Essay
AI
Comment
11 min read

The summit of humanity: decoding AI's affectations

An AI summit’s prophecies need to be placed in the right philosophical register, argues Simon Cross. Because being human in an AI age still means the same thing it has for millennia.

Simon Cross researches ethical aspects of technology and advises on the Church’s of England's policy and legislative activity in these areas.

An AI generated image of robot skulls with bulging eyes on a shelf receding diagonally to the left.
Alessio Ferretti on Unsplash.

The UK’s global artificial intelligence (AI) conference is nearly upon us. If the UK had a ‘prophecy office’ it would have issued a yellow or even amber warning for the first days of November by now. Prophecy used to be a dangerous business, the ancient text of Deuteronomy sanctioned death for false prophets, equating its force with a leading away from God as the ultimate ground of truth. But risks duly acknowledged, here is a prophecy about the prophecies to come. The global AI conference will loudly proclaim three core prophecies about AI. 

  1. This time it’s different. Yes, we said that before but this time it really is different. 
  2. Yes, we need global regulation but, you know, it’s complicated so only the kind of regulation we advise is going to work.  
  3. Look, if we don’t do this someone else will. So, you should get out of our way as much as you possibly can. We are the good guys and if you slow us down the bad guys will win. 

I feel confident about this prediction not because I wish to claim the office of prophet but because just like Big Tobacco and Big Oil, Big Tech’s lobbyists will redeploy a tried and tested playbook. And here are the three plays at the heart of it. 

Tech exceptionalism. (We deserve to be treated differently under the law.) 

Regulatory capture. (We got lucky, last time, with the distinction between platform and publisher that permitted self-regulation of social media, the harvesting of personal data and manipulative design for attention, but the costs of defeating Uber in California and now defending rearguard anti-trust lawsuits means lesson learned, we need to go straight for regulatory capture this time). 

Tech determinism. (If we don’t do it, someone else will. We are the Oppenheimers here.) 

Speaking of Pandora 

What should we make of these claims? We need to start by exploring an underlying premise. One that typically goes like this “AI is calling into question what it means to be human”. 

This premise has become common currency, but it is flawed because it is too totalising. AI emphatically is calling into question a culturally dominant version of human anthropology – one specific ‘science of humanity’. But not all anthropologies. Not the Christian anthropology.  

A further, unspoken, premise driving this claim becomes clearer when we survey the range of responses to the question “what does the advent of what the government is now calling ‘frontier’ AI portend?”  

Either, it means we have finally prized open Pandora’s box; the last thing humans will ever create. AI is our Darwinian evolutionary heir, soon to make us homo sapiens redundant, extinct, even. Which could happen in two very different ways. For some, AI is the vehicle to a new post-human eternal life of ease, roaming the farthest reaches of the universe in disembodied digital repose. To others, AI is now on the very cusp of becoming abruptly and infinitely cleverer than us. To yet others, we are too stupid to avoid blowing ourselves up on the way to inventing so-called artificial general intelligence.  

Cue main global summit speaking points… 

Or, 

AI is just a branch of computing. 

Which of these two starkly contrasting options you choose will depend on your underlying beliefs about ‘what it means to be human’. 

Universal machines and meat machines 

Then again, what does it mean to be artificially intelligent? Standard histories of AI always point to two seminal events. First, Alan Turing published a paper in the 1930s in which he proposed a device called a Universal Turing Machine.  

Turing’s genius was to see a way of writing a type of programme to control a computer’s underlying binary on/off in ways that could vary depending on the task required and yet perform any task a computer can do. The reason your computer is not just a calculator but an excel spreadsheet and a word processor and a video player as well is because it is a kind of Universal Turing Machine. A UTM can compute anything that can be computed. If it has the right programme.  

The second major event in AI folklore was a conference at Dartmouth College in the USA in the early 1950s bringing together the so-called ‘godfathers of AI’.

 This conference set the philosophical and practical approaches from which AI has developed ever since. That this happened in America is important because of the strong link between universities, government, the defence and intelligence industry and the Big Tech Unicorns that have emerged from Silicon Valley to conquer the world. That link is anthropological; it is political, social, and economic and not just technical. 

Let’s take this underlying question of ‘what does it mean to be human?’ and recast it in a binary form as befits a computational approach; ‘Is a human being a machine or is a human being an organism?’ 

