AIES

Publications

2023

Elizabeth Edenberg, Alexandra Wood
Disambiguating Algorithmic Bias: From Neutrality to Justice. AIES (2023)
Kevin Bryson
Designing Interfaces to Elicit Data Issues for Data Workers. AIES (2023)
Donal Khosrowi, Finola Finn, Elinor Clark
Diffusing the Creator: Attributing Credit for Generative AI Outputs. AIES (2023)
Ranjita Naik, Besmira Nushi
Social Biases through the Text-to-Image Generation Lens. AIES (2023)
Paola Ricaurte
AI for/by the majority world: From technologies of dispossession to technologies of radical care. AIES (2023)
Spencer Rarrick, Ranjita Naik, Varun Mathur, Sundar Poudel, Vishal Chowdhary
GATE: A Challenge Set for Gender-Ambiguous Translation Examples. AIES (2023)
Charvi Rastogi, Marco Túlio Ribeiro, Nicholas King, Harsha Nori, Saleema Amershi
Supporting Human-AI Collaboration in Auditing LLMs with LLMs. AIES (2023)
Ian Hardy, Jayanth Yetukuri, Yang Liu
Adaptive Adversarial Training Does Not Increase Recourse Costs. AIES (2023)
Chahat Raj, Anjishnu Mukherjee, Ziwei Zhu
True and Fair: Robust and Unbiased Fake News Detection via Interpretable Machine Learning. AIES (2023)
Olalekan Joseph Akintande
Algorithmic Bias: When stigmatization becomes a perception: The stigmatized become endangered. AIES (2023)
Charlotte Bird, Eddie L. Ungless, Atoosa Kasirzadeh
Typology of Risks of Generative Text-to-Image Models. AIES (2023)
Luca Nannini
Explainability in Process Mining: A Framework for Improved Decision-Making. AIES (2023)
Nora Freya Lindemann
Sealed Knowledges: A Critical Approach to the Usage of LLMs as Search Engines. AIES (2023)
Jess Parris Westbrook
Queering Futures: the design of an expanded mixed methods research framework integrating qualitative, quantitative, and practice-based modes. AIES (2023)
Shin-Shin Hua, Haydn Belfield
Effective Enforceability of EU Competition Law Under AI Development Scenarios: a Framework for Anticipatory Governance. AIES (2023)
Hetvi Jethwani
Multi Value Alignment: four steps for aligning ML/AI development choices with multiple values. AIES (2023)
Mubarak Hussain
Can AlphaGo be apt subjects for Praise/Blame for "Move 37"? AIES (2023)
Harvineet Singh, Rumi Chunara
Measures of Disparity and their Efficient Estimation. AIES (2023)
Shiva Omrani Sabbaghi, Robert Wolfe, Aylin Caliskan
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context. AIES (2023)
Saumik Narayanan, Guanghui Yu, Chien-Ju Ho, Ming Yin
How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making? AIES (2023)
Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso
REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values. AIES (2023)
Darren Cook
The Mechanical Psychologist: Leveraging AI for Detecting Predatory Behaviour in Online Interactions. AIES (2023)
Saumik Narayanan
Exploring the Effect of AI Assistance on Human Ethical Decisions. AIES (2023)
Shalaleh Rismani, AJung Moon
What does it mean to be a responsible AI practitioner: An ontology of roles and skills. AIES (2023)
Christie Lawrence, Isaac Cui, Daniel Ho
The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies. AIES (2023)
Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos
Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy. AIES (2023)
Behrad Taghibeyglou
How to promote equitable sleep care among people experiencing homelessness: An AI-enabled person-centred computer vision-based solution. AIES (2023)
Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities. AIES (2023)
Jinhwa Kim
Safety Issues in Conversational Systems. AIES (2023)
Przemyslaw A. Grabowicz, Nicholas Perello, Kenta Takatsu
Learning from Discriminatory Training Data. AIES (2023)
Anastasia Siapka
AI-driven Automation as a Pre-condition for Eudaimonia. AIES (2023)
Dafna Burema, Nicole Debowski-Weimann, Alexander von Janowski, Jil Grabowski, Mihai Maftei, Mattis Jacobs, Patrick van der Smagt, Djalel Benbouzid
A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context. AIES (2023)
Elizabeth Seger, Aviv Ovadya, Divya Siddarth, Ben Garfinkel, Allan Dafoe
Democratising AI: Multiple Meanings, Goals, and Methods. AIES (2023)
Charvi Rastogi
Investigating the Relative Strengths of Humans and Machine Learning in Decision-Making. AIES (2023)
Pamela Robinson
Action Guidance and AI Alignment. AIES (2023)
Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. AIES (2023)
Aidan Kierans
Benchmarked Ethics: A Roadmap to AI Alignment, Moral Knowledge, and Control. AIES (2023)
Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
A Deep Dive into Dataset Imbalance and Bias in Face Identification. AIES (2023)
Atoosa Kasirzadeh, Charles Evans
User Tampering in Reinforcement Learning Recommender Systems. AIES (2023)
Annette Zimmermann
The Generative AI Deployment Rush: How to Democratize the Politics of Pace. AIES (2023)
Jessica Woodgate
Ethical Principles for Reasoning about Value Preferences. AIES (2023)
Vishwali Mhasawade
Advancing Health Equity with Machine Learning. AIES (2023)
Jayanth Yetukuri, Ian Hardy, Yang Liu
Towards User Guided Actionable Recourse. AIES (2023)
Guusje Juijn, Niya Stoimenova, João Reis, Dong Nguyen
Perceived Algorithmic Fairness using Organizational Justice Theory: An Empirical Case Study on Algorithmic Hiring. AIES (2023)
Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham
Human Uncertainty in Concept-Based AI Systems. AIES (2023)
Alan Chan, Herbie Bradley, Nitarshan Rajkumar
Reclaiming the Digital Commons: A Public Data Trust for Training Data. AIES (2023)
Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth
Multicalibrated Regression for Downstream Fairness. AIES (2023)
Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. AIES (2023)
Eran Tal
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare. AIES (2023)
Michael Feffer, Michael Skirpan, Zachary C. Lipton, Hoda Heidari
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research. AIES (2023)