@inproceedings{
mozikov2024eai,
title={{EAI}: Emotional Decision-Making of {LLM}s in Strategic Games and Ethical Dilemmas},
author={Mikhail Mozikov and Nikita Severin and Valeria Bodishtianu and Maria Glushanina and Ivan Nasonov and Daniil Orekhov and Vladislav Pekhotin and Ivan Makovetskiy and Mikhail Baklashkin and Vasily Lavrentyev and Akim Tsvigun and Denis Turdakov and Tatiana Shavrina and Andrey Savchenko and Ilya Makarov},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=8aAaYEwNR4}
}
One of the urgent tasks of artificial intelligence is to assess the safety and alignment of large language models (LLMs) with human behavior. Conventional verification only in pure natural language processing benchmarks can be insufficient. Since emotions often influence human decisions, this paper examines LLM alignment in complex strategic and ethical environments, providing an in-depth analysis of the drawbacks of our psychology and the emotional impact on decision-making in humans and LLMs. We introduce the novel EAI framework for integrating emotion modeling into LLMs to examine the emotional impact on ethics and LLM-based decision-making in various strategic games, including bargaining and repeated games. Our experimental study with various LLMs demonstrated that emotions can significantly alter the ethical decision-making landscape of LLMs, highlighting the need for robust mechanisms to ensure consistent ethical standards. Our game-theoretic analysis revealed that LLMs are susceptible to emotional biases influenced by model size, alignment strategies, and primary pretraining language. Notably, these biases often diverge from typical human emotional responses, occasionally leading to unexpected drops in cooperation rates, even under positive emotional influence. Such behavior complicates the alignment of multiagent systems, emphasizing the need for benchmarks that can rigorously evaluate the degree of emotional alignment. Our framework provides a foundational basis for developing such benchmarks.
EAI: Emotional Decision-Making of LLMs in Strategic Games and Ethical Dilemmas
Mikhail Mozikov Nikita Severin Valeria Bodishtianu Maria Glushanina Ivan Nasonov Daniil Orekhov Vladislav Pekhotin Ivan Makovetskiy Mikhail Baklashkin Vasily Lavrentyev Akim Tsvigun Denis Turdakov Tatiana Shavrina Andrey Savchenko Ilya Makarov