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Fri Dec 07 05:00 AM -- 03:30 PM (PST) @ Room 516 AB
Workshop on Ethical, Social and Governance Issues in AI
Chloe Bakalar · Sarah Bird · Tiberio Caetano · Edward W Felten · Dario Garcia · Isabel Kloumann · Finnian Lattimore · Sendhil Mullainathan · D. Sculley

Workshop Home Page


Ethics is the philosophy of human conduct: It addresses the question “how should we act?” Throughout most of history the repertoire of actions available to us was limited and their consequences constrained in scope and impact through dispersed power structures and slow trade. Today, in our globalised and networked world, a decision can affect billions of people instantaneously and have tremendously complex repercussions. Machine learning algorithms are replacing humans in making many of the decisions that affect our everyday lives. How can we decide how machine learning algorithms and their designers should act? What is the ethics of today and what will it be in the future?

In this one day workshop we will explore the interaction of AI, society, and ethics through three general themes.

Advancing and Connecting Theory: How do different fairness metrics relate to one another? What are the trade-offs between them? How do fairness, accountability, transparency, interpretability and causality relate to ethical decision making? What principles can we use to guide us in selecting fairness metrics within a given context? Can we connect these principles back to ethics in philosophy? Are these principles still relevant today?

Tools and Applications: Real-world examples of how ethical considerations are affecting the design of ML systems and pipelines. Applications of algorithmic fairness, transparency or interpretability to produce better outcomes. Tools that aid identifying and or alleviating issues such as bias, discrimination, filter bubbles, feedback loops etc. and enable actionable exploration of the resulting trade-offs.

Regulation: With the GDPR coming into force in May 2018 it is the perfect time to examine how regulation can help (or hinder) our efforts to deploy AI for the benefit of society. How are companies and organisations responding to the GDPR? What aspects are working and what are the challenges? How can regulatory or legal frameworks be designed to continue to encourage innovation, so society as a whole can benefit from AI, whilst still providing protection against its harms.

This workshop is designed to be focused on some of the larger ethical issues related to AI and can be seen as a complement to the FATML proposal, which is focused more on fairness, transparency and accountability. We would be happy to link or cluster the workshops together, but we (us and the FATML organizers) think that there is more than 2 day worth of material that the community needs to discuss in the area of AI and ethics, so it would be great to have both workshops if possible.

Welcome and organisers comments (Introduction)
Jon Kleinberg - Fairness, Simplicity, and Ranking (Invited Talk)
Rich Caruna - Justice May Be Blind But It Shouldn’t Be Opaque: The Risk of Using Black-Box Models in Healthcare & Criminal Justice (Invited Talk)
Hoda Heidari - What Can Fair ML Learn from Economic Theories of Distributive Justice? (Invited Talk)
Poster Spotlights 1 (Spotlight talks)
Posters 1 (Poster Session)
BriarPatches: Pixel-Space Interventions for Inducing Demographic Parity (Contributed Talk)
Temporal Aspects of Individual Fairness (Contributed Talk)
Explaining Explanations to Society (Contributed Talk)
Hanna Wallach - Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? (Invited Talk)
Rolle Dobbe - Ethics & Accountability in AI and Algorithmic Decision Making Systems - There's No Such Thing As A Free Lunch (Invited Talk)
Poster Spotlights 2 (Spotlight talks)
Posters 2 (Poster session)
Manuel Gomez Rodriguez - Enhancing the Accuracy and Fairness of Human Decision Making (Invited Talk)
Discussion Panel