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A Bibliometric View of AI Ethics Development (2403.05551v1)

Published 8 Feb 2024 in cs.CY

Abstract: AI Ethics is a nascent yet critical research field. Recent developments in generative AI and foundational models necessitate a renewed look at the problem of AI Ethics. In this study, we perform a bibliometric analysis of AI Ethics literature for the last 20 years based on keyword search. Our study reveals a three-phase development in AI Ethics, namely an incubation phase, making AI human-like machines phase, and making AI human-centric machines phase. We conjecture that the next phase of AI ethics is likely to focus on making AI more machine-like as AI matches or surpasses humans intellectually, a term we coin as "machine-like human".

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Authors (4)
  1. Di Kevin Gao (3 papers)
  2. Andrew Haverly (3 papers)
  3. Sudip Mittal (66 papers)
  4. Jingdao Chen (16 papers)

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