2022 ACM Conference on Fairness, Accountability, and Transparency 2022
DOI: 10.1145/3531146.3533200
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At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance

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Cited by 24 publications
(13 citation statements)
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“…Both approaches are problematic given the wide variation in the moral beliefs people actually hold. 6 Indeed, since most FATE research in AI is situated in the West, it does not meaningfully engage with the conditions, values, and histories of non-West contexts [41,57,66]. As Birhane and Cummins note in [8], "it is possible that what is considered ethical currently and within certain domains for certain societies will not be received similarly at a different time, in another domain, or for a different society. "…”
Section: As a Basis For Cross-cultural Value Alignmentmentioning
confidence: 99%
“…Both approaches are problematic given the wide variation in the moral beliefs people actually hold. 6 Indeed, since most FATE research in AI is situated in the West, it does not meaningfully engage with the conditions, values, and histories of non-West contexts [41,57,66]. As Birhane and Cummins note in [8], "it is possible that what is considered ethical currently and within certain domains for certain societies will not be received similarly at a different time, in another domain, or for a different society. "…”
Section: As a Basis For Cross-cultural Value Alignmentmentioning
confidence: 99%
“…Cultural harm has been described as the development or use of algorithmic systems that affects cultural stability and safety, such as "loss of communication means, loss of cultural property, and harm to social values" Macro socio-economic harms "Harms associated with the labour and material supply chains of AI technologies, beta testing, and commercial exploitation. " [151] Environmental harms "The energy cost of training machine learning models... [and] harms from intensive water and fuel usage and server farms, consequent chemical and e-waste. " [151] (p. 30) [4].…”
Section: Cultural Harmsmentioning
confidence: 99%
“…[151] Environmental harms "The energy cost of training machine learning models... [and] harms from intensive water and fuel usage and server farms, consequent chemical and e-waste. " [151] (p. 30) [4]. As algorithmic technologies can "foreclose alternative ways of understanding the world and restricting imaginations about possible futures" (p. 162) [164], the nature of their harm can encompass adverse cultural such as systemic erasure [61], eurocentric ideas being exported to Global South [67,129], harmful cultural beliefs [66], such as normalizing a culture of non-consensual sexual activity [123], or proliferating false ideas about cultural groups [68,167].…”
Section: Cultural Harmsmentioning
confidence: 99%
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