[{"id":309168,"date":"2026-08-10T06:00:55","date_gmt":"2026-08-10T10:00:55","guid":{"rendered":"https:\/\/3quarksdaily.com\/?p=309168"},"modified":"2026-08-10T03:09:24","modified_gmt":"2026-08-10T07:09:24","slug":"klaatu-barada-nikto-robert-wrights-the-god-test","status":"publish","type":"post","link":"https:\/\/3quarksdaily.com\/3quarksdaily\/2026\/08\/klaatu-barada-nikto-robert-wrights-the-god-test.html","title":{"rendered":"Klaatu barada nikto: Robert Wright\u2019s “The God Test”"},"content":{"rendered":"

by William Benzon<\/strong><\/a><\/p>\n

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Into The God Test, by ChatGPT<\/figcaption><\/figure>\n

The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning<\/em> (2026) is Robert Wright\u2019s sixth book. It builds on themes and concerns in the previous five books, which I\u2019ll get to at the end. As the title indicates The God Test<\/em> is about artificial intelligence.<\/p>\n

Until OpenAI released ChatGPT in late 2022 AI existed mostly in science fiction, a collection of genres that has become increasingly popular in the last five decades. The intellectual discipline was relatively small, problematic, and often institutionally precarious. Moreover those within the discipline were sometimes\/often motivated as much by cultural mythology as by the challenges presented by the discipline itself. Curiosity kept researchers engaged in problem solving while mythology told them why those problems are important.<\/p>\n

The particular approach to AI that produced ChatGPT, so-called deep learning, has a characteristic that differentiates it from much earlier work in AI and from all other work in computing: We don\u2019t know how it works. And by \u201cwe\u201d I don\u2019t mean only the general public or intellectual specialists outside the discipline. By \u201cwe\u201d I mean everyone, including the scientists and engineers who have developed the technology.<\/p>\n

The standard line about computers, that they only do what they\u2019re programmed to do, doesn\u2019t apply to large language models (LLMs), the particular technology that dominates the current scene. The engineers program a transformer to \u201cexamine\u201d (or, if you prefer, \u201dconsume\u201d) a large corpus of texts, and the transformer constructs (\u201cemits\u201d?) a \u201cmodel\u201d of the language in those texts \u2013 Wright discusses this process in \u201cChapter Two: The Great Inversion.\u201d The inner mechanisms of that model, however, are opaque. The engineers who programmed and ran the transformer can\u2019t see into it to see how it works \u2013 something Wright discusses in \u201cChapter Four: The Evolution of a Large Language Model.\u201d<\/p>\n

What strange beast<\/strong><\/p>\n

Subsuming these factors, deeper than any of them, and more elusive is the simple fact that contemporary chatbots and their siblings are deeply STRANGE. They\u2019re not animal, vegetable, or mineral; they\u2019re a new kind of thing that doesn\u2019t fit into pre-existing cultural categories. They\u2019re inanimate things with which we can converse like we would with another human.<\/p>\n

In the 19th century the term \u201ciron horse\u201d arose to characterize steam locomotives. Why? Because it moved autonomously over the surface of the earth like a horse, but it was made of iron and therefore inanimate. Consider this passage from Henry David Thoreau\u2019s \u201cSound\u201d chapter in Walden (1854):<\/p>\n

When I meet the engine with its train of cars moving off with planetary motion . . . with its steam cloud like a banner streaming behind in gold and silver wreaths . . . as if this traveling demigod, this cloud-compeller, would ere long take the sunset sky for the livery of his train; when I hear the iron horse make the hills echo with his snort like thunder, shaking the earth with his feet, and breathing fire and smoke from his nostrils, (what kind of winged horse or fiery dragon they will put into the new Mythology I don\u2019t know), it seems as if the earth had got a race now worthy to inhabit it.<\/p>\n

There you have it, the iron horse and the fire-breathing dragon. Now we have the electronic brain, as it was known in my youth, the thinking machine.<\/p>\n

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The occurrence of “iron horse” from 1800 to the present.<\/figcaption><\/figure>\n

A Cultural Rorschach Blot<\/strong><\/p>\n

These factors make any attempt to explain the technology and its implications a bit like trying to describe a Rorschach blot. There\u2019s something real there but characterizing it is difficult. Consequently any account you give has a large element of projection in it. AI thus functions as a cultural Rorschach blot onto which we project our hopes and fears, who we are and what we are, where we want to go.<\/p>\n

That\u2019s what The God Test<\/em> is, Robert Wright\u2019s interpretation of this strange cultural Rorschach blot. That makes it a very elusive thing to review: Am I talking about Wright\u2019s ideas or the cultural matrix in which they are embedded? He\u2019s using concepts that were forged and came into usage before ChatGPT blasted through barriers of preconceived ideation, as are all of us in the LLM whisperer business. We\u2019re working in a conceptual world that is being consigned to the dust heap of history by the phenomenon we\u2019re trying to apprehend.<\/p>\n

