Researchers from Microsoft have just proposed using a psychological assessment tool called the Defining Issues Test (DIT) to evaluate the moral reasoning capabilities of large language models (LLMs) like GPT-3, ChatGPT, etc.
The DIT presents moral dilemmas and has subjects rate and rank the importance of various ethical considerations related to the dilemma. It allows quantifying the sophistication of moral thinking through a P-score.
In this new paper, the researchers tested prominent LLMs with adapted DIT prompts containing AI-relevant moral scenarios.
Key findings:
- Large models like GPT-3 failed to comprehend prompts and scored near random baseline in moral reasoning.
- ChatGPT, Text-davinci-003 and GPT-4 showed coherent moral reasoning with above-random P-scores.
- Surprisingly, the smaller 70B LlamaChat model outscored larger models in its P-score, demonstrating advanced ethics understanding is possible without massive parameters.
- The models operated mostly at intermediate conventional levels as per Kohlberg's moral development theory. No model exhibited highly mature moral reasoning.
I think this is an interesting framework to evaluate and improve LLMs' moral intelligence before deploying them into sensitive real-world environments - to the extent that a model can be said to possess moral intelligence (or, seem to possess it?).
Here's a link to my full summary with a lot more background on Kohlberg's model (had to read up on it since I didn't study psych). Full paper is here
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