In search of Martin Luther King

Wanting to put flesh on the bones of a much-fabled tale, Ian Hamlin begins a journey in search of his hero.

Ian Hamlin

Ian Hamlin has been the minister of a Baptist church since 1994. He previously worked in financial services.

A street mural of Martin Luther King quoting him.

An MLK commemorative mura.

Stories define us. Especially genesis stories, stories of formation, of how things began. Because beginnings often harbour within them all the seeds of future growth, defining so much of what’s to come, size, shape, colour, character even, and, what’s true of the natural world, is also, so often, true for our own life journeys.

As I embark upon a particular journey, in many ways the centrepiece of my three-month sabbatical break from my life in Christian ministry, I find myself reflecting on a bigger, longer, greater journey that has, consciously and unconsciously, shaped a good deal of that whole life.

I’m writing these words on a train, from Boston, Massachusetts to Washington DC, eight hours through a variety of weather, landscapes, and a whole variety of provincial, and city stations, some of them famous, others vaguely familiar, still more completely unknown. I’m off in search of flesh on the bones of a story, a much-fabled tale, of a man and his life.

I came across a book, a thin tome and looking pretty sorry for itself, clearly already well thumbed. I started to read it and quickly became transfixed.

But first, more of mine. I grew up, the youngest of four children, in a pretty traditional working-class family in Bristol that, by virtue, of my parents owning their own home and my two older brothers having gone to university at the end of the 60’s, now found itself, contrasted starkly with all of my Aunties and Uncles, knocking on the door of middle-class comfort.

By the early 80’s however, as I was preparing to leave school, that all looked, and felt, a little different. Not having acquired sufficient spiritual credits to attend the city’s church school, and with my brother’s academies having long since migrated to the private sector, I’d meandered my way through the local comprehensive, with enough wisdom to avoid most of the outcomes for which it was renowned, but not enough application to really supersede them all. What I did learn though, was a strong sense of justice, together with a certain perplexity as to why this wasn’t more universally shared and even, in some cases its absence appearing to be celebrated.

In our playing fields and its environs there was a pretty regular flow of what today would be called ‘racially aggravated incidents’. I vividly recall one boy in my year having his legs nastily broken. What I also remember though, was the daily ritual of being handed a National Front promotional leaflet at the school gate. Difference begetting antagonism, spawning violence and demanding retribution, seemed to be the story, I hated it, and instinctively railed against it.

My response was hardly dynamic or revolutionary. I think I went on a march or two, I remember buying a mug once, yes, I was that sort of kid, oh, and I put a poster on my wall. Again, a fairly generic image, probably bought from Athena, of a man, half a generation older than me and a whole world away. A man, on a platform, speaking, and some of the words he spoke, super-imposed over the top of him, ‘I have a dream …’

A short while later, at a friend’s house, I came across a book, a thin tome and looking pretty sorry for itself, clearly already well thumbed. I started to read it and quickly became transfixed, it was more speeches from this same man, yet these were different, they spoke more about motivation than outcomes, about the passionate ‘Why’ of action, more than the ‘How’ of achieving meaningful change. It was ‘Strength to Love’, a book or sermons for, I discovered this man was not a politician but a preacher.

To cut a long story short, this encounter, these thoughts, along with a few others, caused me to translate my hitherto rather semi-detached relationship with my local Baptist Church into something more committed. Within eight years I was in London, training for ministry, and I‘ve now been in Church leadership for 30 years.

For stories, rooted in truth, throw a spotlight on those lived, core beliefs, out of which glorious, effective, fulfilled lives develop.

And so, our stories intertwine, mine and Martin Luther King’s, oddly, unexpectedly, yet profoundly, and so I find myself on a train, to DC, and then on to Atlanta, Montgomery, Birmingham, to dig more into his story, to discover more of my own.

Because stories not only define us, they fuel us. Idealism is all well and good, but where does it come from, and how might it be sustained? Inspiration, is often illusive, a fiery necessity for a purposeful effective life, in any sphere, but it needs a source, something in which to be rooted. A craving for justice, an attraction towards generous love, a passion for human fulfilment, and a whole host of other things, all seem like good and obvious things, in and of themselves, but why? And, given they are frequently costly and hard fought, from where might the motivation come to make the necessary sacrifices? Martin Luther King did what he did because he believed what he believed, given that, it seemed obvious, inevitable, for him to act, whatever the cost. The Apostle Paul encouraged the first generation of Christian believers, living challenging lives at the heart of the empire, in Rome, to tell stories; ‘How can they hear unless someone tells them?’ he reasoned, and then, with a flourish, ‘How beautiful are the feet of those who bring good news!’

It seems we need preachers, storytellers, more than we do politicians. For stories, rooted in truth, throw a spotlight on those lived, core beliefs, out of which glorious, effective, fulfilled lives develop. With that knowledge in mind, I’m off on my journey, to experience tales, old and new, and see what they do to me, I’ll let you know what I discover.

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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.