January 27th, 9:40 AM – 10:00 AM
Spotlight 1: Normative Perspectives
Chair: Vincent Conitzer
Rightful Machines and Dilemmas
Ava Thomas Wright
Modelling and Influencing the AI Bidding War: A Research Agenda
The Anh Han, Luis Moniz Pereira and Tom Lenaerts
The Heart of the Matter: Patient Autonomy as a Model for the Wellbeing of Technology Users
Emanuelle Burton, Kristel Clayville, Judy Goldsmith and Nicholas Mattei
Requirements for an Artificial Agent with Norm Competence
Bertram Malle, Paul Bello and Matthias Scheutz
Toward the Engineering of Virtuous Machines
Naveen Sundar Govindarajulu, Selmer Bringsjord and Rikhiya Ghosh
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices
Sophie Jentzsch, Patrick Schramowski, Constantin Rothkopf and Kristian Kersting
Ethically Aligned Opportunistic Scheduling for Productive Laziness
Han Yu, Chunyan Miao, Yongqing Zheng, Lizhen Cui, Simon Fauvel and Cyril Leung
(When) Can AI Bots Lie?
Tathagata Chakraborti and Subbarao Kambhampati
Epistemic Therapy for Bias in Automated Decision-Making
Thomas Gilbert and Yonatan Mintz
Algorithmic greenlining: An approach to increase diversity
Christian Borgs, Jennifer Chayes, Nika Haghtalab, Adam Kalai and Ellen Vitercik
Posters for this session will be presented on January 27th at 10am
Ava Thomas Wright
Modelling and Influencing the AI Bidding War: A Research Agenda
The Anh Han, Luis Moniz Pereira and Tom Lenaerts
The Heart of the Matter: Patient Autonomy as a Model for the Wellbeing of Technology Users
Emanuelle Burton, Kristel Clayville, Judy Goldsmith and Nicholas Mattei
Requirements for an Artificial Agent with Norm Competence
Bertram Malle, Paul Bello and Matthias Scheutz
Toward the Engineering of Virtuous Machines
Naveen Sundar Govindarajulu, Selmer Bringsjord and Rikhiya Ghosh
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices
Sophie Jentzsch, Patrick Schramowski, Constantin Rothkopf and Kristian Kersting
Ethically Aligned Opportunistic Scheduling for Productive Laziness
Han Yu, Chunyan Miao, Yongqing Zheng, Lizhen Cui, Simon Fauvel and Cyril Leung
(When) Can AI Bots Lie?
Tathagata Chakraborti and Subbarao Kambhampati
Epistemic Therapy for Bias in Automated Decision-Making
Thomas Gilbert and Yonatan Mintz
Algorithmic greenlining: An approach to increase diversity
Christian Borgs, Jennifer Chayes, Nika Haghtalab, Adam Kalai and Ellen Vitercik
Posters for this session will be presented on January 27th at 10am
January 27th, 5:00 PM – 5:30 PM
Spotlight 2: Fairness and Explanations
Chair: Shannon Vallor
IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules
Bishwamittra Ghosh and Kuldeep S. Meel
Loss-Aversively Fair Classification
Junaid Ali, Muhammad Bilal Zafar, Adish Singla and Krishna P. Gummadi
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed Chi and Alex Beutel
Taking Advantage of Multitask Learning for Fair Classification
Luca Oneto, Michele Doninini, Amon Elders and Massimiliano Pontil
Explanatory Interactive Machine Learning
Stefano Teso and Kristian Kersting
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Michael P. Kim, Amirata Ghorbani and James Zou
A Formal Approach to Explainability
Lior Wolf, Tomer Galanti and Tamir Hazan
Costs and Benefits of Fair Representation Learning
Daniel McNamara, Cheng Soon Ong and Robert Williamson
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
Stephen Pfohl, Ben Marafino, Adrien Coulet, Fatima Rodriguez, Latha Palaniappan and Nigam Shah
Global Explanations of Neural Networks: Mapping the Landscape of Predictions
Mark Ibrahim, Melissa Louie, Ceena Modarres and John Paisley
Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure
Alexander Amini, Ava Soleimany, Wilko Schwarting, Sangeeta Bhatia and Daniela Rus
Crowdsourcing with Fairness, Diversity and Budget Constraints
Naman Goel and Boi Faltings
What are the biases in my word embedding?
