Political middlemen and dart-throwing chimps

Martha Gill's "Irrational Animals" column.

Predicting the weather was once quite an interesting profession, needing skill in reading the instruments, intuition in deciphering the skies and years of experience in putting it all together. Now it’s the kind of job Nick Cage’s character would be given in a heavy-handed satire of the American dream, possibly also starring Michael Caine. We don’t need these skilled individuals any more – computers do all that. We just need an algorithm and a mouthpiece.

And so to Nate Silver – one of the biggest winners of the US presidential election. As the race neared its end, becoming “too close to call”, with money and opinions frantically changing hands, the New York Times blogger was calmly and correctly predicting voter outcome in every single state. He had what others didn’t – a formula to convert polling information into probabilities – and it turned out to be dead-on. He was not alone in getting it right but he was among the few. Many failed spectacularly.

Here’s Newt Gingrich on Fox News on 25 October: “I believe the minimum result will be 53-47 [per cent] Romney, over 300 electoral votes, and the Republicans will pick up the Senate. I base that . . . on just years and years of experience.” And here’s the GOP strategist Karl Rove in the Wall Street Journal on 31 October: “It comes down to numbers. And in the final days of this presidential race, from polling data to early voting, they favour Mitt Romney.”

These were not small errors. These people were standing in pre-hurricane wind and predicting sunshine. Are pundits more often wrong than not, or was it just this particular election that threw them? And how often do the statistics spewed out by experts hit the mark? One study found a statistic for it.

Algorithm blues

In the 1980s, a psychologist called Philip Tetlock took a group of journalists, foreign policy experts and economists – 284 of them – and spent the next two decades bombarding them with questions: would the dotcom bubble burst? Would George Bush be re-elected? How would apartheid end?

After analysing 82,361 predictions, Tetlock found that his experts performed worse than random chance. In short, they could have been beaten by dart-throwing chimps.

The reason was confidence. Tetlock found that the more often pundits appeared on TV, the more likely they were to be wrong. Their strong opinions were causing them to ignore dissenting facts or explain them away, leaving them trapped, he said, in the cage of their preconceptions.

Now, semi-expert middlemen are being squeezed out as the focus shifts to minute data analysis. Silver is one of the winners of this change but on the losing side is a whole industry of political forecasters. And it’s not just true of politics. Finance has been moving that way for a while. In UBS’s recent swath of job cuts, at least one trader, David Gallers, was replaced with an algorithm.

Difficult times for the old school, but what of the new? Silver expressed his concerns to the Wall Street Journal: “You don’t want to influence the system you are trying to forecast.” Only one problem with the new machines, then – accuracy. They’re so good that they might start controlling the weather.

Newt Gingrich opining away on Fox News. Photograph: Getty Images

Martha Gill writes the weekly Irrational Animals column. You can follow her on Twitter here: @Martha_Gill.

This article first appeared in the 19 November 2012 issue of the New Statesman, The plot against the BBC

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A quote-by-quote analysis of how little Jeremy Hunt understands technology

Can social media giants really implement the health secretary’s sexting suggestions? 

In today’s “Did we do something wrong? No, it was social media” news, Health Secretary Jeremy Hunt has argued that technology companies need to do more to prevent sexting and cyber-bullying.

Hunt, whose job it is to help reduce the teenage suicide rate, argued that the onus for reducing the teenage suicide rate should fall on social media companies such as Facebook and Twitter.

Giving evidence to the Commons Health Committee on suicide prevention, Hunt said: “I think social media companies need to step up to the plate and show us how they can be the solution to the issue of mental ill health amongst teenagers, and not the cause of the problem.”

Pause for screaming and/or tearing out of hair.

Don’t worry though; Hunt wasn’t simply trying to pass the buck, despite the committee suggesting he direct more resources to suicide prevention, as he offered extremely well-thought out technological solutions that are in no way inferior to providing better sex education for children. Here’s a quote-by-quote analysis of just how technologically savvy Hunt is.

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“I just ask myself the simple question as to why it is that you can’t prevent the texting of sexually explicit images by people under the age of 18…”

Here’s Hunt asking himself a question that he should be asking the actual experts, which is in no way a waste of anybody’s time at all.

“… If that’s a lock that parents choose to put on a mobile phone contract…”

A lock! But of course. But what should we lock, Jeremy? Should teenager’s phones come with a ban on all social media apps, and for good measure, a block on the use of the camera app itself? It’s hard to see how this would lead to the use of dubious applications that have significantly less security than giants such as Facebook and Snapchat. Well done.

“Because there is technology that can identify sexually explicit pictures and prevent it being transmitted.”

Erm, is there? Image recognition technology does exist, but it’s incredibly complex and expensive, and companies often rely on other information (such as URLs, tags, and hashes) to filter out and identify explicit images. In addition, social media sites like Facebook rely on their users to click the button that identifies an image as an abuse of their guidelines, and then have a human team that look through reported images. The technology is simply unable to identify individual and unique images that teenagers take of their own bodies, and the idea of a human team tackling the job is preposterous. 

But suppose the technology did exist that could flawlessly scan a picture for fleshy bits and bobs? As a tool to prevent sexting, this still is extremely flawed. What if two teens were trying to message one another Titian’s Venus for art or history class? In September, Facebook itself was forced to U-turn after removing the historical “napalm girl” photo from the site.

As for the second part of Jezza’s suggestion, if you can’t identify it, you can’t block it. Facebook Messenger already blocks you from sending pornographic links, but this again relies on analysis of the URLs rather than the content within them. Other messaging services, such as Whatsapp, offer end-to-end encryption (EE2E), meaning – most likely to Hunt’s chagrin – the messages sent on them are not stored nor easily accessed by the government.

“I ask myself why we can’t identify cyberbullying when it happens on social media platforms by word pattern recognition, and then prevent it happening.”

Jeremy, Jeremy, Jeremy, Jeremy, can’t you spot your problem yet? You’ve got to stop asking yourself!

There is simply no algorithm yet intelligent enough to identify bullying language. Why? Because we call our best mate “dickhead” and our worst enemy “pal”. Human language and meaning is infinitely complex, and scanning for certain words would almost definitely lead to false positives. As Labour MP Thangam Debbonaire famously learned this year, even humans can’t always identify whether language is offensive, so what chance does an algorithm stand?

(Side note: It is also amusing to imagine that Hunt could even begin to keep up with teenage slang in this scenario.)

Many also argue that because social media sites can remove copyrighted files efficiently, they should get better at removing abusive language. This is a flawed argument because it is easy to search for a specific file (copyright holders will often send social media giants hashed files which they can then search for on their databases) whereas (for the reasons outlined above) it is exceptionally difficult for algorithms to accurately identify the true meaning of language.

“I think there are a lot of things where social media companies could put options in their software that could reduce the risks associated with social media, and I do think that is something which they should actively pursue in a way that hasn’t happened to date.”

Leaving aside the fact that social media companies constantly come up with solutions for these problems, Hunt has left us with the burning question of whether any of this is even desirable at all.

Why should he prevent under-18s from sexting when the age of consent in the UK is 16? Where has this sudden moral panic about pornography come from? Are the government laying the ground for mass censorship? If two consenting teenagers want to send each other these aubergine emoji a couple of times a week, why should we stop them? Is it not up to parents, rather than the government, to survey and supervise their children’s online activities? Would education, with all of this in mind, not be the better option? Won't somebody please think of the children? 

“There is a lot of evidence that the technology industry, if they put their mind to it, can do really smart things.

Alas, if only we could say the same for you Mr Hunt.

Amelia Tait is a technology and digital culture writer at the New Statesman.