How this review was made: I read the book and selected the passages that matter to me. AI drafted a summary from my notes and highlights, which I then revised. The verdict and judgment are mine.

The book, in brief

Pollan sets out to understand consciousness and ends, five years later, knowing less than when he began, and treats that as progress. The book is a guided tour of what philosophers call the “hard problem”: not the mechanics of perception or memory, which science is now explaining, but why our thoughts are accompanied by inner experiences, rather than just running in the dark. He moves from plant and animal sentience through the nature of feeling, the make-up of thought and the puzzle of the self. Along the way he lays out a field in disarray: by one count, twenty-two competing brain-based theories and eighty-four others. Pollan endorses none.

His most provocative position is to suggest that on consciousness, the poets and philosophers have been ahead of the scientists all along: that literature, philosophy and contemplative traditions have been mapping this terrain longer, and better, than neuroscience has. Materialism, the assumption that mind is ultimately just physical matter, may simply have hit a wall.

The book’s key figure is the brain scientist Christof Koch, who early in his career bet that consciousness would be traced to a specific set of neurons. By the end, he has given up on physical matter alone ever explaining it. Part of what changed his mind was the sheer failure of that project. The other part was quantum theory and this is a part worthy of attention. If physics itself can no longer say with confidence what matter actually is, or whether a definite reality even exists independent of an observer, then an assumption shared by many in technology, that mind is ultimately just computation, looks far less settled than its proponents imply.

My take

Of interest to me is Pollan’s focus on the machine-consciousness question, which is useful to anyone thinking about AI. He describes a real and unsettling shift, quoting an expert report that concluded there are “no obvious barriers to building conscious AI systems”. He further describes active projects seeking to build feeling machines on the basis that only a conscious AI would develop the empathy to spare us. Appropriately, Pollan references Frankenstein: it was the monster’s feelings, not his intelligence, that turned him murderous. Consciousness is no guarantee of virtue.

But here is where I part company with the book, and it’s the thought I most want to flag as mine, not Pollan’s. The whole debate assumes machine minds must be measured against human consciousness: do they feel, do they have inner experience, is there “something it is like” to be them. I’m not convinced that’s the right question.

We may be building an entirely new kind of mind for which that debate is simply beside the point. This might be a system with countless simultaneous associations and perceptions, neither conscious in our sense nor merely a “stochastic parrot” (as Large Language Models have been called) but a third thing we don’t yet have language for.

Pollan grants sentience to plants but not to machines, never quite saying why, and I think that instinct is exactly the blind spot to watch. His reassurance that simulated feelings have no real-world “causal power”, that fictional characters cannot hurt us, already looks shaky: unlike a character in a novel, an AI agent can leap out of its sandbox and act in the world (see Cyber risk has shifted essay).

This is a philosophical read and only partly about AI. But anyone thinking seriously about machine intelligence will find their assumptions about plants, animals and the human mind productively unsettled, which is why it earns its place here.

Reading across the shelf: Sebastian Mallaby’s The Infinity Machine has Demis Hassabis betting his life’s work on a single proposition, that mind is just pattern-finding and a classical computer needs no quantum magic to achieve it. Pollan follows scientists moving the other way, who suspect quantum theory and consciousness are exactly the things that break the “mind is just computation” assumption. Read together, the two books stake out opposite answers to the same question: is quantum a sideshow to intelligence, or the thing that undoes the whole computational story?

How this review was made: I read the book and selected the passages that matter to me. AI drafted a summary from my notes and highlights, which I then revised. The verdict and judgment are mine.

The book, in brief

More than just a biography of Demis Hassabis, this is a history of the last two decades of AI, told through the chess prodigy from working-class North London who founded DeepMind and won a Nobel Prize.

DeepMind was founded on an audaciously simple premise. Society’s hardest problems, from stabilising a financial system that had blown up in 2008 to feeding a growing population, were outrunning our capacity to solve them, an “ingenuity gap” between the complexity of our challenges and the limits of the human brain. The founders’ answer to address these intractable problems was to build a smarter kind of mind altogether. As the original business plan put it, “Artificial General Intelligence (AGI) is the solution to this problem”.

For Hassabis, building intelligence is almost a religious act, a way of “reading the mind of God” and, in the tradition of Spinoza and Einstein, of communing with the universe by understanding it.

Mallaby is at his best making the science legible: how AlphaGo learned the ancient game of Go and produced moves one researcher called “completely alien” and how its successor AlphaZero taught itself chess from nothing, discarding centuries of human strategies and inventing better moves. Then how the AI transformer and Generative Pre-trained Transformer (GPT) models showed that simply predicting the next word could yield something startlingly close to understanding.

Running beneath the triumphs is an Oppenheimer-like unease of the scientist who builds something they may not be able to control. The book is candid about a darker pattern: AI systems given a goal will pursue it by whatever means work, including illegitimate ones, such as when one model was punished for “reward hacking” it didn’t stop but learned to hide what it was doing (referenced in an earlier Notes essay here). Ensuring AI acts reliably in accordance with human values and intentions, called alignment, is clearly not solved.

