2023/10/19 by Cedegao E. Zhang, Zhang, Cedegao E., Katherine M. Collins +5 · 2 citations
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Cognitive Science and Mapping #FOS: Biological sciences #FOS: Computer and information sciences #Neurons and Cognition (q-bio.NC) #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2310.13021
openalex publication_date 2023/10/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Mathematics is one of the most powerful conceptual systems developed and used by the human species. Dreams of automated mathematicians have a storied history in artificial intelligence (AI). Rapid progress in AI, particularly propelled by advances in large language models (LLMs), has sparked renewed, widespread interest in building such systems. In this work, we reflect on these goals from a cognitive science perspective. We call attention to several classical and ongoing research directions from cognitive science, which we believe are valuable for AI practitioners to consider when seeking to build truly human (or superhuman)-level mathematical systems. We close with open discussions and questions that we believe necessitate a multi-disciplinary perspective -- cognitive scientists working in tandem with AI researchers and mathematicians -- as we move toward better mathematical AI systems which not only help us push the frontier of the mathematics, but also offer glimpses into how we as humans are even capable of such great cognitive feats.