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The Emergent Mind: How Intelligence Arises in People and Machines
Written by experts at the forefront of cognitive science and artificial intelligence, The Emergent Mind is an essential read for anyone captivated by the mysteries of human intelligence or the transformative rise of AI.
Have you ever wondered how our minds work – how we think, feel, and act? How is this different from artificial intelligence? And with AI advancing so rapidly, how are these two worlds beginning to intersect?
In this groundbreaking book, leading scientists Gaurav Suri and Jay McClelland answer these urgent questions by exploring a powerful idea called ‘emergence’ – the concept that complex systems can form from the interaction of simple parts. By applying this to both the human brain and AI, they reveal how mind-like abilities take shape.
By using the concept of neural network – the same framework inspired by the human brain that powers today’s AI – this book offers a clear and engaging guide to understanding intelligence. The Emergent Mind offers a fascinating tour of our minds, showing how we make decisions, why we change our minds and how our thoughts are shaped by our experiences. It's a groundbreaking look at how a data-driven neural network can create thoughts, emotions, and ideas – a mind – in both humans and machines.
Have you ever wondered how our minds work – how we think, feel, and act? How is this different from artificial intelligence? And with AI advancing so rapidly, how are these two worlds beginning to intersect?
In this groundbreaking book, leading scientists Gaurav Suri and Jay McClelland answer these urgent questions by exploring a powerful idea called ‘emergence’ – the concept that complex systems can form from the interaction of simple parts. By applying this to both the human brain and AI, they reveal how mind-like abilities take shape.
By using the concept of neural network – the same framework inspired by the human brain that powers today’s AI – this book offers a clear and engaging guide to understanding intelligence. The Emergent Mind offers a fascinating tour of our minds, showing how we make decisions, why we change our minds and how our thoughts are shaped by our experiences. It's a groundbreaking look at how a data-driven neural network can create thoughts, emotions, and ideas – a mind – in both humans and machines.
368 pages, Hardcover
First published October 21, 2025
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Displaying 1 - 20 of 20 reviews
May 12, 2026
The basic premise of this book is that our minds are fundamentally neural networks. It doesn't say that is all that they are; there are many other aspects of our minds that we don't understand. But the neural network model seems to be close in many ways to how nerve cells connect and has an explanatory power for rational and irrational behaviors that goes beyond models based on systems of rules or more traditional explanations of how the mind takes in sense impressions and then translates them into thoughts and actions. I'm fine with the idea that it is possible to build systems based on neural networks that will be able to mirror abstract reasoning, human desire systems and even consciousness. I am not daunted by the complexity of these results any more than I am by the idea that a simple light detecting cell could evolve through natural selection to something as complex as a human eye. Many baby steps driven by simple rules and the power of networking can create incredible complex results.
I enjoyed the chapters describing how neural networks work and how their implementation is both similar and different in brains and AI systems. I knew a lot of this stuff, but the reinforcement was helpful (no doubt strengthening many of the activations in my personal neural network!). I sometimes wished that the prose could have been a little more lucid, but it's hard to describe even a simple logical system accurately without getting a little dense.
This is mainly a book about how brains work, but also a book about how AI works. It was refreshing to read an AI book that was value neutral, neither evangelism nor fear mongering for once, though it tends a little bit toward the evangelism side and I thought understated the dangers.
I enjoyed the chapters describing how neural networks work and how their implementation is both similar and different in brains and AI systems. I knew a lot of this stuff, but the reinforcement was helpful (no doubt strengthening many of the activations in my personal neural network!). I sometimes wished that the prose could have been a little more lucid, but it's hard to describe even a simple logical system accurately without getting a little dense.
This is mainly a book about how brains work, but also a book about how AI works. It was refreshing to read an AI book that was value neutral, neither evangelism nor fear mongering for once, though it tends a little bit toward the evangelism side and I thought understated the dangers.
Did Not Finish
January 19, 2026I understand that it must be tricky, as a scientist, to find the right way of explaining to a reader that’s not another scientist like you. You don’t want to make it too hard so it goes over your reader’s head, but that could easily make you fall into the trap that I felt these two fell into, to sound slightly condescending. It’s not their fault, their editor should have been able to pick this up.
December 31, 2025
The Emergent Mind explores how we learn, why we make decisions, how our thoughts relate to our actions, and what ultimately differentiates us from AI. All of this is presented in an engaging and easy-to-follow way.
This was probably my favorite book of 2025. Though, I did not have time to read many books this year, but the way this one was written — and the topics it covered — really impressed me.
