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AI - Artificial Intelligence
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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.  

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AI - Artificial Intelligence
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4 min read

It's our mistakes that make us human

What we learn distinguishes us from tech.

Silvianne Aspray is a theologian and postdoctoral fellow at the University of Cambridge.

A man staring at a laptop grimmaces and holds his hands to his head.
Francisco De Legarreta C. on Unsplash.

The distinction between technology and human beings has become blurry: AI seems to be able to listen, answer our questions, even respond to our feelings. It becomes increasingly easy to confuse machines with humans. In this situation, it is increasingly important to ask: What makes us human, in distinction from machines? There are many answers to this question, but for now I would like to focus on just one aspect of what I think is distinctively human: As human beings, we live and learn in time.  

To be human means to be intrinsically temporal. We live in time and are oriented towards a future good. We are learning animals, and our learning is bound up with the taking of time. When we learn to know or to do something, we necessarily make mistakes, and we take practice. But keeping in view something we desire – a future good – we keep going.  

Let’s take the example of language. We acquire language in community over time. Toddlers make all sorts of hilarious mistakes when they first try to talk, and it takes them a long time even to get single words right, let alone to try and form sentences. But they keep trying, and they eventually learn. The same goes with love: Knowing how to love our family or our neighbours near and far is not something we are good at instantly. It is not the sort of learning where you absorb a piece of information and then you ‘get’ it. No, we learn it over time, we imitate others, we practice and even when we have learned, in the abstract, what it is to be loving, we keep getting it wrong. 

This, too, is part of what it means to be human: to make mistakes. Not the sort of mistakes machines make, when they classify some information wrongly, for instance, but the very human mistake of falling short of your own ideal. Of striving towards something you desire – happiness, in the broadest of terms – and yet falling short, in your actions, of that very goal. But there’s another very human thing right here: Human beings can also change. They – we – can have a change of heart, be transformed, and at some point in time, actually start to do the right thing – even against all the odds. Statistics of past behaviours, do not always correctly predict future outcomes. Part of being human means that we can be transformed.  

Transformation sometimes comes suddenly, when an overwhelming, awe-inspiring experience changes somebody’s life as by a bolt of lightning. Much more commonly, though, such transformation takes time. Through taking up small practices, we can form new habits, gradually acquire virtue, and do the right thing more often than not. This is so human: We are anything but perfect. As Christians would say: We have a tendency to entangle ourselves in the mess of sin and guilt. But we also bear the image of the Holy One who made us, and by the grace and favour of that One, we are not forever stuck in the mess. We are redeemed: are given the strength to keep trying, despite the mistakes we make, and given the grace to acquire virtue and become better people over time. All of this to say that being human means to live in time, and to learn in time. 

So, this is a real difference between human beings and machines: Human beings can, and do strive toward a future good. 

Now compare this to the most complex of machines. We say that AI is able to “learn”. But what does it mean to learn, for AI? Machine learning is usually categorized into supervised learning, unsupervised and self-supervised learning. Supervised learning means that a model is trained for a specific task based on correctly labelled data. For instance, if a model is to predict whether a mammogram image contains a cancerous tumour, it is given many example images which are correctly classed as ‘contains cancer’ or ‘does not contain cancer’. That way, it is “taught” to recognise cancer in unlabelled mammograms. Unsupervised learning is different. Here, the system looks for patterns in the dataset it is given. It clusters and groups data without relying on predefined labels. Self-supervised learning uses both methods: Here, the system uses parts of the data itself as a kind of label – such as, for instance, predicting the upper half of an image from its lower half, or the next word in a given text. This is the predominant paradigm for how contemporary large-scale AI models “learn”.  

In each case, AI’s learning is necessarily based on data sets. Learning happens with reference to pre-given data, and in that sense with reference to the past. It may look like such models can consider the future, and have future goals, but only insofar as they have picked up patterns in past data, which they use to predict future patterns – as if the future was nothing but a repetition of the past.  

So this is a real difference between human beings and machines: Human beings can, and do strive toward a future good. Machines, by contrast, are always oriented towards the past of the data that was fed to them. Human beings are intrinsically temporal beings, whereas machines are defined by temporality only in a very limited sense: it takes time to upload data, and for the data to be processed, for instance. Time, for machines, is nothing but an extension of the past, whereas for human beings, it is an invitation to and the possibility for being transformed for the sake of a future good. We, human beings, are intrinsically temporal, living in time towards a future good – which machines do not.  

In the face of new technologies we need a sharpened sense for the strange and awe-inspiring species that is the human race, and cultivate a new sense of wonder about humanity itself.