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Demystifying AI with Hacks/Hackers NYC

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Betaworks Studios

29 Little West 12th Street

New York, NY 10014

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Everybody is talking about artificial intelligence, but not many people really know what it means. On Sept. 27, we’ll demystify AI and answer some pressing questions about the field by talking to people who use it in their daily work.

Our event will feature Solon Barocas, Cornell University and Luis Daniel, Bloomberg in discussion with Meredith Broussard, author of the new book “Artificial Unintelligence: How Computers Misunderstand the World,” which explores the inner workings and outer limits of technology from a data journalist’s perspective. (Madeline Elish, Data & Society, is unable to attend.)

To attend:
RSVP today ($10 + $1.94 processing fee, payable in advance) to Hacks/Hackers NYC.

Refund policy:
Cancel at least 24 hours before the event (that is, no later than 6:30 p.m. Sept. 26) to receive a full refund. We cannot issue refunds after Sept. 26.

Our panelists will discuss:
• What can AI do for journalists, and what can’t it do at all?
• How are people using AI in the newsroom?
• How are policymakers thinking about AI and fairness?
• How have journalists translate academic work about AI into stories that are relevant to our audiences?
• How have investigative reporters used AI to find stories?
• What does it mean to say that a story was written by an algorithm?
• When learning about AI, where to even start?

Schedule:
6:30 p.m.: Doors, refreshments + socializing
7 p.m.: Panel with Solon Barocas (Cornell University), Madeline Elish (Data & Society), and Luis Daniel, (Bloomberg); Meredith Broussard, moderator.
~8:15 p.m.: Hiring announcements, networking and socializing

A big thanks to Betaworks Studios for hosting us this month!

About our panelists:
Solon Barocas is Assistant Professor in the Department of Information Science at Cornell University. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University. His current research explores ethical and policy issues in artificial intelligence, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference. He co-founded the annual workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) and later established the ACM conference on Fairness, Accountability, and Transparency (FAT*).

Luis Daniel currently leads the News Automation Team at Bloomberg News. The News Automation team leverages the vast data trove on the Bloomberg terminal to produce and deliver timely, relevant and 100% fully-automated news to clients. He was a Technical Fellow at NYU's Governance Lab, a John D. Solomon Fellow with NYC Digital, and is a graduate of NYU's Interactive Telecommunications Program. Prior to all this, Luis could be found working on oil rigs in the south Texas desert.

Madeleine Clare Elish is a cultural anthropologist whose work examines the social impacts of AI and automation on society. She currently leads the Intelligence & Autonomy Initiative at Data & Society, a non-profit research institute in New York focused on the cultural dimensions of data-driven technology. The Intelligence & Autonomy Initiative aims to reframe debates about the rise of AI and reposition the value of human intelligence in the design, deployment, and evaluation of AI-driven systems. Her recent work has investigated how AI technologies affect understandings of values and ethical norms and how professional work lives change in response. She has conducted field work across varied industries and communities, ranging from the Air Force, civilian drone regulation, and commercial aviation to precision agriculture and emergency clinical care. Her research has been published and cited in scholarly journals as well as publications including the New York Times, Slate, Vice, and USA Today. She holds a PhD in Anthropology from Columbia University and an S.M. in Comparative Media Studies from MIT.

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Betaworks Studios

29 Little West 12th Street

New York, NY 10014

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Refund Policy

Refunds up to 1 day before event

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