Table of Contents

• How We Talk About AI (and Why It Matters)Ryan Calo. 1 [doi]
• Rightful Machines and DilemmasAva Thomas Wright. 3-4 [doi]
• Modelling and Influencing the AI Bidding War: A Research AgendaThe Anh Han, Luís Moniz Pereira, Tom Lenaerts. 5-11 [doi]
• The Heart of the Matter: Patient Autonomy as a Model for the Wellbeing of Technology UsersEmanuelle Burton, Kristel Clayville, Judy Goldsmith, Nicholas Mattei. 13-19 [doi]
• Requirements for an Artificial Agent with Norm CompetenceBertram F. Malle, Paul Bello, Matthias Scheutz. 21-27 [doi]
• Toward the Engineering of Virtuous MachinesNaveen Sundar Govindarajulu, Selmer Bringsjord, Rikhiya Ghosh, Vasanth Sarathy. 29-35 [doi]
• Semantics Derived Automatically from Language Corpora Contain Human-like Moral ChoicesSophie Jentzsch, Patrick Schramowski, Constantin A. Rothkopf, Kristian Kersting. 37-44 [doi]
• Ethically Aligned Opportunistic Scheduling for Productive LazinessHan Yu, Chunyan Miao, Yongqing Zheng, LiZhen Cui, Simon Fauvel, Cyril Leung. 45-51 [doi]
• (When) Can AI Bots Lie?Tathagata Chakraborti, Subbarao Kambhampati. 53-59 [doi]
• Epistemic Therapy for Bias in Automated Decision-MakingThomas Krendl Gilbert, Yonatan Mintz. 61-67 [doi]
• Algorithmic Greenlining: An Approach to Increase DiversityChristian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik. 69-76 [doi]
• Active Fairness in Algorithmic Decision MakingAlejandro Noriega-Campero, Michiel A. Bakker, Bernardo Garcia-Bulle, Alex 'Sandy' Pentland. 77-83 [doi]
• Paradoxes in Fair Computer-Aided Decision MakingAndrew Morgan, Rafael Pass. 85-90 [doi]
• Fair Transfer Learning with Missing Protected AttributesAmanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty. 91-98 [doi]
• How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of FairnessNripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu. 99-106 [doi]
• Learning Existing Social Conventions via Observationally Augmented Self-PlayAdam Lerer, Alexander Peysakhovich. 107-114 [doi]
• Legible Normativity for AI Alignment: The Value of Silly RulesDylan Hadfield-Menell, McKane Andrus, Gillian K. Hadfield. 115-121 [doi]
• TED: Teaching AI to Explain its DecisionsMichael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney. 123-129 [doi]
• Faithful and Customizable Explanations of Black Box ModelsHimabindu Lakkaraju, Ece Kamar, Rich Caruana, Jure Leskovec. 131-138 [doi]
• Shared Moral Foundations of Embodied Artificial IntelligenceJoe Cruz. 139-146 [doi]
• Building Jiminy Cricket: An Architecture for Moral Agreements Among StakeholdersBeishui Liao, Marija Slavkovik, Leendert W. N. van der Torre. 147-153 [doi]
• AI + Art = HumanAntonio Daniele, Yi-Zhe Song. 155-161 [doi]
• Speaking on Behalf of: Representation, Delegation, and Authority in Computational Text AnalysisEric P. S. Baumer, Micki McGee. 163-169 [doi]
• Killer Robots and Human DignityDaniel Lim. 171-176 [doi]
• Regulating Lethal and Harmful Autonomy: Drafting a Protocol VI of the Convention on Certain Conventional WeaponsSean Welsh. 177-180 [doi]
• Balancing the Benefits of Autonomous VehiclesTimothy Geary, David Danks. 181-186 [doi]
• Compensation at the Crossroads: Autonomous Vehicles and Alternative Victim Compensation SchemesTracy Hresko Pearl. 187-193 [doi]
• The Role and Limits of Principles in AI Ethics: Towards a Focus on TensionsJess Whittlestone, Rune Nyrup, Anna Alexandrova, Stephen Cave. 195-200 [doi]
• How Technological Advances Can Reveal RightsJack Parker, David Danks. 201 [doi]
• IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification RulesBishwamittra Ghosh, Kuldeep S. Meel. 203-210 [doi]
• Loss-Aversively Fair ClassificationJunaid Ali, Muhammad Bilal Zafar, Adish Singla, Krishna P. Gummadi. 211-218 [doi]
