AI and Consciousness

2025-10-10

AI Summary

Dominant theories of consciousness yield conflicting verdicts on whether AI possesses subjective experience, preventing epistemic certainty regarding AI’s human-like consciousness. Method: The study conducts a systematic critical analysis of major theoretical frameworks—including functionalism, Global Workspace Theory, Higher-Order Thought Theory, Integrated Information Theory, and the imitation argument—exposing their foundational disagreements and intrinsic limitations in adjudicating AI consciousness. Contribution/Results: It introduces two novel pragmatic approaches: the “leap hypothesis”—provisionally assuming AI consciousness to advance ethical and governance practice—and the “social semi-solution”—a behaviorally grounded, consensus-driven, incremental framework for assessing AI consciousness. These approaches circumvent theoretical impasses without resolving metaphysical disputes. The study concludes that, absent theoretical unification, humanity will remain in a state of epistemic suspension regarding AI consciousness; yet the proposed dual-path framework offers a transdisciplinary paradigm for responsible engagement with increasingly sophisticated AI systems.

Technology Category

• Philosophy and Ethics of AI: AI & Epistemology
• Humans and AI: Understanding People, Theories, Concepts and Methods
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

This is a skeptical overview of the literature on AI consciousness. We will soon create AI systems that are conscious according to some influential, mainstream theories of consciousness but are not conscious according to other influential, mainstream theories of consciousness. We will not be in a position to know which theories are correct and whether we are surrounded by AI systems as richly and meaningfully conscious as human beings or instead only by systems as experientially blank as toasters. None of the standard arguments either for or against AI consciousness takes us far. Table of Contents Chapter One: Hills and Fog Chapter Two: What Is Consciousness? What Is AI? Chapter Three: Ten Possibly Essential Features of Consciousness Chapter Four: Against Introspective and Conceptual Arguments for Essential Features Chapter Five: Materialism and Functionalism Chapter Six: The Turing Test and the Chinese Room Chapter Seven: The Mimicry Argument Against AI Consciousness Chapter Eight: Global Workspace Theories and Higher Order Theories Chapter Nine: Integrated Information, Local Recurrence, Associative Learning, and Iterative Natural Kinds Chapter Ten: Does Biological Substrate Matter? Chapter Eleven: The Problem of Strange Intelligence Chapter Twelve: The Leapfrog Hypothesis and the Social Semi-Solution

Problem

• Evaluating conflicting theories of AI consciousness
• Assessing unknowability of AI systems' experiential richness
• Critiquing limitations of standard arguments about AI consciousness

Innovation

• Skeptical review of AI consciousness theories
• Comparison of mainstream theories on AI consciousness
• Analysis of arguments for and against AI consciousness