Illusory Correlations: An Investigation in a Social Media Setting. - Abeba Birhane; Roisin Fitzpatrick; Caoimhe Kavanagh; John Rogers (AICS, 2016)

Conversational AI: Social and Ethical Considerations. - Elayne Ruane; Abeba Birhane; Anthony Ventresque (AICS, 2019)

Algorithmic Injustices: Towards a Relational Ethics. - Abeba Birhane; Fred Cummins (CoRR, 2019)

Robot Rights?: Let's Talk about Human Welfare Instead. - Abeba Birhane; Jelle van Dijk (AIES, 2020)

Towards decolonising computational sciences. - Abeba Birhane; Olivia Guest (CoRR, 2020)

Narratives and Counternarratives on Data Sharing in Africa. - Rediet Abebe; Kehinde D. Aruleba; Abeba Birhane; Sara Kingsley; George Obaido; Sekou L. Remy; Swathi Sadagopan (FAccT, 2021)

Large image datasets: A pyrrhic win for computer vision? - Abeba Birhane; Vinay Uday Prabhu (WACV, 2021)

The Impossibility of Automating Ambiguity. - Abeba Birhane (Artif. Life, 2021)

Multimodal datasets: misogyny, pornography, and malignant stereotypes. - Abeba Birhane; Vinay Uday Prabhu; Emmanuel Kahembwe (CoRR, 2021)

Ethical and social risks of harm from Language Models. - Laura Weidinger; John Mellor; Maribeth Rauh; Conor Griffin; Jonathan Uesato; Po-Sen Huang; Myra Cheng; Mia Glaese; Borja Balle; Atoosa Kasirzadeh; Zac Kenton; Sasha Brown; et al. (CoRR, 2021)

Algorithmic injustice: a relational ethics approach. - Abeba Birhane (Patterns, 2021)

The Limits of Fairness. - Abeba Birhane (AIES, 2022)

Power to the People? Opportunities and Challenges for Participatory AI. - Abeba Birhane; William Isaac 001; Vinodkumar Prabhakaran; Mark Diaz; Madeleine Clare Elish; Iason Gabriel; Shakir Mohamed (EAAMO, 2022)

Handling and Presenting Harmful Text in NLP Research. - Hannah Kirk; Abeba Birhane; Bertie Vidgen; Leon Derczynski (EMNLP (Findings), 2022)

The Values Encoded in Machine Learning Research. - Abeba Birhane; Pratyusha Kalluri; Dallas Card; William Agnew; Ravit Dotan; Michelle Bao (FAccT, 2022)

The Forgotten Margins of AI Ethics. - Abeba Birhane; Elayne Ruane; Thomas Laurent 003; Matthew S. Brown; Johnathan Flowers; Anthony Ventresque; Christopher L. Dancy (FAccT, 2022)

Taxonomy of Risks posed by Language Models. - Laura Weidinger; Jonathan Uesato; Maribeth Rauh; Conor Griffin; Po-Sen Huang; John Mellor; Amelia Glaese; Myra Cheng; Borja Balle; Atoosa Kasirzadeh; Courtney Biles; Sasha Brown; et al. (FAccT, 2022)

The Games We Play: Critical Complexity Improves Machine Learning. - Abeba Birhane; David J. T. Sumpter (HHAI, 2022)

Auditing saliency cropping algorithms. - Abeba Birhane; Vinay Uday Prabhu; John Whaley (WACV, 2022)

Advancing Data Justice Research and Practice: An Integrated Literature Review. - David Leslie; Michael A. Katell; Mhairi Aitken; Jatinder Singh; Morgan Briggs; Rosamund Powell; Cami Rincón; Thompson Chengeta; Abeba Birhane; Antonella Perini; Smera Jayadeva; Anjali Mazumder (CoRR, 2022)

Data Justice Stories: A Repository of Case Studies. - David Leslie; Morgan Briggs; Antonella Perini; Smera Jayadeva; Cami Rincón; Noopur Raval; Abeba Birhane; Rosamund Powell; Michael A. Katell; Mhairi Aitken (CoRR, 2022)

Handling and Presenting Harmful Text. - Leon Derczynski; Hannah Rose Kirk; Abeba Birhane; Bertie Vidgen (CoRR, 2022)

Automating Ambiguity: Challenges and Pitfalls of Artificial Intelligence. - Abeba Birhane (CoRR, 2022)

Into the LAION's Den: Investigating Hate in Multimodal Datasets. - Abeba Birhane; Vinay Uday Prabhu; Sanghyun Han; Vishnu Boddeti; Sasha Luccioni (NeurIPS, 2023)

The Lost Art of Mathematical Modelling. - Linnéa Gyllingberg; Abeba Birhane; David J. T. Sumpter (CoRR, 2023)

On Hate Scaling Laws For Data-Swamps. - Abeba Birhane; Vinay Uday Prabhu; Sang Han; Vishnu Naresh Boddeti (CoRR, 2023)

The Surveillance AI Pipeline. - Pratyusha Ria Kalluri; William Agnew; Myra Cheng; Kentrell Owens; Luca Soldaini; Abeba Birhane (CoRR, 2023)

Into the LAIONs Den: Investigating Hate in Multimodal Datasets. - Abeba Birhane; Vinay Uday Prabhu; Sang Han; Vishnu Naresh Boddeti; Alexandra Sasha Luccioni (CoRR, 2023)

Beyond Single-Mindedness: A Figure-Ground Reversal for the Cognitive Sciences. - Mark Dingemanse; Andreas Liesenfeld; Marlou Rasenberg; Saul Albert; Felix K. Ameka; Abeba Birhane; Dimitris Bolis; Justine Cassell; Rebecca Clift; Elena Cuffari; Hanne De Jaegher; Catarina Dutilh Novaes; et al. (Cogn. Sci., 2023)

The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models. - Abeba Birhane; Sepehr Dehdashtian; Vinay Uday Prabhu; Vishnu Boddeti (FAccT, 2024)

AI auditing: The Broken Bus on the Road to AI Accountability. - Abeba Birhane; Ryan Steed; Victor Ojewale; Briana Vecchione; Inioluwa Deborah Raji (SaTML, 2024)

Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agency. - Abeba Birhane; Marek McGann (CoRR, 2024)

The reanimation of pseudoscience in machine learning and its ethical repercussions. - Mel Andrews; Andrew Smart; Abeba Birhane (Patterns, 2024)

Debunking robot rights metaphysically, ethically, and legally. - Abeba Birhane; Jelle van Dijk; Frank Pasquale (First Monday, 2024)

Undersea cables in Africa: The new frontiers of digital colonialism. - Esther Mwema; Abeba Birhane (First Monday, 2024)

Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. - Victor Ojewale; Ryan Steed; Briana Vecchione; Abeba Birhane; Inioluwa Deborah Raji (CHI, 2025)

Computer-vision research powers surveillance technology. - Pratyusha Ria Kalluri; William Agnew; Myra Cheng; Kentrell Owens; Luca Soldaini; Abeba Birhane (Nat., 2025)