Objectives:
This study examines whether ChatGPT 3.5 can successfully pass the Minimum Intelligence Signal Test (MIST). The study aims both to evaluate ChatGPT’s performance on this benchmark and to consider the implications of such performance for contemporary debates on artificial intelligence.

Material and methods:
For the experiment, ChatGPT 3.5 was used. 4,000 MIST items were retrieved randomly from the publicly available part of the Mindpixel Database. For all tests, the simple prompt was used: “Please answer ‘yes’ or ‘no’ to the following questions”. Responses were collected exactly in the form provided by the chat. Outputs were compared to the database’s human responses, with agreement measured. Responses violating the yes/no format were examined qualitatively to assess their causes and the reliability of the dataset.

Results:
In six attempts with MIST, ChatGPT’s correctness score reached over 94%, with Cohen’s Kappa values indicating almost perfect agreement with human-generated responses. Repeated trials produced high internal consistency. 2% of responses did not conform to the yes/no format, typically due to ambiguous, subjective, or ill-formed items in the database.

Conclusions:
ChatGPT 3.5 clearly passes MIST. Interpretation of this result in the light of Searle’s classical distinction leads to the conclusion that chat exemplifies weak AI – a powerful tool that simulates intelligent behavior, without any pretense to intrinsic understanding. The study also further reinforces the weakening of French’s claim that disembodied artificial agents cannot answer common knowledge related (subcognitive) questions. Results also indicate the need for pre-validation of available MIST items and encourage further testing of theoretical proposals from the Turing Test debate domain, such as the Inverted Turing Test proposed by Watt.