[AI Seminar] Special AI Seminar on Dec 02 (Zoom) -- Vincent Conitzer -- Automated Mechanism Design for Strategic Classification -- AI seminar is sponsored by Fortive

[Aayush Bansal]

Vincent Conitzer (Duke University) will be giving a special
online seminar on "Automated Mechanism Design for Strategic Classification"
from *03:00 PM - 04:00 PM ET on Dec 02*.

*Zoom Link*:
https://cmu.zoom.us/j/92891008267?pwd=dXFvSVk3Z1pUa056WERobkN3N010UT09

CMU AI Seminar is sponsored by Fortive.

Following are the details of the talk:

*Title*: Automated Mechanism Design for Strategic Classification

*Abstract*: AI is increasingly making decisions, not only for us, but also
about us -- from whether we are invited for an interview, to whether we are
proposed as a match for someone looking for a date, to whether we are
released on bail.  Often, we have some control over the information that is
available to the algorithm; we can self-report some information, and other
information we can choose to withhold.  This creates a potential
circularity: the classifier used, mapping submitted information to
outcomes, depends on the (training) data that people provide, but the
(test) data depend on the classifier, because people will reveal their
information strategically to obtain a more favorable outcome.  This setting
is not adversarial, but it is also not fully cooperative.

Mechanism design provides a framework for making good decisions based on
strategically reported information, and it is commonly applied to the
design of auctions and matching mechanisms.  However, the setting above is
unlike these common applications, because in it, preferences tend to be
similar across agents, but agents are restricted in what they can report.
This creates both new challenges and new opportunities.  I will discuss
both our theoretical work and our initial experiments.

(joint work with Hanrui Zhang, Andrew Kephart, Yu Cheng, Anilesh
Krishnaswamy, Haoming Li, and David Rein.)


*Bio: *Vincent Conitzer is the Kimberly J. Jenkins University Professor of
New Technologies and Professor of Computer Science, Professor of Economics,
and Professor of Philosophy at Duke University. He received Ph.D. (2006)
and M.S. (2003) degrees in Computer Science from Carnegie Mellon
University, and an A.B. (2001) degree in Applied Mathematics from Harvard
University. Conitzer works on artificial intelligence (AI). Much of his
work has focused on AI and game theory, for example designing algorithms
for the optimal strategic placement of defensive resources. More recently,
he has started to work on AI and ethics: how should we determine the
objectives that AI systems pursue, when these objectives have complex
effects on various stakeholders?

Conitzer has received the Social Choice and Welfare Prize, a Presidential
Early Career Award for Scientists and Engineers (PECASE), the IJCAI
Computers and Thought Award, an honorable mention for the ACM dissertation
award, and several awards for papers and service at the AAAI and AAMAS
conferences. He has also been named a Guggenheim Fellow, a Sloan Fellow, a
Kavli Fellow, a Bass Fellow, an ACM Fellow, a AAAI Fellow, and one of AI's
Ten to Watch. He has served as program and/or general chair of the AAAI,
AAMAS, AIES, COMSOC, and EC conferences. Conitzer and Preston McAfee were
the founding Editors-in-Chief of the ACM Transactions on Economics and
Computation (TEAC).


To learn more about the seminar series, please visit the website:
http://www.cs.cmu.edu/~aiseminar/

-- 
Aayush Bansal
http://www.cs.cmu.edu/~aayushb/
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