I may have been slightly biased going in, since I had previously listened to the EconTalk episode featuring the author. The metaphor of water flowing down a mountain and gradually forming connections felt especially fitting for how neural pathways develop over time. As a hiker myself, it is beautiful to see this metaphor.
I think the definition for "learning" is too broad however. In Chapter 10 (“Our Emergent Thoughts”) it was written that we may learn while unconscious. The study cited seemed to demonstrate priming in anesthetized patients rather than learning in the sense of longer-term memory building. While priming may be an early step — involving neural activation without conscious awareness — I don’t think it qualifies as knowledge acquisition. If it did, we might also expect things like language learning during sleep, which current evidence does not support.
That said, this disagreement only made the book more interesting and pushed me to think more deeply about the topic. I will definitely keep reading on this topic. Overall, a thought-provoking and highly enjoyable read.
This was probably my favorite book of 2025. Though, I did not have time to read many books this year, but the way this one was written — and the topics it covered — really impressed me.
I may have been slightly biased going in, since I had previously listened to the EconTalk episode featuring the author. The metaphor of water flowing down a mountain and gradually forming connections felt especially fitting for how neural pathways develop over time. As a hiker myself, it is beautiful to see this metaphor.
I think the definition for "learning" is too broad however. In Chapter 10 (“Our Emergent Thoughts”) it was written that we may learn while unconscious. The study cited seemed to demonstrate priming in anesthetized patients rather than learning in the sense of longer-term memory building. While priming may be an early step — involving neural activation without conscious awareness — I don’t think it qualifies as knowledge acquisition. If it did, we might also expect things like language learning during sleep, which current evidence does not support.
That said, this disagreement only made the book more interesting and pushed me to think more deeply about the topic. I will definitely keep reading on this topic. Overall, a thought-provoking and highly enjoyable read.
September 19, 2026
2,5 stars; for a promising title this was a bit of a let down; beyond stating that intelligence emerges from neural networks interacting in an adaptive complex system configuration (no surprises here) there is not at all that much to be savored here; all good points but no revelations that make reading/listening to this volume worth your time.
December 25, 2025
To start, I am not a scientist. I am aware that some of my thoughts on this book can be wrong, uninformed and coming from not understanding this piece of work properly. However, considering this book is also meant for the general population, I will just go ahead to add my two cents:
- the concept is not properly explained. At the start the authors mention the neural network is only a model, not actual view of the brain, but then, during the entire book, they proceed to speak of it as if it was literal. Like they quite specifically speak in the sense that "this is exactly how the brain works!!". Make up your mind maybe? I can take a guess as to why this is written like this, sure. But as a "noob" into this topic, I cannot know what EXACTLY you mean as authors unless you specifically explain it. This is especially important when the book is on such a topic that you do not meet with in everyday life. I have studied journalism and sociology, I am not entirely a stranger to the concept of models, and even I had issues with this - much less a potential reader who has not met with these topics, ever. When you leave your audience wondering whether the BASIC idea of your concept is literal or not, you've already lost them.
- I do not think I've ever read a more boring book. It's not due to the concept, but the writing was just putting me to sleep, and it didn't matter what time of the day it was or where I was. This is not a scientific article, this is a book meant also for general population to buy and read, but it's so full of science-speak and expert phrases that for someone who has not studied this subject, the book just reads so bad.
- most of the book sources consist of other pieces of work of Suri and McClelland, so it's not exactly giving it too much of credibility when it comes to "you can double check this info from other sources" kind of thing. I believe they're trusted scientists in their own rights, but as a reader who does not know them, I cannot treat a scientific study on a "trust me bro" basis.
- the concept is not properly explained. At the start the authors mention the neural network is only a model, not actual view of the brain, but then, during the entire book, they proceed to speak of it as if it was literal. Like they quite specifically speak in the sense that "this is exactly how the brain works!!". Make up your mind maybe? I can take a guess as to why this is written like this, sure. But as a "noob" into this topic, I cannot know what EXACTLY you mean as authors unless you specifically explain it. This is especially important when the book is on such a topic that you do not meet with in everyday life. I have studied journalism and sociology, I am not entirely a stranger to the concept of models, and even I had issues with this - much less a potential reader who has not met with these topics, ever. When you leave your audience wondering whether the BASIC idea of your concept is literal or not, you've already lost them.
- I do not think I've ever read a more boring book. It's not due to the concept, but the writing was just putting me to sleep, and it didn't matter what time of the day it was or where I was. This is not a scientific article, this is a book meant also for general population to buy and read, but it's so full of science-speak and expert phrases that for someone who has not studied this subject, the book just reads so bad.
