Seattle Public Library: Microsoft Auditorium Plenary
01 Nov 2018 07:30 PM - 09:00 PM(America/Los_Angeles)
20181101T1930 20181101T2100 America/Los_Angeles PSA2018 Public Forum: For the Public Good? Values and Accountability in AI and Data Science

For the Public Good?

Values and Accountability in AI and Data Science

7:30 - 9:00 pm

1 November 2018

The Seattle Public Library, Microsoft Auditorium

1000 Fourth Ave, Seattle, WA 98104

 Click here for directions

 

 

 Artificial intelligence (AI) and data-intensive science are influencing all aspects of our lives. Our smart phones and search engines anticipate our needs and preferences, driverless cars and autonomous military weapons are no longer the stuff of SciFi, and life-changing judgments about everything from medical diagnoses and credit ratings to college admissions and parole decisions are informed by algorithm-driven data analysis. Yet questions about which data sets to mine, how a particular algorithm is constructed, and what kind of transparency we can demand for these powerful technologies persist. The PSA invites the public to join us in exploring these important issues:

What assumptions are built into the algorithms that make data mining and AI possible?  How should developers change their practice to address encoded values?  And ultimately, what “public good” should  data science and AI serve?

Panelists

Heather Douglas (Associate Professor of Philosophy, Michigan State University) Bases for Trust in AI Eric Horvitz (Technical Fellow and Director of Microsoft Research Labs) AI, People, and Society: Rising Questions and Directions Sabina Leonelli (Professor of Sociology, Philosophy and Anthropolo ...

Seattle Public Library: Microsoft Auditorium PSA2018: The 26th Biennial Meeting of the Philosophy of Science Association office@philsci.org

For the Public Good?

Values and Accountability in AI and Data Science

7:30 - 9:00 pm

1 November 2018

The Seattle Public Library, Microsoft Auditorium

1000 Fourth Ave, Seattle, WA 98104

 Click here for directions

 

Heather DouglasEric HorvitzSabina LeonelliDavid Danks

 

 Artificial intelligence (AI) and data-intensive science are influencing all aspects of our lives. Our smart phones and search engines anticipate our needs and preferences, driverless cars and autonomous military weapons are no longer the stuff of SciFi, and life-changing judgments about everything from medical diagnoses and credit ratings to college admissions and parole decisions are informed by algorithm-driven data analysis. Yet questions about which data sets to mine, how a particular algorithm is constructed, and what kind of transparency we can demand for these powerful technologies persist. The PSA invites the public to join us in exploring these important issues:

  • What assumptions are built into the algorithms that make data mining and AI possible? 
  • How should developers change their practice to address encoded values? 
  • And ultimately, what “public good” should  data science and AI serve?


Panelists

Moderator

  • David Danks, Thurstone Professor of Philosophy and Psychology, Carnegie Mellon University

Sponsored by

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University of Washington

 

Michigan State University
University of Exeter
Microsoft Research Labs
Carnegie Mellon University
 Walter Veit
University of Bristol
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