Computers wrote 1 billion articles last year. Will journalists soon be extinct?

Narrative Science's algorithms produce a piece every 30 seconds. Automated Insights created one billion pieces of content last year. That means there's an excellent chance something you read in the last month was written entirely by a computer.

Anna Karenina took Tolstoy four years. A Russian publishing house put out a computer-generated one in 72 hours

If that sounds warped, go to Amazon.com and search for Philip Parker. A professor at Insead Business School, he has authored over a million books - of which 1,06,000-odd are listed on Amazon - making him arguably the most prolific author you've never heard of.

The only writing he's actually done? A computer programme that generates these books; everything from crossword puzzles to estimates for the market size for a range of products (The 2007-2012 Outlook for Smoothies in India is a Parker original).

The average book takes under an hour, is primarily an act of data-crunching and prediction using formulae, and is printed on demand rather than in bulk.

Illustration: Eastforth/Deviantart/Creative Commons

Now, writers workshops for computers

That most writing is formulaic is brought home by how Narrative Science 'trained' their algorithms to write.

First, they programmed a set of rules that govern a particular event. For example, the team that scores the maximum runs in a cricket game wins.

Next, they coded algorithms to search databases to collate extra info, such as whether the last five matches were won or lost.

The final step? Using (human) journalists to create story templates for the algorithms to follow.

That model, it turns out, is replicable across domains. Using customer reviews on set parameters - service quality, food taste, pricing - algorithms can now generate lists of 'the best sushi in Atlanta' or 'the best pizza in Mumbai'.

But algorithms - or certainly those who create them - are not content with doing the functional. They're now making serious inroads into creative writing.

Competition for Shakespeare

It started back in 2008, when a St Petersburg-based publishing house published a 320-page computer-written novel based on Tolstoy's Anna Karenina, but written in the style of Haruki Murakami.

Last November, the process took a dystopian leap when programmers started writing code to help people write novels faster. This was to coincide with National Novel Writing Month in the US, when thousands attempt to finish a 50,000-word novel on deadline.

Even that, it turns out, is but one step on the ladder of automated literary ambition. In studies where they didn't know the source, people often preferred poetry written by computers - against Shakespearean sonnets.

The New York Times ran a quiz and found readers couldn't tell the difference between stories by humans and computers

And then there's Watson, the cult IBM computer that is finally moving into the realm of cognitive computing: the ability of a computer to continue to learn, not just process what it has already learnt.

Humans gone - and no one's the wiser

The final nick is this: readers can't tell the difference. The New York Times recently created a quiz with excerpts of poems, novels and news stories written by humans and computers; the challenge was to pick which was which.

My score was, let's just say, disturbing. If you're feeling confident about your abilities, take the quiz here.

There's obvious alarm bells about computers taking over human roles; what isn't immediately obvious is that the risks are far more insidious than the loss of jobs and even the ceding of control over information flow. When journalists or professional writers write a piece, their biases - intended or inherent - can be traced. You can, if you were so inclined, place their work in a context, track their affiliations, hold them to account.

Algorithms aren't immune to bias; they will reflect those of their programmers. They can be manipulated. But those manipulations would be invisible.

Most conversations about artificial intelligence eventually arrive at the Turing Test, but that obsession may be misplaced. Not all technological achievement needs to be assessed at the altar of human redundancy. It's possible, without romanticising, to argue that humanity loses something when Tolstoy is reduced to a formula. When a computer says something ironic without understanding what irony is.

It's inevitable that computers will constantly learn to do more.The thing to think about is whether that's turning us into a species increasingly content to do less.