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.

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Mental Health

1 February 2024

4 min read

We need to weep over the wreckage of mental illness

While its now OK to talk about mental illnesses, we need to weep over the harm caused and how we’ve tried to treat them, writes Rachael Newham.

Rachael Newham

Rachael is an author and theology of mental health specialist.

A grey and white wall graffited with a tag a image of a person crumpled and crying.

Today, February 1st, is Time to Talk Day. It's part of a long-running campaign encouraging people to have open and honest conversations about mental health. It's aim is to break down the barriers of stigma and misunderstanding. It has been a staggering success - what was a fringe issue talked by those only affected by mental illness a decade ago is now part of common parlance. Mental health training is widely available, and the charity’s work has been seen to have a significant positive impact on the mental health conversation

However, as our familiarity with the language of mental health has grown so too has the way we use it. People might talk about having PTSD after a bad date, or their friend being ‘so OCD’ about the way they organise. Unwittingly, as psychotherapist and author Julia Samuels points out, “[we have] awareness without real understanding.”

However, awareness without understanding means we actually don’t reach those most impacted by mental illness. We know about mental health in the way we know about our physical health - but we are no more aware about the serious, sometimes lifelong mental illnesses which rob people of hope, joy and vitality - sometimes leaving them with lifelong disability.

If you ask most people about mental illness they may tell you about depression and anxiety; the two most common mental illnesses which have become the acceptable face of mental illness. It’s reflected in the way funding is channeled to interventions that get people with mental illnesses back to work, or to NHS ‘Talking Therapies’ which offers short term psychological therapies (both of which are important initiatives) but have cut the number of inpatient beds from over 50,000 in 2001 to under 25,000 in 2022[3] which means those at the more severe end of the spectrum of mental health to mental illness are left to travel 300 miles for the care they need.

We have to survey the wreckage that severe and enduring mental illness causes, before we can begin to rebuild a society that is kinder - without prejudice or stigma.

Whilst it’s right that we have raised awareness about the most common conditions, we can’t ignore the illnesses which are termed ‘severe and enduring mental illnesses’ which include those such as bipolar disorder, major depression, schizophrenia and complex post-traumatic stress disorder.

For people living with these conditions, the general mental health advice that we give; for example getting enough sleep and time outdoors may not be enough to keep the symptoms at bay. Just as general physical health advice like getting your five a day will not cure or prevent all severe physical illnesses. Medication, hospitalisation, and at times even restrictions of freedom like being detained under the mental health act might be necessary to save lives.

These are stories that we need to hear. The debilitating side effects of life saving medications that can raise blood pressure, cause speech impediments. The injustices to confront (such as the fact that black people are five times more likely to be detained under the mental health act than their white counterparts) and the adjustments to life that those with disabilities are required to make to their lives.

We have to survey the wreckage that severe and enduring mental illness causes, before we can begin to rebuild a society that is kinder - without prejudice or stigma. We have to listen to the perhaps devastating, perhaps uncomfortable stories of those who live with severe and enduring mental illness. The mental health npatient units miles from home, the lack of freedom, the searing - unending grief.

Weep for the lives lost, the crumbling systems, the harm caused both by mental illness and the way we’ve tried to treat them.

By hearing these stories, we are accepting them as a part of reality. For those of us in churches it might be that the healing didn’t come in the way we expected, it might be also be all of us accepting that the systems designed to care for those with mental illness have in fact, caused more harm. It’s seeing the injustices and understanding that we, our systems and professionals need to change our attitudes.

Understanding and acceptance of the injustice are the way forward- that’s the only way change can come.

It might look like standing in the rubble, it might feel too huge and all but hopeless.

And yet in scripture and in life that is so often the only way we can begin to rebuild.

In the book of Nehemiah, one of the Old Testament prophets who had lived in exile far away from home for his whole life, we see that upon hearing about the state of the walls of Jerusalem, before he did any of the things we expect heroes and innovators to do- he wept. In fact, it’s estimated that for four months he wept over the state of the place that had once been the envy of the ancient world.

Perhaps we too need hear the stories and then weep.

Weep for the lives lost, the crumbling systems, the harm caused both by mental illness and the way we’ve tried to treat them and then slowly, we can begin the work of rebuilding.

It isn’t a work that can be done alone by a single agency much less a single person - it requires society to hear stories of the more than just ‘palatable’ mental illnesses with neat and tidy endings to the messy and sometimes traumatic stories that are there if we just care to listen to them. It might be reflected in the petitions we sign, the way we vote, the stories we choose to read.

So ,this Time to Talk Day - I’m saying let’s continue the amazing work of talking about mental health - we need to keep talking about anxiety and depression. But let us also make conversations wider, so that they encompass the whole continuum of mental health and illness.

We’ve seen the difference Time to Talk can make - now it’s time to talk about severe and enduring mental illnesses, too.