Article
AI - Artificial Intelligence
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.  

Article
Belief
Creed
Identity
Truth and Trust
5 min read

Calls to revive the Enlightenment ignore its own illusions

Returning to the Age of Reason won’t save us from post-Truth

Alister McGrath retired as Andreas Idreos Professor of Science and Religion at Oxford University in 2022.

In the style of a Raeburn portrait, a set of young people lounge around on their phones looking diffident
Enlightened disagreement (with apologies to Henry Raeburn).
Nick Jones/Midjourney.ai.

Is truth dead? Are we living in a post-truth era where forcefully asserted opinions overshadow evidence-based public truths that once commanded widespread respect and agreement? Many people are deeply concerned about the rise of irrational beliefs, particularly those connected to identity politics, which have gained considerable influence in recent years. It seems we now inhabit a culture where emotional truths take precedence, while factual truths are relegated to a secondary status. Challenging someone’s beliefs is often portrayed as abusive, or even as a hate crime. Is it any surprise that irrationality and fantasy thrive when open debate and discussion are so easily shut down? So, what has gone wrong—and what can we do to address it? 

We live in an era marked by cultural confusion and uncertainty, where a multitude of worldviews, opinions, and prejudices vie for our attention and loyalty. Many people feel overwhelmed and unsettled by this turmoil, often seeking comfort in earlier modes of thinking—such as the clear-cut universal certainties of the eighteenth-century “Age of Reason.” In a recent op-ed in The Times, James Marriott advocates for a return to this kind of rational thought. I share his frustration with the chaos in our culture and the widespread hesitation to challenge powerful irrationalities and absurdities out of fear of being canceled or marginalized. However, I am not convinced that his proposed solution is the right one. We cannot simply revert to the eighteenth century. Allow me to explain my concerns. 

What were once considered simple, universal certainties are now viewed by scholars as contested, ethnocentric opinions. These ideas gained prominence not because of their intellectual merit, but due to the economic, political, and cultural power of dominant cultures. “Rationality” does not refer to a single, universal, and correct way of thinking that exists independently of our cultural and historical context. Instead, global culture has always been a bricolage of multiple rationalities. 

The great voyages of navigation of the early seventeenth century made it clear that African and Asian understandings of morality and rationality differed greatly from those in England. These accounts should have challenged the emerging English philosophical belief in a universal human rationality. However, rather than recognizing a diverse spectrum of human rationalities—each shaped by its own unique cultural evolution—Western observers dismissed these perspectives as “primitive” or “savage” modes of reasoning that needed to be replaced by modern Western thought. This led to forms of intellectual colonialism, founded on the questionable assumption that imposing English rational philosophies was a civilizing mission intended to improve the world. 

Although Western intellectual colonialism was often driven by benign intentions, its consequences were destructive. The increasing influence of Charles Darwin’s theory of biological and cultural evolution in the late nineteenth century led Darwin’s colleague, Alfred Russel Wallace, to conclude that intellectually and morally superior Westerners would “displace the lower and more degraded races,” such as “the Tasmanian, Australian and New Zealander”—a process he believed would ultimately benefit humanity as a whole. 

We can now acknowledge the darker aspects of the British “Age of Reason”: it presumed to possess a definitive set of universal rational principles, which it then imposed on so-called “primitive” societies, such as its colonies in the south Pacific. This reflected an ethnocentric illusion that treated distinctly Western beliefs as if they were universal truths. 

A second challenge to the idea of returning to the rational simplicities of the “Age of Reason” is that its thinkers struggled to agree on what it meant to be “rational.” This insight is often attributed to the philosopher Alasdair MacIntyre, who argued that the Enlightenment’s legacy was the establishment of an ideal of rational justification that ultimately proved unattainable. As a result, philosophy relies on commitments whose truth cannot be definitively proven and must instead be defended on the basis of assumptions that carry weight for some, but not for all. 

We have clearly moved beyond the so-called rational certainties of the “Age of Reason,” entering a landscape characterized by multiple rationalities, each reasonable in its own unique way. This shift has led to a significant reevaluation of the rationality of belief in God. Recently, Australian atheist philosopher Graham Oppy has argued that atheism, agnosticism, and theism should all be regarded as “rationally permissible” based on the evidence and the rational arguments supporting each position. Although Oppy personally favours atheism, he does not expect all “sufficiently thoughtful, intelligent, and well-informed people” to share his view. He acknowledges that the evidence available is insufficient to compel a definitive conclusion on these issues. All three can claim to be reasonable beliefs. 

The British philosopher Bertrand Russell contended that we must learn to accept a certain level of uncertainty regarding the beliefs that really matter to us, such as the meaning of life. Russell’s perspective on philosophy provides a valuable counterbalance to the excesses of Enlightenment rationalism: “To teach how to live without certainty, and yet without being paralyzed by hesitation, is perhaps the chief thing that philosophy, in our age, can still do for those who study it.” 

Certainly, we must test everything and hold fast to what is good, as St Paul advised. It seems to me that it is essential to restore the role of evidence-based critical reasoning in Western culture. However, simply returning to the Enlightenment is not a practical solution. A more effective approach might be to gently challenge the notion, widespread in some parts of our society, that disagreement equates to hatred. We clearly need to develop ways of modelling a respectful and constructive disagreement, in which ideas can be debated and examined without diminishing the value and integrity of those who hold them. This is no easy task—yet we need to find a way of doing this if we are to avoid fragmentation into cultural tribes, and lose any sense of a “public good.” 

Support Seen & Unseen

Since Spring 2023, our readers have enjoyed over 1,500 articles. All for free. 
This is made possible through the generosity of our amazing community of supporters.

If you enjoy Seen & Unseen, would you consider making a gift towards our work?

Do so by joining Behind The Seen. Alongside other benefits, you’ll receive an extra fortnightly email from me sharing my reading and reflections on the ideas that are shaping our times.

Graham Tomlin
Editor-in-Chief