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Original Study
| Published: July 23, 2023
Prediction Machines – Comparative Analysis of Theory of Mind Abilities in Machine Learning Models
Indian Institute of Psychology & Research, Bangalore Google Scholar More about the auther
Indian Institute of Psychology & Research, Bangalore Google Scholar More about the auther
DIP: 18.01.092.20231103
DOI: 10.25215/1103.092
ABSTRACT
With the advent of Machine Learning models in the current global markets, questions pertaining to artificial mental states and Artificial General Intelligence (AGI) come to the forefront. The current study seeks to find support for possible mental states by subjecting three different Machine Learning models – GPT 3.5 (Generative Pre-Trained Transformer), Bard, and GPT 3 – Ada to psychological tests concerning Theory of Mind (ToM). To discern another’s mental state one must be capable of distinguishing oneself as an entity separate from the other. The three models were presented with the Strange Story Task and the Theory of Mind Scale. The idea of artificial ToM by observation and prediction has been posited. As hypothesized, GPT 3.5 significantly outperformed GPT 3 (Ada) and failed to outperform Bard. Further implications and limitations have been discussed.
Keywords
Machine Learning, AI, Theory of Mind, AGI, Natural Language Processing, Cognition
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2023, Fernandes, S.J. & Dhananjaya, T.
Received: May 24, 2023; Revision Received: July 20, 2023; Accepted: July 23, 2023
Article Overview
ISSN 2348-5396
ISSN 2349-3429
18.01.092.20231103
10.25215/1103.092
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Published in Volume 11, Issue 3, July-September, 2023