Meaningful Long-Term Thought Partnerships of Minds and Machines
K. Collins et al.
What the paper says
Many innovations have come from people working together as partners in thought. These partnerships, however, are not restricted to single encounters. Some of the most meaningful collaborations evolve over weeks, months, or even lifetimes. What are the core computations that enable long-term thought partnerships? Prior work in cognitive science has made initial progress by investigating how people construct mental models of their partners on the fly, establish common ground using language and other modalities, and generate joint plans that lead to successful outcomes. However, it remains unknown what cognitive mechanisms enable such interactions to evolve into genuine partnerships over longer timescales, especially under measures of success that extend beyond task performance. Theoretical and empirical progress on these issues could be instrumental for defining and designing AI systems that may even be capable of establishing long-term thought partnerships with humans. This article outlines several promising avenues for leveraging approaches from cognitive science and AI to study enriching intellectual partnerships.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.