Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT

• URL: http://arxiv.org/abs/2305.04518v1
• Date: Mon, 8 May 2023 07:28:16 GMT
• Title: Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT
• Authors: Guo Lin and Yongfeng Zhang
• Abstract summary: An AGR comprises both conversationality and universality to engage in natural dialogues and generate recommendations across various domains. We propose ten fundamental principles that an AGR should adhere to, each with its corresponding testing protocols. We assess whether ChatGPT, a sophisticated LLM, can comply with the proposed principles by engaging in recommendation-oriented dialogues with the model while observing its behavior.
• Score: 33.424692414746836
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study investigates the feasibility of developing an Artificial General Recommender (AGR), facilitated by recent advancements in Large Language Models (LLMs). An AGR comprises both conversationality and universality to engage in natural dialogues and generate recommendations across various domains. We propose ten fundamental principles that an AGR should adhere to, each with its corresponding testing protocols. We proceed to assess whether ChatGPT, a sophisticated LLM, can comply with the proposed principles by engaging in recommendation-oriented dialogues with the model while observing its behavior. Our findings demonstrate the potential for ChatGPT to serve as an AGR, though several limitations and areas for improvement are identified.

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