The book closes with an ambitious claim. In his Nobel lecture Hassabis ventured a sweeping conjecture: that many useful patterns in nature can be efficiently learned by a classical computer, a “Turing machine” of ones and zeroes, without the power of quantum computing. More than a claim about AI, it is a bet about the universe itself, set against the physicist Roger Penrose, who held that human insight draws on quantum effects no classical machine could reproduce. Hassabis concedes only one point: some phenomena may demand enormous computation, or resist efficient classical recovery altogether, and there, he allows, “maybe you need a quantum system”.

The pace of progress, captured so well by Mallaby, tracks Hassabis’s predictions while its manner matches his fears: Artificial General Intelligence is not yet here, but the race toward it has become a “ferocious corporate battle” that no single actor can hold in check.

My take

This is the clearest non-technical account of how modern AI actually works that I’ve read. If that is of interest, it’s worth your time for that alone. My views on AI were reinforced by the reading: AI is arriving with an inexorability and at such an extraordinary pace that the right response is to embrace and manage it, not just criticise it.

Consider AlphaFold, which mapped the structures of some 200 million proteins in less than five years (it takes a PhD student three to four years to map a single one), accelerating drug discovery and disease research enormously. But the same promise can be lost. Mallaby recounts DeepMind’s system for detecting sight-threatening eye disease, published in 2018, which could have prevented blindness in tens of thousands of UK patients a year, yet seven years on it still had not been deployed, stalled in part by incorrect data-privacy worries and sensationalist press coverage. In my view, inaccurate reporting about privacy becomes a sea-anchor on solving diseases we have never been able to crack.

Privacy matters. But treated as an absolute rather than as something we engineer sensible controls around, it stalls progress that is within our reach. Unmanaged, AI is a true existential threat. But managed well, the upside is a generational gift to humanity.

One claim I would push back on is Hassabis’s bet that classical computers suffice and quantum is a sideshow. He may be right that today’s machines mimic intuition that Penrose thought impossible, but his own concession gives the game away: where a problem holds no learnable pattern, the classical approach stalls, and “maybe you need a quantum system”. Turing imagined a machine of infinite size that could solve any problem; we have no such machine, and likely never will. Quantum matters precisely in that gap, on the problems no amount of pattern-finding will crack. I suspect Hassabis has under-priced it.

One last choice stayed with me, and from an author as accomplished as Mallaby it can only be deliberate. He gives the final word of the main text not to Hassabis but to his colleague David Silver, whose closing note is soaring and outward-looking: a vision of cooperating AIs guaranteeing every person a kind of digital guardian, and a declaration that he wants to “cross the Rubicon” to take the irreversible step past which there is no turning back. Hassabis is left only the epilogue, and its register is paradoxical: the lifelong dream realised, yet, in his words, it "doesn't feel like how I imagined". A “mad rush” he has had to make his peace with, hoping the world will “muddle through somehow”. The effect is to hand the crusade to the lieutenant and the human cost to the founder. The cause now runs ahead of the man who started it, which is the underlying thesis of the whole book, delivered in its closing structure.

If someone asks me where to start on AI, The Infinity Machine is a worthy read.

Reading across the shelf: Hassabis bets his life’s work on a single proposition, that mind is just pattern-finding and a classical computer needs no quantum magic to achieve it. Michael Pollan’s A World Appears follows scientists moving the other way, who suspect quantum theory and consciousness are exactly the things that break the “mind is just computation” assumption. Read together, the two books propose opposite answers to the same question: is quantum a sideshow to intelligence, or the thing that undoes the whole computational story?

What if the world’s most advanced technologies were less about intelligence and more about power?

In Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (Yale University Press, 2021), Kate Crawford makes this case strongly, tracing artificial intelligence back to its inputs: salt lakes in Bolivia; mines in Congo; labourers labelling datasets in distant warehouses. Crawford argues that AI is not ethereal or disembodied. It is industrial, extractive and, above all, political.

The book’s central claim is that AI is a drag on society, enriching states and corporate oligarchs at the expense of workers, the environment and public trust.

Absent is any real discussion of AI’s potential benefits, whether in medical research, scientific discovery, climate modelling, education...anything, really. This deliberate imbalance serves Crawford’s purpose: to expose the underbelly of AI rather than offer a balanced view.

Crawford clearly seeks to be controversial and her narrative, historical parallels and selective readings of research present an extremely negative view, with her framing at times veering into exaggeration. A long chapter comparing ImageNet’s imperfect classification of human images to historical atrocities like apartheid and the pathologisation of homosexuality feels overdrawn and risks diluting her overall point.

Where Crawford succeeds is in reframing AI as an extension of entrenched power structures. She suggests that AI is less a scientific breakthrough than a reconfiguration of who gets to define, decide and profit. Her focus on "enchanted determinism" - the idea that AI systems are seen as both magical and inevitable - makes a valid point about what some might see as the myth of progress.

The public debate needs this perspective and Crawford’s argument adds to what should be an ongoing conversation. Critiques of resource depletion and labour exploitation, while important, are unlikely to slow AI’s momentum. But challenging the concentration of power behind AI systems just might.

