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Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation
Feb. 21, 2024, 5:48 a.m. | Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang, Dawn Song, James Evans
cs.CL updates on arXiv.org arxiv.org
Abstract: Large language models steer their behaviors based on texts generated by others. This capacity and their increasing prevalence in online settings portend that they will intentionally or unintentionally "program" one another and form emergent AI subjectivities, relationships, and collectives. Here, we call upon the research community to investigate these "society-like" properties of interacting artificial intelligences to increase their rewards and reduce their risks for human society and the health of online environments. We use a …
abstract arxiv call capacity cs.cl cs.cy diversity form generated human language language models large language large language models regulation relationships research self-regulation type will
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