Riding from darkness to light

Long-distance cycle rides give Graeme Holdsworth time to contemplate traveling from light to darkness and back again. And, to grapple with the wordless way our bodies do what they were created to do.

Graeme Holdsworth

Graeme is a vicar of Marsden and Slaithwaite in West Yorkshire. He also cycles and juggles.

A cyclist ascends a village street between stone-built houses as twilight turns to night

An audax cyclist passes through a village as night falls.

I’m standing next to my bicycle at a petrol station in Blackpool, it is 1am. I’m eating a cheap cheese sandwich and drinking cold coffee from a can. What I want is hot coffee, but the machine only takes cash, and the cash machine charges for withdrawals. I’m making do with cheap and cold, because the need for calories outweighs the need for taste. On this night, I’m cycling from Slaithwaite to Blackpool and back, checking the route for a cycling event I’m organising. It’s an audax: a type of sporting experience typically documented by forecourt-chic social media posts. Its name is derived from the French for audacious.

A glance though long-distance cycling blogs, vlogs and curated media, hints at an experience of transcendence; the emptying of self, in the search of meaning from the zip of tyres over tarmac as the kilometres click past.

The reality, however, can be more mundane: long distance cycling often involves sitting on a weed strewn curb, while a friend fixes a puncture and though the clouds are not quite heavy enough to rain, there’s a mizziness to the air that seeps through your sportwool baselayer. There is no film crew to capture this epic moment, and you’re alone with your thoughts, which are mainly thankfulness that it isn’t your puncture.

I’m a vicar in West Yorkshire, but haven’t always been a vicar, or even a Christian and I’ve been riding bikes for much longer than I’ve been a person of faith. As a child cycling was about belonging, I was part of a BMX community whose hierarchy was measured by how high you could bunny-hop. Later, that belonging was replaced with a different sort of identity, found through music. It was only when I was older and fatter that I rediscovered cycling thanks to my wife, who thought we both needed some exercise.

We loved to explore, and perhaps this physical exploration was why we also began a journey of spiritual exploration.

Together we remembered how to cycle, and as we gathered experiences, we grew in the wisdom of the cyclo-tourist. We learned that mudguards and rain capes are things of comfort and therefore beauty. We loved to explore, and perhaps this physical exploration was why we also began a journey of spiritual exploration. I’ve no intention to suggest that cycling is a gateway drug to Christianity, more that perhaps our curiosity was being fed physically, mentally, and spiritually, in ways that were not of our making.

The first time I noticed a spiritual element to my cycling was coming back from a meeting, crossing the North Yorkshire Moors at night. It was autumn and the evening turned to dark quite early, leaving only a puddle of weak bike light to ride with. A phrase from morning prayer returned to me: ‘even the darkness is not dark to you’. A single line from a psalm in the Bible. This one line, on this one night, redefined my relationship with God. Even though all around me had turned to darkness, there was nowhere I could be lost from God.

These remote fans and supporters are constructing narratives to explain rider’s movement, or lack of it. Yet the rules of self-sufficiency mean you are alone, no one can set you back on the right path.

Not being lost is an important element to cycling a long distance, especially in a race. In events like the TransContinental – a multi-day self-sufficient cycle race across Europe, spending hours cycling in the wrong direction could be a racing disaster. Race winner Emily Chappell, in Where there’s a Will, eloquently documents the racer’s experience of being ‘watched over’. She tells of ‘dot-watchers’ following a rider’s GPS tracks across a map of Europe. These are remote fans and supporters constructing narratives to explain rider’s movement, or lack of it. Yet the rules of self-sufficiency mean you are alone, no one can set you back on the right path.

Being alone with your thoughts is a common theme to long distance cycling. While our bodies silently convert glucose into energy through glycolysis, and our muscle memory converts this into kilometres covered, our minds are set free to process our past and present experiences.

During my time at theological college, I wanted to explore the idea of physical exercise being an expression of prayer. I tried to grapple with the wordless way our bodies do what bodies were created to do. Can our bodies worship without words? Is there a physical language of lactic acid, originally written by a creator who celebrates when creation is true to itself? There’s a poetic language in the Bible that hints at this, that

‘the mountains and hills will burst into song before you, and all the trees of the field will clap their hands’.

Pro-cyclist Jens Voigt famously told his legs to shut up… maybe he should have let them sing.

Audaxing, long distance cycling, racing across continents; these are extraordinary journeys in which we might travel from light to darkness and back again. Simultaneously, there is a physical descent from adventurous confidence to uncertain determination, where the will to go on is no longer found in the legs, but in a dogmatic determination to see this through. Then, with the dawning of the day, there is a fresh hope: a hope of warmth and a return to strength. With the dawning of the day, the opening of the first coffee shop and this long-distance cyclist’s prayer is answered.

“O Lord, open my lips,

and I shall drink this coffee.”

Article

AI - Artificial Intelligence

Comment

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.