Summary of Ai Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-disclosure, by Xi Chen et al.
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
by Xi Chen, Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Chao Du, Xi Cheng, Hangxin Liu, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
First submitted to arxiv on: 26 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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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 A novel approach to developing large language model (LLM)-based AI delegates is presented, which prioritizes balancing privacy protection with disclosure requirements in various social scenarios. The paper conducts a pilot study to investigate user preferences for AI delegates across different social relations and task scenarios, leading to the proposal of a novel AI delegate system that enables privacy-conscious self-disclosure. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this paper, researchers develop an AI delegate system that protects user privacy while still allowing users to disclose private information in certain situations. This is achieved through a pilot study that explores how users want their AI delegates to behave in different social scenarios. |
Keywords
» Artificial intelligence » Large language model
