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ORCIDAIES 2023: Montréal, QC, Canada
- Francesca Rossi, Sanmay Das, Jenny Davis, Kay Firth-Butterfield, Alex John:
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, AIES 2023, Montréal, QC, Canada, August 8-10, 2023. ACM 2023
Keynote Talks
- Annette Zimmermann
:
The Generative AI Deployment Rush: How to Democratize the Politics of Pace. 1 - Jamie Morgenstern:
Changing distributions and preferences in learning systems. 2 - Paola Ricaurte:
AI for/by the majority world: From technologies of dispossession to technologies of radical care. 3-4
Contributed Papers
- Darren Cook, Miri Zilka, Heidi DeSandre, Susan Giles, Simon Maskell:
Protecting Children from Online Exploitation: Can a Trained Model Detect Harmful Communication Strategies? 5-14 - Tunazzina Islam, Ruqi Zhang, Dan Goldwasser:
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. 15-25 - Johanna Walker, Gefion Thuermer, Julián Vicens, Elena Simperl:
AI Art and Misinformation: Approaches and Strategies for Media Literacy and Fact Checking. 26-37 - Michael Feffer, Michael Skirpan, Zachary C. Lipton, Hoda Heidari:
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research. 38-48 - Saumik Narayanan, Guanghui Yu, Chien-Ju Ho, Ming Yin:
How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making? 49-57 - Atoosa Kasirzadeh, Charles Evans:
User Tampering in Reinforcement Learning Recommender Systems. 58-69 - Shalaleh Rismani, Renee Shelby, Andrew Smart, Renelito Delos Santos, AJung Moon, Negar Rostamzadeh:
Beyond the ML Model: Applying Safety Engineering Frameworks to Text-to-Image Development. 70-83 - Thomas Krendl Gilbert, Nathan Lambert, Sarah Dean, Tom Zick, Aaron J. Snoswell, Soham Mehta:
Reward Reports for Reinforcement Learning. 84-130 - William Seymour, Xiao Zhan, Mark Coté, Jose M. Such:
A Systematic Review of Ethical Concerns with Voice Assistants. 131-145 - Julia Barnett:
The Ethical Implications of Generative Audio Models: A Systematic Literature Review. 146-161 - Tyler Cook:
Robust Artificial Moral Agents and Metanormativity. 162-169 - Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima:
Mitigating Voter Attribute Bias for Fair Opinion Aggregation. 170-180 - Nathanael Jo, Sina Aghaei, Jack Benson, Andrés Gómez, Phebe Vayanos:
Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy. 181-192 - Jindi Zhang, Luning Wang, Dan Su, Yongxiang Huang, Caleb Chen Cao, Lei Chen:
Model Debiasing via Gradient-based Explanation on Representation. 193-204 - Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis:
Sampling Individually-Fair Rankings that are Always Group Fair. 205-216 - Alexandre Nanchen, Lakmal Meegahapola, William Droz, Daniel Gatica-Perez:
Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores. 217-228 - 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. 229-247 - Yilun Zhou:
Iterative Partial Fulfillment of Counterfactual Explanations: Benefits and Risks. 248-258 - Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth:
Multicalibrated Regression for Downstream Fairness. 259-286 - Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. 287-296 - Mackenzie Jorgensen, Hannah Richert, Elizabeth Black, Natalia Criado, Jose M. Such:
Not So Fair: The Impact of Presumably Fair Machine Learning Models. 297-311 - Eran Tal:
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare. 312-321 - SJ Bennett, Caroline Claisse, Ewa Luger, Abigail C. Durrant:
Unpicking Epistemic Injustices in Digital Health: On the Implications of Designing Data-Driven Technologies for the Management of Long-Term Conditions. 322-332 - Ming-Ying Yang, Gloria Hyun-Jung Kwak, Tom J. Pollard, Leo Anthony Celi, Marzyeh Ghassemi:
Evaluating the Impact of Social Determinants on Health Prediction in the Intensive Care Unit. 333-350 - Hubert Dariusz Zajac, Natalia Rozalia Avlona, Finn Kensing, Tariq Osman Andersen, Irina Shklovski:
Ground Truth Or Dare: Factors Affecting The Creation Of Medical Datasets For Training AI. 351-362 - Harry H. Jiang, Lauren Brown, Jessica Cheng, Mehtab Khan, Abhishek Gupta, Deja Workman, Alex Hanna, Johnathan Flowers, Timnit Gebru:
AI Art and its Impact on Artists. 363-374 - 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, Jessica de Jesus de Pinho Pinhal:
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. 375-386 - Pamela Robinson:
