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The annual meeting of the Cognitive Science Society is aimed at basic and applied cognitive science research. The conference hosts the latest theories and data from the world's best cognitive science researchers. Each year, in addition to submitted papers, researchers are invited to highlight some aspect of cognitive science. Abstraction enables humans to distill a cascade of sensory experiences into a useful format for making sense of the world and generalizing to new contexts.
In developing theories of how these various forms of abstraction are discovered and used, cognitive scientists have proposed a multitude of representational formats with different properties to capture behavioral data and neural activity. However, because abstraction manifests in human cognition and behavior in so many ways, individual communities within cognitive science have generally studied these specific forms of abstraction under domain-specific representational assumptions.
The goal of this workshop is to facilitate the search for unifying principles governing how humans learn, discover, and use abstractions in different domains, by providing a venue for the exchange of theoretical and empirical insights between research communities. What are the current limits of AI models in explaining human cognition and behavior? How might approaches from the cognitive sciences drive the development of more robust and reliable AI systems? The goal of this workshop is bring together researchers across cognitive science and artificial intelligence AI to engage with these questions and identify opportunities to work together to advance progress in both fields.
In particular, we propose Cognitive-AI Benchmarking as a particularly promising strategy that is, the community-coordinated establishment of common benchmarks, tools, and best practices for model-human comparisons across diverse and ecologically relevant domains and tasks.
