the ACM Prize in Computing.

*Zoom Link*:
https://cmu.zoom.us/j/98138716931?pwd=TmUyWjlTSnZsbEtvTjd3OGVXUXNzZz09
<https://www.google.com/url?q=https://cmu.zoom.us/j/98138716931?pwd%3DTmUyWjlTSnZsbEtvTjd3OGVXUXNzZz09&sa=D&source=calendar&ust=1620620634218000&usg=AOvVaw0uYZqBAG-_e0ZznJNuLFJl>


Thanks,
Shaojie Bai (MLD)
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