Nathaniel Swinger, Maria De-Arteaga, Neil Heffernan Iv, Mark Dm Leiserson and Adam Kalai
Equalized Odds Implies Partially Equalized Outcomes Under Realistic Assumptions
Daniel McNamara
The Right To Confront Your Accuser: Opening the Black Box of Forensic DNA Software
Jeanna Matthews, Marzieh Babaeianjelodar, Stephen Lorenz, Abigail Matthews, Mariama Njie, Nathan Adams, Dan Krane, Jessica Goldthwaite and Clinton Hughes
Posters for this session will be presented on January 27th at 7pm
Bishwamittra Ghosh and Kuldeep S. Meel
Loss-Aversively Fair Classification
Junaid Ali, Muhammad Bilal Zafar, Adish Singla and Krishna P. Gummadi
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed Chi and Alex Beutel
Taking Advantage of Multitask Learning for Fair Classification
Luca Oneto, Michele Doninini, Amon Elders and Massimiliano Pontil
Explanatory Interactive Machine Learning
Stefano Teso and Kristian Kersting
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Michael P. Kim, Amirata Ghorbani and James Zou
A Formal Approach to Explainability
Lior Wolf, Tomer Galanti and Tamir Hazan
Costs and Benefits of Fair Representation Learning
Daniel McNamara, Cheng Soon Ong and Robert Williamson
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
Stephen Pfohl, Ben Marafino, Adrien Coulet, Fatima Rodriguez, Latha Palaniappan and Nigam Shah
Global Explanations of Neural Networks: Mapping the Landscape of Predictions
Mark Ibrahim, Melissa Louie, Ceena Modarres and John Paisley
Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure
Alexander Amini, Ava Soleimany, Wilko Schwarting, Sangeeta Bhatia and Daniela Rus
Crowdsourcing with Fairness, Diversity and Budget Constraints
Naman Goel and Boi Faltings
What are the biases in my word embedding?
Nathaniel Swinger, Maria De-Arteaga, Neil Heffernan Iv, Mark Dm Leiserson and Adam Kalai
Equalized Odds Implies Partially Equalized Outcomes Under Realistic Assumptions
Daniel McNamara
The Right To Confront Your Accuser: Opening the Black Box of Forensic DNA Software
Jeanna Matthews, Marzieh Babaeianjelodar, Stephen Lorenz, Abigail Matthews, Mariama Njie, Nathan Adams, Dan Krane, Jessica Goldthwaite and Clinton Hughes
Posters for this session will be presented on January 27th at 7pm
January 28th, 9:40 AM – 10:00 AM
Spotlight 3: Empirical Perspectives
Chair: Gillian Hadfield
“Scary Robots”: Examining Public Responses to AI
Stephen Cave, Kate Coughlan and Kanta Dihal
Framing Artificial Intelligence in American Newspaper
Ching-Hua Chuan, Wan-Hsiu Tsai and Su Yeon Cho
Perceptions of Domestic Robots’ Normative Behavior Across Cultures
Huao Li, Stephanie Milani, Vigneshram Krishnamoorthy, Michael Lewis and Katia Sycara
Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery
Wenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David Lobell and Stefano Ermon
Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data
Bradley Gram-Hansen, Patrick Helber, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova and Piotr Bilinski
Human-AI Learning Performance in Multi-Armed Bandits
Ravi Pandya, Sandy Huang, Dylan Hadfield-Menell and Anca Dragan
A Comparative Analysis of Emotion-Detecting AI Systems with Respect to Algorithm Performance and Dataset Diversity
De’Aira Bryant and Ayanna Howard
Degenerate Feedback Loops in Recommender Systems
Ray Jiang, Silvia Chiappa, Tor Lattimore, Andras Gyorgy and Pushmeet Kohli
TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles
Vahid Behzadan, James Minton and Arslan Munir
The Seductive Allure of Artificial Intelligence-Powered Neurotechnology
Charles Giattino, Lydia Kwong, Chad Rafetto and Nita Farahany
Posters for this session will be presented on January 28th at 10am
Stephen Cave, Kate Coughlan and Kanta Dihal
Framing Artificial Intelligence in American Newspaper
Ching-Hua Chuan, Wan-Hsiu Tsai and Su Yeon Cho
Perceptions of Domestic Robots’ Normative Behavior Across Cultures
Huao Li, Stephanie Milani, Vigneshram Krishnamoorthy, Michael Lewis and Katia Sycara
Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery
Wenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David Lobell and Stefano Ermon
Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data
Bradley Gram-Hansen, Patrick Helber, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopackova and Piotr Bilinski
Human-AI Learning Performance in Multi-Armed Bandits
Ravi Pandya, Sandy Huang, Dylan Hadfield-Menell and Anca Dragan
A Comparative Analysis of Emotion-Detecting AI Systems with Respect to Algorithm Performance and Dataset Diversity
De’Aira Bryant and Ayanna Howard
Degenerate Feedback Loops in Recommender Systems
Ray Jiang, Silvia Chiappa, Tor Lattimore, Andras Gyorgy and Pushmeet Kohli
TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles
Vahid Behzadan, James Minton and Arslan Munir
The Seductive Allure of Artificial Intelligence-Powered Neurotechnology
Charles Giattino, Lydia Kwong, Chad Rafetto and Nita Farahany
Posters for this session will be presented on January 28th at 10am