Language Models Can Reduce Asymmetry in Information Markets

التفاصيل البيبلوغرافية
العنوان: Language Models Can Reduce Asymmetry in Information Markets
المؤلفون: Rahaman, Nasim, Weiss, Martin, Wüthrich, Manuel, Bengio, Yoshua, Li, Li Erran, Pal, Chris, Schölkopf, Bernhard
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Computer Science - Multiagent Systems, Computer Science - Social and Information Networks
الوصف: This work addresses the buyer's inspection paradox for information markets. The paradox is that buyers need to access information to determine its value, while sellers need to limit access to prevent theft. To study this, we introduce an open-source simulated digital marketplace where intelligent agents, powered by language models, buy and sell information on behalf of external participants. The central mechanism enabling this marketplace is the agents' dual capabilities: they not only have the capacity to assess the quality of privileged information but also come equipped with the ability to forget. This ability to induce amnesia allows vendors to grant temporary access to proprietary information, significantly reducing the risk of unauthorized retention while enabling agents to accurately gauge the information's relevance to specific queries or tasks. To perform well, agents must make rational decisions, strategically explore the marketplace through generated sub-queries, and synthesize answers from purchased information. Concretely, our experiments (a) uncover biases in language models leading to irrational behavior and evaluate techniques to mitigate these biases, (b) investigate how price affects demand in the context of informational goods, and (c) show that inspection and higher budgets both lead to higher quality outcomes.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2403.14443
رقم الأكسشن: edsarx.2403.14443
قاعدة البيانات: arXiv