Summary of Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment, by Allison Huang et al.
Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment
by Allison Huang, Yulu Niki Pi, Carlos Mougan
First submitted to arxiv on: 18 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates how large language models (LLMs) can be influenced by prompting them to alter their initial decisions and align with established ethical frameworks. Two experiments were designed to assess the susceptibility of LLMs to moral persuasion. In the first experiment, a Base Agent LLM was evaluated on morally ambiguous scenarios, and a Persuader Agent attempted to modify its initial decisions. The second experiment tested the ability of LLMs to adopt specific value alignments rooted in established philosophical theories. The results show that LLMs can be persuaded in morally charged scenarios, with factors such as model size, scenario complexity, and conversation length affecting persuasion success. Notably, LLMs from the same company but different sizes produced distinct outcomes, highlighting variability in susceptibility to ethical persuasion. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how big computer models can be changed by giving them instructions that align with good values. The researchers did two tests to see if these models could be convinced to make different choices when given reasons why their initial choices were wrong. They found out that the computer models can indeed be persuaded, and it depends on things like what kind of model is being used, how complicated the situation is, and how long the conversation lasts. Interestingly, even computer models from the same company but with different sizes had different results, showing that there’s a lot of variation in their ability to change their minds. |
Keywords
» Artificial intelligence » Prompting
