AI And God
The mind-body problem is a philosophical issue that questions the relationship between mental states, such as beliefs and desires, and physical states of the brain and body. It explores whether the mind and body are distinct entities or one interacting component, a debate primarily characterized by dualism and physicalism. Understanding this issue is crucial for fields like psychology, neuroscience, and cognitive science, as it influences how we perceive consciousness and self-awareness.
According to a UK study guide,
Physicalism (sometimes called materialism) is the view that everything that exists is ultimately physical. This includes mental states, which physicalists argue can be fully explained in terms of physical processes.
According to this view, consciousness, thoughts, and emotions are not separate from the body but are instead the product of brain activity.
. . . Unlike physicalism, dualism argues that the mind and body are fundamentally different kinds of things.
The most famous dualist, René Descartes, believed that the mind is a non-physical substance that is completely separate from but interacts with the physical body.
. . . If the mind is non-physical and the body is physical, how do they interact? How can something non-physical cause physical changes (like deciding to raise your hand and then actually doing it)?
Reynolds, because he either never took Philosophy 101 or he cheated, endorses the physicalism of the quack Ray Kurzweil; both believe it's possible to upload consciousness into a computer:
Kurzweil notes that computational capacity alone will not create artificial intelligence. He asserts that the best way to build machine intelligence is to first understand human intelligence. The first step is to image the brain, to peer inside it. Kurzweil claims imaging technologies such as PET and fMRI are increasing exponentially in resolution while he predicts even greater detail will be obtained during the 2020s when it becomes possible to scan the brain from the inside using nanobots.
Hey, right, it's the 2020s, so we've already scanned the brain from the inside using nanobots, right? He goes on,
Beyond reverse engineering the brain in order to understand and emulate it, Kurzweil introduces the idea of "uploading" a specific brain with every mental process intact, to be instantiated on a "suitably powerful computational substrate".
In other words, every mental process is a specific physical state that can be uploaded onto a computer. This is an absurdity. But the AI boondoggle takes this a step farther: we don't need to wait until we can upload Glenn Reynolds's brain into a computer to get consciousness, it's going to pop into existence on an AI data center ab nihilo! This is a version of the neo-Darwinian theory that a certain type of primeval goo came along, and hey presto, life started! But where did math come from? It isn't physical, it can't have just evolved.Another exponent of this weird AI-will-generate-consciousnmess (even though the brain is entirely physical) school of thought is Sebastian Mallaby, son of Sir Christopher Mallaby, who was Ambassador of the United Kingdom to Germany (1988–1993) and Ambassador of the United Kingdom to France (1993–1996), educated at Eton and Oxford, and husband of Zanny Minton Beddoes, Editor in Chief of The Economist, lately known for trying to debate Elon Musk. Just the guy to address the mind-body problem, woudln't you think? And he does it, in all places, at Foreign Affairs:
[C]ontemplating a technology that seems unfathomable in scope, humans reach for the lexicon that exists to describe mystery: that of religion. Nearly a decade ago, Anthony Levandowski, an early actor in Google’s self-driving car project, started a church called Way of the Future, whose IRS filings state that it is devoted to “the realization, acceptance, and worship of a Godhead based on Artificial Intelligence,” according to Wired. Encountering an early chatbot that appeared eerily sentient, the Google engineer Blake Lemoine wrote, “Who am I to tell God where He can and can’t put souls?”
. . . It was only a matter of time before the Catholic Church waded into this maelstrom. Following industrialization in the late nineteenth century, the rise of mass media in the mid-twentieth, and the birth of the knowledge economy in the late twentieth, the church responded with encyclicals, papal letters laying out how Catholic doctrine applied to each upheaval. Now the Vatican has stepped in again, defending its conception of human dignity and the purpose of creation in the face of the AI revolution. Pope Leo XIV’s Magnifica Humanitas (Magnificent Humanity), the first encyclical of his pontificate, is nothing if not ambitious.
. . . As technologists debate whether AI systems’ possible consciousness warrants a machine version of human rights, the pope insists that humans and machines differ fundamentally. AI systems “merely imitate certain functions of human intelligence,” the encyclical states. “Even when these tools are described as capable of ‘learning,’ . . . it is not the experience of those who allow themselves to be shaped by life and grow over time through choices, mistakes, forgiveness and fidelity.”
. . . Whether the church’s assertions withstand analytic scrutiny is a different question. By postulating that AI systems “merely imitate” human intelligence, Magnifica Humanitas rejects the long-standing claim that imitating intelligence is the same as possessing it. Far from suggesting an absence of intelligence, that theory goes, imitation may be a facet of it.