This particular Rorschach blot, The God Test<\/em>, draws two kinds of projection out of Wright. He expresses them in fifteen chapters and an appendix. There is Wright\u2019s account of how contemporary A.I. works; he concentrates on LLMs (large language models). That material is concentrated in chapters two, four, five, and six, though some is here and there elsewhere in the book. Wright uses the rest of the book (chapters one and three, seven through fifteen, and the appendix) to establish a cosmic context \u2013 his phrase \u2013 for his argument, which is about the significance of A.I. for human life and the future of humankind. This is the important material, this is why I\u2019m attempting to review the book, and it is not very tightly coupled with the material on how this technology works.<\/p>\n

I suppose that\u2019s inevitable, because, as I\u2019ve indicated, most of the thinking and writing that\u2019s been done about artificial intelligence has been based on little more than the idea that one day we\u2019ll create a computer system that\u2019s as smart as we are, quite possibly even smarter, and even very much super-duper giant economy size smarter. That thinking hasn\u2019t actually had to deal with, interact directly with, that kind of a system. Now we have no choice. It\u2019s unsettling.<\/p>\n

Thus I would say that my own belief in the power of this technology is grounded primarily in my experience using chatbots over the last three and a half years, which necessarily includes how much they have improved in that time. I take that experience in the context of my general life experience, which of course includes my experience interacting with other human being and with other computer systems. It is into THAT that I project various attempts to explain what these chatbots are doing.<\/p>\n

If you don\u2019t have much direct experience of chatbots, then you are not going to understand why so many people are talking and writing about them. If you do have some experience with them, more than a little, but not necessarily a whole lot \u2013 I know, kinda\u2019 vague, isn\u2019t it? \u2013 and you aren\u2019t impressed, then nothing I say, or Robert Wright says, or anyone else, whether Geoffrey Hinton, Yann LeCun, or even Gary Marcus for that matter, nothing anyone else says will convince you otherwise.<\/p>\n

If you don\u2019t already believe that this technology is powerful and important, it is unlikely that Wright will convince you otherwise, nor, for that matter, will you find the rest of the book compelling. If you already believe in the technology, then Wright\u2019s account of how it works serves a purpose that\u2019s more rhetorical and even clinical than explanatory. He doesn\u2019t know how it works, nor does anyone else, but he\u2019s not crazy for trying to understand it and neither are you. There\u2019s something there, really.<\/p>\n

Still, if you\u2019re satisfied on the score you can skip over my next section, which is a brief note on meaning, and go right onto \u201cKlaatu barada nikto,\u201d where I transition to cosmic mode.<\/p>\n

The Problem of Meaning<\/strong><\/p>\n

Let\u2019s consider a typical passage. \u201cSearle\u201d is the philosopher John Searle and in 1980 paper is the one the introduced the Chinese Room thought experiment<\/a>, perhaps the best-known thought experiment of the last 50 years.<\/p>\n

If a human being looked at an apple and said, \u201cThat\u2019s an apple, and it\u2019s an edible fruit, and you can use it to make an apple pie,\u201d Searle would say the human is exhibiting understanding. And, to judge by his 1980 paper, that wouldn\u2019t be because the human has the subjective experience of understanding. Rather, it would be because the human\u2019s brain is performing the functions that the paper associates with understanding\u2014assigning meaning to words and doing so not just by mapping the relative semantic relationships among them but by mapping them onto things in the real world. And that\u2019s something AIs can now do. (p. 72)<\/p>\n

Notice that final contrast between \u201cmapping the relative semantic relationships among\u201d and \u201cmapping them onto things in the real world.\u201d The contrast is obvious, but its implications are not at all what Wright thinks they are.<\/p>\n

Yes, the real world is full of things we can point to, apples, oranges, birds, bees, trees and flowers, mountains, lakes, the sky, clouds in the sky, the sun, the moon, the stars. But what of abstract things, such as truth and justice? Where do we see them? How do we point to them? What about atoms? Yes, they are physical things, but no one has ever seen an atom. These things are abstract. We understand them through complex webs of conceptual relationships, relationships which we track through the relationships between words.<\/p>\n

Back in 2016 Steven Harnad and his colleagues published a paper about the relationships between words in dictionaries, The Latent Structure of Dictionaries<\/a>. They found that a set of only 1% of the words in the dictionary was sufficient to define all the other words. The meanings of that 1% are then grounded in physical referents in the external world.<\/p>\n

Semantic relationships between words are thus far more important that Wright acknowledges. This is important for our understanding of LLMs, which are grounded entirely in a world of words, though we can now connect them to the visible world through models that are trained on images. Semantic relations between words, that\u2019s where almost all the action is.<\/p>\n

Just how this criticism affects Wright\u2019s account is not clear \u2013 things are never clear in these matters \u2013 but the issue he\u2019s wrestling with is whether or not LLMs can really understand language in the sense that humans do. On that issue I\u2019m attracted to a remark that Harnad uttered in a podcast at The Gradient<\/a>: \u201cWhat is most remarkable about [LLMs] is what they can accomplish without understanding.\u201d<\/p>\n

I\u2019ve got other problems with Wright\u2019s discussion of how LLMs work, but I want to move on. If you want to explore those kinds of issues, Bert Idem has published a useful discussion at Finite Ape<\/a>. It\u2019s time to zoom out to Wright\u2019s cosmic context.<\/p>\n

<\/a>Klaatu barada nikto<\/strong><\/p>\n