Creating a large language model of a philosopher

Author:

Schwitzgebel Eric1ORCID,Schwitzgebel David2ORCID,Strasser Anna34ORCID

Affiliation:

1. Department of Philosophy University of California Riverside California USA

2. Institut Jean Nicod, École Normale Supérieure, Université Paris Sciences et Lettres Paris France

3. Faculty of Philosophy Ludwig‐Maximilians‐Universität München München Germany

4. DenkWerkstatt Berlin Berlin Germany

Abstract

Can large language models produce expert‐quality philosophical texts? To investigate this, we fine‐tuned GPT‐3 with the works of philosopher Daniel Dennett. To evaluate the model, we asked the real Dennett 10 philosophical questions and then posed the same questions to the language model, collecting four responses for each question without cherry‐picking. Experts on Dennett's work succeeded at distinguishing the Dennett‐generated and machine‐generated answers above chance but substantially short of our expectations. Philosophy blog readers performed similarly to the experts, while ordinary research participants were near chance distinguishing GPT‐3's responses from those of an “actual human philosopher”.

Funder

University of California

Publisher

Wiley

Subject

Linguistics and Language,Philosophy,Language and Linguistics

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