-------- Forwarded Message --------
UT and the McCombs School of Business’ Center for Analytics &
Transformative Technologies (CATT) would like to invite you to its
2021 Global Analytics Conference, being held online on November 11
(afternoon) and 12 (morning). This year’s theme is “Explainable
AI.” Please share the following information with your colleagues
who would find this of interest.
The registration fee will be waived for this year’s online
conference and attendance will be completely free of charge. Be
sure to reserve your spot by registering soon, as attendance is
limited.
To view program information and to register, please visit:
https://bit.ly/3pnM5Hz
As artificial intelligence and machine learning techniques are
evolving and becoming ever more sophisticated, their value to
businesses are also increasing. But this sophistication inevitably
brings some opacity—and that opacity can be a barrier to more
widespread adoption. Business leaders and their data science
organizations require solutions that are interpretable,
transparent, fair, and defensible—in short, they need solutions
that are explainable. To overcome the stigma of the “black box,”
explanations are needed for a wide and diverse set of audiences,
including management and senior leadership, customers and clients,
regulators, and other internal or external stakeholders. The
implications are sweeping, including in areas like risk
management, ethics, compliance, reliability, and customer
relationship management. This conference will feature leading
experts from both academia and business to share current best
practices and research on effective, interpretable, and
explainable AI.
We have a terrific lineup of great speakers over the two half-day
sessions:
PROGRAM AGENDA
November 11, 2021 (afternoon session)
12:45pm Introductory Remarks
· Lillian Mills, PhD (Dean, McCombs School of Business, UT
Austin)
1:00pm Keynote I: Explainability and More: What is Needed
to Get a Model Into Production
· Charles Elkan, PhD (Professor of Computer Science, UCSD &
Former Managing Director, Goldman Sachs)
· Introduced by Joydeep Ghosh, PhD (Professor of Electrical and
Computer Engineering, UT Austin)
1:50pm Panel I: Explainable vs. Ethical AI—Just Semantics?
· Moderator: TBD (UT Austin)
Panelists:
· Polo Chau, PhD (Assoc. Prof., School of Computational Science
& Engineering, Georgia Tech)
· Alice Xiang, JD (Sr. Research Scientist & Head of AI Ethics
Office, Sony Group)
· Deepayan Chakrabarti, PhD (Asst. Professor, Dept. of IROM, UT
Austin)
2:50pm BREAK
3:00pm Presentation/Talk I: Responsible AI in Industry
· Krishnaram Kenthapadi, PhD (Principal Scientist, Amazon AWS AI)
3:50pm Panel II: Adopting AI: Industry Challenges and the
Role of XAI
· Moderator: Junfeng Jiao, PhD (Director, Urban Information Lab,
School of Architecture & Director, Good Systems, UT Austin)
Speakers:
· Michael Shepherd (Distinguished Engineer, Dell Technologies)
· James Guszcza, PhD (Chief Data Scientist, Deloitte LLP &
Research Affiliate, CASBS, Stanford University)
· Hima Lakkaraju, PhD (Asst. Prof., HBS and Dept. of CS, Harvard
University)
5:00pm Presentation/Talk II: The Role of Explainable AI
when “Data is the New Programming Language”
· Mark Johnson, PhD (Chief AI Scientist, Oracle Corp.)
November 12, 2020 (morning session)
8:45am Introductory Remarks
9:00am Keynote II: Scoring Systems: At the Extreme of
Interpretable Machine Learning
· Cynthia Rudin, PhD (Professor of CS, Duke University &
Principal Investigator, Interpretable Machine Lab)
· Introduced by Kumar Muthuraman, PhD (Professor of IROM &
Faculty Director for CATT, UT Austin)
9:50am Panel III: XAI Solutions—Different Approaches to
Explainability
· Moderator: Maria DeArteaga, PhD (Asst. Prof., Dept. of IROM, UT
Austin)
Panelists:
· Scott Lundberg, PhD (Senior Researcher, Microsoft Research)
· Jette Henderson, PhD (Senior Machine Learning Scientist,
CognitiveScale, Inc.)
· Zachary Lipton, PhD (Asst. Prof., Dept. of Operations Research
& Machine Learning, Carnegie Mellon University)
10:50am BREAK
11:00am Presentation/Talk III: Explainable AI for
Intelligent Financial Services: Examples and Challenges
· Daniele Magazzeni, PhD (AI Research Director & Head of the
Explainable AI Center of Excellence, JP Morgan)
11:50am Panel IV: Explanations, but for Whom?
· Moderator: Raymond Mooney, PhD (Professor of CS & Director
of UT Artificial Intelligence Lab)
Panelists:
· Christoforos Anagnostopoulos, PhD (Senior Principal Data
Scientist, McKinsey & Co.)
· Nazneen Rajani, PhD (Research Scientist, Salesforce Research)
· Sanmi Koyejo, PhD (Assoc. Professor, Dept. of CS, University of
Illinois at Urbana-Champaign)
12:50pm Closing Remarks
· Susan Broniarczyk, PhD (Associate Dean for Research &
Professor of Marketing, UT Austin)
1:00pm Formal Conference Concludes
This year’s conference has been made possible with the generous
support of the McCombs School of Business, Dell Technologies, and
the Good Systems Initiative—A UT Grand Challenge.
CATT GLOBAL ANALYTICS CONFERENCE 2021 (XAI) PROGRAM COMMITTEE
__________________________________________________
Center for Analytics and Transformative Technologies
McCombs School of Business
The University of Texas at Austin
Office: CBA 6.316 | (512) 232-2735
Mail: 2110 Speedway, Stop B6600
Austin, TX 78712-1276
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