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Organized by the Center for Global Policy Solutions, this three-day summit will address pathways to greater economic opportunity through the lens of “Technology, Inclusion, and Social Change.”  Approximately 300 policymakers, journalists, advocates, and experts at the intersection of government, technology, economics, education, health, and human and civil rights will discuss and advance solutions to today’s biggest societal changes. Sessions will explore the impact of the latest technological advancements in big data, machine learning, and artificial intelligence. It will also feature the “Inclusion Revolution Innovation Competition” that will award a $10,000 prize to innovators who develop products, services, programs, or policies that help make the application of technology, big data, and/or the operation of the tech sector more inclusive and economically and socially beneficial to marginalized communities.

Abstract:
Explanation has long been deemed a crucial aspect of accountability.  By requiring that powerful actors explain the bases of their decisions — the logic goes — we reduce the risks of error, abuse, and arbitrariness, thus producing more socially desirable decisions.  Decisionmaking processes employing machine learning algorithms and similar data-driven approaches complicate this equation.  Such approaches promise to refine and improve the accuracy and efficiency of decisionmaking processes, but the logic and rationale behind each decision remains opaque to human understanding.  The conference will grapple with the question of when and to what extent decisionmakers should be legally or ethically obligated to provide humanly meaningful explanations of individual decisions to those who are affected or to society at large.

List of Speakers:
Julius Adebayo, FastForward Labs
Guruduth Banavar, IBM Watson Lab
Solon Barocas, Microsoft Research
Enrico Bertini, NYU (Engineering)
Kiel Brennan-Marquez, NYU (Law)
Julie Brill, Hogan Lovells
Jim Burch, Police Foundation
Jenna Burrell, UC Berkeley (Information)
Federico Cabitza, Università degli Studi di Milano-Bicocca (Italy)
Rich Caruana, Cornell (CS)
Alexandra Chouldechova, Carnegie Mellon (CS)
Anupam Datta, Carnegie Mellon (CS)
Deven Desai, Georgia Tech (Law)
Nick Diakopoulos, University of Maryland (Journalism)
Brad Greenberg, Yale ISP (Law)
Krishna Gummadi, MPI-SWS (Germany)
Jeremy Heffner, Hunchlab
Alison Howard, Microsoft
Zachary Lipton, UCSD (Biomedical Informatics)
Gilad Lotan, Buzzfeed
Frank Pasquale, University of Maryland (Law)
Foster Provost, NYU (Stern)
Dan Raviv, Lendbuzz
Aaron Rieke, Upturn
Paul Rifelj, Wisconsin Public Defenders
Andrea Roth, UC Berkeley (Law)
Andrew Selbst, Information Society Project
Kevin Stack, Vanderbilt (Law)
Katherine Strandburg, NYU (Law)
Jer Thorpe, Office for Creative Research
Sandra Wachter – Alan Turing Institute
Duncan Watts, Microsoft Research

Watch teams of students pitch a panel of experts on draft legislation addressing:

• always-on in-home listening devices
• police geolocation tracking
• predictive policing
• commercial face recognition
• driver privacy and data transparency
• face news

Panel of Judges:

• Jay Edelson
• Alex MacGillivray
• Betsy Masiello
• Maneesha Mithal
• Michelle Richardson

Contact [email protected] for details.

bout Privacy Lab:

Privacy Lab is a meetup for privacy minded people to foster communication and collaboration. This event focusing on the Future of Privacy and Artificial Intelligence (AI) features Peter Eckersley as its speaker.

About The Speaker:

Peter Eckersley

Peter is Chief Computer Scientist for the Electronic Frontier Foundation. He leads a team of technologists who watch for technologies that, by accident or design, pose a risk to computer users’ freedoms—and then look for ways to fix them. They write code to make the Internet more secure, more open, and safer against surveillance and censorship. They explain gadgets to lawyers and policymakers, and law and policy to gadgets.

Peter will discuss the new EFF initiative that he is leading on the policy, strategy and governance questions raised by artificial intelligence and machine learning technologies.

