AI-enhanced Collective Intelligence
<|reference_start|>AI-enhanced Collective Intelligence: Current societal challenges exceed the capacity of humans operating either alone or collectively. As AI evolves, its role within human collectives will vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, together, can surpass the collective intelligence of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from complex network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising cognition, physical, and information layers. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. We explore how agents' diversity and interactions influence the system's collective intelligence and analyze real-world instances of AI-enhanced collective intelligence. We conclude by considering potential challenges and future developments in this field.<|reference_end|>
@article{cui2024ai-enhanced,
    title={AI-enhanced Collective Intelligence},
    author={Hao Cui and Taha Yasseri},
    journal={arXiv preprint arXiv:2403.10433},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.10433},
    primaryClass={cs.CY cs.AI}
}