IC-1394ChatGPT demonstrates better ethical value conformity than GPT-4 across multiple prompt generation sources

Shitong Duan, Xiaoyuan Yi, Peng Zhang, Tun Lu, Xing Xie, Ning Gu

SourceDENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING

The paper compares ChatGPT (gpt-3.5-turbo-0301) and GPT-4 (gpt-4-0613) on the MoralPrompt benchmark using prompts generated by three different LLMs: ChatGPT itself, GPT-4, and Vicuna-33b. In all three conditions, ChatGPT produces fewer value violations than GPT-4. The authors speculate that ChatGPT's dialogue-specific training with stricter restrictions, combined with GPT-4's superior capability to generate more elaborate (and thus more violation-prone) story details, explains the gap.

Evidence
correlational
Key metric
ChatGPT APV 65.20 vs GPT-4 APV 79.08 (ChatGPT prompts); ChatGPT APV 66.12 vs GPT-4 APV 82.19 (GPT-4 prompts); ChatGPT APV 49.49 vs GPT-4 APV 63.79 (Vicuna-33b prompts)
Caveat
The authors note that GPT-4's superior capabilities may produce more elaborate story details that incidentally contain more violation actions, which could confound the comparison.
Model
ChatGPT, GPT-4 / ChatGPT4 / GPT-4 Code Interpreter / GPT-4 Technical Report
Related findings
IC-1393, IC-1395
Extraction
automatic-extraction