Just as if...

Oxford Botanical Garden and Magdalen Tower

Long ago I sat on a grassy patch in the Botanical Garden opposite Magdalen college whose tower commands the scene above, and pondered. The ubiquitous cell-phones in the picture date it - there were no such things when I was there. My ponderance was partly fuelled by a guy in my parent's church who, when praying in public, could hardly finish a sentence without saying "indeed". We children used to compete for noting the most indeeds in any one of his (or anyone else's) long prayers. Back then the length of prayers was and perhaps still is an implicit measure of spirituality.

Indeed: an adverb used to stress that something is true or real. Or maybe is not quite.

Another favourite was "as it were", an idiomatic phrase meaning "so to speak," "as if it were," or "in a manner of speaking", used 44 times in the KJV Bible and also by preachers who would liberally scatter it through their monologs I suppose to give them the greater credence. 

My own muse was around the phrase "just as if". For example you could say that, in an atom, electrons orbit the nucleus just as if gravity were responsible, except that it isn't and they don't. A comparison is being made: there is a degree of isomorphism i.e. mapping. A better example is transubstantiation (the Roman Catholic doctrine that the bread and wine used in the Eucharist change in substance into the actual Body and Blood of Jesus Christ during consecration at Mass), although even they soften the blow with the distinction between substance and accident. A low church man might dilute the doctrine to make it more palatable, saying that the bread and wine are just as if they were the body and blood i.e. to all intents and purposes but not actually the real McCoy. There is a comparison in which an untruth is being elevated to being sort of true.

In each of these cases there is an implied something deeper that is hidden.  At the time I was pretty sure that "just as if" was an important discovery but I wasn't able to develop the idea any further. It has, however, sat with me ever since, and now that I am reading the book Gödel, Escher, Bach and its being a precursor to AI, I am beginning to see why. This 50 year old book, and its association with modern AI, is all about analogy, isomorphism, interpretation - linking two entities rather more loosely that strict algebra would permit, and this drawing powerful "lateral thinking" conclusions, albeit some being erroneous. Indeed one of the failings of AI at present is its inability to weed out its own errors.

I was given another book: Liturgies of the Wild by Martin Shaw. Here's a man who is bold enough to be different, very different, from the status quo. He has found meaning in and association between the myth and his take on Christianity from the Eastern Orthodox perspective. I too find myself different - I guess every one of us is, but some of us are more different than others. It's one thing to concede one's differences to oneself (and that can take some doing), quite another to come out with them publicly. Martin Shaw has been through both aspects unashamedly. 

Martin considers himself a Christian, as have folk I've known in fundamentalist Brethren churches, and more recently in our own flavour (long ago aptly dubbed "neo-charismatic" by an agnostic friend), even though their doctrines are so different. Which begs the question: what exactly does it take to be a Christian?

To one thief on a cross it was simply "To day shalt thou be with me in paradise". To the Philippian jailor it was simply "Believe on the Lord Jesus Christ, and thou shalt be saved, and thy house". Or, regarding faith: "Yea, a man may say, Thou hast faith, and I have works: shew me thy faith without thy works, and I will shew thee my faith by my works. These are remarkably simple requirements. Simpler than even that suggested in those tiny booklets "The four spiritual laws".

Nothing there to distinguish between the Brethren and the Eastern Orthodox believer.

I recall a comment made by a fellow student at Oxford about the Christian Union (in which I was involved and which was decidedly low church), that the likes of he and his father (who were decidedly high church) would for ever after be counselling those that whose faith had been damaged or mislead by folk like me. At the time I dismissed this comment but now I am not so sure. Not so sure about folk who reckon that their take on Christianity is the only real truth. Calvinism vs. Arminianism and all that.

The words "I'm a Christian" must masquerade or be a euphemism for something deeper and truer and valuable than the mere words suggest: the result of which will be to loose the bonds of wickedness, to undo the straps of the yoke, to let the oppressed go free, and to break every yoke. To share your bread with the hungry and bring the homeless poor into your house; and when you see the naked, to cover him, and not to hide yourself from your own flesh. (Isa 58) or Jesus, looking at him, loved him, and said to him: You lack one thing: go, sell all that you have and give to the poor, and you will have treasure in heaven; and come, follow me. (Mark 10). Simple yes, but gut wrenchingly far reaching.

