Exploring the psychology of LLMs’ moral and legal reasoning
N/D
Autores
Nunes, José Luiz
Engelmann, Neele
Wiegmann, Alex
Araújo, Marcelo de
Orientador
Co-orientadores
Citações na Scopus
Tipo de documento
Artigo Científico
Data
2024
Título da Revista
ISSN da Revista
Título do Volume
Resumo
Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models reason about moral and legal issues. In this paper, we employ the methods of experimental psychology to probe into this question. We replicate eight studies from the experimental literature with instances of Google's Gemini Pro, Anthropic's Claude 2.1, OpenAI's GPT-4, and Meta's Llama 2 Chat 70b. We find that alignment with human responses shifts from one experiment to another, and that models differ amongst themselves as to their overall alignment, with GPT-4 taking a clear lead over all other models we tested. Nonetheless, even when LLM-generated responses are highly correlated to human responses, there are still systematic differences, with a tendency for models to exaggerate effects that are present among humans, in part by reducing variance. This recommends caution with regards to proposals of replacing human participants with current state-of-the-art LLMs in psychological research and highlights the need for further research about the distinctive aspects of machine psychology
Palavras-chave
Titulo de periódico
Artificial Intelligence
Título de Livro
URL na Scopus
Idioma
en
URL permanente
Notas
Membros da banca
Área do Conhecimento CNPQ
CIENCIAS SOCIAIS APLICADAS