Making AI intelligible : : philosophical foundations / / Herman Cappelen and Josh Dever.

• Superior document: Oxford scholarship online
• VerfasserIn: Cappelen, Herman,; Dever, Josh,
• TeilnehmendeR: Dever, Josh,
• Place / Publishing House: Oxford : : Oxford University Press,, 2021.
• Year of Publication: 2021
• Edition: First edition.
• Language: English
• Series: Oxford scholarship online.
• Physical Description: 1 online resource (192 pages).
• Notes: This edition also issued in print: 2021.; "This is an open access publication, available online and distributed under the terms of a Creative Commons Attribution - Non Commercial - No Derivatives 4.0 International licence (CC BY-NC-ND 4.0)"--Home page.

Can humans and artificial intelligences share concepts and communicate? This book 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.

Table of Contents

Cover -- Making AI Intelligible Philosophical Foundations: Philosophical Foundations -- Copyright -- Contents -- Part I: Introduction and Overview -- Chapter 2: Alfred (the Dismissive Sceptic): Philosophers, Go Away! -- A Dialogue with Alfred (the Dismissive Sceptic) -- Part II: A Proposal for how to Attribute Content to AI -- Chapter 3: Terminology: Aboutness, Representation, and Metasemantics -- Loose Talk, Hyperbole, or 'Derived Intentionality'? -- Aboutness and Representation -- AI, Metasemantics, and the Philosophy of Mind -- Chapter 4: Our Theory: De-Anthropocentrized Externalism -- First Claim: Content for AI Systems Should Be Explained Externalistically -- Second Claim: Existing Externalist Accounts of Content Are Anthropocentric -- Third Claim: We Need Meta-Metasemantic Guidance -- A Meta-Metasemantic Suggestion: Interpreter-centric Knowledge-Maximization -- Chapter 5: Application: The Predicate 'High Risk' -- The Background Theory: Kripke-Style Externalism -- Starting Thought: SmartCredit Expresses High Risk Contents Because of its Causal History -- Anthropocentric Abstraction of 'Anchoring' -- Schematic AI-Suitable Kripke-Style Metasemantics -- Complications and Choice Points -- Taking Stock -- Appendix to Chapter 5: More on Reference Preservation in ML Systems -- Chapter 6: Application: Names and the Mental Files Framework -- Does SmartCredit Use Names? -- The Mental Files Framework to the Rescue? -- Epistemically Rewarding Relations for Neural Networks? -- Case Studies, Complications, and Reference Shifts -- Taking Stock -- Chapter 7: Application: Predication and Commitment -- Predication: Brief Introduction to the Act Theoretic View -- Turning to AI and Disentangling Three Different Questions -- The Metasemantics of Predication: A Teleofunctionalist Hypothesis -- Some Background: Teleosemantics and Teleofunctional Role.

Predication in AI -- AI Predication and Kinds of Teleology -- Why Teleofunctionalism and Not Kripke or Evans? -- Teleofunctional Role and Commitment (or Assertion) -- Theories of Assertion and Commitment for Humans and AI -- Part III: Conclusion -- Chapter 8: Four Concluding Thoughts -- Dynamic Goals -- A Story of Neural Networks Taking Over in Ways We Cannot Understand -- Why This Story is Disturbing and Relevant -- Taking Stock and General Lessons -- The Extended Mind and AI Concept Possession -- Background: The Extended Mind and Active Externalism -- The Extended Mind and Conceptual Competency -- From Experts Determining Meaning to Artificial Intelligences Determining Meaning -- Some New Distinctions: Extended Mind Internalist versus Extended Mind Externalists -- Kripke, Putnam, and Burge as Extended Mind Internalists -- Concept Possession, Functionalism, and Ways of Life -- Implications for the View Defended in This Book -- An Objection Revisited -- Reply to the Objection -- What Makes it a Stop Sign Detector? -- Adversarial Perturbations -- Explainable AI and Metasemantics -- Bibliography -- Index.