Action Guidance and AI Alignment. 387-395 - Charlotte Bird, Eddie L. Ungless, Atoosa Kasirzadeh:
Typology of Risks of Generative Text-to-Image Models. 396-410 - Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni:
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. 411-431 - Ian Hardy, Jayanth Yetukuri, Yang Liu:
Adaptive Adversarial Training Does Not Increase Recourse Costs. 432-442 - Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso:
REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values. 443-453 - Carlos Mougan, José M. Álvarez, Salvatore Ruggieri, Steffen Staab:
Fairness Implications of Encoding Protected Categorical Attributes. 454-465 - Glen Berman:
Machine Learning practices and infrastructures. 466-481 - Agathe Balayn, Mireia Yurrita, Jie Yang, Ujwal Gadiraju:
"☑ Fairness Toolkits, A Checkbox Culture?" On the Factors that Fragment Developer Practices in Handling Algorithmic Harms. 482-495 - Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee, Kai-Wei Chang:
Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness. 496-511 - Vincent J. Straub, Deborah Morgan, Youmna Hashem, John Francis, Saba Esnaashari, Jonathan Bright:
A multidomain relational framework to guide institutional AI research and adoption. 512-519 - Keziah Naggita, Julienne LaChance, Alice Xiang:
Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data. 520-530 - Rachel Hong, Tadayoshi Kohno, Jamie Morgenstern:
Evaluation of targeted dataset collection on racial equity in face recognition. 531-541 - Shiva Omrani Sabbaghi, Robert Wolfe, Aylin Caliskan:
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context. 542-553 - Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar, Ting-Hao Kenneth Huang, Shomir Wilson:
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles. 554-565 - Tom Williams, Kerstin Sophie Haring:
No Justice, No Robots: From the Dispositions of Policing to an Abolitionist Robotics. 566-575 - Violet Turri, Rachel Dzombak:
Why We Need to Know More: Exploring the State of AI Incident Documentation Practices. 576-583 - Shalaleh Rismani, AJung Moon:
What does it mean to be a responsible AI practitioner: An ontology of roles and skills. 584-595 - Shin-Shin Hua, Haydn Belfield:
Effective Enforceability of EU Competition Law Under AI Development Scenarios: a Framework for Anticipatory Governance. 596-605 - Christie Lawrence, Isaac Cui, Daniel E. Ho:
The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies. 606-652 - Matteo Fabbri:
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. 653-661 - Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson:
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. 662-678 - Avijit Ghosh, Pablo Kvitca, Christo Wilson:
When Fair Classification Meets Noisy Protected Attributes. 679-690 - Elizabeth Edenberg, Alexandra Wood:
Disambiguating Algorithmic Bias: From Neutrality to Justice. 691-704 - 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. 705-714 - Elizabeth Seger, Aviv Ovadya, Divya Siddarth, Ben Garfinkel, Allan Dafoe:
Democratising AI: Multiple Meanings, Goals, and Methods. 715-722 - Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N'Mah Yilla-Akbari, Jess Gallegos, Andrew Smart, Emilio García, Gurleen Virk:
Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction. 723-741 - Jayanth Yetukuri, Ian Hardy, Yang Liu:
Towards User Guided Actionable Recourse. 742-751 - Przemyslaw A. Grabowicz, Nicholas Perello, Kenta Takatsu:
Learning from Discriminatory Training Data. 752-763 - Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett:
Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities. 764-774 - Guusje Juijn, Niya Stoimenova, João Reis, Dong Nguyen:
Perceived Algorithmic Fairness using Organizational Justice Theory: An Empirical Case Study on Algorithmic Hiring. 775-785 - Ranjita Naik, Besmira Nushi:
Social Biases through the Text-to-Image Generation Lens. 786-808 - Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell:
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. 809-833 - Philippe Lammerts, Philip Lippmann, Yen-Chia Hsu, Fabio Casati, Jie Yang:
How do you feel? Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection. 834-844 - Spencer Rarrick, Ranjita Naik, Varun Mathur, Sundar Poudel, Vishal Chowdhary:
GATE: A Challenge Set for Gender-Ambiguous Translation Examples. 845-854 - Alan Chan, Herbie Bradley, Nitarshan Rajkumar:
