Tuesday, April 02, 2024

Dennett, AI and the computational mind

Daniel Dennett is an American philosopher who studied under Gilbert Ryle, the famous anti-dualist philosopher, at the University of Oxford and became the co-director of the Center for Cognitive Studies and a Professor of Philosophy at Tufts University. 

A renowned philosopher but also a polymath, with a deep understanding of psychology, science and maths, he is known for his controversial philosophy of consciousness and philosophy of mind, especially in relation to evolutionary theory and cognitive science. He has played a formative role in connectionism, as he has helped create this new multidisciplinary field of psychology that includes philosophy, psychology, evolution, neuroscience, computer science artificial intelligence and language. 


In Darwin's Dangerous Idea (1995) he explains the evolution of Consciousness arguing that, just as physical traits are subject to evolutionary pressures, so too are mental faculties like consciousness, which have evolved due to their adaptive advantages. This is a hallmark of his work, a commitment to evolution as a foundational, naturalistic theory that shaped the mind as opposed to dualistic views of the mind. His criticism of Cartesian dualism, the idea that mind and body are fundamentally different substances, argues for a more materialistic understanding of consciousness, suggesting that what we call the mind is simply a product of physical processes in the brain with an emphasis on the computation theory of mind.

Computational theory of the mind

Dennett advocates for a form of functionalism, suggesting that mental states are defined by their functional roles, not by their internal constitution. In Consciousness Explained (1991) he argues for a form of functionalism, a model of consciousness that involves multiple parallel processes and interactions which can be likened to computational processes. 

It is vital, he believes, that we understand the brain's information processing mechanisms to comprehend consciousness and cognition. This is not to to see the brain as a computer a reductive fashion. We need more complex view, recognising the intricacies and unique aspects of human cognition that go beyond traditional computational models. He integrates insights from evolutionary biology, cognitive science, and artificial intelligence to explore these ideas. His emphasis is on the need for a comprehensive and interdisciplinary approach to studying consciousness and cognition.


Again, in Consciousness Explained (1991), where he offers a detailed theory of consciousness with the idea, going back to Hume and others, that a central narrative or a unified ‘self’ is an illusion created by the brain. Conscious experiences are constructed by the brain out of a variety of sensory inputs and mental processes that occur simultaneously and are then retrospectively made sense of as a coherent narrative.

His ‘Multiple Drafts’ model of consciousness, which is an alternative to the traditional idea of a Cartesian Theatre, sees multiple and parallel perceptual experiences unified into a single stream of consciousness. Dennett argues that various events, called ‘drafts’, happen in different places in the brain simultaneously and without any central place where can be said to be a self. There is no central theatre where consciousness comes together; rather, our brains create a coherent narrative from these overlapping drafts.

Bayesian brain

He adds to this ‘multiple drafts’ model of consciousness, a computational model of the mind and intentional stance. His vision, which has gained lots of recent traction in cognitive science, is that the brain uses Bayesian hierarchical coding, a prediction machine, constantly modelling forward. 

He sees this as the cause of dreams and hallucinations – random and arbitrary attempts at Bayesian prediction, an interesting species of the computational model of the brain that explains why the networked structure of the brain has been a productive, intuitive source of inspiration for AI, especially neural networks. It also explains why there has been interest in reversing that trend so that our knowledge of cognition can learn from computer science and artificial intelligence.


Inspired by Richard Dawkins' concept of the meme, Dennett has explored the idea of memetics, which views ideas, beliefs, and cultural phenomena as replicators similar to genes, subject to evolutionary pressures. Language plays a significant role in consciousness for Dennett and he suggests that our ability to report on our experiences is not just a by-product of consciousness but an integral part of its operation. 

He examines cultural evolution, such as religion, as the invasion or infection of the brain by memes, primarily words, and that these memes operate in a sort of Bayesian marketplace, without a single soul or executive function. These informational memes, like Darwinian evolution, show fitness in the sense of being advantageous to themselves. That brings us back to the ethical considerations around AI. He surfaces the contribution of Baldwin as an evolutionary theorist who saw 'learning' as an evolutionary accelerator.

Artificial Intelligence

His book Bacteria to Bach and Back (2017) is essential reading for those who want to see a synthesis of human evolution and AI, and its consequences for the ethics of AI. Dennett has the background depth in philosophy to understand the exaggerations and limits of AI and its consequences for ethics. He also grounds his views in biology and ourselves as humans, as both benchmark and progenitor of AI.

Just as the Darwinian evolution of life over nearly 4 billion years has been ‘competence without comprehension’ the result of blind design, what Dawkins called the ‘blind watchmaker’, so cultural evolution and AI is often competence without comprehension. This is the context of his views on AI.

Watson may have won Jeopardy but it didn’t know it had won. This basic concept of competence without comprehension is something that has to be understood to counter the exaggeration and anthropomorphism around in the subject, especially in the ethics debate. We have all sorts of memes in our brains but it is not clear that we know why they are there. Similarly with AI,

As he rightly says, we make children without actually understanding the entirety of the process, so it is with generative technology. Almost all AI is parasitic on human achievements, corpuses of text, images, video, music, maths and so on. We already trust systems that are way more competent than we humans and so we should. His call is for us to keep an eye on the boundaries between mind and machine, as we have a tendency to over-estimate the 'comprehension' of the machines, way beyond their actual competence. We all too readily read intentionality, comprehension, even consciousness into technology when it is completely absent.


His hope is that machines will open up “notorious pedagogical bottlenecks” even “imagination prostheses” working with and for us to solve big problems. We must recognise that the future is only partly, yet largely, in our control. Let our artificial intelligences depend on us even as we become “more warily dependent on them.”

AI, for Dennett, is a powerful cognitive tool that can augment human abilities, especially in the context of education, as it could be used to enhance teaching methods, personalise learning experiences and help students and educators identify and overcome learning challenges more efficiently. Also, he often explores how understanding AI can lead to better insights into human cognition. This perspective implies that advances in AI could lead to improved educational strategies by providing a deeper understanding of how we learn and process information.

His interdisciplinary approach to AI, combining philosophy, cognitive science, and biology, could influence educational models, encouraging interdisciplinary learning and the integration of AI into various fields of study.


Some feel he too easily that he explains consciousness away too easily, taking too reductive an approach  to the rich, subjective experiences and emnergent properties of cognitive processes, cognition and agency. Dennett’s comparisons between AI and human cognition are sometimes seen as overstretched and too speculative. They argue that equating human cognitive processes with computational models may ignore the unique, non-computational aspects of human thought and consciousness.


Dennett's theories are influential because they blend philosophical inquiry with empirical science, providing a framework for understanding the mind and consciousness in terms of physical processes and evolutionary biology. His work has contributed significantly to debates in philosophy of mind, cognitive science, and artificial intelligence.


Dennett, D. C. (1969). Content and consciousness. London: Routledge & Kegan Paul.

Dennett, D. C. (1978). Brainstorms: Philosophical essays on mind and psychology. Montgomery, VT: Bradford Books.

Dennett, D. C. (1984). Elbow room: The varieties of free will worth wanting. Cambridge, MA: MIT Press.

Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press.

Dennett, D. C. (1991). Consciousness explained. Boston, MA: Little, Brown and Co.

Dennett, D. C. (1995). Darwin's dangerous idea: Evolution and the meanings of life. New York, NY: Simon & Schuster.

Dennett, D.C., (2017). From bacteria to Bach and back: The evolution of minds. WW Norton & Company.

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