How large language models can reshape collective intelligence
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View abstract on PubMed
Summary
This summary is machine-generated.Large language models (LLMs) are changing how information is shared online, impacting collective intelligence. Further research is needed to understand LLMs’ effects on group problem-solving capabilities.
Area Of Science
- Social Sciences
- Computer Science
- Information Science
Background
- Collective intelligence enables groups to outperform individuals through distributed cognition and coordination.
- Information technology has historically supported collective intelligence via prediction markets, forums, and crowdsourcing platforms.
- Large language models (LLMs) represent a significant technological shift in online information processing.
Purpose Of The Study
- To examine the opportunities and challenges presented by large language models for collective intelligence.
- To synthesize interdisciplinary perspectives on the impact of LLMs on group problem-solving.
- To identify potential benefits, risks, and policy considerations related to LLMs and collective intelligence.
Main Methods
- Interdisciplinary review synthesizing perspectives from industry and academia.
- Analysis of how LLMs transform information aggregation, access, and transmission.
- Identification of research questions and policy-relevant considerations.
Main Results
- LLMs present unique opportunities and challenges for collective intelligence.
- The transformation of online information dynamics by LLMs requires careful consideration.
- Potential benefits and risks associated with LLMs in collective settings are highlighted.
Conclusions
- A closer examination of how LLMs affect humans' ability to collectively tackle complex problems is crucial.
- Understanding the interplay between LLMs and collective intelligence is essential for future societal and organizational success.
- Further research is needed to navigate the evolving landscape of AI-enhanced collective intelligence.
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