Cognitive scientist Daniel Dennett was recently interviewed in the New York Times. For Dennett our minds and bodies are a “consortia of tiny robots”. Dennett is an evolutionary biologist and a powerful voice for a particular form of atheism and its answer to the question ‘what does it mean to be human?’ Dennett regards consciousness as ephemera, a by-product of brain activity. Another godfather of AI, Marvin Minsky, famously described human beings as ‘meat machines.’

By contrast, Joseph Weizenbaum was also one of the early computer pioneers in the 1960s and 1970s. Weizenbaum created one of the first ever chatbots, ELIZA– and was utterly horrified at the results. His test subjects could not stop treating ELIZA as a real person. At one point his own secretary sat down at the terminal to speak to ELIZA and then turned to him and asked him to leave the room so she could have some privacy. Weizenbaum spent the latter part of his professional life arguing passionately that there are things we ought not to get computers to do even if they can, in principle, perform them in a humanlike manner. To Joseph Weizenbaum computers were/are fundamentally different to human beings in ways that matter ineluctably, anthropologically. And it certainly seems as if the full dimensionality of human being cannot yet be reduced to binary on/off internal states without jettisoning free will, consciousness and transcendence. Prominent voices like Dennett and Yuval Noah Harari are willing to take this intellectual step. Their computer says ‘no’. By their own logic it could not say otherwise. In which case here’s a third way of asking that seemingly urgent and pressing question about human being;  

“Are we just warm, wet, computers?” 

The immanent frame 

A way to make sense of this, for many people, influential and intuitively attractive meaning of human being is to understand how the notion of artificial intelligence fits a particular worldview that has come to dominate recent decades and, indeed, centuries. 

In 2007 Charles Taylor wrote A Secular Age. In it he tracks the changing view of what it means to be human as the Western Enlightenment unfolds. Taylor detects a series of what he calls ‘subtraction stories’ that gradually explain away the central human experience of transcendence until society is left with what he calls an ‘immanent frame’. Now we are individual ‘buffered selves’ insulated by rational mind so that belief in any transcendent reality, let alone God, is just one possible choice among personal belief systems. But, says Taylor, this fracturing of a shared overarching answer to the question ‘What does it mean to be human’ over the past, say, 500 years doesn’t actually answer the question or resolve the ambiguities. Rather, society is now subject to what Taylor calls ‘cross pressures’ and a lack of societal consensus about the answers to the biggest questions of human meaning and purpose. 

In this much broader context, it becomes easier to see why as well as how it can be the case that AI is either a profound anthropological threat or just a branch of computing – depending on who you talk to… 

The way we describe AI profoundly influences our understanding of it. When Dennett talks about a ‘consortia of tiny robots’ is he speaking univocally or metaphorically? What about when we say that AI “creates”, or “decides” or “discovers” or ‘seeks to maximise its own reward function’. How are we using those words? If we mean words like ‘consortia’ or ‘choose’ and ‘reward’ in as close to the human sense as makes no difference, then of course the difference between us and our machines becomes paper-thin. But are human beings really a kind of UTM? Are UTMs really universal? Are you a warm wet computational meat-machine?  

Or is AI just the latest and greatest subtraction story?

To say AI is just a branch of computing is not to say the harms of outsourcing key features of human being to machines are trivial. Quite the opposite. 

How then should we judge prophecies about AI emanating from this global conference or in the weeks and months to follow?  I suggest two responses. The first follows from my view of AI, the other from my view of human being.  

Our view of current AI should be clear eyed, albeit open to revision should future development(s) so dictate. I am firmly on the side of those who, without foreclosing the possibility, see no philosophical breakthrough in the current crop of tools and techniques. These are murky philosophical waters but clocks don’t really have human hands now do they, and a collapsed metaphor can’t validate itself however endemic the reference to the computational theory of mind has become.  

Google’s large language model, Bard, for example, has no sense of what time it is where ‘he’ is, let alone can freely choose to love you or not, or to forgive you if you hurl an insult at ‘him’. But all kinds of anthropological harms already flow from the unconscious consequences of re-tuning human being according to the methodological image of our machines. To say AI is just a branch of computing is not to say the harms of outsourcing key features of human being to machines are trivial. Quite the opposite. 

