Hype is a form of ingratitude

On thinking enough to thank others

Above: I’m also grateful for this.

I recently did a short Q&A for my speaking agency’s website, looking at what’s over-hyped and under-hyped in the realm of AI. I enjoy the chance for self-reflection that interviews like this offer, and wanted to share both the result and a reflection on two contrasting themes I was asked to explore: hype and mentorship.

Have you ever had a mentor? Thinking about this question made me realise I’ve had plenty, though I wouldn’t have called them all mentors at the time. In fact, almost all of the things I’m most grateful for in my professional life—getting to write books about crazily varied fields like video games, critical thinking and the deep history of humanity; teaching and collaborating around cognition in a digital age; meeting and speaking with brilliant people across a host of fields—have their roots in the personal generosity of someone else.

As I note at the end of the interview, it’s equally important to acknowledge this in terms of gratitude, honesty and the hope that I can live up to others’ examples. To do otherwise would be both churlish and self-deceived. And this applies elsewhere. Because hype is also a form of ingratitude: a story of heroism or inexorability that pretends there’s no such thing as luck or indebtedness.

In the case of technology, hype is often the story of magical machines that will dissolve all difficulties. And this means it’s also an erasure of the circumstances, learning and labour that lie behind enchantment: the incremental, imperfect business of making and re-making; the human words, works and hopes that are much more than grist to algorithmic mills.

To be grateful is to acknowledge and celebrate interdependence as a defining human attribute: a form of strength that accepts nothing we do is either possible or purposeful without others.

Here’s the interview.

What aspect of AI do you think is receiving TOO LITTLE attention?

I wish people would spend more time talking about what is actually going on within specific systems, and what in particular they can do, rather than dealing in generalisations and prognostications that treat AI as magical or human-like. It’s a vast, fascinating, fast-evolving field, and it’s so important not to be bewitched by language or to rely on faulty analogies – such as to our own minds, unrelated technologies, or myths and movies – when debating its risks and potentials.

What aspect of AI is receiving TOO MUCH attention?

Stories of triumph and disaster attract attention for similar reasons: they’re striking, simple and appear to offer certainty. I worry that both those hyping up AI and those convinced it’s a bubble can get stuck in a loop that glosses over real-world risks, complexities and opportunities. I think AI is a very big deal; but the interesting story, for me, is how different industries and institutions can specifically make use of statistical insights, automation and pattern-recognition within areas where they have high-quality data and understandings. And when such data and understanding are lacking, they need to watch out.

What’s the last book you read?

I’m just finishing The Atomic Human by Neil Lawrence, the inaugural DeepMind Professor of Machine Learning at Cambridge. It’s a brilliant book, partly because it resists hype and has a great sense of historical context, complete with vividly-told stories; and partly because it insists on a tangible, engineering-led understanding of machine learning systems as human-made artefacts that exist in the real world. AI, in Lawrence’s account, is a form of automated decision-making that can only be understood via its instantiation in particular human contexts. Similarly, human cognition can only be understood in terms of our biology and evolutionary history – and Lawrence is clear and thoughtful in teasing out what this implies in an age of ever-more-powerful machines.

Have you ever had a mentor?

Looking back, I would say I’ve had several, although none I would necessarily have called a mentor at the time. I was supported and encouraged immensely by my tutor at St John’s College, Oxford, Professor John Kelly, from my time as an undergraduate to my doctorate and beyond. He was a brilliant polymath, and in addition to his charisma and personal warmth helped me see how important it is to build relationships with people across a diversity of fields. Among many others, I also owe a lifelong debt to Ziyad Marar, author and President of Global Publishing at SAGE, who has endlessly supported my writing and thinking over the last decade, and helped me find a global network of fascinating people whose work and ideas fuel my own.

If you could go back in time and give your younger self one piece of advice, what would it be?

Don’t be afraid to express gratitude and admiration: do so openly, honestly and often. You never know when it will be too late to thank someone.