Web based E-Government Data Distribution. - Paul J. Fortier; Andrew Smart (HICSS, 2001)

Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning. - Andrew Smart; Larry James; Ben Hutchinson; Simone Wu; Shannon Vallor (AIES, 2020)

Towards a critical race methodology in algorithmic fairness. - Alex Hanna; Emily Denton; Andrew Smart; Jamila Smith-Loud (FAT*, 2020)

Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. - Inioluwa Deborah Raji; Andrew Smart; Rebecca N. White; Margaret Mitchell; Timnit Gebru; Ben Hutchinson; Jamila Smith-Loud; Daniel Theron; Parker Barnes (FAT*, 2020)

Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics. - Donald Martin Jr.; Vinodkumar Prabhakaran; Jill Kuhlberg; Andrew Smart; William S. Isaac (CoRR, 2020)

Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context. - Donald Martin Jr.; Vinodkumar Prabhakaran; Jill Kuhlberg; Andrew Smart; William S. Isaac (CoRR, 2020)

Bringing the People Back In: Contesting Benchmark Machine Learning Datasets. - Emily Denton; Alex Hanna; Razvan Amironesei; Andrew Smart; Hilary Nicole; Morgan Klaus Scheuerman (CoRR, 2020)

Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives. - Angie Peng; Jeff Naecker; Ben Hutchinson; Andrew Smart; Nyalleng Moorosi (CoRR, 2020)

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. - Ben Hutchinson; Andrew Smart; Alex Hanna; Emily Denton; Christina Greer; Oddur Kjartansson; Parker Barnes; Margaret Mitchell (FAccT, 2021)

The Use and Misuse of Counterfactuals in Ethical Machine Learning. - Atoosa Kasirzadeh; Andrew Smart (FAccT, 2021)

On the genealogy of machine learning datasets: A critical history of ImageNet. - Emily Denton; Alex Hanna; Razvan Amironesei; Andrew Smart; Hilary Nicole (Big Data Soc., 2021)

Healthsheet: Development of a Transparency Artifact for Health Datasets. - Negar Rostamzadeh; Diana Mincu; Subhrajit Roy; Andrew Smart; Lauren Wilcox; Mahima Pushkarna; Jessica Schrouff; Razvan Amironesei; Nyalleng Moorosi; Katherine A. Heller (FAccT, 2022)

Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction. - Renee Shelby; Shalaleh Rismani; Kathryn Henne; AJung Moon; Negar Rostamzadeh; Paul Nicholas; N'Mah Yilla; Jess Gallegos; Andrew Smart; Emilio Garcia; Gurleen Virk (CoRR, 2022)

Beyond the ML Model: Applying Safety Engineering Frameworks to Text-to-Image Development. - Shalaleh Rismani; Renee Shelby; Andrew Smart; Renelito Delos Santos; AJung Moon; Negar Rostamzadeh (AIES, 2023)

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 García; Gurleen Virk (AIES, 2023)

From Plane Crashes to Algorithmic Harm: Applicability of Safety Engineering Frameworks for Responsible ML. - Shalaleh Rismani; Renee Shelby; Andrew Smart; Edgar W. Jatho III; Joshua A. Kroll; AJung Moon; Negar Rostamzadeh (CHI, 2023)

Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs. - Sanna J. Ali; Angèle Christin; Andrew Smart; Riitta Katila (FAccT, 2023)

Statistical Methods for Auditing the Quality of Manual Content Reviews. - Xuan Yang; Andrew Smart; Daniel Theron (Tiny Papers @ ICLR, 2023)

The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development. - Jamila Smith-Loud; Andrew Smart; Darlene Neal; Amber Ebinama; Eric Corbett; Paul Nicholas; Qazi Rashid; Anne Peckham; Sarah Murphy-Gray; Nicole Morris; Elisha Smith Arrillaga; Nicole-Marie Cotton; et al. (CoRR, 2023)

Assessing LLMs for Moral Value Pluralism. - Noam Benkler; Drisana Mosaphir; Scott Friedman 001; Andrew Smart; Sonja Schmer-Galunder (CoRR, 2023)

Unsocial Intelligence: An Investigation of the Assumptions of AGI Discourse. - Borhane Blili-Hamelin; Leif Hancox-Li; Andrew Smart (AIES (1), 2024)

Unsocial Intelligence: a Pluralistic, Democratic, and Participatory Investigation of AGI Discourse. - Borhane Blili-Hamelin; Leif Hancox-Li; Andrew Smart (CoRR, 2024)

Discipline and Label: A WEIRD Genealogy and Social Theory of Data Annotation. - Andrew Smart; Ding Wang; Ellis Monk; Mark Díaz; Atoosa Kasirzadeh; Erin van Liemt; Sonja Schmer-Galunder (CoRR, 2024)

Socially Responsible Data for Large Multilingual Language Models. - Andrew Smart; Ben Hutchinson; Lameck Mbangula Amugongo; Suzanne Dikker; Alex Zito; Amber Ebinama; Zara Wudiri; Ding Wang; Erin van Liemt; João Sedoc; Seyi Olojo; Stanley Uwakwe; et al. (CoRR, 2024)

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

Lost in Machine Translation: The Sociocultural Implications of Language Technologies in Nigeria. - Seyi Olojo; Janina Zakrzewski; Andrew Smart; Erin van Liemt; Milagros Miceli; Amber Ebinama; Lameck Mbangula Amugongo (FAccT, 2025)

Stop treating 'AGI' as the north-star goal of AI research. - Borhane Blili-Hamelin; Christopher Graziul; Leif Hancox-Li; Hananel Hazan; El-Mahdi El-Mhamdi; Avijit Ghosh; Katherine A. Heller; Jacob Metcalf; Fabricio Murai; Eryk Salvaggio; Andrew Smart; Todd Snider; et al. (CoRR, 2025)

Beyond model interpretability: socio-structural explanations in machine learning. - Andrew Smart; Atoosa Kasirzadeh (AI Soc., 2025)