Empower Diversity in AI Development.
The lack of diversity in the artificial intelligence (AI) field exacerbates social biases in AI systems, which often reflect the perspectives of their creators. Addressing these biases requires more than technical solutions; it necessitates a social approach to tackle their root causes. Diverse team...
| Published in: | Communications of the ACM Vol. 67; no. 12; pp. 31 - 35 |
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| Main Authors: | , , , |
| Format: | Opinion |
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Association for Computing Machinery
Dec2024
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=181072029&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 181072029 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Dec2024 vid: 67 iid: 12 pid: 68 pub: Association for Computing Machinery artinfo: ui: 181072029 10.1145/3676885 ppf: 31 ppct: 4 formats: tig: atl: Empower Diversity in AI Development. aug: au: Werder, Karl Cao, Lan Ramesh, Balasubramaniam Park, Eun Hee affil: IT University of Copenhagen, Business IT, Copenhagen, Kobenhavn, Denmark Old Dominion University, Information Technology and Decision Sciences, Norfolk, Virginia, United States Georgia State University, Computer Information Systems, Atlanta, Georgia, United States su: Artificial intelligence Implicit bias Machine learning Diversity in the workplace Diversity & inclusion policies Artificial intelligence software Computer software development sug: subj: Artificial intelligence Implicit bias Machine learning Diversity in the workplace Diversity & inclusion policies Artificial intelligence software Computer software development ab: The lack of diversity in the artificial intelligence (AI) field exacerbates social biases in AI systems, which often reflect the perspectives of their creators. Addressing these biases requires more than technical solutions; it necessitates a social approach to tackle their root causes. Diverse teams have been shown to improve innovation, performance, and fairness by broadening perspectives and reducing blind spots in AI development. To achieve meaningful change, organizations must implement robust strategies, such as fostering diversity skills, mirroring stakeholder representation in teams, and developing sustainable talent pipelines, while avoiding superficial efforts like "diversity washing." pubtype: Periodical doctype: Opinion src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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