Article
AI - Artificial Intelligence
Attention
Culture
5 min read

Will AI’s attentions amplify or suffocate us?

Keeping attention on the right things has always been a problem.

Mark is a research mathematician who writes on ethics, human identity and the nature of intelligence.

A cute-looking robot with big eyes stares up at the viewer.
Robots - always cuter than AI.
Alex Knight on Unsplash.

Taking inspiration from human attention has made AI vastly more powerful. Can this focus our minds on why attention really matters? 

Artificial intelligence has been developing at a dizzying rate. Chatbots like ChatGPT and Copilot can automate everyday tasks and can effortlessly summarise information. Photorealistic images and videos can be generated from a couple of words and medical AI promises to revolutionise both drug discovery and healthcare. The technology (or at least the hype around it) gives an impression of boundless acceleration. 

So far, 2025 has been the year AI has become a real big-ticket political item. The new Trump administration has promised half a trillion dollars for AI infrastructure and UK prime minister Keir Starmer plans to ‘turbocharge’ AI in the UK. Predictions of our future with this new technology range from doom-laden apocalypse to techno-utopian superabundance. The only certainty is that it will lead to dramatic personal and social change. 

This technological impact feels even more dramatic given the relative simplicity of its components. Huge volumes of text, image and videos are converted into vast arrays of numbers. These grids are then pushed through repeated processes of addition, multiplication and comparison. As more data is fed into this process, the numbers (or weights) in the system are updated and the AI ‘learns’ from the data. With enough data, meaningful relationships between words are internalised and the model becomes capable of generating useful answers to questions. 

So why have these algorithms become so much more powerful over the past few years? One major driver has been to take inspiration from human attention. An ‘attention mechanism’ allows very distant parts of texts or images to be associated together. This means that when processing a passage of conversation in a novel, the system is able to take cues on the mood of the characters from earlier in the chapter. This ability to attend to the broader context of the text has allowed the success of the current wave of ‘large language models’ or ‘generative AI’. In fact, these models with the technical name ‘Transformer’ were developed by removing other features and concentrating only on the attention mechanisms. This was first published in the memorably named ‘Attention is All You Need’ paper written by scientists working at Google in 2017. 

If you’re wondering whether this machine replication of human attention has much to do with the real thing, you might be right to be sceptical. That said, this attention-imitating technology has profound effects on how we attend to the world. On the one hand, it has shown the ability to focus and amplify our attention, but on the other, to distract and suffocate it. 

Attention is a moral act, directed towards care for others.

A radiologist acts with professional care for her patients. Armed with a lifetime of knowledge and expertise, she diligently checks scans for evidence of malignant tumours. Using new AI tools can amplify her expertise and attention. These can automatically detect suspicious patterns in the image including very fine detail that a human eye could miss. These additional pairs of eyes can free her professional attention to other aspects of the scan or other aspects of the job. 

Meanwhile, a government acts with obligations to keep its spending down. It decides to automate welfare claim handling using a “state of the art” AI system. The system flags more claimants as being overpaid than the human employees used to. The politicians and senior bureaucrats congratulate themselves on the system’s efficiency and they resolve to extend it to other types of payments. Meanwhile, hundreds of thousands are being forced to pay non-existent debts. With echoes of the British Post Office Horizon Scandal, the 2017-2020 the Australian Robo-debt scandal was due to flaws in the algorithm used to calculate the debts. To have a properly functioning welfare safety net, there needs to be public scrutiny, and a misplaced deference to machines and algorithms suffocated the attention that was needed.   

These examples illustrate the interplay between AI and our attention, but they also show that human attention has a broader meaning than just being the efficient channelling of information. In both cases, attention is a moral act, directed towards care for others. There are many other ways algorithms interact with our attention – how social media is optimised to keep us scrolling, how chatbots are being touted as a solution to loneliness among the elderly, but also how translation apps help break language barriers. 

Algorithms are not the first thing to get in the way of our attention, and keeping our attention on the right things has always been a problem. One of the best stories about attention and noticing other people is Jesus’ parable of the Good Samaritan. A man lies badly beaten on the side of the road after a robbery. Several respectable people walk past without attending to the man. A stranger stops. His people and the injured man’s people are bitter enemies. Despite this, he generously attends to the wounded stranger. He risks the danger of stopping – perhaps the injured man will attack him? He then tends the man’s wounds and uses his money to pay for an indefinite stay in a hotel. 

This is the true model of attention. Risky, loving “noticing” which is action as much as intellect. A model of attention better than even the best neuroscientist or programmer could come up with, one modelled by God himself. In this story, the stranger, the Good Samaritan, is Jesus, and we all sit wounded and in need of attention. 

But not only this, we are born to imitate the Good Samaritan’s attention to others. Just as we can receive God’s love, we can also attend to the needs of others. This mirrors our relationship to artificial intelligence, just as our AI toys are conduits of our attention, we can be conduits of God’s perfect loving attention. This is what our attention is really for, and if we remember this while being prudent about the dangers of technology, then we might succeed in elevating our attention-inspired tools to make AI an amplifier of real attention. 