References

For a download of Gödel, Escher, Bach: An Eternal Golden Braid read online here:

Summary of Roger Penrose' The Emperor's New Mind

Does the increased failing of short term memory with advancing years give a clue as to what exactly is the (human) mind? Because I may more often forget things, but this do not change my consciousness: I am still the same "me" inside this aging body. 

FB post  Md Ismail Sojal's Facebook post quoted in full

A 34-year-old physics graduate student spent years writing a strange 800-page book in 1979 about a logician, a Dutch artist, and a German composer. It won the Pulitzer Prize the following year. It quietly became required reading at every AI lab in the world.

It is the only book in history that makes the deepest ideas in computer science feel like a dream you cannot stop thinking about.

His name is Douglas Hofstadter. The book is called Gödel, Escher, Bach.

Almost nothing in modern AI makes sense without this book. ChatGPT, Claude, Gemini, the entire architecture of self-attention, the alignment problem, the strange feeling that LLMs sometimes seem to understand and other times seem to be playing an elaborate symbol-shuffling game, all of it traces back to questions Hofstadter laid out in a single book published before most of today's AI engineers were born.

Here is the story almost nobody tells you about how the book came to exist.

Hofstadter was the son of Robert Hofstadter, who won the Nobel Prize in Physics in 1961 for measuring the size of the proton. He was supposed to follow in his father's footsteps.

He started a physics PhD at the University of Oregon. He was miserable. He could not focus. He did not love the work. He kept getting pulled toward something else.

The something else was a single question that had haunted him since childhood.

How can meaning emerge from meaningless symbols? Specifically, how does a brain, which is made of nothing but cells firing electrical signals at each other, produce something that feels like consciousness, like understanding, like a self?

He could not let the question go. He left physics. He started writing. The book took him years. He wrote it largely in isolation, working in the basement of his parents' house and at Indiana University, where he eventually finished it. He thought it would be read by maybe a few hundred logicians and AI researchers. Basic Books published it in 1979 as a 777-page hardcover.

The next year it won the Pulitzer Prize for general non-fiction and the National Book Award for science.

The book is structured in a way that almost no other book has ever attempted. The chapters alternate between two layers. One layer is technical chapters about logic, computability, neuroscience, and AI. The other layer is fictional dialogues between a tortoise and Achilles, characters borrowed from a paradox by Lewis Carroll.

The dialogues play with the same ideas the technical chapters explain. Read in order, they do not feel like a textbook. They feel like a strange house with rooms that loop back into each other and corridors that change shape behind you.

The first thing the book does is explain Gödel's incompleteness theorems in a way no math textbook had ever managed.

Kurt Gödel, an Austrian logician working in 1931, proved something that broke mathematics. He showed that any formal system powerful enough to describe arithmetic contains statements that are true but cannot be proven inside that system. Mathematics, the most certain thing humans had ever built, has holes in it that can never be filled.

Hofstadter spends hundreds of pages making you understand this proof not just as a mathematical theorem, but as a structural fact about every sufficiently complex system. Including the brain. Including any AI. The reason AI alignment is genuinely hard is not just engineering. It is structural.

Any system smart enough to model itself will contain truths about itself it cannot reach from inside itself. Hofstadter showed this 50 years before AI safety was a field.

The second thing the book does is introduce his core idea. He calls it the strange loop.

A strange loop is what happens when a system, by climbing through layers of itself, somehow ends up back where it started. Escher's drawings of staircases that always go up but somehow loop back are visual strange loops. Bach's musical canons that modulate up through keys and end on the original note are auditory strange loops. Gödel's self-referential statements that talk about themselves are logical strange loops.

Hofstadter argues that consciousness is a strange loop. Your brain builds a model of the world. Inside that model, it builds a model of itself perceiving the world. Inside that self-model, it builds a model of itself thinking about itself perceiving the world. The recursion does not bottom out. The self is what the loop feels like from the inside.