Which brings me to the second response. When you hear the now stock claim that AI is calling into question what it means to be human, don’t buy it. Push back. Point out the totalising lack of nuance. The latest tools and techniques of AI are calling a culturally regnant but philosophically reductive anthropology into question. That much is definitely true. But that is all. 

And it is important to resist this totalising claim because if we don’t, an increasingly common and urgent debate about the fullness of human being and the limitations of UTMs will struggle from the start. One of the biggest mistakes I think public theology made twenty-some years ago was to cede a normative use of language that distinguished between people of faith and people of no faith. There is no such thing as being human without faith commitments of one kind or another. If you have any doubt about this, I commend No One Sees God: The Dark Night of Atheists and Believers by Michael Novak. But the problem with accepting the false distinction between ‘having faith’ and having ‘no faith’ is that it has allowed the Dennetts and Hararis of this world to insist that atheism is on a stronger philosophical footing than theism. After which all subsequent debate had, first, to establish the legitimacy of faith per se before getting to the particular truth claims in, say, Christianity.  

What it means to be human 

I see a potentially similar misstep for anthropology – the science of human being – in this new and contemporary context of AI. Everywhere at the moment, and I mean but everywhere, a totalising claim is being declared ever more loudly and urgently: that the tools and techniques of AI are calling into question the very essence of human identity. The risk in ceding this claim is that we get stuck in an arid debate about content instead of significance; a debate about ‘what it means to be human’ instead of a debate about ‘what it means to be human.’  

This global AI summit’s proclamations and prophecies need to be placed in the right philosophical register, because to be human in an age of AI still means the same thing it has for millennia.  

Universals like wonder, love, justice, the need for mutually meaningful relationships and a sense of purpose, and so too personal idiosyncrasies like a soft spot for the moose are central features of what it means to be this human being.  

Suchlike are the essential ingredients of the ‘me’ that is reading this article. They are not tertiary. Perhaps they can be computationally mimicked but that does not mean they are, in themselves, ephemeral or mere artifice. In which case their superficial mimicry carries substantial risks, just as Joseph Weizenbaum prophesied in Computer Power and Human Reason in the 1970s.  

Of course, you may disagree. You may even disagree in good faith, for there are no knockdown arguments in metaphysics. And in my worldview, you are free to do so. But fair warning. If the human-determinism of Dennett or the latest prophecies of Harari are right, no credit follows. You, and they, are right only because by arbitrary alignment of the metaphysical stars, you, and they, have never been free to be wrong. It was all decided long ago. No need for prophecies. We are all just UTMs with the soul of a marionette  

But when you hear the three Global summit prophecies I predicted earlier, consider these three alternatives; 

This time is not different, it is not true that AI is calling into question all anthropologies. AI is (only) calling into question a false and reductive Enlightenment prophecy about ‘what it means to be human.’  

The perennial systematic and doctrinal anthropology of Christianity understands human being as free-willed, conscious, unified body soul and spirit.  It offers credible answers to the urgent questions and cross-pressures society is now wrestling with. It also offers an ethical framework for answering the question ‘what ought computers to be used for and what ought computers not to be used for – even if they appear able to be used for anything and everything? 

This Christian philosophical perspective on the twin underlying metaphysical questions of human being and purpose are not being called into question, either at this global summit or by any developments in AI today or the foreseeable future. They can, however, increasingly be called into service to answer those questions – at least for those with ears to hear.  

Article
AI
Attention
Culture
5 min read

Will AI’s attentions amplify or suffocate us?

Keeping attention on the right things has always been a problem.

Mark is a research mathematician who writes on ethics, human identity and the nature of intelligence.

A cute-looking robot with big eyes stares up at the viewer.
Robots - always cuter than AI.
Alex Knight on Unsplash.

Taking inspiration from human attention has made AI vastly more powerful. Can this focus our minds on why attention really matters? 

Artificial intelligence has been developing at a dizzying rate. Chatbots like ChatGPT and Copilot can automate everyday tasks and can effortlessly summarise information. Photorealistic images and videos can be generated from a couple of words and medical AI promises to revolutionise both drug discovery and healthcare. The technology (or at least the hype around it) gives an impression of boundless acceleration. 

