Andrew Smart

Orcid: 0000-0002-9816-7348

According to our database1, Andrew Smart authored at least 25 papers between 2001 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
The reanimation of pseudoscience in machine learning and its ethical repercussions.
Patterns, 2024

Socially Responsible Data for Large Multilingual Language Models.
CoRR, 2024

Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning.
CoRR, 2024

Discipline and Label: A WEIRD Genealogy and Social Theory of Data Annotation.
CoRR, 2024

Unsocial Intelligence: a Pluralistic, Democratic, and Participatory Investigation of AGI Discourse.
CoRR, 2024

2023
Assessing LLMs for Moral Value Pluralism.
CoRR, 2023

The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development.
CoRR, 2023

Statistical Methods for Auditing the Quality of Manual Content Reviews.
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.
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.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction.
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.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction.
CoRR, 2022

Healthsheet: Development of a Transparency Artifact for Health Datasets.
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.
Big Data Soc., July, 2021

The Use and Misuse of Counterfactuals in Ethical Machine Learning.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020
Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives.
CoRR, 2020

Bringing the People Back In: Contesting Benchmark Machine Learning Datasets.
CoRR, 2020

Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context.
CoRR, 2020

Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics.
CoRR, 2020

Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Towards a critical race methodology in algorithmic fairness.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning.
Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2001
Web based E-Government Data Distribution.
Proceedings of the 34th Annual Hawaii International Conference on System Sciences (HICSS-34), 2001


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