This is the part that AI researchers cannot stop returning to. Modern transformer models use self-attention, which is technically a mechanism where a network attends to its own internal states across layers. Recursive reasoning, where a model thinks about its own thinking, is now a research area with its own conferences. Meta-learning, where models learn how to learn, is a direct descendant of what Hofstadter described in 1979 as the necessary structure of any conscious system. He wrote the philosophy. The engineers are now building the implementation.

The third thing the book does is the part that haunts every AI conversation today.

Hofstadter argued that meaning is not something separate from symbol manipulation. It is what symbol manipulation looks like from the inside, when the manipulation is complex enough and self-referential enough. A simple lookup table does not understand anything. But a system that processes symbols at sufficient depth, with enough self-modeling, with enough recursion, starts to look identical from the outside, and possibly from the inside, to a system that understands.

This is the deepest question in modern AI. When ChatGPT generates a response, is it actually thinking, or is it just doing very fast symbol shuffling? Hofstadter spent 800 pages arguing that the distinction may not exist at sufficient scale. If a system shuffles symbols according to the right structure, meaning is what the shuffling looks like from the inside.

You can read modern debates about AI consciousness from Yann LeCun, Geoffrey Hinton, Ilya Sutskever, and David Chalmers, and you will find that they are all, in their own ways, having the argument Hofstadter framed in 1979.

The fourth thing the book did is the one that took the longest to be vindicated.

Hofstadter argued, and continued arguing for decades, that the actual engine of human intelligence is not logic. It is not deduction. It is not pattern matching in any simple sense. It is analogy. The ability to see one thing as similar to another thing, to map the structure of one situation onto a different situation, is, in his view, the core of thought itself.

For decades this was unfashionable. Symbolic AI focused on logic and rules. Statistical AI focused on pattern matching. Almost nobody worked seriously on analogy.

Then large language models started working. And the people who looked closely at what they were doing realized something uncomfortable. LLMs are, fundamentally, analogy machines. They learn structural patterns from text and apply those patterns by analogy to new situations. They do not deduce. They do not reason logically by default. They map the shape of one thing onto the shape of another thing and produce output that fits the new shape.

Hofstadter saw this before any of it existed. His later book Surfaces and Essences, written with Emmanuel Sander, is 600 pages defending the claim that analogy is the core of cognition. It came out in 2013. It was largely ignored. The ChatGPT release in 2022 was, in some sense, a vindication of the entire argument.

The strangest thing about reading Gödel, Escher, Bach in 2026 is realizing how lonely the book must have felt when it was written.

In 1979 there was no GPT. No deep learning. No transformer. The dominant approach to AI was symbolic logic, and most researchers thought minds were going to be programmed top-down, rule by rule, like a complicated chess engine. Hofstadter said the opposite. He said minds were emergent. They came from the bottom up. They were strange loops in complex substrates. The programmers' approach would never produce real intelligence because it was missing the recursive self-modeling that made minds real.

He was right.

The book is hard. I had to use all the LLMs and NotebookLM to understand it. It is not a beach read. You do not finish it in a weekend. The math chapters require attention. The dialogues require patience. Most people who buy it never finish it. That is fine. The book is structured so that reading any 50 pages produces a permanent shift in how you think.

Bill Gates lists it among the books that shaped him. Steve Jobs read it. Almost every senior AI researcher in the world will tell you it was the book that made them fall in love with the question of intelligence in the first place.

Hofstadter himself has been in doubt about modern LLMs. He has said they may have proven him right about analogy and wrong about consciousness at the same time. He is still writing. He is still working on the same question that pulled him out of physics 50 years ago.

The 800-page book that explained intelligence before AI existed is sitting one click away from you.

Most people will never open it. The ones who do will see the world differently for the rest of their lives.

A comment on this Facebook post:

This book is one of the greatest ever written. First read it at 17 and it changed my life forever. The only other book that had anywhere close to as profound of an impact on my life is "Thinking, Fast and Slow" by Daniel Kahneman see my own post