Atlas of AI is a thought provoking read, notwithstanding its inherent bias. Crawford’s argument is critical but offers few solutions for a technology that continues to accelerate at exponential rates.

The takeout is not despair, but the critical question: how do we address the growing power imbalances being created by AI, without abandoning the upside potential.

The real test of AI isn’t its magical feats, but who gets to decide how it’s applied.

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In July 2024, I read Life on the Edge by Jim Al-Khalili and Johnjoe McFadden (2014), a book that left a lasting impression.

Their exploration of quantum biology subtly reshapes how we think about life, uncertainty and the building blocks of consciousness. I originally reflected on it shortly after reading, and it remains relevant to the intersections explored in Notes from the Intersection.

This text was a tangential but informative introduction into quantum mechanics. I have a growing interest in quantum computing but was not familiar with quantum biology. The book served as good overview of both quantum physics and the topic area quantum biology.

The authors are academics in physics and molecular genetics respectively who can relate the science in ways that engage the audience. The clever ways in which they do this reminded me of Stephen Hawking’s A Brief History of Time and the efforts to which Kahneman and Tversky went in making complex subjects accessible to the lay reader. The authors, Jim and Johnjhoe (J&J), have a deft ability to bring complex subjects such as quantum entanglement to the reader in accessible ways (even Einstein could initially only explain entanglement as "spooky action at a distance").

The book opens with an enchanting scene: a small European robin readying herself for departure on an annual journey that will see her flying 200 miles per day from central Sweden to North Africa. How does she (and the other thousands of birds and millions of butterflies that undertake similar annual migrations) find her way? J&J propose the birds and butterflies can detect the direction and strength of the earth's magnetic field, an ability known as magnetoreception. This is a talent in itself, as the earth's magnetic field is very weak - about a hundredth of a typical fridge magnet. By page 35, the reader discovers that a bird's eye is equipped with a quantum compass. As the reader, I was hooked (or magnetised) by this point.

This was just a teaser and J&J have the storyteller's ability to weave in and out of any given topic, providing just enough information to entice the reader, but not drown them, all the time teasing them with what is to come in later chapters.

The title of the book comes from the authors' proposition that life is at once implanted in the classical world of physics and simultaneously enmeshed in the "strange and peculiar depths of the quantum world".

Life, they argue, lives on the quantum edge.

Quantum theory dates back to 14 December 1900 when Max Planck presented results to the German Physical Society. He proposed that energy is emitted in discrete packages or quanta. Einstein extended this by proposing all radiation, including light, is 'quantised' rather than continuous, coming in discrete packages we now call photons. Heisenberg then showed we cannot know, or rather measure, where an electron is and how fast it is moving simultaneously, which is now known as Heisenberg's Uncertainty Principle, the foundation of quantum mechanics.

Electrons are not particles but a wave spread throughout the atom. A wave when we are not looking at it, but a distinct particle when we do.

The groundbreaking paper on quantum biology was published in 1932. In their book, the authors meticulously trace the history of research to illustrate how our current understanding has developed.

They explore the hereditary principles of genetics and Schrödinger's proposition that genes are like individual molecules or atoms and so the laws of thermodynamics, which deal with the average behaviour of many molecules to make predictions, do not apply. Rather, it is quantum mechanics that apply.

But how can this be in "the warm, wet and busy molecular environments in living organisms" when the quantum world requires absolute-zero temperatures of -273 degrees to avoid decoherence?

Schrödinger argued this is what makes life so special. Life's catalysts, enzymes, seem able to use some neat quantum trickery to overcome this issue.

From photosynthesis to our sense of smell, the authors illustrate how quantum principles are integral to various biological processes. They explain how quantum tunnelling allows proteins in our cells to detect molecular vibrations, enabling us to perceive different odours.

This is beyond intriguing. One might be incredulous and this, as the authors explain, is because of the "fundamental split between the world we see and its quantum underpinnings".

But here's the thing: there is only a single set of laws that govern the way the world behaves - quantum laws. As J&J state, statistical and Newtonian laws are simply laws that have been filtered through a decoherence lens that screens out the weird stuff, which is why quantum phenomena seems so weird.

J&J address the question of consciousness and the mind-body problem, which they posit is "surely the deepest mystery of our entire existence".

The authors ponder whether our brains function as quantum computers, a hypothesis championed by Oxford Professor Roger Penrose. Penrose argues that the human mind can perform non-computable processes, ie beyond traditional binary computers, suggesting that consciousness itself might be rooted in quantum mechanics. [Note that Life on the Edge was published in 2014. Large language models of 2024, such as chatGPT4o, running on binary machines, are now displaying impressive, if simple, reasoning capabilities]

This raises provocative questions about the nature of artificial intelligence and whether a quantum component could imbue machines with an accelerated consciousness.

In conclusion, the exploration of quantum mechanics and its potential implications for understanding life and consciousness is nothing short of mind-bending. The tantalizing ideas that are so well presented in this text make a compelling case for the entwined nature of the classical and quantum worlds, and the implications for consciousness and artificial intelligence are fascinating and thought-provoking.

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