Making AI Intelligible Philosophical Foundations 1st edition by Herman Cappelen, Josh Dever 0192647563 9780192647566

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ISBN-10 :  0192647563 

ISBN-13 :  9780192647566

Author : Herman Cappelen, Josh Dever 

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.

Making AI Intelligible: Philosophical Foundations 1st Table of contents:

Part I: Introduction and Overview
1. Introduction
The Goals of This Book: The Role of Philosophy in AI Research
Abstraction: The Relevant Features of the Systems We Will be Concerned with in This Book
The Ubiquity of AI Decision-Making
The Central Questions of this Book
‘Content? That’s So 1980’
What This Book is Not About: Consciousness and Whether ‘Strong AI’ is Possible
Connection to the Explainable AI Movement
Broad and Narrow Questions about Representation
Our Interlocutor: Alfred, The Dismissive Sceptic
Who is This Book for?
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
3. Terminology: Aboutness, Representation, and Metasemantics
Loose Talk, Hyperbole, or ‘Derived Intentionality’?
Aboutness and Representation
AI, Metasemantics, and the Philosophy of Mind
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
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
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
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
8. Four Concluding Thoughts
Dynamic Goals
The Extended Mind and AI Concept Possession
An Objection Revisited
Explainable AI and Metasemantics

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