How to shape peace today

On International Day of Peace, Christine Schliesser counts today’s conflicts, deliberately imagines peace, and recalls an old song.

Christine Schliesser

Christine Schliesser lectures in Theology and Ethics at Zurich University, and is a scientific collaborator with the Center for Faith & Society at Fribourg University.

a dirt barricade blocks a cross roads, behind which stands a roadside cross

A crossroads in Ukraine.

Jonny Gios on Unsplash.

One in four. This is the number of people living in conflict-affected areas on this planet. A record 100 million people have been forcibly displaced worldwide. Psychologists tell us that we can only process numbers in the two-digit realm in a meaningful way. Any number larger than that eclipses our capacities to attach a face, a story, an existence to that number. 100,000,000 is simply too large to picture. So imagine the entire UK population on the run, plus the population of Australia, plus that of Hongkong. In 2022, 16,988 civilians were killed in armed conflicts, which is a 53 per cent increase compared to the year before. And as you read these lines, there are 32 ongoing violent conflicts in the world, including drug wars, terrorist insurgencies, ethnic conflict, and civil wars.

Just as we are overwhelmed with trying to grasp the extent of violence, conflict and war, we are equally at loss with imagining peace. When in 1981 the United Nations General Assembly established the International Day of Peace (IDP), it was recognizing exactly this by emphasizing that “it is in the minds of men that the defences of peace must be constructed”. Constructing, envisioning, imagining. The tough world of realpolitik, however, seems to leave no place for such kind of romantic games of mind. Helmut Schmidt, former chancellor of Germany, made no attempt to hide his scorn for the imaginary, “Let him who has visions consult a doctor”. This shows a remarkable misconception of reality, however. French philosopher Henri Bergson points to the power of imagination, for to invent “gives being to what did not exist; it might never have happened”. Perceiving and transforming reality thus become mutually supportive forces. And the numbers above make it clear that peace is not the default option of reality, but needs to be envisioned. “Inventing peace”, as film director Wim Wenders calls this conscious effort.

Restoring momentum to the SDGs is a crucial sign of life for global cooperation – and for peace.

So peace begins in our minds, but it cannot remain there. Just as love yearns to be embodied, peace seeks concrete shape. And just as the shape of love is acts of kindness, the shape of peace is acts of justice. In the Jewish and Christian tradition, the term shalom is used to convey this kind of inclusive vision of peace and justice. This year’s International Day of Peace (IDP) coincides with the UN General Assembly. When conceived 78 years ago, a vital part of the United Nations’ raison d'être was the common vision for peace. The experiences of the horrors of two world wars totalling more than 76 million people dead – another one of these unfathomable numbers –united the nations of this world in their quest for peace. Yet the shape of peace is justice. So three years after the conception of the UN, the Universal Declaration of Human Rights was born, celebrating its 75th birthday this year.

As the world leaders currently convene for the UN General Assembly, however, the nations assembled there will be anything but united. The demand and supply of international collaboration seem grossly disproportionate as multiple challenges, including geopolitical, ecological and economic crises, eat away on multilateral ties. This year’s IDP also coincides with the Sustainable Development Goals (SDG) summit, marking the mid-point milestone of the goals.

Endorsed in 2015, the 17 SDGs unfold the vision of a better world, including the eradication of poverty, advancing education and gender equality and environmental stewardship. If justice is the currency of peace, it seems only appropriate that this year’s IDP’s theme is ‘Actions for Peace: Our Ambition for the #GlobalGoals’. “Peace is needed today more than ever”, says UN Secretary-General António Guterres. This, in turn, means that the vision spelt out by the SDGs is needed today more than ever. It is a misunderstanding to conceive of the SDGs as an add-on for better times. Rather, restoring momentum to the SDGs is, as Stewart Patrick and Minh-Thu Pham from the Carnegie Foundation point out, a crucial sign of life for global cooperation – and for peace, one may add.

To dispel the ever-prevalent “myth of redemptive violence” as the still predominant paradigm, we need exactly this kind of active imagination.

One would think that the scale of the challenges spelt out by the 17 SDGs requires the joint collaboration of all actors. Yet one factor that is strikingly absent in this equation is religion. This is all the more remarkable given the fact that 85 per cent of this planet’s population profess adherence to a faith tradition, according to the World Population Review 2022. This makes faith communities the largest transnational civil society actors. Now religion – every religion – is inherently ambivalent. But this means that each religion can not only be used to incite hatred and violence, but also contains potent resources for peace and reconciliation.

Many of the SDGs including peace, justice, equality and care of creation to name but a few align with core concerns of, for example, the Christian faith tradition. Just imagine the potential for transformational change towards peace and justice if faith-based actors worked together, among each other and with secular actors! To dispel the ever-prevalent “myth of redemptive violence” (Walter Wink) as the still predominant paradigm, we need exactly this kind of active imagination. Or as the poet of an ancient song once put it:

“Kindness and truth shall meet; justice and peace shall kiss”.

For more information on the role of religion in the SDGs, read the Open Access book series “Religion Matters. On the Significance of Religion for Global Issues” (Routledge), edited by Christine Schliesser et al.

Article

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.