So far, 2025 has been the year AI has become a real big-ticket political item. The new Trump administration has promised half a trillion dollars for AI infrastructure and UK prime minister Keir Starmer plans to ‘turbocharge’ AI in the UK. Predictions of our future with this new technology range from doom-laden apocalypse to techno-utopian superabundance. The only certainty is that it will lead to dramatic personal and social change. 

This technological impact feels even more dramatic given the relative simplicity of its components. Huge volumes of text, image and videos are converted into vast arrays of numbers. These grids are then pushed through repeated processes of addition, multiplication and comparison. As more data is fed into this process, the numbers (or weights) in the system are updated and the AI ‘learns’ from the data. With enough data, meaningful relationships between words are internalised and the model becomes capable of generating useful answers to questions. 

So why have these algorithms become so much more powerful over the past few years? One major driver has been to take inspiration from human attention. An ‘attention mechanism’ allows very distant parts of texts or images to be associated together. This means that when processing a passage of conversation in a novel, the system is able to take cues on the mood of the characters from earlier in the chapter. This ability to attend to the broader context of the text has allowed the success of the current wave of ‘large language models’ or ‘generative AI’. In fact, these models with the technical name ‘Transformer’ were developed by removing other features and concentrating only on the attention mechanisms. This was first published in the memorably named ‘Attention is All You Need’ paper written by scientists working at Google in 2017. 

If you’re wondering whether this machine replication of human attention has much to do with the real thing, you might be right to be sceptical. That said, this attention-imitating technology has profound effects on how we attend to the world. On the one hand, it has shown the ability to focus and amplify our attention, but on the other, to distract and suffocate it. 

Attention is a moral act, directed towards care for others.

A radiologist acts with professional care for her patients. Armed with a lifetime of knowledge and expertise, she diligently checks scans for evidence of malignant tumours. Using new AI tools can amplify her expertise and attention. These can automatically detect suspicious patterns in the image including very fine detail that a human eye could miss. These additional pairs of eyes can free her professional attention to other aspects of the scan or other aspects of the job. 

Meanwhile, a government acts with obligations to keep its spending down. It decides to automate welfare claim handling using a “state of the art” AI system. The system flags more claimants as being overpaid than the human employees used to. The politicians and senior bureaucrats congratulate themselves on the system’s efficiency and they resolve to extend it to other types of payments. Meanwhile, hundreds of thousands are being forced to pay non-existent debts. With echoes of the British Post Office Horizon Scandal, the 2017-2020 the Australian Robo-debt scandal was due to flaws in the algorithm used to calculate the debts. To have a properly functioning welfare safety net, there needs to be public scrutiny, and a misplaced deference to machines and algorithms suffocated the attention that was needed.   

These examples illustrate the interplay between AI and our attention, but they also show that human attention has a broader meaning than just being the efficient channelling of information. In both cases, attention is a moral act, directed towards care for others. There are many other ways algorithms interact with our attention – how social media is optimised to keep us scrolling, how chatbots are being touted as a solution to loneliness among the elderly, but also how translation apps help break language barriers. 

Algorithms are not the first thing to get in the way of our attention, and keeping our attention on the right things has always been a problem. One of the best stories about attention and noticing other people is Jesus’ parable of the Good Samaritan. A man lies badly beaten on the side of the road after a robbery. Several respectable people walk past without attending to the man. A stranger stops. His people and the injured man’s people are bitter enemies. Despite this, he generously attends to the wounded stranger. He risks the danger of stopping – perhaps the injured man will attack him? He then tends the man’s wounds and uses his money to pay for an indefinite stay in a hotel. 

This is the true model of attention. Risky, loving “noticing” which is action as much as intellect. A model of attention better than even the best neuroscientist or programmer could come up with, one modelled by God himself. In this story, the stranger, the Good Samaritan, is Jesus, and we all sit wounded and in need of attention. 

But not only this, we are born to imitate the Good Samaritan’s attention to others. Just as we can receive God’s love, we can also attend to the needs of others. This mirrors our relationship to artificial intelligence, just as our AI toys are conduits of our attention, we can be conduits of God’s perfect loving attention. This is what our attention is really for, and if we remember this while being prudent about the dangers of technology, then we might succeed in elevating our attention-inspired tools to make AI an amplifier of real attention. 

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