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• W4313458147 abstract "AI/ML increasingly impacts the ability of humans to have a good life. Various sets of indicators exist to measure well-being/the ability to have a good life. Students play an important role in AI/ML discussions. The purpose of our study using an online survey was to learn about the perspectives of undergraduate STEM students on the impact of AI/ML on well-being/the ability to have a good life. Our study revealed that many of the abilities participants perceive to be needed for having a good life were part of the well-being/ability to have a good life indicator lists we gave to participants. Participants perceived AI/ML to have and continue to have the most positive impact on the ability to have a good life for disabled people, elderly people, and individuals with a high income and the least positive impact for people of low income and countries from the global south. Regarding indicators of well-being and the ability to have a good life given to participants, we found a significant techno-positive sentiment. 30% of respondents selected the purely positive box for 28 of the indicators and none did so for the purely negative box. For 52 indicators, the purely negative was below 10% (not counting the 0%) and for 10 indicators, none selected purely negative. Our findings suggest that our questions might be valuable tools to develop an inventory of STEM and other students' perspectives on the implications of AI/ML on the ability to have a good life." @default.
• W4313458147 created "2023-01-06" @default.
• W4313458147 creator A5058080767 @default.
• W4313458147 creator A5059630707 @default.
• W4313458147 date "2023-01-03" @default.
• W4313458147 modified "2023-10-17" @default.
• W4313458147 title "Auditing the impact of artificial intelligence on the ability to have a good life: using well-being measures as a tool to investigate the views of undergraduate STEM students" @default.
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• W4313458147 doi "https://doi.org/10.1007/s00146-022-01618-5" @default.
• W4313458147 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36619527" @default.
• W4313458147 hasPublicationYear "2023" @default.
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