There’s more than one way to lose our humanity

How we treat immigrants and how AI might treat humans weighs on the mind of George Pitcher.

George Pitcher

George is a visiting fellow at the London School of Economics and an Anglican priest.

A grey multi-story accommodation barge floats beside a dock.

The Bibby Stockholm accommodation barge in Portland Harbour.

shley Smith, CC BY-SA 4.0 , via Wikimedia Commons.

“The greatness of humanity,” said Mahatma Gandhi, “is not in being human, but in being humane.” At first glance, this is something of a truism. But actually Gandhi neatly elides the two meanings of humanity in this tight little phrase.

Humanity means both the created order that we know as the human race and its capacity for self-sacrificial love and compassion. In the Christian tradition, we celebrate at Christmas what we call the incarnation – the divine sharing of the human experience in the birth of the Christ child.

Our God shares our humanity and in doing so, shows his humanity in the form of a universal and unconditional love for his people. So, it’s an act both for humanity and of humanity.

This Christmas, there are two very public issues in which humanity has gone missing in both senses. And it’s as well to acknowledge them as we approach the feast. That’s in part a confessional act; where we identify a loss of humanity, in both its definitions, we can resolve to do something about it. Christmas is a good time to do that.

The first is our loss of humanity in the framing of legislation to end illegal immigration to the UK. The second is the absence of humanity in the development of artificial intelligence. The former is about political acts that are inhumane and the latter goes to the nature of what it is to be human.

We have literally lost a human to our inhumanity, hanged in a floating communal bathroom. It’s enough to make us look away from the crib, shamed rather than affirmed in our humanity.

There is a cynical political line that the principal intention of the government’s Safety of Rwanda (Asylum and Immigration) Bill, voted through the House of Commons this week, is humane, in that it’s aimed at stopping the loss of life among migrants exploited by criminal gangs. But it commodifies human beings, turning them into cargo to be exported elsewhere. That may not be a crime – the law has yet to be tested – but it is at least an offence against humanity.

Where humanity, meaning what it is to be human, is sapped, hope withers into despair. When a human being is treated as so much freight, its value not only diminishes objectively but so does its self-worth. The suicide of an asylum seeker on the detention barge Bibby Stockholm in Portland Harbour is a consequence of depreciated humanity. Not that we can expect to hear any official contrition for that.

To paraphrase Gandhi, when we cease to be humane we lose our humanity. And we have literally lost a human to our inhumanity, hanged in a floating communal bathroom. It’s enough to make us look away from the crib, shamed rather than affirmed in our humanity.

That’s inhumanity in the sense of being inhumane. Turning now to humanity in the sense of what it means to be human, we’re faced with the prospect of artificial intelligence which not only replicates but replaces human thought and function.

To be truly God-like, AI would need to allow itself to suffer and to die on humanity’s part.

The rumoured cause of the ousting of CEO Sam Altman last month from OpenAI (before his hasty reinstatement just five days later) was his involvement in a shadowy project called Q-star, GPT-5 technology that is said to push dangerously into the territory of human intelligence.

But AI’s central liability is that it lacks humanity. It is literally inhuman, rather than inhumane. We should take no comfort in that because that’s exactly where its peril lies. Consciousness is a defining factor of humanity. AI doesn’t have it and that’s what makes it so dangerous.

To “think” infinitely quicker across unlimited data and imitate the best of human creativity, all without knowing that it’s doing so, is a daunting technology. It begins to look like a future in which humanity becomes subservient to its technology – and that’s indeed dystopian.

But we risk missing a point when our technology meets our theology. It’s often said that AI has the potential to take on God-like qualities. This relates to the prospect of its supposed omniscience. Another way of putting that is that it has the potential to be all-powerful.

The trouble with that argument is that it takes no account of the divine quality of being all-loving too, which in its inhumanity AI cannot hope to replicate. In the Christmastide incarnation, God (as Emmanuel, or “God with us”) comes to serve, not to be served. If you’ll excuse the pun, you won’t find that mission on a computer server.

Furthermore, to be truly God-like, AI would need to allow itself to suffer and to die on humanity’s part, albeit to defeat its death in a salvific way. Sorry, but that isn’t going to happen. We must be careful with AI precisely because it’s inhuman, not because it’s too human.

Part of what we celebrate at Christmas is our humanity and, in doing so, we may re-locate it. We need to do that if we are to treat refugees with humanity and to re-affirm that humanity’s intelligence is anything but artificial. Merry Christmas.

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21 June 2024

4 min read

It's our mistakes that make us human

What we learn distinguishes us from tech.

Silvianne Aspray

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.