AIJun 12, 2024

Making AI Intelligible: Philosophical Foundations

arXiv:2406.08134v142 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the theoretical and practical challenge of interpretable AI for improving trust in AI systems that influence human life, though it appears incremental in applying existing philosophical ideas.

The authors tackle the problem of whether humans and AIs can share concepts and communicate, using philosophical foundations to propose models for mutual understanding and justify reliance on AI in decision-making.

Can humans and artificial intelligences share concepts and communicate? 'Making AI Intelligible' shows that philosophical work on the metaphysics of meaning can help answer these questions. Herman Cappelen and Josh Dever use the externalist tradition in philosophy to create models of how AIs and humans can understand each other. In doing so, they illustrate ways in which that philosophical tradition can be improved. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. Many important decisions about human life are now influenced by AI. In giving that power to AI, we presuppose that AIs can track features of the world that we care about (for example, creditworthiness, recidivism, cancer, and combatants). If AIs can share our concepts, that will go some way towards justifying this reliance on AI. This ground-breaking study offers insight into how to take some first steps towards achieving Interpretable AI.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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