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Fairness, accountability, transparency in AI at scale: lessons from national programs
Abstract
The panel aims to elucidate how different national govenmental programs are implementing accountability of machine learning systems in healthcare and how accountability is operationlized in different cultural settings in legislation, policy and deployment. We have representatives from three different govenments, UAE, Singapore and Maldives who will discuss what accountability of AI and machine learning means in their contexts and use cases. We hope to have a fruitful conversation around FAT ML as it is operationalized ccross cultures, national boundries and legislative constraints.
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Nineteen studies had mentioned human-centered considerations, and raised attention to educate citizens to become socially responsible and ethical users.
“Nineteen studies had mentioned human-centered considerations, and raised attention to educate citizens to become socially responsible and ethical users (Ahmad, Teredesai, & Eckert, 2020).”
From Conceptualizing AI literacy: An exploratory review (2021) · cites this paper as Ahmad, Teredesai, & Eckert, 2020
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Metadata
- Authors
- Ahmad, M. A., Teredesai, A., & Eckert, C.
- Affiliations
- University of Washington Tacoma (US)
- University of Washington (US)
- Venue
- Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency
- Publisher
- ACM
- Published
- 2020-01-27
- Pages
- 690-690
- OpenAlex
- W3214861879
- Cited by
- 23
- References
- 0
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 5 · 2022: 1 · 2021: 4 · 2020: 1
- Type
- conference abstract
- Language
- en
- Open access
- closed
- Locations
- ACM Conference on Fairness, Accountability, and Transparency (FAccT) (publishedVersion)
- University of Washington Tacoma Digital Commons (University of Washington Tacoma) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- fairness, accountability, and transparency, artificial intelligence in healthcare, AI regulation, national AI policy, cross-cultural comparison, Singapore, Maldives
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