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Garbage In, Garbage Out: The Predictable and Unpredictable Challenges of Regulating Machine Learning Systems

September 25, 2019 @ 10:30 pm - September 26, 2019 @ 12:30 am

We are in a new golden age of artificial intelligence research, eclipsing the postwar zenith and driven by a fundamentally different conceptual approach. It’s powered by big data, new storage and processing capacities, and pattern-discrimination systems that learn from those data, constructing rules for their behavior as they go. This isn’t just in the lab. These machine learning systems are implemented by all the big tech companies in everything from ad auctions to photo-tagging, and are supplementing or replacing human decision making in a host of more mundane, but possibly more consequential, areas like loans, bail, policing, and hiring. And we’ve already seen plenty of dangerous failures: Computer vision systems that don’t recognize black faces or classify them as gorillas, risk assessment tools systematically rating black arrestees as riskier than white ones, hiring algorithms that learned to reject women. These issues force a fundamental reconsideration of core democratic values—not just in what decisions are made, but how they are reached, and with sort of accountability. This talk will review fundamental issues of fairness and equity in machine learning systems and demonstrate how they play out in the specific domain of policing. Finally, we will discuss emergent approaches for designing, auditing, and regulating these systems, and what we can learn both from other fields that have faced similar conflicts, and from activists on the ground. 

Speaker(s): Dr Daniel Greene,

Agenda:

6:30 PM to 7:00 PM – Refreshments and Networking

7:00 PM – 7:05 PM – Chapter announcements and Speaker Introduction

7:05 PM – Talk

Location:
Room: Large Meeting Room (2nd Floor)
Bldg: Tenley-Friendship Neighborhood Library
4450 Wisconsin Ave NW
Metro Station: Tenleytown-AU
Washington, District of Columbia

Details

Start:
September 25, 2019 @ 10:30 pm
End:
September 26, 2019 @ 12:30 am
Website:
http://events.vtools.ieee.org/m/200590

Organizer

[email protected]