AIES 2023 Accepted Papers

How do you feel? Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection
Philippe Lammerts, Philip Lippmann, Yen-Chia Hsu, Fabio Casati and Jie Yang.
Iterative Partial Fulfillment of Counterfactual Explanations: Benefits and Risks
Yilun Zhou.
Fairness implications of encoding protected categorical attributes
Carlos Mougan, Jose Alvarez, Salvatore Ruggieri and Steffen Staab.
Reclaiming the Digital Commons: A Public Data Trust for Training Data
Alan Chan, Herbie Bradley and Nitarshan Rajkumar.
Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data
Keziah Naggita, Julienne LaChance and Alice Xiang.
Mitigating Voter Attribute Bias for Fair Opinion Aggregation
Ryosuke Ueda, Koh Takeuchi and Hisashi Kashima.
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research
Michael Feffer, Michael Skirpan, Hoda Heidari and Zachary Lipton.
Evaluation of targeted dataset collection on racial equity in face recognition
Rachel Hong, Tadayoshi Kohno and Jamie Morgenstern.
No Justice, No Robots: From the Dispositions of Policing to an Abolitionist Robotics
Tom Williams and Kerstin Sophie Haring.
Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy
Nathanael Jo, Sina Aghaei, Jack Benson, Andres Gomez and Phebe Vayanos.
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging
Tunazzina Islam, Ruqi Zhang and Dan Goldwasser.
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context
Shiva Omrani Sabbaghi, Robert Wolfe and Aylin Caliskan.
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles
Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar, Ting-Hao Huang and Shomir Wilson.
Model Debiasing via Gradient-based Explanation on Representation
Jindi Zhang, Luning Wang, Dan Su, Yongxiang Huang, Caleb Chen Cao and Lei Chen.
User Tampering in Reinforcement Learning Recommender Systems
Charles Evans and Atoosa Kasirzadeh.
Artificial Intelligence, Radical Ignorance, and the Institutional Context of Consent
Etye Steinberg.
Sampling Individually-Fair Rankings that are Always Group Fair
Sruthi Gorantla, Anay Mehrotra, Amit Deshpande and Anand Louis.
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages
Sourojit Ghosh and Aylin Caliskan.
Identifying Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
Renee Shelby, Shalaleh Rismani, Kathryn Henne, Ajung Moon, Negar Rostamzadeh, Paul Nicholas, N’Mah Yilla-Akbari, Jess Gallegos, Andrew Smart, Emilio Garcia and Gurleen Virk.
“Fairness Toolkits, A Checkbox Culture?” On the Factors that Fragment Developer Practices in Handling Algorithmic Harms
Agathe Balayn, Mireia Yurrita, Jie Yang and Ujwal Gadiraju.
GATE: A Challenge Set for Gender-Ambiguous Translation Examples
Spencer Rarrick, Ranjita Naik, Varun Mathur, Sundar Poudel and Vishal Chowdhary.
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations
Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic and Daniele Magazzeni.
Perceived Algorithmic Fairness using Organizational Justice Theory: An Empirical Case Study on Algorithmic Hiring
Guusje Juijn, Niya Stoimenova, Joao Reis and Dong Nguyen.
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare
Eran Tal.
A Systematic Review of Ethical Concerns with Voice Assistants
William Seymour, Xiao Zhan, Mark Coté and Jose Such.
A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context
Dafna Burema, Nicole Debowski-Weimann, Alexander von Janowski, Jil Grabowski, Mihai Maftei, Mattis Jacobs, Patrick van der Smagt and Djalel Benbouzid.
AI Art and its Impact on Artists
Harry Jiang, Timnit Gebru, Jessica Cheng, Lauren Brown, Mehtab Khan, Johnathan Flowers, Abhishek Gupta, Deja Workman and Alex Hanna.
Ethical Unaffordances: Collaboratively Developing Evaluation Frameworks for Queer AI Harms
Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo and Jess de Jesus de Pinho Pinhal.
Multicalibrated Regression for Downstream Fairness
Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern and Aaron Roth.
Unpicking Epistemic Injustices in Digital Health: On Designing Data-Driven Technologies to Support the Self-Management of Long-Term Health Conditions
S J Bennett, Caroline Claisse, Ewa Luger and Abigail C. Durrant.
Beyond the ML Model: Applying Safety Engineering Frameworks to Text-to-Image Development
Shalaleh Rismani, Renee Shelby, Andrew Smart, Renelito Delos Santos, Ajung Moon and Negar Rostamzadeh.
The Ethical Implications of Generative Audio Models: A Systematic Literature Review
Julia Barnett.
