The Ghost in the Quantum Turing Machine (1306.0159v2)

Abstract: In honor of Alan Turing's hundredth birthday, I unwisely set out some thoughts about one of Turing's obsessions throughout his life, the question of physics and free will. I focus relatively narrowly on a notion that I call "Knightian freedom": a certain kind of in-principle physical unpredictability that goes beyond probabilistic unpredictability. Other, more metaphysical aspects of free will I regard as possibly outside the scope of science. I examine a viewpoint, suggested independently by Carl Hoefer, Cristi Stoica, and even Turing himself, that tries to find scope for "freedom" in the universe's boundary conditions rather than in the dynamical laws. Taking this viewpoint seriously leads to many interesting conceptual problems. I investigate how far one can go toward solving those problems, and along the way, encounter (among other things) the No-Cloning Theorem, the measurement problem, decoherence, chaos, the arrow of time, the holographic principle, Newcomb's paradox, Boltzmann brains, algorithmic information theory, and the Common Prior Assumption. I also compare the viewpoint explored here to the more radical speculations of Roger Penrose. The result of all this is an unusual perspective on time, quantum mechanics, and causation, of which I myself remain skeptical, but which has several appealing features. Among other things, it suggests interesting empirical questions in neuroscience, physics, and cosmology; and takes a millennia-old philosophical debate into some underexplored territory.

• The paper introduces Knightian freedom by suggesting that inherent quantum uncertainties in the universe's initial conditions may drive unpredictable human decision-making.
• It leverages the quantum No-Cloning Theorem to argue that uncopyable quantum states, or freebits, challenge traditional deterministic models.
• The study explores implications for AI and neuroscience, highlighting that brain processes might amplify quantum-level uncertainties to shape free will.

An Expert Review of "The Ghost in the Quantum Turing Machine"

The paper "The Ghost in the Quantum Turing Machine" by Scott Aaronson explores a profound exploration of free will interwoven with concepts from quantum mechanics and computational theory. It seeks to provide a nuanced perspective on the age-old philosophical debate of free will versus determinism, using the modern language of physics and computer science.

Aaronson introduces the notion of "Knightian freedom," a form of unpredictability that transcends probabilistic randomness, akin to the uncertainties introduced by Knightian uncertainty in economics. He scrutinizes the potential for such unpredictability within the universe's initial quantum conditions—states that inherently resist cloning as per the quantum No-Cloning Theorem, which may impact predictability in complex systems like human brains.

Key Concepts and Arguments

1. Knightian Freedom and Predictability: Aaronson contends that true unpredictability in human decisions could arise from Knightian uncertainty embedded in quantum mechanics. Unlike deterministic systems or those governed by known probabilities, Knightian freedom suggests decisions may be influenced by uncontrollable and unquantifiable aspects of initial quantum states.
2. Quantum Mechanics and Initial Conditions: By considering quantum states at the universe's inception, Aaronson suggests these may hold freebits—qubits with inherent Knightian uncertainty. The No-Cloning Theorem is pivotal here, highlighting the fundamental limits in copying quantum states, implying unpredictability in any system influenced by such states.
3. Freebit Picture: Aaronson presents a "freebit picture," suggesting some choices have Knightian freedom due to unknown quantum states linked to the universe's origin, necessitating an empirical lens to delineate between predictable mechanistic systems and those exhibiting Knightian freedom.
4. Freedom from the Inside Out (FIO): This perspective implies the absence of intrinsic causal directionality within the spacetime block of the universe, allowing for potential backward causation of some states, aligning with the freebit notion. Aaronson hypothesizes that freebits may furnish the randomness necessary for human unpredictability, opposing a deterministic framework.
5. Implications for AI and Neuroscience: Aaronson explores implications for brain uploading and AI, noting that predictability of behavior might be fundamentally limited by Knightian uncertainty. This challenges attempts to perfectly emulate or predict human behavior using AI.

Empirical and Philosophical Implications

• Empirical Questions: A central assertion is that neuroscience must determine whether brain processes can amplify quantum-level events into macroscopic effects, while physics explores if quantum states can indeed exhibit Knightian uncertainty. These are profound empirical questions that, while open-ended, could dramatically reshape understandings of autonomy and decision-making.
• Philosophical Depth: Aaronson addresses the free will debate with a sophisticated mix of philosophy and physics, posing that free will could be a reflective emergence from inherently unpredictable foundational quantum states, contrasted with pure randomness. This positions his work at an intersection of philosophy, physics, and computer science—a rare, interdisciplinary approach that provokes re-evaluation of entrenched philosophical binaries.

Critiques and Future Prospects

While Aaronson provides a compelling argument infused with theoretical innovation, the speculative nature of correlating fundamental quantum uncertainty with free will necessitates empirical validation. His framing raises questions about how Knightian uncertainty can be reconciled with operational models in neuroscience and AI.

Future progress in AI might probe the limits of predictability Aaronson identifies. Similarly, advances in quantum physics could clarify whether foundational quantum states hold secrets to human freedom, potentially augmenting or refuting Aaronson's freebit picture.

In conclusion, Aaronson's paper stands as a rigorous academic endeavor, re-examining free will through a lens that bridges conceptual divides. It urges a collaboration between physics, neuroscience, and AI research to explore the tangible frontiers of predictability and autonomy.