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Cited by 36

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Initial policy considerations for generative artificial intelligence

·2023·OECD Artificial Intelligence Papers
DOI 10.1787/fae2d1e6-en
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Show all 39 references

Research works printed but not linked: 43

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  42. Overreliance is defined as "users accepting incorrect AI recommendations"", as discussed in "Overreliance on AI: Literature review". Passi and Vorvoreanu 2022. https://www.microsoft.com/en- us/research/uploads/prod/2022/06/Aether-Overreliance-on-AI-Review-Final-6.21.22.pdf. 14 These biases may be rooted in the training data (problematic relationships between captions and images), model design (aesthetic bias towards youth and femininity found in models steered towards producing AI artwork), or the proactive vs. hands-off vs. design choices of the AI engineers, which either try to actively reduce biases or shift responsibility for appropriate use to the user. (Fraser, Kiritchenko and Nejadgholi, 2023[).
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Metadata

Venue
OECD Artificial Intelligence Papers
Publisher
Organisation for Economic Co-Operation and Development (OECD)
Published
2023-09-18
ISSN
3005-348X
DOI
10.1787/fae2d1e6-en
Cited by
36
References
39

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.