2023
DOI: 10.1007/s00146-023-01648-7
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A phenomenological perspective on AI ethical failures: The case of facial recognition technology

Abstract: As more and more companies adopt artificial intelligence to increase the efficiency and effectiveness of their products and services, they expose themselves to ethical crises and potentially damaging public controversy associated with its use. Despite the prevalence of AI ethical problems, most companies are strategically unprepared to respond effectively to the public. This paper aims to advance our empirical understanding of company responses to AI ethical crises by focusing on the rise and fall of facial re… Show more

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Cited by 3 publications
(2 citation statements)
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“…Recently, research showed that certain facial recognition technologies were unable to accurately report the gender of dark-skinned women over 20% of the time, compared to 0.8% for light-skinned men. 4 AI photo enhancers have faced similar criticisms of adjusting images to fit Eurocentric beauty standards, such as straightening hair and lightening skin tones. 5 Beauty is incredibly complex, subjective, and influenced by a variety of factors such as geographics, culture, and demographicssomething that AI photo enhancers may fail to encapsulate in their images due to prioritization of features associated with Western beauty standards.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Recently, research showed that certain facial recognition technologies were unable to accurately report the gender of dark-skinned women over 20% of the time, compared to 0.8% for light-skinned men. 4 AI photo enhancers have faced similar criticisms of adjusting images to fit Eurocentric beauty standards, such as straightening hair and lightening skin tones. 5 Beauty is incredibly complex, subjective, and influenced by a variety of factors such as geographics, culture, and demographicssomething that AI photo enhancers may fail to encapsulate in their images due to prioritization of features associated with Western beauty standards.…”
Section: Discussionmentioning
confidence: 99%
“…While not explicitly stated on AI technology websites, initial training datasets are likely limited in diversity. Recently, research showed that certain facial recognition technologies were unable to accurately report the gender of dark‐skinned women over 20% of the time, compared to 0.8% for light‐skinned men 4 . AI photo enhancers have faced similar criticisms of adjusting images to fit Eurocentric beauty standards, such as straightening hair and lightening skin tones 5 .…”
Section: Discussionmentioning
confidence: 99%