Hello World: Being Human in the Age of Algorithms

by Hannah Fry

visitors were much more likely to download tracks they knew were liked by others.

Perceived popularity became real popularity, so that eventual success was just randomness magnified over time.

social proof. Whenever we haven’t got enough information to make decisions for ourselves, we have a habit of copying the behaviour of those around us.

theatres sometimes secretly plant people in the audience to clap and cheer at the right times. As soon as we hear others clapping, we’re more likely to join in.

We use popularity as a proxy for quality in all forms of entertainment.

for some, quality itself isn’t necessarily important.

the million-dollar question is: can you spot the guaranteed successes in advance? Can an algorithm pick out the hits?

spate

precipice

we’re put off by the banal, but also hate the radically unfamiliar.

if you can’t use popularity to tell you what’s ‘good’ then how can you measure quality?

our judgements of beauty are not wholly subjective, nor can they be entirely objective. They are sensory, emotional and intellectual all at once – and, crucially, can change over time depending on the state of mind of the observer.

an experiment conducted by the Washington Post in 2007.17 The paper asked the internationally renowned violinist Joshua Bell to add an extra concert to his schedule of sold-out symphony halls. Armed with his $3.5 million Stradivarius violin, Bell pitched up at the top of an escalator in a metro station in Washington DC during morning rush hour, put a hat on the ground to collect donations and performed for 43 minutes. As the Washington Post put it, here was one of ‘the finest classical musicians in the world, playing some of the most elegant music ever written on one of the most valuable violins ever made’. The result? Seven people stopped to listen for a while. Over a thousand more walked straight past. By the end of his performance, Bell had collected a measly $32.17 in his hat.

once you take away popularity and inherent quality, you’re left with the only thing that can be quantified: a metric for similarity to whatever has gone before.

Similarity works perfectly well for recommendation engines.

people form emotional relationships with objects that don’t love them back – like treasured childhood teddy bears or pet spiders.

problems with privacy, bias, error, accountability and transparency that aren’t going to go away easily.

Perhaps thinking of algorithms as some kind of authority is exactly where we’re going wrong.

‘Centaur Chess’, where a human player and an algorithm collaborate with one another to compete with another hybrid team.

blunder,