Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY

Schedule: Impact of AI on business and society sessions

The rapid integration of AI in industry is affecting how society operates. Join the discussions on issues of business, fairness, and ethics—including job dislocation, transparency, and legal treatment of emerging AI products.

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9:00am12:30pm Tuesday, June 27, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Kristian Hammond (Narrative Science)
Average rating: ****.
(4.00, 12 ratings)
Kristian Hammond shares a practical framework for understanding the role of AI technologies in problem solving and decision making, focusing on how they can be used, the requirements for doing so, and the expectations for their effectiveness. Read more.
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1:30pm5:00pm Tuesday, June 27, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Machine Learning
Vikash Mansinghka (MIT), Richard Tibbetts (Empirical Systems)
Average rating: ****.
(4.50, 2 ratings)
Businesses have spent decades trying to make better decisions by analyzing structured data. New AI technologies are just beginning to transform this process. Vikash Mansinghka and Richard Tibbetts explore AI that guides business analysts to ask statistically sensible questions and lets junior data scientists answer in minutes questions that previously took hours for trained statisticians. Read more.
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2:35pm3:15pm Wednesday, June 28, 2017
Location: Beekman Level: Beginner
Secondary topics:  Natural Language, User interface and experience
Ben Medlock (Microsoft)
Average rating: *****
(5.00, 1 rating)
Ben Medlock explores the future of AI, explaining why the potential it holds is not at all frightening. Ben argues that the key to achieving elusive human-like AI lies in a central piece of the puzzle: embodiment. Read more.
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4:00pm4:40pm Wednesday, June 28, 2017
Location: Beekman Level: Intermediate
Secondary topics:  Ethics, Governance, and Privacy
Chuck Howell (MITRE), Lashon Booker (MITRE)
Lack of confidence in the fairness of an AI-based system will limit support for its use and likely preclude adoption, even if that adoption could provide significant benefits. Chuck Howell and Lashon Booker explore tools, techniques, and best practices from the safety-critical software community that can be adapted to provide a “fairness case” framework to address fairness concerns effectively. Read more.
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4:50pm5:30pm Wednesday, June 28, 2017
Location: Beekman Level: Non-technical
Secondary topics:  Ethics, Governance, and Privacy, Financial services, Natural Language
Tim Estes (Digital Reasoning)
Average rating: ****.
(4.50, 2 ratings)
As AI moves from concept to reality, debates about ethics are evolving into excitement and the desire to learn more about AI and its promise of a better world. Tim Estes discusses two customer use cases: Nasdaq, which found a way to use AI to help safeguard financial markets, and Thorn, which found a way to use AI to combat human trafficking and rescue children. Read more.
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4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton North Level: Non-technical
Katy George (McKinsey & Company)
Average rating: *****
(5.00, 2 ratings)
The speed with which automation technologies are emerging today and the extent to which they could disrupt the world of work are largely without precedent. How big could the impact be on the world of work, and how rapidly will it be felt? Katy George explores these questions, drawing on a major new report from the McKinsey Global Institute. Read more.
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4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton Center Level: Non-technical
Madeleine Elish (Data & Society)
Average rating: ****.
(4.50, 2 ratings)
When we worry about the Terminator or superintelligence, we miss the social implications of AI that are already beginning to take shape. Madeleine Elish outlines the core challenges to the responsible design and deployment of AI systems and reviews current trends in the ways in which designers and engineers are addressing these challenges across sectors. Read more.
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2:35pm3:15pm Thursday, June 29, 2017
Location: Gramercy East/West
Secondary topics:  Health care
Kavya Kopparapu (GirlsComputingLeague)
Average rating: *****
(5.00, 3 ratings)
Artificial intelligence is revolutionizing medicine through computer-aided diagnostic systems. High school student Kavya Kopparapu presents the Eyeagnosis system, which utilizes artificial intelligence techniques and a smartphone camera to automatically screen for diabetic retinopathy, the leading cause of preventable blindness worldwide. Read more.
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2:35pm3:15pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Machine Learning, Media, Retail and e-commerce
Nikita Lytkin (Facebook)
Average rating: *****
(5.00, 2 ratings)
Nikita Lytkin offers an overview of personalized digital advertising and explains how Facebook uses modern supervised machine learning methods, such as factorization machines and deep neural networks, to recommend ecommerce products to nearly two billion people. Read more.
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2:35pm3:15pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Non-technical
Secondary topics:  Media, Natural Language
Codruta Gamulea (Bakken & Bæck)
Average rating: ***..
(3.00, 1 rating)
The promise of AI in the newsroom is contradictory: NLG revolutionizes news writing, but robot journalists threaten jobs; NLP improves fact-checking but requires investments that slimmed-down newsrooms cannot afford. Drawing on Norwegian AI startup Orbit’s experience, Codruta Gamulea explains how AI can help solve the industry resource constraints and improve the quality of journalism. Read more.
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4:00pm4:40pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Non-technical
Secondary topics:  Ethics, Governance, and Privacy
Aileen Nielsen (One Drop)
Average rating: *****
(5.00, 1 rating)
While the commercial use of AI in everything from hiring to medical diagnosis to work scheduling is exploding, legislation and case law alike have yet to make major statements about how AI will be treated by the American legal system. Aileen Nielsen offers a historical overview of how the law has dealt with decision-making technologies in the past and what this suggests about AI's legal future. Read more.
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4:50pm5:30pm Thursday, June 29, 2017
Location: Beekman Level: Intermediate
Patrick Hall (H2O.ai | George Washington University), Sri Satish (H2O.ai)
Average rating: *****
(5.00, 1 rating)
Interpreting deep learning and machine learning models is not just another regulatory burden to be overcome. People who use these technologies have the right to trust and understand AI. Patrick Hall and Sri Satish share techniques for interpreting deep learning and machine learning models and telling stories from their results. Read more.