Article
AI
Comment
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.  

Explainer
Ageing
Comment
Politics
3 min read

Jonathan Aitken: I’m in my 80s and here’s what I’d tell Joe Biden

Don't succumb to this politicians' fantasy.

Jonathan is a former politician, and now a prison chaplain.

President Biden sits at a desk, holding his balled hands to his mouth.
Biden in the Oval Office, 2022.
The White House.

I am the same age as President Biden. So part of my heart went out to him as I watched his catastrophic confrontation with Donald Trump last week.   

As we octogenarians know, or should know, our physical and mental faculties simply don’t work as well as they used to. If tested in the white heat of a Presidential debate, or at a multitude of far lower-level challenges, it is all too easy to slip, stumble or fall.  

These human weaknesses have been almost unchanged for time immemorial. They were painfully if poignantly expressed some 2,500 years ago in the Psalms of David: 

“The days of our age are threescore years and ten; and though men be so strong that they come to fourscore years: yet is their strength then but labour and sorrow; so soon passeth it away, and we are gone.”   

Modern optimists may try to argue with the ancient psalmist. In our 21st century era of vitamin pills, workouts in the gym, macrobiotic diets and intermittent fasting, we are all too willing to believe that we can postpone the arrival of the grim reaper or at least prolong our youthful vitality.   

Politicians are particularly susceptible to the fantasy that they can stay on their best form into old age longer than anyone else. “Age shall not weary us” they whisper to themselves, citing elderly successes such as Winston Churchill who became Prime Minister in 1940 aged 67, leaving Downing Street at the age of 80; William Gladstone who formed his last administration when he was 82; or Ronald Reagan who rode off into the sunset aged 77. 

There are many reasons why political leaders have a tendency to hold on to power beyond their sell by date. Their egos make them believe they are indispensable. Their courtiers, their staff and their appointees like to stay in power too. When the White House changes hands approximately 30,000 people lose their jobs, from mighty Cabinet Secretaries in Washington to humble rural postmasters in Hicksville. So there is a built-in bias for preserving the status quo, by fair means or by flattery. 

What President Biden now needs is loving, personal advice from his nearest and dearest, and wise political advice from disinterested friends whose candour he really trusts. Will he get it? 

My late wife, Elizabeth, was brave in giving what she called “frank notes” to all three of her husbands when she watched them perform on stage, on screen, or, in my case, in pulpits. 

Her movie star spouses, Rex Harrison and Richard Harris, were not always pleased when her notes criticised them for forgetting their lines, failing to sound consonants, or dropping their voices at the end of sentences. I, too, was sometimes less than appreciative, but I always took Elizabeth’s advice. Would that Jill Biden might now imitate such similar Elizabethan candour. 

In his perceptive article on this subject for Seen & Unseen, young Bishop Graham Tomlin (he’s about 20 years younger than me!) made excellent points about the calling of old age. To which I can cheerfully shout, as if I was still in the House of Commons: “Hear! Hear!” 

For, since being ordained at 74, I have found enormous fulfilment in the calling of prison chaplaincy, pastoral care, and preaching. These are not to be compared to the fastest tracks in competitive careers like politicians or investment bankers. Yet they have brought me great joy and I hope they have sometimes helped my prisoners and parishioners. 

The race is not always to be swift.