An Investigation of Experiences Engaging the Margins in Data-Centric Innovation
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913647753691136 |
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| author | Thompson, Gabriella Haque, Ebtesam Al Blanc, Paulette Styles, Meme Ford, Denae Smith, Angela D. R. Johnson, Brittany |
| author_facet | Thompson, Gabriella Haque, Ebtesam Al Blanc, Paulette Styles, Meme Ford, Denae Smith, Angela D. R. Johnson, Brittany |
| contents | Data-centric technologies provide exciting opportunities, but recent research has shown how lack of representation in datasets, often as a result of systemic inequities and socioeconomic disparities, can produce inequitable outcomes that can exclude or harm certain demographics. In this paper, we discuss preliminary insights from an ongoing effort aimed at better understanding barriers to equitable data-centric innovation. We report findings from a survey of 261 technologists and researchers who use data in their work regarding their experiences seeking adequate, representative datasets. Our findings suggest that age and identity play a significant role in the seeking and selection of representative datasets, warranting further investigation into these aspects of data-centric research and development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07690 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Investigation of Experiences Engaging the Margins in Data-Centric Innovation Thompson, Gabriella Haque, Ebtesam Al Blanc, Paulette Styles, Meme Ford, Denae Smith, Angela D. R. Johnson, Brittany Human-Computer Interaction Data-centric technologies provide exciting opportunities, but recent research has shown how lack of representation in datasets, often as a result of systemic inequities and socioeconomic disparities, can produce inequitable outcomes that can exclude or harm certain demographics. In this paper, we discuss preliminary insights from an ongoing effort aimed at better understanding barriers to equitable data-centric innovation. We report findings from a survey of 261 technologists and researchers who use data in their work regarding their experiences seeking adequate, representative datasets. Our findings suggest that age and identity play a significant role in the seeking and selection of representative datasets, warranting further investigation into these aspects of data-centric research and development. |
| title | An Investigation of Experiences Engaging the Margins in Data-Centric Innovation |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2501.07690 |