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Know Thyself, Improve Thyself: Personalized LLMs for Self-Knowledge and Moral Enhancement.

Authors :
Giubilini, Alberto
Porsdam Mann, Sebastian
Voinea, Cristina
Earp, Brian
Savulescu, Julian
Source :
Science & Engineering Ethics; Dec2024, Vol. 30 Issue 6, p1-15, 15p
Publication Year :
2024

Abstract

In this paper, we suggest that personalized LLMs trained on information written by or otherwise pertaining to an individual could serve as artificial moral advisors (AMAs) that account for the dynamic nature of personal morality. These LLM-based AMAs would harness users’ past and present data to infer and make explicit their sometimes-shifting values and preferences, thereby fostering self-knowledge. Further, these systems may also assist in processes of self-creation, by helping users reflect on the kind of person they want to be and the actions and goals necessary for so becoming. The feasibility of LLMs providing such personalized moral insights remains uncertain pending further technical development. Nevertheless, we argue that this approach addresses limitations in existing AMA proposals reliant on either predetermined values or introspective self-knowledge. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13533452
Volume :
30
Issue :
6
Database :
Complementary Index
Journal :
Science & Engineering Ethics
Publication Type :
Academic Journal
Accession number :
181104597
Full Text :
https://doi.org/10.1007/s11948-024-00518-9