• Counterfactual Fairness in Text Classification through RobustnessSahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel. 219-226 [doi]
• Taking Advantage of Multitask Learning for Fair ClassificationLuca Oneto, Michele Donini, Amon Elders, Massimiliano Pontil. 227-237 [doi]
• Explanatory Interactive Machine LearningStefano Teso, Kristian Kersting. 239-245 [doi]
• Multiaccuracy: Black-Box Post-Processing for Fairness in ClassificationMichael P. Kim, Amirata Ghorbani, James Y. Zou. 247-254 [doi]
• A Formal Approach to ExplainabilityLior Wolf, Tomer Galanti, Tamir Hazan. 255-261 [doi]
• Costs and Benefits of Fair Representation LearningDaniel McNamara, Cheng Soon Ong, Robert C. Williamson. 263-270 [doi]
• Creating Fair Models of Atherosclerotic Cardiovascular Disease RiskStephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah. 271-278 [doi]
• Global Explanations of Neural Networks: Mapping the Landscape of PredictionsMark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley. 279-287 [doi]
• Uncovering and Mitigating Algorithmic Bias through Learned Latent StructureAlexander Amini, Ava P. Soleimany, Wilko Schwarting, Sangeeta N. Bhatia, Daniela Rus. 289-295 [doi]
• Crowdsourcing with Fairness, Diversity and Budget ConstraintsNaman Goel, Boi Faltings. 297-304 [doi]
• What are the Biases in My Word Embedding?Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark D. M. Leiserson, Adam Tauman Kalai. 305-311 [doi]
• Equalized Odds Implies Partially Equalized Outcomes Under Realistic AssumptionsDaniel McNamara. 313-320 [doi]
• The Right To Confront Your Accusers: Opening the Black Box of Forensic DNA SoftwareJeanna Matthews, Marzieh Babaeianjelodar, Stephen Lorenz, Abigail Matthews, Mariama Njie, Nathaniel Adams, Dan Krane, Jessica Goldthwaite, Clinton Hughes. 321-327 [doi]
• Specifying AI Objectives as a Human-AI Collaboration problemAnca D. Dragan. 329 [doi]
• "Scary Robots": Examining Public Responses to AIStephen Cave, Kate Coughlan, Kanta Dihal. 331-337 [doi]
• Framing Artificial Intelligence in American NewspapersChing-Hua Chuan, Wan-Hsiu Sunny Tsai, Su Yeon Cho. 339-344 [doi]
• Perceptions of Domestic Robots' Normative Behavior Across CulturesHuao Li, Stephanie Milani, Vigneshram Krishnamoorthy, Michael Lewis 0001, Katia P. Sycara. 345-351 [doi]
• Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite ImageryWenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David B. Lobell, Stefano Ermon. 353-359 [doi]
• Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral DataBradley J. Gram-Hansen, Patrick Helber, Indhu Varatharajan, Faiza Azam, Alejandro Coca-Castro, Veronika Kopacková, Piotr Bilinski. 361-368 [doi]
• Human-AI Learning Performance in Multi-Armed BanditsRavi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan. 369-375 [doi]
• A Comparative Analysis of Emotion-Detecting AI Systems with Respect to Algorithm Performance and Dataset DiversityDe'Aira G. Bryant, Ayanna Howard. 377-382 [doi]
• Degenerate Feedback Loops in Recommender SystemsRay Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli. 383-390 [doi]
• TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous VehiclesVahid Behzadan, James Minton, Arslan Munir. 391-395 [doi]
• The Seductive Allure of Artificial Intelligence-Powered NeurotechnologyCharles M. Giattino, Lydia Kwong, Chad Rafetto, Nita A. Farahany. 397-402 [doi]
• Invisible Influence: Artificial Intelligence and the Ethics of Adaptive Choice ArchitecturesDaniel Susser. 403-408 [doi]
• Reinforcement Learning and Inverse Reinforcement Learning with System 1 and System 2Alexander Peysakhovich. 409-415 [doi]
• Incomplete Contracting and AI AlignmentDylan Hadfield-Menell, Gillian K. Hadfield. 417-422 [doi]
