Track Editors

Ulises Cortés
Virginia Dignum
Marija Slavkovik
Toby Walsh

Previous Track Editors and Associate Editors

Vincent Conitzer (Track Editor)
Milind Tambe (Track Editor)
Erik Brynjolfsson (AI and Economics)
Gary Marcus (AI and Psychology)
Stuart Russell (Long Term Societal Impact of AI)
Manuela Veloso (AI and Autonomy)
Nick Bostrom (AI and Philosophy)
Rebecca Crootof (AI and Law)


Overview

The Journal of Artificial Intelligence Research (JAIR) is pleased to announce the launch of the JAIR Special Track on AI & Society. AI is rarely out of the news. There's a strong appetite within society to understand the impact that technology in general, and AI in particular will have in both the short and long term. The goal of the AI & Society track is to provide scholarly input to the debate around the impact AI will have on society, as well as to provide a forum in which research in AI focused on social good can be presented. All aspects of the impact of AI on society will be covered including but not limited to ethics, philosophy, economics, sociology, psychology, law, history, and politics.

Call for Submissions

4 types of articles will be published:

  • regular journal articles
  • viewpoints (short articles of up to 2000 words, dedicated to technical views and opinions on the impact AI will have on society in which positions are substantiated by facts or principled arguments)
  • point/counterpoints (two viewpoints, taking opposite sides of an argument)
  • multi-author discussion articles (e.g. half a dozen authors discuss arguments around an issue concerning the impact of AI on society)

Journal articles should present novel research. Novelty can be in the AI techniques themselves. However, it can also be in the application of existing AI techniques to a novel domain with a societal benefit. There is no necessity for the AI methods to extend the state of the art if the application itself is particularly novel. Novelty could also be in careful experimental comparison, e.g., of different AI techniques, in such applications.

It is expected that many point/counterpoint and multi-author discussion articles will be commissioned. However, they will still be peer reviewed, like all the other pieces published in the track. Controversial issues will not be avoided but should be dealt with fairly. Viewpoints and point/counterpoint articles may be more opinion based but should nevertheless be substantiated by facts or principled arguments. Viewpoints and point/counterpoint articles do not need to contain primary research data, although they may present 'sociological' data (funding trends, demographics, bibliographic data, etc.). The best such articles will be provocative, justifying a new concept or point of view.


Contents

Contents of the special track will be made available as articles are accepted.


Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML

Hilde Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, and Frank Hutter

Undesirable Biases in NLP: Addressing Challenges of Measurement

Oskar van der Wal, Dominik Bachmann, Alina Leidinger, Leendert van Maanen, Willem Zuidema, and Katrin Schulz

Your Prompt is My Command: On Assessing the Human-Centred Generality of Multimodal Models

Wout Schellaert, Fernando Martínez-Plumed , Karina Vold, John Burden, Pablo A. M. Casares, Bao Sheng Loe, Roi Reichart, Sean Ó hÉigeartaigh, Anna Korhonen and José Hernández-Orallo

Fair Influence Maximization in Large-scale Social Networks Based on Attribute-aware Reverse Influence Sampling

Mingkai Lin, Lintan Sun, Rui Yang, Xusheng Liu, Yajuan Wang, Ding Li, Wenzhong Li, and Sanglu Lu

Liability Regimes in the Age of AI: a Use-Case Driven Analysis of the Burden of Proof

David Fernández Llorca, Vicky Charisi, Ronan Hamon, Ignacio Sánchez, and Emilia Gómez

Viewpoint: Artificial Intelligence Accidents Waiting to Happen?

Federico Bianchi, Amanda Cercas Curry, and Dirk Hovy

Learning to Design Fair and Private Voting Rules

Farhad Mohsin, Ao Liu, Pin-Yu Chen, Francesca Rossi and Lirong Xia

Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula

Rana Tallal Javed, Osama Nasir, Melania Borit, Lois Vanhee, Elias Zea, Shivam Gupta, Ricardo Vinuesa and Junaid Qadir

Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge

Pierre Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young and Brian Belgodere

Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

Baobao Zhang, Markus Anderljung, Lauren Kahn, Noemi Dreksler, Michael C. Horowitz and Allan Dafoe

Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks

Songül Tolan, Annarosa Pesole, Fernando Martínez-Plumed, Enrique Fernández-Macías, José Hernández-Orallo and Emilia Gómez

The Societal Implications of Deep Reinforcement Learning

Jess Whittlestone, Kai Arulkumaran and Matthew Crosby

Superintelligence Cannot be Contained: Lessons from Computability Theory

Manuel Alfonseca, Manuel Cebrian, Antonio Fernandez Anta, Lorenzo Coviello, Andrés Abeliuk and Iyad Rahwan

Viewpoint: A Critical View on Smart Cities and AI

Daniela Inclezan and Luis I. Pradanos

Viewpoint: When Will AI Exceed Human Performance? Evidence from AI Experts

Katja Grace, John Salvatier, Allan Dafoe, Baobao Zhang and Owain Evans

The Force Awakens: Artificial Intelligence for Consumer Law

Marco Lippi, Giuseppe Contissa, Agnieszka Jablonowska, Francesca Lagioia, Hans-Wolfgang Micklitz, Przemyslaw Palka, Giovanni Sartor and Paolo Torroni

To Regulate or Not: A Social Dynamics Analysis of an Idealised AI Race

The Anh Han, Luis Moniz Pereira, Francisco C. Santos and Tom Lenaerts