This event will include a panel as well as roundtable discussions. Each panelist will briefly describe their own work, and then examine the ethical issues around how data is used, software is used, as well as issues of data generators use and issues regarding their subject.

Panelists include Virajita Singh, Sorelle Friedler, Jonathan Kahn, and Madison Van Oort. This event is free and open to all; if you would like to confirm your attendance, please email us.

Machine learning models are becoming increasingly opaque to human examination, even to their designers.  Yet these models are also increasingly used to make high-stakes decisions; who goes to jail, what neighborhoods police deploy to, and who should be hired for a job.  But how can we practically achieve accountability and transparency in the face of increasingly complex models?  And how do we know if the algorithmic decisions are fair or discriminatory - what does it mean for an algorithm to be fair?  In this talk, we’ll discuss recent work from the new and growing field of Fairness, Accou