Reclaiming the Digital Commons: A Public Data Trust for Training Data. 855-868 - 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. 869-889 - Donal Khosrowi, Finola Finn, Elinor Clark:
Diffusing the Creator: Attributing Credit for Generative AI Outputs. 890-900 - Sourojit Ghosh, Aylin Caliskan:
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. 901-912 - Charvi Rastogi, Marco Túlio Ribeiro, Nicholas King, Harsha Nori, Saleema Amershi:
Supporting Human-AI Collaboration in Auditing LLMs with LLMs. 913-926 - Harvineet Singh, Rumi Chunara:
Measures of Disparity and their Efficient Estimation. 927-938
Student Abstracts
- Saumik Narayanan:
Exploring the Effect of AI Assistance on Human Ethical Decisions. 939-940 - Jess Parris Westbrook:
Queering Futures: the design of an expanded mixed methods research framework integrating qualitative, quantitative, and practice-based modes. 941 - Valerie Chen:
Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions. 942-944 - Daniel Affsprung:
The ELIZA Defect: Constructing the Right Users for Generative AI. 945-946 - Emmie Hine:
Governing Silicon Valley and Shenzhen: Assessing a New Era of Artificial Intelligence Governance in the US and China. 947-949 - Jinhwa Kim:
Safety Issues in Conversational Systems. 950-951 - Bhargavi Ganesh:
The Role of Governance in Bridging AI Responsibility Gaps: An interdisciplinary evaluation of emerging AI governance measures. 952-954 - Vishwali Mhasawade:
Advancing Health Equity with Machine Learning. 955-956 - Kevin Bryson:
Designing Interfaces to Elicit Data Issues for Data Workers. 957-958 - Chinasa T. Okolo:
Navigating the Limits of AI Explainability: Designing for Novice Technology Users in Low-Resource Settings. 959-961 - Chahat Raj, Anjishnu Mukherjee, Ziwei Zhu:
True and Fair: Robust and Unbiased Fake News Detection via Interpretable Machine Learning. 962-963 - Aidan Kierans:
Benchmarked Ethics: A Roadmap to AI Alignment, Moral Knowledge, and Control. 964-965 - Olalekan Joseph Akintande:
Algorithmic Bias: When stigmatization becomes a perception: The stigmatized become endangered. 966-971 - Jessica Woodgate:
Ethical Principles for Reasoning about Value Preferences. 972-974 - Luca Nannini:
Explainability in Process Mining: A Framework for Improved Decision-Making. 975-976 - Mubarak Hussain:
Can AlphaGo be apt subjects for Praise/Blame for "Move 37"? 977-979 - Deborah Morgan:
Anticipatory regulatory instruments for AI systems: A comparative study of regulatory sandbox schemes. 980-981 - Terkura Thomas Mchia:
Examining the Ethics of Brain-Computer Interfaces: Ensuring Safety, the Rights and Dignity of Personhood. 982 - Behrad Taghibeyglou:
How to promote equitable sleep care among people experiencing homelessness: An AI-enabled person-centred computer vision-based solution. 983-984 - Nora Freya Lindemann:
Sealed Knowledges: A Critical Approach to the Usage of LLMs as Search Engines. 985-986 - Charvi Rastogi:
Investigating the Relative Strengths of Humans and Machine Learning in Decision-Making. 987-989 - Joshua Brand:
Exploring the Moral Value of Explainable Artificial Intelligence Through Public Service Postal Banks. 990-992 - Anastasia Siapka:
AI-driven Automation as a Pre-condition for Eudaimonia. 993-994 - Hetvi Jethwani:
Multi Value Alignment: four steps for aligning ML/AI development choices with multiple values. 995 - Anna Marie Rezk:
"Way too good and way beyond comfort": The trade-off between user perception of benefits and comfort in media personalisation. 996-998 - Anna Schmitz:
Towards formalizing and assessing AI fairness. 999-1001 - Matteo Fabbri:
How and to which extent will the provisions of the Digital Services Act of the European Union impact on the relationship between users and platforms as information providers? 1002-1003 - Pranav Narayanan Venkit:
Towards a Holistic Approach: Understanding Sociodemographic Biases in NLP Models using an Interdisciplinary Lens. 1004-1005 - Rachel Hong:
Evaluation of targeted dataset collection on racial equity in face recognition. 1006-1007 - Jayanth Yetukuri:
Individual and Group-level considerations of Actionable Recourse. 1008-1009 - Darren Cook:
The Mechanical Psychologist: Leveraging AI for Detecting Predatory Behaviour in Online Interactions. 1010-1012
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