Abstract:This paper introduces function alignment, a novel theory of mind and intelligence that is both intuitively compelling and structurally grounded. It explicitly models how meaning, interpretation, and analogy emerge from interactions among layered representations, forming a coherent framework capable not only of modeling minds but also of serving as a blueprint for building them. One of the key theoretical insights derived from function alignment is bounded interpretability, which provides a unified explanation for previously fragmented ideas in cognitive science, such as bounded rationality, symbol grounding, and analogy-making. Beyond modeling, the function alignment framework bridges disciplines often kept apart, linking computational architecture, psychological theory, and even contemplative traditions such as Zen. Rather than building on any philosophical systems, it offers a structural foundation upon which multiple ways of understanding the mind may be reconstructed.
Abstract:This first international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and digital arts to explore the role of XAI for the Arts. Workshop held at the 15th ACM Conference on Creativity and Cognition (C&C 2023).