[CMU AI Seminar] Mar 30 at 2pm (Zoom) -- Been Kim (Google Brain) -- AI Interpretability: the Past, Present and Future -- AI Seminar sponsored by Fortive

[Shaojie Bai]

Dear all,

We look forward to seeing you *next Tuesday (3/30)* from *2:00-3:00 PM
(U.S. Eastern time)* for the next talk of our *CMU AI seminar*, sponsored
by Fortive <https://careers.fortive.com/>. (Note: not the usual 12pm!)

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 3/30, *Been Kim* (Google Brain) will be giving a talk on "*AI
Interpretability: the Past, Present and Future*."

*Title*: AI Interpretability: the Past, Present and Future

*Talk Abstract*: Interpretable machine learning has been a popular topic of
study in the past many years. But are we making progress? In this talk, I
will talk about my reflections on the progress by taking a critical look at
some of the existing methods, and discussing series of user-centric methods
that can "speak" the user's language, rather than the computer's language.

*Speaker Bio*: Been Kim is a staff research scientist at Google Brain. Her
research focuses on improving interpretability in machine learning by
building interpretability methods for already-trained models or building
inherently interpretable models. She gave a talk at the G20 meeting in
Argentina in 2019. Her work TCAV received UNESCO Netexplo award, was
featured at Google I/O 19' and in Brian Christian's book on "The Alignment
Problem". Been has given keynote at ECML 2020, tutorials on
interpretability at ICML, University of Toronto, CVPR and at Lawrence
Berkeley National Laboratory. She was a co-workshop Chair ICLR 2019, and
has been an area chair/senior area chair at conferences including NeurIPS,
ICML, ICLR, and AISTATS. She received her Ph.D. from MIT.

*Zoom Link*:
https://cmu.zoom.us/j/92759487765?pwd=Zzl4Ui9LU0cwMFdRTkYyZDdZQ2MyQT09


Thanks,
Shaojie Bai (MLD)
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