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Published as a conference paper at NeurIPS 2026

Position: Neurosymbolic AI is a strong technical foundation for trustworthy, deployable AI by design

Chandler Squires, Yaqi Xie, Simon Stepputtis, Katia Sycara, Pradeep Ravikumar

Abstract

As AI becomes more widely adopted, this technology has started to reach a new stage of maturity, with new expectations. In many domains, features like interpretability, controllability, and reliability can no longer be treated as secondary considerations, but must be treated as primary concerns. We argue that the currently dominant *incremental refinement* strategy should be complemented by a more design-oriented *first principles* strategy, and that *neurosymbolic AI* provides one of the most coherent and practically promising technical foundations for this strategy. In particular, we describe certain technical capabilities provided by neurosymbolic AI, including knowledge integration, conceptual alignment, modifiability, and structured generalization, and argue that these capabilities are crucial for building AI that is trustworthy and deployable by design.

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