تقرير
Algorithmic Collusion by Large Language Models
| العنوان: | Algorithmic Collusion by Large Language Models |
|---|---|
| المؤلفون: | Fish, Sara, Gonczarowski, Yannai A., Shorrer, Ran I. |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science Quantitative Finance |
| مصطلحات موضوعية: | Economics - General Economics, Computer Science - Artificial Intelligence, Computer Science - Computer Science and Game Theory |
| الوصف: | The rise of algorithmic pricing raises concerns of algorithmic collusion. We conduct experiments with algorithmic pricing agents based on Large Language Models (LLMs), and specifically GPT-4. We find that (1) LLM-based agents are adept at pricing tasks, (2) LLM-based pricing agents autonomously collude in oligopoly settings to the detriment of consumers, and (3) variation in seemingly innocuous phrases in LLM instructions ("prompts") may increase collusion. These results extend to auction settings. Our findings underscore the need for antitrust regulation regarding algorithmic pricing, and uncover regulatory challenges unique to LLM-based pricing agents. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2404.00806 |
| رقم الأكسشن: | edsarx.2404.00806 |
| قاعدة البيانات: | arXiv |
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