Which finally brings me to my prediction for 2018, which is what you are expecting me to write about. 2018 is going to be the year of machine learning. Or, for old folk like me, artificial intelligence.
Let me make it clear from the start that, for me at least, there is a gulf between “bots” which apply machine learning to data sets, and “robots” in the traditional sense of the world. One of the top talking points at IBC2017 was robotics, and the disconcertingly alluring Sophia in particular.
This seems to me to be very clever technology, but I am far from convinced that I know what it is for. We are comfortable in dealing with the sound of artificial intelligence, through chatting to Siri and Alexa. But the physical manifestation seems – to me, at least – to be an unnecessary step too far.
On a more practical level, the IBC Conference Prize, which goes to the most innovative thinking in the technical papers programme, went to TV Globo in 2017, for a paper called Big data for data journalism, enhanced business analytics and video recommendation. It describes three projects, all of which use machine learning in one way or another.
Video recommendation is an obvious application for machine learning. If you have ever bought anything from Amazon, you will know that forever afterwards it will attempt to predict your next purchase. Recommending content to subscribers is the logical extension.
But TV Globo is also using machine learning algorithms to trawl through publicly available data, such as government papers and economic resources. Using the cloud grunt provided by AWS, it created what it called a data lake, which then allowed journalists to access the data to understand what was going on. In a test exercise, a typical research project took a week to answer a business question using Excel, and seven seconds using the big data environment.
Another pioneer in the field is Amagi, which has demonstrated a system to suggest where commercial breaks should go. This is a real-life and not very stimulating task: content comes in from around the world with different commercial break patterns or none, and someone has to decide where the ads are going when you show it.
My oft-repeated principle is that computers are very good at dull, repetitive tasks; people are good at creative tasks. So I asked KS Srinivasan, co-founder of Amagi, if machine learning is going to change that basic principle. “The biggest question that broadcasters would need to answer is ‘do we really need machine learning, and why’,” he said.
“The most labour intensive jobs in broadcast today depend on human experience,” Srini continued. “As machine learning systems evolve, these jobs could be performed by machines instead.”
Which might have sounded a little far-fetched, were it not for a recent interview in Broadcast with Matthew Postgate, BBC CTO. He revealed that, at the Edinburgh Fringe Festival back in August, BBC experimented with using AI in place of a director on a comedy panel show. In what he admitted was a sledgehammer technique, the computer analysed thousands of shows to learn how to direct the relatively formulaic genre.
“We aren’t trying to replace TV directors,” he is reported as saying. “But because we don’t have infinite resource, this could open up the number of events we can cover.”
If even directors can be replaced – admittedly only for the simple stuff (today) – then should we all be retraining as machine learning designers? Gartner, one of the heavyweights in technology research, has said not to panic: artificial intelligence may actually create more jobs that it is expected to eliminate.
By 2020, it forecasts, artificial intelligence will generate 2.3 million jobs, exceeding the 1.8 million that it will wipe out. In the next five years, to 2025, the net increase in jobs attributable to machine learning will reach two million, according to the report.
So, it would seem, we have nothing to fear from TV Globo’s analysts, the BBC’s machine directors and even Sophia and her chums. According to Garnter’s research director, Manjunath Bhat, “robots are not here to take away our jobs. They are here to give us a promotion – I think that is the way we should start looking at artificial intelligence.”