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AAAI/ACM Conference on AI, Ethics, and Society

AIES

C

CORE rank

CORE rank (raw)

C

Fields of research

Human-Centred Computing · Artificial Intelligence · Machine Learning

Papers indexed

1,025

2018–2025

Papers per year

2018279 peak2025

AIES papers

1,025 records sourced from DBLP. Search titles, filter by year, sort by recency.

YearTitleAuthors
2023How 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?Matteo Fabbri
2023Self-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
2023Disambiguating Algorithmic Bias: From Neutrality to Justice.Elizabeth Edenberg, Alexandra Wood
2023Bound by the Bounty: Collaboratively Shaping Evaluation Processes 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, Jessica de Jesus de Pinho Pinhal
2023Protecting Children from Online Exploitation: Can a Trained Model Detect Harmful Communication Strategies?Darren Cook, Miri Zilka, Heidi DeSandre, Susan Giles, Simon Maskell
2023The Mechanical Psychologist: Leveraging AI for Detecting Predatory Behaviour in Online Interactions.Darren Cook
2023Robust Artificial Moral Agents and Metanormativity.Tyler Cook
2023Human Uncertainty in Concept-Based AI Systems.Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham
2023A Deep Dive into Dataset Imbalance and Bias in Face Identification.Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
2023Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.Valerie Chen
2023Reclaiming the Digital Commons: A Public Data Trust for Training Data.Alan Chan, Herbie Bradley, Nitarshan Rajkumar
2023A 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, Djalel Benbouzid
2023Designing Interfaces to Elicit Data Issues for Data Workers.Kevin Bryson
2023Exploring the Moral Value of Explainable Artificial Intelligence Through Public Service Postal Banks.Joshua Brand
2023Typology of Risks of Generative Text-to-Image Models.Charlotte Bird, Eddie L. Ungless, Atoosa Kasirzadeh
2023Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities.Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
2023Machine Learning practices and infrastructures.Glen Berman
2023Unpicking Epistemic Injustices in Digital Health: On the Implications of Designing Data-Driven Technologies for the Management of Long-Term Conditions.SJ Bennett, Caroline Claisse, Ewa Luger, Abigail C. Durrant
2023The Ethical Implications of Generative Audio Models: A Systematic Literature Review.Julia Barnett
2023"☑ Fairness Toolkits, A Checkbox Culture?" On the Factors that Fragment Developer Practices in Handling Algorithmic Harms.Agathe Balayn, Mireia Yurrita, Jie Yang, Ujwal Gadiraju
2023Evaluating the Fairness of Discriminative Foundation Models in Computer Vision.Junaid Ali, Matthus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
2023On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations.Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
2023Algorithmic Bias: When stigmatization becomes a perception: The stigmatized become endangered.Olalekan Joseph Akintande
2023The ELIZA Defect: Constructing the Right Users for Generative AI.Daniel Affsprung
2023Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models.Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn
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