- most of the book sources consist of other pieces of work of Suri and McClelland, so it's not exactly giving it too much of credibility when it comes to "you can double check this info from other sources" kind of thing. I believe they're trusted scientists in their own rights, but as a reader who does not know them, I cannot treat a scientific study on a "trust me bro" basis.
July 12, 2026
My main issue with The Emergent Mind is that I wasn't quite sure who the book was written for.
If you already know the basics of neural networks, the many simple diagrams and long explanations of how they work can feel repetitive. If you're new to the subject, though, I'm not sure they provide enough to really understand it.
What I enjoyed most were the parts about neuroscience. I just wish the book had spent more time there.
If you already know the basics of neural networks, the many simple diagrams and long explanations of how they work can feel repetitive. If you're new to the subject, though, I'm not sure they provide enough to really understand it.
What I enjoyed most were the parts about neuroscience. I just wish the book had spent more time there.
May 26, 2026
Excellent book for anyone who enjoys cognitive science and its connection to the development of artificial intelligence. The book has great scientific examples of how learning and memory develop in humans, nature, and computers.
September 30, 2026
Deze recensie werd eerder gepubliceerd op mijn blog GraagGelezen.
Hoe eenvoud leidt tot oneindige complexiteit
Wat gebeurt er als je miljarden relatief simpele neuronen met elkaar verbindt? Dan ontstaat er iets wonderlijks: menselijk denken, emoties en bewuste beslissingen.
In Waar denken begint nemen twee vooraanstaande wetenschappers, de neurowetenschapper Gaurav Suri en cognitiewetenschapper Jay McClelland de lezer mee op een fascinerende reis langs de fundamenten van intelligentie, zowel in het biologische brein als in moderne AI-systemen. Het boek combineert een sterk inhoudelijke en heldere analyse met filosofische vragen.
De kernvraag van het boek is even oud als intrigerend: waar komen onze gedachten vandaan? De auteurs leggen op toegankelijke wijze uit hoe complexe eigenschappen kunnen ontwaken uit systemen waarvan de afzonderlijke onderdelen dat zelf helemaal niet bezitten – een fenomeen dat doet denken aan de evolutie van een simpel lichtgevoelig celletje tot een complex menselijk oog.
“Een entomoloog die iets wil leren over het gedrag van een mierenkolonie die rond obstakels navigeert, moet iets weten over mieren. Als hij niet zou weten dat mieren bijvoorbeeld feromonen uitscheiden en dat ze het sterkste feromonenspoor volgen, zou hij geen volledige mechanistische verklaring kunnen geven over hoe mierenkolonies uiteindelijk de kortste route rond een obstakel nemen.
Een belangrijke doelstelling van dit boek is om je te laten kennismaken met neurale netwerken die veel van de emergente eigenschappen vertonen die in de menselijke geest optreden. Deze neurale netwerken bestaan uit eenheden waarvan de eigenschappen geïnspireerd zijn op de eigenschappen van neuronen in een echt brein. We moeten dus iets weten over deze eigenschappen.”
Daarnaast brengt het boek een broodnodige verschuiving teweeg in hoe we naar besluitvorming kijken. Waar traditionele modellen vaak leunen op starre regelsystemen of ongenuanceerde stimulus-respons-ketens (een psychologisch concept dat stelt dat al het gedrag ontstaat als een automatische reactie op prikkels uit de omgeving), laten Suri en McClelland zien dat neurale netwerken een veel krachtigere en een meer realistische verklaring bieden voor zowel ons rationele als ons irrationele gedrag. Waarom veranderen we van gedachten? Hoe beïnvloeden ervaringen ons denken? Het neurale netwerk vormt de rode draad die antwoord geeft.
Een van de sterkste punten van Waar denken begint is de toon. In een tijd waarin publicaties over kunstmatige intelligentie en de werking van de hersenen vaak worden overschaduwd door doemscenario's, hype of persoonlijke meningen, kiest dit boek voor een verfrissend nuchtere en objectieve benadering. Het biedt een heldere spiegel: hoe functioneren biologische hersenen en hoe bootsen AI-systemen die architectuur na? De hoofdstukken die de overeenkomsten en verschillen tussen deze twee werelden blootleggen, behoren tot de absolute hoogtepunten van het werk.