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective
Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines and John Dickerson.
Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores
Alexandre Nanchen, Lakmal Meegahapola, William Droz and Daniel Gatica-Perez.
Machine Learning practices and infrastructures
Glen Berman.
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models
Peter Henderson, Eric Mitchell, Christopher Manning, Dan Jurafsky and Chelsea Finn.
A Deep Dive into Dataset Imbalance and Bias in Face Identification
Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John Dickerson, Micah Goldblum and Tom Goldstein.
Human Uncertainty in Concept-Based AI Systems
Katherine Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller and Krishnamurthy Dvijotham.
“Democratising AI”: Multiple Meanings, Goals, and Methods
Elizabeth Seger, Aviv Ovadya, Divya Siddarth, Ben Garfinkel and Allan Dafoe.
Effective Enforceability of EU Competition Law Under AI Development Scenarios: a Framework for Anticipatory Governance
Shin-Shin Hua and Haydn Belfield.
Disambiguating Algorithmic Bias: From Neutrality to Justice
Elizabeth Edenberg and Alexandra Wood.
Protecting Children from Online Exploitation: Can a trained model detect harmful communication strategies?
Darren Cook, Miri Zilka, Heidi Desandre, Susan Giles and Simon Maskell.
Measures of Disparity and their Efficient Estimation
Harvineet Singh and Rumi Chunara.
Reward Reports for Reinforcement Learning
Thomas Gilbert, Nathan Lambert, Sarah Dean, Tom Zick and Aaron Snoswell.
Not So Fair: The Impact of Presumably Fair Machine Learning Models
Mackenzie Jorgensen, Hannah Richert, Elizabeth Black, Natalia Criado and Jose Such.
Why We Need to Know More: Exploring the State of AI Incident Documentation Practices
Violet Turri and Rachel Dzombak.
The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies
Christie Lawrence, Isaac Cui and Daniel Ho.
What does it mean to be a responsible AI practitioner: An ontology of existing roles
Shalaleh Rismani and Ajung Moon.
Robust Artificial Moral Agents and Metanormativity
Tyler Cook.
Adaptive Adversarial Training Does Not Increase Recourse Costs
Ian Hardy, Jayanth Yetukuri and Yang Liu.
Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness
Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee and Kai-Wei Chang.
REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values
Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lecue, Daniele Magazzeni and Manuela Veloso.
When Fair Classification Meets Noisy Protected Attributes
Avijit Ghosh, Pablo Kvitca and Christo Wilson.
Towards User Guided Actionable Recourse
Jayanth Yetukuri, Ian Hardy and Yang Liu.
How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making?
Saumik Narayanan, Guanghui Yu, Chien-Ju Ho and Ming Yin.
Learning from Discriminatory Training Data
Przemyslaw Grabowicz, Nicholas Perello and Kenta Takatsu.
Social Biases through the Text-to-Image Generation Lens
Ranjita Naik and Besmira Nushi.
Designing for Human-AI Collaboration in Auditing LLMs with LLMs
Charvi Rastogi, Marco Tulio Ribeiro, Nicholas King, Harsha Nori and Saleema Amershi.
Stress-testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities
Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng and Kristin Bennett.
Action Guidance and AI Alignment
Pamela Robinson.
AI Art and Misinformation∗ Approaches and strategies for media literacy and fact checking
Johanna Walker, Gefion Thuermer, Elena Simperl and Julian Vincens.
Diffusing the Creator: Attributing Credit in Generative AI
Donal Khosrowi, Finola Finn and Elinor Clark.
Self-determination through explanation: an ethical perspective on the implementation of the transparency requirements for recommender systems set by the Digital Services Act of the European Union
Matteo Fabbri.
A multidomain relational framework to guide institutional AI research and adoption
Vincent Straub, Deborah Morgan, Youmna Hashem, John Francis, Saba Esnaashari and Jonathan Bright.
Evaluating the Impact of Social Determinants on Health Prediction
Ming Ying Yang, Gloria Hyunjung Kwak, Tom Pollard, Leo Anthony Celi and Marzyeh Ghassemi.
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision
Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher and Chris Russell.
Ground Truth Or Dare: Factors Affecting The Design Of Ground Truth In The Creation Of Medical Datasets For Training AI Models
Hubert D. Zając, Natalia R. Avlona, Finn Kensing, Tariq O. Andersen and Irina Shklovski.
Ethical and Social Risks of Generative Text-to-Image Models
Charlotte Bird, Eddie Ungless and Atoosa Kasirzadeh.