Hello World: Being Human in the Age of Algorithms

by Hannah Fry

Understanding our own flaws and weaknesses – as well as those of the machine – is the key to remaining in control.

‘When people are unaware they are being manipulated, they tend to believe they have adopted their new thinking voluntarily,’

It’s like the saying among airline pilots that the best flying team has three components: a pilot, a computer and a dog. The computer is there to fly the plane, the pilot is there to feed the dog. And the dog is there to bite the human if it tries to touch the computer.

People are less tolerant of an algorithm’s mistakes than of their own – even if their own mistakes are bigger.

Eric Schmidt, who, while serving as the executive chairman of Google, said he tries to think of things in terms of an imaginary creepy line. ‘The Google policy is to get right up to the creepy line but not cross it.’4

The methods can work, yes. But the advertisers aren’t injecting their messages straight into the minds of a passive audience. We’re not sitting ducks. We’re much better at ignoring advertising or putting our own spin on interpreting propaganda than the people sending those messages would like us to be. In the end, even with the best, most deviously micro-profiled campaigns, only a small amount of influence will leak through to the target.

That was the deal that we made. Free technology in return for your data and the ability to use it to influence and profit from you. The best and worst of capitalism in one simple swap.

Whenever we use an algorithm – especially a free one – we need to ask ourselves about the hidden incentives. Why is this app giving me all this stuff for free? What is this algorithm really doing? Is this a trade I’m comfortable with? Would I be better off without it?

knowing that errors are inevitable, knowing that if we proceed we have no choice but to embrace uncertainty, the conundrums within the world of driverless cars will force us to decide how good something needs to be before we’re willing to let it loose on our streets. That’s an important question, and it applies elsewhere. How good is good enough? Once you’ve built a flawed algorithm that can calculate something, should you let it?

Five thousand faces is, in fact, a pathetically small number to test your algorithm on.

When it comes to fighting crime, every way you turn you’ll find algorithms that show great promise in one regard, but can be deeply worrying in another.

theatres sometimes secretly plant people in the audience to clap and cheer at the right times.

When it comes to choosing music, it’s not that we necessarily have a preference for listening to the same songs as others, but that popularity is a quick way to insure yourself against disappointment. ‘People are faced with too many options,’ Salganik told LiveScience at the time. ‘Since you can’t listen to all of them, a natural short cut is to listen to what other people are listening to.’