What they don’t tell you about when someone you love dies

Sharing her experience of her husband’s death, Yvonne Tulloch charts grief’s journey and shares signposts to help. Part of the How to Die Well series.

Yvonne Tulloch

Yvonne Tulloch is Founder and CEO of AtaLoss, helping bereaved people find support and wellbeing.

A group of grieving friends with their hands on each others backs.

The Good Funeral Guide on Unsplash.

Turn on the news and death is all around us. Yet somehow, we think it will never happen to us. In one sense that’s good. We have a child-like innocence that protects us from the harsh realities of life.

A few years ago, as a church minister, I thought I knew about death. I’d been trained to take funerals and had supported families when a loved one had died. But it wasn’t until I was bereaved myself - when my husband died suddenly of a heart attack - that I realised how little even I knew.

Although busy, life had been good until then. My husband had a successful job, my own work was going well and our three children were flying the nest and finding their feet in university. Little did I know that in one, short phone call from a colleague, our lives would change forever.

Simon had been found dead in his hotel in Spain, and I was faced with telling each of the children and his mother, the worst news anyone could convey. Concerned about social media the news was embargoed until all family members knew, then I had to go to Spain to find, as well as identify the body, and bring him home. I had to work out our finances – no one knew what we had to live off – close accounts and put things in my name. I discovered our house wasn’t insured, nor our car for me to drive, that bank accounts were frozen, and that no organisation is geared up to help. Everyone insists on speaking to the account holder or seeing the actual death certificate before being willing to oblige. I had a funeral and thanksgiving to organise – two big occasions in just 3 weeks - and a mountain of admin to deal with, which would be difficult at any time.

Grief is a journey of adjustment of who we are to a new existence – one that takes a long time and never comes at a convenient time.

We’ve been a death-denying culture, I now realise, for many years. With death invariably happening in hospices or hospitals, we’ve pushed death away and pretended it doesn’t happen. Consequently, we’ve lost knowledge of bereavement and the art of support. We’ve tended only to think about preparing for funerals and then counselling if the person isn’t doing well. But what about all the other help that’s needed? Understanding and support is necessary in all manner of ways. Bereavement is one of the most stressful times of life, affecting everyone sooner or later and every part of their life. Grief is a journey of adjustment of who we are to a new existence – one that takes a long time and never comes at a convenient time.

At first most of us are shocked or emotionally numb; we run on adrenaline and we’re in survival mode. At the funeral others can think we’re doing well, and we can too. But it’s after, when the real sadness tends to hit, when the future must be faced and by then support has dropped away.

Many of us experience a roller coaster of changing reactions and responses which we don’t recognise as us or don’t associate with grief.

There are the physical reactions, for instance. I couldn’t eat, I couldn’t sleep, I was cold and I shook for months, I had a heavy ‘weight’ in my gut and was taken to hospital three times with suspected heart problems - our bodies are always in tune with our emotions.

And there are the psychological reactions. We can experience anxiety, anger and guilt; we can’t concentrate or remember, or function to do the most basic of tasks. I kept thinking I was seeing Simon and had a psychosis which made me feel separated from the world. We can think we’re going mad.

Grief is a natural response to loss which we need to work through for our future wellbeing.

For me help came from two initiatives I was fortunate to find: Care for the Family’s Widowed Young Support and The Bereavement Journey course run by a church in London. In each of these I discovered others who had been bereaved, who understood what I was going through and who helped me to navigate the alien territory I found myself in. They also helped me to understand my spiritual responses which had been the biggest surprise. I had never doubted my Christian faith but with bereavement, that too was challenged, and God, who had always felt present, suddenly disappeared. I realize now that this is natural. Grieving is a process of deconstruction and reconstruction of meaning, and therefore some of whatever meaning we had before the person died, will deconstruct as we grieve.

Roll on a few years and I’m on the other side, running a charity helping people to understand that in our death-denying society bereavement impacts greatly, and that grief is a natural response to loss which we need to work through for our future wellbeing. Support is needed in various ways which we direct to through our signposting website ataloss.org. And I’m helping people myself through The Bereavement Journey course to find healing and hope, offering also spiritual support for the faith questioning I find most people have. Unfortunately, though, because we’ve neglected death, many haven’t been supported through a bereavement in the past and are carrying loss which is unresolved.

Article

AI - Artificial Intelligence

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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.