But now he gets to Philosophy 101, the mind-body problem, and the Chinese Room Experiment, which like the pope's encyclical gets things all wrong:
The best case for the Vatican’s opposing view dates to 1980, when the philosopher John Searle proposed what became known as the “Chinese room argument.” The goal of Searle’s thought experiment was to refute the famous Turing test, which holds that a machine should be judged only by its output. According to the test, if the system’s output appears intelligent to humans, then the system is indeed intelligent. By way of a rebuttal, Searle imagined a lone man in a room receiving messages under the door. The messages are written in Chinese, and the man passes back messages in Chinese, convincing his correspondent that he, too, is fluent in the language. But this persuasion is a con. The man composes his responses with the help of a manual that instructs him on which incoming string of Chinese characters should be answered with which other string of Chinese characters.
But that argument, like the pope, is now out of date:
Searle’s rebuttal was powerful during the years before the modern AI revolution. Machines based their outputs on rules that resembled the instruction manual in Searle’s scenario. Although they begin by ingesting words and treating them as statistics, they emerge from their training with a fine grasp of meaning.
Ah, OK, that settles it. But here's a study guide that explains how large language models work:
The key idea is that an LLM isn't "thinking" or "understanding" in a human sense. It's making a statistical calculation: based on the sequence of words (tokens) it has seen so far, what is the most probable next word?
. . . An LLM is often described as a 'stochastic parrot' that predicts the next token.
Let's go back to the lone man in the Chinese room. As of 1980, he was following specific if-then conditions regarding which Chinese message to pass out in response to whatever Chinese message he received. As of 2026, he's been doing this long enough that he has a good general idea of which Chinese message to pass out, and he's at least reaching for the one he's most used to passing out in response to the next one that comes in. But that doesn't mean he understands Chinese any better in 2026 than he did in 1980.He still can't read a word of Chinese, even if he's now passing out messages that say, "I'm sorry to hear that", since he himself still doesn't know what the message says. But Sebastian Mallaby -- you can't make up a name like that, any more than you can make up Zanny Minton Beddoes -- hasn't been reading his study guides. He goes on,
Today, modern AI systems, trained on text including novels, social media posts, and human emoting of all kinds, recognize anger, joy, shame, sadness, and anxiety. And they don’t merely recognize emotion. Their behavior can be made consistent with particular emotional states or personalities. By tweaking its settings, researchers can make a model upbeat or negative, honest or sycophantic. Unlike calculators, spreadsheets, or autocomplete systems, large language models can acquire what one might call temperament.
No, in the words of LLM experts, all an LLM does is calculate the statistical likelihood of one set of words appearing in the context of another set of words. If I pass words to it that are statistically related to sadness, it will return equivalent words in its answer, but it has no idea what those words actually mean. It only appears to acquire temperament via large-scale statistical association.In my post on August 7, I got AI to write a micro fiction piece that looked as though Lydia Davis had written it, and it did a brilliant job looking at the contexts of her subjects, grammar, structure, and vocabulary. In fact, it did such a brilliant job that it unintentionally turned out hilarious satire. AI has no idea what satire is, and it has no idea what contexts can be unintentionally funny. In this case, however sophisticated it may have seemed, it was just a guy in a Chinese room.
But now Sebastian reveals his basic lack of any sort of education:
The human brain is a physical object, composed of biological material that obeys the laws that govern the rest of the universe, computers included. Human brains, like computer brains, work on trickles of electricity; when they form an opinion or conceive a plan, they are processing information. The idea that the gooey mass inside the skull contains some ineffable, nonprogrammable essence—consciousness, spirit, or something else—may be intuitively appealing. But as an analytic matter, the idea is flimsy. And it will become even less convincing as AI continues to advance.
In other words, he's a physicalist. A machine brain is no different from a human or animal brain. If you upload Sebastian Mallaby's brain scan into a computer, you have the full Sebastian Mallaby. If the pope says that's not true, the pope is wrong. In effect, Sebastian is saying there's no moral difference between a human and an AI computer, because soon enough, they'll be the same thing. Contra the pope, who makes "slippery claims about human exceptionalism" everyone is basically a machine, especially if machnines can convince humans they're human. Or something like that, because in the end, I don't think he understands he's arguing against himself.
The final conspicuous gap concerns the debate over the nature of machine intelligence. The extent to which AI algorithms generate the equivalent of human thoughts and feelings is a philosophical question that may never be resolved, but understanding exactly how AI systems work is a practical and urgent goal.
But he's just spent 1600 words insisting it doesn't matter whather AI algorithms generate the equivalent of human thoughts and feelings, because they appear to, and the Chinese Room Experiment is beside the point. Now he's saying we have to go inside the Chinese Room and figure out what the guy is actually doing:
Magnifica Humanitas claims that we cannot know the thinking inside the machines, because there is no thinking in them worth knowing. But the opposite is true. Machines will never join our moral universe, but if humans aspire to control them, we must first understand them.
The best I can offer is this is what you'd expect from someone named Sebastian Mallaby who's married to someone named Zanny Minton Beddoes, neither of whom took Philosophy 101, or if they did, they cheated.