Waar denken begint is een stimulerend en diepgaand boek voor iedereen die verder wil kijken dan de oppervlakte van intelligentie. Het sluit geen ogenschijnlijke onmogelijkheden uit – zoals de optie dat netwerken ooit abstract redeneren of zelfs bewustzijn weerspiegelen – maar bouwt dat geloof zorgvuldig op vanuit logica en wetenschap. Een absolute aanrader voor nieuwsgierige geesten die willen begrijpen hoe kleine stapjes en eenvoudige regels de complexiteit van ons universum (en onze geest) vormgeven.
Waar denken begint bestaat uit vier delen en het leent zich uitstekend om een deel te lezen, even weg te leggen om op een andere dag het volgend deel te lezen.
Hoe eenvoud leidt tot oneindige complexiteit
Wat gebeurt er als je miljarden relatief simpele neuronen met elkaar verbindt? Dan ontstaat er iets wonderlijks: menselijk denken, emoties en bewuste beslissingen.
In Waar denken begint nemen twee vooraanstaande wetenschappers, de neurowetenschapper Gaurav Suri en cognitiewetenschapper Jay McClelland de lezer mee op een fascinerende reis langs de fundamenten van intelligentie, zowel in het biologische brein als in moderne AI-systemen. Het boek combineert een sterk inhoudelijke en heldere analyse met filosofische vragen.
De kernvraag van het boek is even oud als intrigerend: waar komen onze gedachten vandaan? De auteurs leggen op toegankelijke wijze uit hoe complexe eigenschappen kunnen ontwaken uit systemen waarvan de afzonderlijke onderdelen dat zelf helemaal niet bezitten – een fenomeen dat doet denken aan de evolutie van een simpel lichtgevoelig celletje tot een complex menselijk oog.
“Een entomoloog die iets wil leren over het gedrag van een mierenkolonie die rond obstakels navigeert, moet iets weten over mieren. Als hij niet zou weten dat mieren bijvoorbeeld feromonen uitscheiden en dat ze het sterkste feromonenspoor volgen, zou hij geen volledige mechanistische verklaring kunnen geven over hoe mierenkolonies uiteindelijk de kortste route rond een obstakel nemen.
Een belangrijke doelstelling van dit boek is om je te laten kennismaken met neurale netwerken die veel van de emergente eigenschappen vertonen die in de menselijke geest optreden. Deze neurale netwerken bestaan uit eenheden waarvan de eigenschappen geïnspireerd zijn op de eigenschappen van neuronen in een echt brein. We moeten dus iets weten over deze eigenschappen.”
Daarnaast brengt het boek een broodnodige verschuiving teweeg in hoe we naar besluitvorming kijken. Waar traditionele modellen vaak leunen op starre regelsystemen of ongenuanceerde stimulus-respons-ketens (een psychologisch concept dat stelt dat al het gedrag ontstaat als een automatische reactie op prikkels uit de omgeving), laten Suri en McClelland zien dat neurale netwerken een veel krachtigere en een meer realistische verklaring bieden voor zowel ons rationele als ons irrationele gedrag. Waarom veranderen we van gedachten? Hoe beïnvloeden ervaringen ons denken? Het neurale netwerk vormt de rode draad die antwoord geeft.
Een van de sterkste punten van Waar denken begint is de toon. In een tijd waarin publicaties over kunstmatige intelligentie en de werking van de hersenen vaak worden overschaduwd door doemscenario's, hype of persoonlijke meningen, kiest dit boek voor een verfrissend nuchtere en objectieve benadering. Het biedt een heldere spiegel: hoe functioneren biologische hersenen en hoe bootsen AI-systemen die architectuur na? De hoofdstukken die de overeenkomsten en verschillen tussen deze twee werelden blootleggen, behoren tot de absolute hoogtepunten van het werk.
Waar denken begint is een stimulerend en diepgaand boek voor iedereen die verder wil kijken dan de oppervlakte van intelligentie. Het sluit geen ogenschijnlijke onmogelijkheden uit – zoals de optie dat netwerken ooit abstract redeneren of zelfs bewustzijn weerspiegelen – maar bouwt dat geloof zorgvuldig op vanuit logica en wetenschap. Een absolute aanrader voor nieuwsgierige geesten die willen begrijpen hoe kleine stapjes en eenvoudige regels de complexiteit van ons universum (en onze geest) vormgeven.
Waar denken begint bestaat uit vier delen en het leent zich uitstekend om een deel te lezen, even weg te leggen om op een andere dag het volgend deel te lezen.
September 16, 2026
Maybe not the easiest book to absorb in audio format. My main takeaway is AI neural networks function differently than biological brains, so while both use similar concepts and more research about each can help us understand the other, they are distinct.
