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2020 – today
- 2024
[j2]Mel Andrews, Andrew Smart
, Abeba Birhane:
The reanimation of pseudoscience in machine learning and its ethical repercussions. Patterns 5(9): 101027 (2024)- [i19]Borhane Blili-Hamelin, Leif Hancox-Li, Andrew Smart:
Unsocial Intelligence: a Pluralistic, Democratic, and Participatory Investigation of AGI Discourse. CoRR abs/2401.13142 (2024) - [i18]Andrew Smart, Ding Wang, Ellis Monk, Mark Díaz, Atoosa Kasirzadeh, Erin van Liemt, Sonja Schmer-Galunder:
Discipline and Label: A WEIRD Genealogy and Social Theory of Data Annotation. CoRR abs/2402.06811 (2024) - [i17]Andrew Smart, Atoosa Kasirzadeh:
Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning. CoRR abs/2409.03632 (2024) - [i16]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, Edem Wornyo, Sonja Schmer-Galunder, Jamila Smith-Loud:
Socially Responsible Data for Large Multilingual Language Models. CoRR abs/2409.05247 (2024) - 2023
- [c12]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. AIES 2023: 70-83 - [c11]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. AIES 2023: 723-741 - [c10]Shalaleh Rismani, Renee Shelby, Andrew Smart, Edgar W. Jatho III, Joshua A. Kroll, AJung Moon, Negar Rostamzadeh:
From Plane Crashes to Algorithmic Harm: Applicability of Safety Engineering Frameworks for Responsible ML. CHI 2023: 2:1-2:18 - [c9]Sanna J. Ali, Angèle Christin, Andrew Smart, Riitta Katila:
Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs. FAccT 2023: 217-226 - [c8]Xuan Yang, Andrew Smart, Daniel Theron:
Statistical Methods for Auditing the Quality of Manual Content Reviews. Tiny Papers @ ICLR 2023 - [i15]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:
The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development. CoRR abs/2303.08177 (2023) - [i14]Sanna J. Ali, Angèle Christin, Andrew Smart, Riitta Katila:
Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs. CoRR abs/2305.09573 (2023) - [i13]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. CoRR abs/2307.10312 (2023) - [i12]Noam Benkler, Drisana Mosaphir, Scott Friedman, Andrew Smart, Sonja Schmer-Galunder:
Assessing LLMs for Moral Value Pluralism. CoRR abs/2312.10075 (2023) - 2022
- [c7]Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine A. Heller:
Healthsheet: Development of a Transparency Artifact for Health Datasets. FAccT 2022: 1943-1961 - [i11]Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine A. Heller:
Healthsheet: Development of a Transparency Artifact for Health Datasets. CoRR abs/2202.13028 (2022) - [i10]Shalaleh Rismani, Renee Shelby, Andrew Smart, Edgar W. Jatho III, Joshua A. Kroll, AJung Moon, Negar Rostamzadeh:
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML. CoRR abs/2210.03535 (2022) - [i9]Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N'Mah Yilla, Jess Gallegos, Andrew Smart, Emilio Garcia, Gurleen Virk:
Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction. CoRR abs/2210.05791 (2022) - 2021
- [j1]Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicole:
On the genealogy of machine learning datasets: A critical history of ImageNet. Big Data Soc. 8(2): 205395172110359 (2021) - [c6]Atoosa Kasirzadeh, Andrew Smart:
The Use and Misuse of Counterfactuals in Ethical Machine Learning. FAccT 2021: 228-236 - [c5]Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell:
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. FAccT 2021: 560-575 - [i8]Atoosa Kasirzadeh, Andrew Smart:
The Use and Misuse of Counterfactuals in Ethical Machine Learning. CoRR abs/2102.05085 (2021) - 2020
- [c4]Andrew Smart, Larry James, Ben Hutchinson, Simone Wu, Shannon Vallor:
Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning. AIES 2020: 372-377 - [c3]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. FAT* 2020: 33-44 - [c2]Alex Hanna, Emily Denton, Andrew Smart, Jamila Smith-Loud:
Towards a critical race methodology in algorithmic fairness. FAT* 2020: 501-512 - [i7]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. CoRR abs/2001.00973 (2020) - [i6]Donald Martin Jr., Vinodkumar Prabhakaran, Jill Kuhlberg, Andrew Smart, William S. Isaac:
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics. CoRR abs/2005.07572 (2020) - [i5]Donald Martin Jr., Vinodkumar Prabhakaran, Jill Kuhlberg, Andrew Smart, William S. Isaac:
Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context. CoRR abs/2006.09663 (2020) - [i4]Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicole, Morgan Klaus Scheuerman:
Bringing the People Back In: Contesting Benchmark Machine Learning Datasets. CoRR abs/2007.07399 (2020) - [i3]Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, Margaret Mitchell:
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. CoRR abs/2010.13561 (2020) - [i2]Angie Peng, Jeff Naecker, Ben Hutchinson, Andrew Smart, Nyalleng Moorosi:
Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives. CoRR abs/2012.04216 (2020)
2010 – 2019
- 2019
- [i1]Alex Hanna, Emily Denton, Andrew Smart, Jamila Smith-Loud:
Towards a Critical Race Methodology in Algorithmic Fairness. CoRR abs/1912.03593 (2019)
2000 – 2009
- 2001
- [c1]Paul J. Fortier, Andrew Smart:
Web based E-Government Data Distribution. HICSS 2001
Coauthor Index
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last updated on 2024-10-23 21:25 CEST by the dblp team
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