About The Venue Host:

Bonsai makes AI for everyone and is helping everyone become producers of AI. It is on a mission to make intelligence a core component of every hardware and software application. Big thanks to Team Bonsai, including but not limited to Keen Browne, Darius Garza, and Bridget Hickey, for hosting us!

Address & Logistics:

Bonsai is headquartered in downtown Berkeley (near the Downtown Berkeley BART Station). Its offices are located at: 2150 Shattuck Avenue, Suite 1100 Berkeley, CA 94704

FYI: Parking near the office can be tricky; come early if parking. You are highly encouraged to use BART.

Additional Information:

More about Privacy Lab: https://wiki.mozilla.org/Privacy/Privacy_Lab

Mailing list: https://mail.mozilla.org/listinfo/privacy-events.

Anti-harassment policy: https://wiki.mozilla.org/Privacy/Privacy_Lab#Code_of_Conduct

The Program on Economics & Privacy (PEP) at George Mason University Antonin Scalia Law School will host a Scholars Conference on the economics of digital information policy on Friday, April 28, 2017. The mission of PEP is to promote the sound application of economic analysis to issues surrounding the digital information economy through original research, policy outreach, and education.

The Scholars Conference will showcase fourteen original law & economics research papers on such topics as:

• James Cooper (Director, PEP) on Measuring Autonomy Losses from the 2012 Google Privacy Policy Changes
• Martina Ferracane (European Centre for Intl Political Economy) on Stricter Regimes of Data Flows
• Mark Flood (US Treasury Office of Financial Research) on Cryptography and the Economics of Supervisory Information
• Jon Klick (U of Pennsylvania Law) on State Data Breaches and Income Tax e-Filing
• Meiping Sun (Columbia) on EMV Technology and Credit Card Fraud
• Jose Tudon (U of Chicago) on an Empirical Investigation on Net Neutrality

The Conference will also feature a luncheon keynote from Ginger Jin, Director of the Federal Trade Commission’s Bureau of Economics.

A full list of speakers is available on the PEP website here.

Abstract:
Explanation has long been deemed a crucial aspect of accountability.  By requiring that powerful actors explain the bases of their decisions — the logic goes — we reduce the risks of error, abuse, and arbitrariness, thus producing more socially desirable decisions.  Decisionmaking processes employing machine learning algorithms and similar data-driven approaches complicate this equation.  Such approaches promise to refine and improve the accuracy and efficiency of decisionmaking processes, but the logic and rationale behind each decision remains opaque to human understanding.  The conference will grapple with the question of when and to what extent decisionmakers should be legally or ethically obligated to provide humanly meaningful explanations of individual decisions to those who are affected or to society at large.

List of Speakers:
Julius Adebayo, FastForward Labs
Guruduth Banavar, IBM Watson Lab
Solon Barocas, Microsoft Research
Enrico Bertini, NYU (Engineering)
Kiel Brennan-Marquez, NYU (Law)
Julie Brill, Hogan Lovells
Jim Burch, Police Foundation
Jenna Burrell, UC Berkeley (Information)
Federico Cabitza, Università degli Studi di Milano-Bicocca (Italy)
Rich Caruana, Cornell (CS)
Alexandra Chouldechova, Carnegie Mellon (CS)
Anupam Datta, Carnegie Mellon (CS)
Deven Desai, Georgia Tech (Law)
Nick Diakopoulos, University of Maryland (Journalism)
Brad Greenberg, Yale ISP (Law)
Krishna Gummadi, MPI-SWS (Germany)
Jeremy Heffner, Hunchlab
Alison Howard, Microsoft
Zachary Lipton, UCSD (Biomedical Informatics)
Gilad Lotan, Buzzfeed
Frank Pasquale, University of Maryland (Law)
Foster Provost, NYU (Stern)
Dan Raviv, Lendbuzz
Aaron Rieke, Upturn
Paul Rifelj, Wisconsin Public Defenders
Andrea Roth, UC Berkeley (Law)
Andrew Selbst, Information Society Project
Kevin Stack, Vanderbilt (Law)
Katherine Strandburg, NYU (Law)
Jer Thorpe, Office for Creative Research
Sandra Wachter – Alan Turing Institute
Duncan Watts, Microsoft Research