Mimetic vs Anchored Value Alignment in Artificial Intelligence
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Abstract (arXiv)
"Value alignment" (VA) is considered as one of the top priorities in AI research. Much of the existing research focuses on the "A" part and not the "V" part of "value alignment." This paper corrects that neglect by emphasizing the "value" side of VA and analyzes VA from the vantage point of requirements in value theory, in particular, of avoiding the "naturalistic fallacy"--a major epistemic caveat. The paper begins by isolating two distinct forms of VA: "mimetic" and "anchored." Then it discusses which VA approach better avoids the naturalistic fallacy. The discussion reveals stumbling blocks for VA approaches that neglect implications of the naturalistic fallacy. Such problems are more serious in mimetic VA since the mimetic process imitates human behavior that may or may not rise to the level of correct ethical behavior. Anchored VA, including hybrid VA, in contrast, holds more promise for future VA since it anchors alignment by normative concepts of intrinsic value.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Oct 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 1.
3 papers.
- 2023The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Modelscited by 7
- 2025On the Inevitability of Left-Leaning Political Bias in Aligned Language Modelscited by 4
- 2021When is it permissible for artificial intelligence to lie? A trust-based approachcited by 2
- 2025On the Inevitability of Left-Leaning Political Bias in Aligned Language Models21 Jul 2025
- 2023The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Models3 Oct 2023
- 2021When is it permissible for artificial intelligence to lie? A trust-based approach9 Mar 2021