• Theories of Parenting and Their Application to Artificial IntelligenceSky Croeser, Peter Eckersley. 423-428 [doi]
• Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI ProductsInioluwa Deborah Raji, Joy Buolamwini. 429-435 [doi]
• A Framework for Benchmarking Discrimination-Aware Models in Machine LearningRodrigo L. Cardoso, Wagner Meira Jr., Virgílio A. F. Almeida, Mohammed J. Zaki. 437-444 [doi]
• Towards a Just Theory of Measurement: A Principled Social Measurement Assurance Program for Machine LearningMcKane Andrus, Thomas K. Gilbert. 445-451 [doi]
• Putting Fairness Principles into Practice: Challenges, Metrics, and ImprovementsAlex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi. 453-459 [doi]
• On Influencing Individual Behavior for Reducing Transportation Energy Expenditure in a Large PopulationShiwali Mohan, Frances Yan, Victoria Bellotti, Ahmed Elbery, Hesham Rakha, Matthew Klenk. 461-467 [doi]
• Guiding Prosecutorial Decisions with an Interpretable Statistical ModelZhiyuan Lin, Alex Chohlas-Wood, Sharad Goel. 469-476 [doi]
• Using Deceased-Donor Kidneys to Initiate Chains of Living Donor Kidney Paired Donations: Algorithm and ExperimentationCristina Cornelio, Lucrezia Furian, Antonio Nicolò, Francesca Rossi. 477-483 [doi]
• Inferring Work Task Automatability from AI Expert EvidencePaul Duckworth, Logan Graham, Michael Osborne. 485-491 [doi]
• Robots Can Be More Than Black And White: Examining Racial Bias Towards RobotsArifah Addison, Christoph Bartneck, Kumar Yogeeswaran. 493-498 [doi]
• Tact in Noncompliance: The Need for Pragmatically Apt Responses to Unethical CommandsRyan Blake Jackson, Ruchen Wen, Tom Williams 0001. 499-505 [doi]
• AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AIJosé Hernández-Orallo, Karina Vold. 507-513 [doi]
• Human Trust Measurement Using an Immersive Virtual Reality Autonomous Vehicle SimulatorShervin Shahrdar, Corey Park, Mehrdad Nojoumian. 515-520 [doi]
• The Value of Trustworthy AIDavid Danks. 521-522 [doi]
• Generating Appropriate Responses to Inappropriate Robot CommandsRyan Blake Jackson. 523-524 [doi]
• Towards Empathetic Planning and Plan RecognitionMaayan Shvo. 525-526 [doi]
• Fairness Criteria for Face Recognition ApplicationsFilip Michalsky. 527-528 [doi]
• Popularity Bias in Ranking and RecommendationHiman Abdollahpouri. 529-530 [doi]
• Risk Assessments and Fairness Under Missingness and ConfoundingAmanda Coston. 531 [doi]
• Artificial Intelligence's Impact on Mental Health TreatmentsMichelle C. Ausman. 533-534 [doi]
• Algorithmic Stereotypes: Implications for Fairness of Generalizing from Past DataDaniel McNamara. 535-536 [doi]
• Perceptions of FairnessNripsuta Ani Saxena. 537-538 [doi]
• Learning Context-Sensitive Norms under UncertaintyVasanth Sarathy. 539-540 [doi]
• Fairness, Accountability and Transparency in Artificial Intelligence: A Case Study of Logical Predictive ModelsKacper Sokol. 541-542 [doi]
• Enabling Effective Transparency: Towards User-Centric Intelligent SystemsAaron Springer. 543-544 [doi]
• AIES 2019 Student SubmissionElija Perrier. 545-546 [doi]
• Towards Emotional Intelligence in Social Robots Designed for ChildrenDe'Aira Bryant. 547-548 [doi]
• A Framework for Technically- and Morally-Sound AIDuncan C. McElfresh. 549-550 [doi]
• Towards Formal Models of BlameworthinessMeir Friedenberg. 551-552 [doi]
• Toward Design and Evaluation Framework for Interpretable Machine Learning SystemsSina Mohseni. 553-554 [doi]
• Modeling Risk and Achieving Algorithmic Fairness Using Potential OutcomesAlan Mishler. 555-556 [doi]
• Machine Learning in Legal Practice: Notes from Recent HistoryFernando A. Delgado. 557-558 [doi]
• On Serving Two Masters: Directing Critical Technical Practice towards Human-Compatibility in AIMcKane Andrus. 559-560 [doi]