Andrew Smart

According to our database, Andrew Smart authored at least 22 papers between 2001 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Unsocial Intelligence: a Pluralistic, Democratic, and Participatory Investigation of AGI Discourse.

Borhane Blili-Hamelin, Leif Hancox-Li, Andrew Smart

CoRR, 2024

2023

Assessing LLMs for Moral Value Pluralism.

Noam Benkler, Drisana Mosaphir, Scott Friedman, Andrew Smart, Sonja Schmer-Galunder

CoRR, 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, Emnet Almedom, Olivia Araiza, Eliza McCullough, Abbie Langston, Christopher Nellum

CoRR, 2023

Statistical Methods for Auditing the Quality of Manual Content Reviews.

Xuan Yang, Andrew Smart, Daniel Theron

Proceedings of the First Tiny Papers Track at ICLR 2023, 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

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 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

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 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

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

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

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

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

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

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

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., July, 2021

The Use and Misuse of Counterfactuals in Ethical Machine Learning.

Atoosa Kasirzadeh, Andrew Smart

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

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

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives.

Angie Peng, Jeff Naecker, Ben Hutchinson, Andrew Smart, Nyalleng Moorosi

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

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

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

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

Proceedings of the FAT* '20: Conference on Fairness, 2020

Towards a critical race methodology in algorithmic fairness.

Alex Hanna, Emily Denton, Andrew Smart, Jamila Smith-Loud

Proceedings of the FAT* '20: Conference on Fairness, 2020

Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning.

Andrew Smart, Larry James, Ben Hutchinson, Simone Wu, Shannon Vallor

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2001

Web based E-Government Data Distribution.

Paul J. Fortier, Andrew Smart

Proceedings of the 34th Annual Hawaii International Conference on System Sciences (HICSS-34), 2001