An Investigation into Black and Brown Communities’ Engagement with Data & Technology

Over the years, we have witnessed significant biases in datasets and AI-driven systems. While these biases can impact anyone, there is a heightened risk for disproportionate harm to Black and Brown communities. Despite efforts to address these inequities, a critical gap remains in understanding how Black and Brown communities perceive and interact with data-centric innovations. In this paper, we present findings from a survey of 60 technology users with diverse racial, ethnic, and gender identities. Our findings reveal that while Black and Brown users may frequently contribute data through social media and research participation, discomfort arises when data is used without explicit consent, particularly by for-profit organizations. Transparency, trust, and familiarity with data collection entities and outcomes emerged as key factors influencing engagement. These insights inform our ongoing efforts, as well as the development of ethical, inclusive approaches to data-driven innovation that center marginalized voices and foster equitable outcomes.

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Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2025-10-15
DOI
https://doi.org/10.1609/aies.v8i1.36531
Citations
1
Primary Topic
ICT in Developing Communities
Type
article
Field-Weighted Citation Impact
3.25

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article

An Investigation into Black and Brown Communities’ Engagement with Data & Technology

Angela D. R. Smith, G.H.B. Thompson, Brittany Johnson, Ebtesam Al-Haque
1 citations
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
ICT in Developing Communities
3.25
article

An Investigation into Black and Brown Communities’ Engagement with Data & Technology

Angela D. R. Smith, G.H.B. Thompson, Brittany Johnson, Ebtesam Al-Haque
article en
1 citations

Abstract

Over the years, we have witnessed significant biases in datasets and AI-driven systems. While these biases can impact anyone, there is a heightened risk for disproportionate harm to Black and Brown communities. Despite efforts to address these inequities, a critical gap remains in understanding how Black and Brown communities perceive and interact with data-centric innovations. In this paper, we present findings from a survey of 60 technology users with diverse racial, ethnic, and gender identities. Our findings reveal that while Black and Brown users may frequently contribute data through social media and research participation, discomfort arises when data is used without explicit consent, particularly by for-profit organizations. Transparency, trust, and familiarity with data collection entities and outcomes emerged as key factors influencing engagement. These insights inform our ongoing efforts, as well as the development of ethical, inclusive approaches to data-driven innovation that center marginalized voices and foster equitable outcomes.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 8(1)
George Mason University (US), The University of Texas at Austin (US)
National Science Foundation
Openalex Percentile: Top 6%
ICT in Developing Communities
3.25
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