Brains are more efficient, learning via bodily experience, with limited access to data. We don’t understand many of our own motivations, as they happen at a subconscious level.
AI can train on vast datasets, recognizing patterns.
We don’t fully understand consciousness in humans, or animals, so ascribing feelings, motives, or a type of consciousness to AI, at this point seems dubious. That’s not to say we shouldn’t worry about safety, alignment and containment concerns.
Brains are more efficient, learning via bodily experience, with limited access to data. We don’t understand many of our own motivations, as they happen at a subconscious level.
AI can train on vast datasets, recognizing patterns.
We don’t fully understand consciousness in humans, or animals, so ascribing feelings, motives, or a type of consciousness to AI, at this point seems dubious. That’s not to say we shouldn’t worry about safety, alignment and containment concerns.
February 18, 2026
Really cool book on both AI and How our own brains work.
The idea that thoughts "arise" (emerge) has always seemed like a concept reserved to Buddhism but this book walked through how it actually seems to be a good description for both the processes of human brains and our machines.
Importantly, it starts to ask some basic questions about consciousness WITHOUT relying on an external non-measurable source that somehow endows us with god like thinking capacities.
The ideas on how motivation occurs in human brains (chap 10) was really helpful in thinking about how I want to design my own life.
The idea that thoughts "arise" (emerge) has always seemed like a concept reserved to Buddhism but this book walked through how it actually seems to be a good description for both the processes of human brains and our machines.
Importantly, it starts to ask some basic questions about consciousness WITHOUT relying on an external non-measurable source that somehow endows us with god like thinking capacities.
The ideas on how motivation occurs in human brains (chap 10) was really helpful in thinking about how I want to design my own life.
February 6, 2026
This book is probably a good primer for the neuro-curious (and provides some AI/neural network/LLM basic knowledge to boot).
It did not contain a lot of new stuff for me personally, so my grade reflects that. Writing-wise it was ok, not bad, not fantastic. The dialogues that are sprinkled are not Hofstadter-level. The part on consciousness was a bit uninformed and lacked anchoring in their theories, so came off more like an overview of others' theories than something that was thought through deeply.
It did not contain a lot of new stuff for me personally, so my grade reflects that. Writing-wise it was ok, not bad, not fantastic. The dialogues that are sprinkled are not Hofstadter-level. The part on consciousness was a bit uninformed and lacked anchoring in their theories, so came off more like an overview of others' theories than something that was thought through deeply.
May 22, 2026
I had much higher expections. There was scant insight for me. They view neuronal functioning as the key to life rather than as an intermediary mechanism. They explain how neural networks might operate, but can't tell us much more. Without context, brain function alone is relatively meaningless. Possibly, the only new idea I got from the whole book was a page or two about how inhibitory processes work. It was very disappointing for me.
July 26, 2026
I think lay people can learn a lot from this well-written approachable book. The suggestions in the last chapter for using research about the brain to improve AI algorithms was my favorite part. (The rest of the last chapter was kind of pedestrian.)
The authors make complicated mental processes comprehensible. However, because some of the material is complicated, you need to read slowly and concentrate in order to get their insights.
The authors make complicated mental processes comprehensible. However, because some of the material is complicated, you need to read slowly and concentrate in order to get their insights.
August 4, 2026
This book is full of topics I already knew about (how neurons work, meaning as connections, emergence, machine learning, topics in psychology), but somehow, this brought a lot of them together for me in a way I haven't understood before - explaining how these things make sense in a context of neural networks, though the book didn't go all the way in explaining all of it like that.
December 30, 2025
I loved this book. It's not an easy read - not because it is technical - but because it's really a book about ideas and ideas need to simmer. I'm a bit shook by what this book says about what I am (or what any human is).
May 22, 2026
This book needs some heavy editing… I found it a tough / boring read and in places it came across as quite self-indulgent by the authors by, e.g., explicit reference of examples of their own work and explanations rather than something more pedagogical
September 7, 2026
Since 2026, AI systems have routinely solved problems that once served as benchmarks for human reasoning: probability puzzles like the birthday problem, logic questions such as “Jane’s sister Mary has a new baby named Allen. Allen’s mother’s name is?”
August 3, 2026
Destul de tehnica. O carte care intra in top 5 cele mai slabe
August 24, 2026
I'm too dumb to fully grasp neuroscience but the book is good.
September 2, 2026
Timely reading. Maybe LLMs are not that different from us after all?
Displaying 1 - 20 of 20 reviews