If you’re like me, you enjoy the fact (most of the time) that algorithms can suggest a movie to watch or a new song to play or an efficient way to organize your social media feeds. But what about an algorithm that helps the police predict who might have committed a crime? Or one that allows you to be diagnosed by a computer rather than a doctor? You’d probably have some follow-up questions before deciding whether you’re as comfortable with these things as with the recommendation engines on Spotify and Netflix. In “Hello World: Being Human in the Age of Algorithms,” the mathematician Hannah Fry looks closely at the potential benefits and hazards of a world increasingly run by code. Below, she discusses a “massive wake-up call” she experienced in Berlin, the scale of data mining, a person who inspired the way she talks to audiences and more.
When did you first get the idea to write this book?
One of the first things I did when I finished my Ph.D. was work with the police to look at what happened during the London riots in 2011, which took over the city. The work we were doing was all retrospective; the riots had already happened. We got data from the police and were trying to make predictions about what would happen and where people would be. The intention was that the police would be able to predict where riots would move.
I went to Berlin to give a talk, and I was really inexperienced and naïve. I was jolly and made jokes, and said, “Here’s how you contain riots.” If there’s one city in the world that really understands what it is to be oppressed by a police state, it’s Berlin. And they almost literally tore me apart on stage. It was a massive wake-up call for me. You can’t sit around and play with this stuff and not realize there are wider implications for it.
And then I saw governments using really substandard algorithms for really important stuff. I thought, the people who are writing these aren’t talking to the people who are using them, and the people who are using them aren’t talking to the people whose lives are being changed by their decisions. And I thought it was really important to bridge the gaps between those three groups.
What’s the most surprising thing you learned while writing it?
I changed my mind on a lot of things while I was writing it. For example, when I first learned about the algorithms that predict whether someone will commit a crime, I was really horrified at the idea that something that was flawed, something that made mistakes, could be given that much power over someone’s future. But having read into it, it’s not fair to imagine this perfect world and then criticize anything that doesn’t match up to it. I think you have to deal with what you’re left with if you don’t use any of these systems. And what surprised me is just how bad humans are at these things; the biases you have are just unbelievable. So even systems with really big problems — you have to think about what gives you the best outcome.
Also, I’ve worked in data science for ages but I didn’t know just how much data the data brokers have on you. They are massive companies. There’s all the standard stuff, like your name, age, gender, height. But there’s also things like: whether or not you’ve had an abortion or a miscarriage; what your proclaimed sexuality is and what your true sexuality is.
Everything we’re doing online is being not just monitored, but that information is being packaged up and sold and resold to manipulate us. I think the Cambridge Analytica stuff is just the very tip of the iceberg.
Curating our data is valuable. Like 23andMe — while selling us the chance to know whether we’re Vikings or whatever, they’re amassing these huge DNA databases that are unimaginably valuable. Get people to pay you to add their DNA to this database. Genius!
In what way is the book you wrote different from the book you set out to write?
I thought I’d do a jolly jaunt and be done with it in six months. It was much harder than I thought. There’s real nuance in these questions. They don’t have easy answers. To be able to answer them, or to create something that was interesting to read, I had to research so deeply. I did more work for this, and I read more, than I did for my Ph.D.
The last chapter in the book is about whether or not machines can be creative, and whether a machine can recognize true beauty. So I had to define beauty in some way. I’m a mathematician, do you know what I mean? Writing about “What is art?” is not something I ever thought I’d be doing.
Who is a creative person (not a writer) who has influenced you and your work?
Hans Rosling, the doctor and statistician. They called him the Mick Jagger of TED. He died last year. I find him inspirational because the stuff he was communicating about was essentially statistics, and that’s not something people are immediately warm to. I think he totally understood that when you’re speaking to an audience, the audience has come to first. He knew that whatever people are interested in, whatever niche, there’s common ground. All of us like humor, wit, a little bit of silliness. He would get his audience whipped into a frenzy about something ridiculous, and then, when he had them in the palm of his hand, he would hit them with the message that he wanted to convey. That’s a remarkable thing, and I try to copy it in everything I do.
Persuade someone to read “Hello World” in 50 words or less.
This isn’t really a book about algorithms. It’s about humans. It’s about who we are, where we’re going, what’s important to us — and how that is changing with technology. I can’t promise it will give any answers, but I do hope it will change the way people see the world.
This interview has been condensed and edited.
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