mlsanityData to 7 Oct 2026

A computational framework for human values

arXiv 2305.02748 ↗First posted 4 May 2023cs.AI cs.CY cs.MAcited by 10

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Abstract (arXiv)

In the diverse array of work investigating the nature of human values from psychology, philosophy and social sciences, there is a clear consensus that values guide behaviour. More recently, a recognition that values provide a means to engineer ethical AI has emerged. Indeed, Stuart Russell proposed shifting AI's focus away from simply ``intelligence'' towards intelligence ``provably aligned with human values''. This challenge -- the value alignment problem -- with others including an AI's learning of human values, aggregating individual values to groups, and designing computational mechanisms to reason over values, has energised a sustained research effort. Despite this, no formal, computational definition of values has yet been proposed. We address this through a formal conceptual framework rooted in the social sciences, that provides a foundation for the systematic, integrated and interdisciplinary investigation into how human values can support designing ethical AI.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 6 of its 42 references that are in the map. First posted on arXiv 4 May 2023.

Builds on

6 of 42 references.

References · 6

  1. 2020Artificial Intelligence, Values and Alignmentcited by 443
  2. 2020Trustworthy AIcited by 62
  3. 2017Acquiring Background Knowledge to Improve Moral Value Predictioncited by 22
  4. 2021Value alignment: a formal approachcited by 18
  5. 2019A Value-based Trust Assessment Model for Multi-agent Systemscited by 4
  6. 2023uHelp: intelligent volunteer search for mutual help communitiescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 4.

10 papers.