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Article
AI - Artificial Intelligence
Community
Culture
Education
5 min read

Artificial Intelligence needs these school lessons to avoid a Frankenstein fail

To learn and to learn to care are inseparable

Joel Pierce is the administrator of Christ's College, University of Aberdeen. He has recently published his first book.

A cyborg like figure opens the door to a classroom.
AI in the classroom.
Nick Jones/Midjourney.ai.

Recent worries expressed by Anthropic CEO, Dario Amodei, over the welfare of his chatbot bounced around my brain as I dropped my girls off for their first days at a new primary school last month. Maybe I felt an unconscious parallel. Maybe setting my daughters adrift in the swirling energy of a schoolyard containing ten times as many pupils as their previous one gave me a twinge of sympathy for a mogul launching his billion-dollar creation into the id-infused wilds of the internet. But perhaps it was more the feeling of disjuncture, the intuition that whatever information this bot would glean from trawling the web,it was fundamentally different from what my daughters would receive from that school, an education.  

We often struggle to remember what it is to be educated, mistaking what can be assessed in a written or oral exam for knowledge. However, as Hannah Arendt observed over a half century ago, education is not primarily about accumulating a grab bag of information and skills, but rather about being nurtured into a love for the world, to have one’s desire to learn about, appreciate, and care for that world cultivated by people whom one respects and admires. As I was reminded, watching the hundreds of pupils and parents waiting for the morning bell, that sort of education only happens in places, be it at school or in the home, where children themselves feel loved and valued.  

Our attachments are inextricably linked to learning. That’s why most of us can rattle off a list of our favourite teachers and describe moments when a subject took life as we suddenly saw it through their eyes. It’s why we can call to mind the gratitude we felt when a tutor coached us through a maths problem, lab project, or piano piece which we thought we would never master. Rather than being the pouring of facts into the empty bucket of our minds, our educations are each a unique story of connection, care, failure, and growth.  

I cannot add 8+5 without recalling my first-grade teacher, the impossibly ancient Mrs Coleman, gazing benevolently over her half-moon glasses, correcting me that it was 13, not 12. When I stride across the stage of my village pantomime this December, I know memories of a pint-sized me hamming it up in my third-grade teacher’s self-penned play will flit in and out of mind. I cannot write an essay without the voice of Professor Coburn, my exacting university metaphysics instructor, asking me if I am really saying what is truthful, or am resorting to fuzzy language to paper over my lack of understanding. I have been shaped by my teachers. I find myself repaying the debts accrued to them in the way I care for students now. To learn and to learn to care are inseparable. 

But what if they weren’t? AI seems to open the vista where intelligences can simply appear, trained not by humans, but by recursive algorithms, churning through billions of calculations on rows of servers located in isolated data centres. Yes, those calculations are mostly still done on human produced data, though the insatiable need for more has eaten through most everything freely available on the web and in whatever pirated databases of books and media these companies have been able to locate, but learning from human products is not the same as learning from human beings. The situation seems wholly original, wholly unimaginable. 

Except it was imagined in a book written over two hundred years ago which, as Guillermo del Toro’s recent attempt to capture that vision reminds us, remains incredibly relevant today. Filmmakers, and from trailers I suspect Del Toro is no different here, tend to treat the story of Frankenstein as one of glamorous transgression: Dr Frankenstein as Faust, heroically testing the limits of human knowledge and human decency. But Mary Shelley’s protagonist is an altogether more pathetic character, one who creates in an extended bout of obsessive experimentation and then spends the rest of the book running from any obligation to care for the creature he has made.  

It is the creature who is the true hero of the novel and he is a tragic one precisely because his intelligence, skills, and abilities are acquired outside the realm of human connection. When happenstance allows him to furtively observe lessons given within a loving, but impoverished family, he imagines himself into that circle of growing love and knowledge. It is when he is disabused of this notion, when the family discovers him and is disgusted, when he learns that he is doomed to know, but not be known, that he turns into a monster bent on revenge. As the Milton-quoting monster reminds Frankenstein, even Adam, though born fully grown, was nurtured by his maker. Since even this was denied creature, what choice does he have but to take the role of Satan and tear down the world that birthed him? 

Are our modern maestros of AI Dr Frankensteins? Not yet. For all the talk of sentient-like responses by LLMs, avoiding talking about distressing topics for example, the best explanation of such behaviour is that they simply are mimicking their training sets which are full of humans expressing discomfort about those same topics. However, if these companies are really as serious about developing a fully sentient AGI, about achieving the so-called singularity, as much of the buzz around them suggests, then the chief difference between them and Frankenstein is one of ability rather than ambition. If eventually they are able to realise their goals and intelligences emerge, full of information, but unnurtured and unloved, how will they behave? Is there any reason to think that they will be more Adam than Satan when we are their creators? 

At the end of Shelley’s novel, an unreconstructed Frankenstein tells his tale to a polar explorer in a ship just coming free from the pack ice. The explorer is facing the choice of plunging onward in the pursuit of knowledge, glory, and, possibly, death, or heeding the call of human connections, his sister’s love, his crew’s desire to see their families. Frankenstein urges him on, appeals to all his ambitions, hoping to drown out the call of home. He fails. The ship turns homeward. Knowledge shorn of attachment, ambition that ignores obligation, these, Shelley tells us, are not worth pursuing. Will we listen to her warning? 

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