I heard somebody recently having quite a vocal rant against Facebook in the light of the ongoing Cambridge Analytica scandal.
Although he didn’t participate in the personality test that gave the company access to 87 million users’ data, he was tempted. And his faith in the company has been severely dented as a result of recent events, as has that of many Facebokers.
But then, mid-flow, he said that he’d actually written a post about it. On Facebook itself, of all places.
Which I can sort of understand.
After all, if you’re going to make a public protest, it might as well be in the forum that abused your trust in the first place. But what struck me, as a lapsed user, is the irony of being unable to simply walk away. And I think that’s because the company has been successful at hooking people in by appealing to their emotions.
Much of Facebook’s success comes down to knowing as much as possible about those people, and using data in ways to make the platform as sticky as it can be.
And behind all of that insight are some very clever algorithms that predict how people will react, what they’ll click on or buy, and what ties in with their self-image.
Except that sometimes, algorithms get it wrong.
Which is the subject of a very thought-provoking TED talk by Cathy O’Neill. She’s a mathematician and data scientist, and author of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.
Her talk is equally provocative, taking as its title The era of blind faith in big data must end.
You’ll find out how we all use algorithms every day, whether we know it or not. And why the ‘black ops’ algorithms that organisations use may not be as clever as you think, reinforcing bias and perpetuating the status quo. As well as why auditioning behind a sheet may get you hired, while being a dot in the wrong place on a chart could get you fired.
With the General Data Protection Regulation legislation just about to kick in across Europe, it’s a timely reminder about the power of data, as well as its use and abuse.
I hope you enjoy it.
[If you’re reading this in an email, click here to see the talk on TED.com]