Channelling the Hype
The next macro-trend of the decade is taking shape but, asks Contagious’ head of trends Patrick Jeffrey, can it live up to its billing?
One of the trickiest things about working at Contagious is separating probability from hyperbole. We tend to cover the most optimistic aspects of the industry — where brands are enthusiastically embracing new technologies; where agencies are pursuing bold new strategies; and where startups are figuring out how to change the world. Amid all this energy, it can be hard to stay rational and not get caught up in the whirlwind.
But sometimes a new trend comes along that feels like it might live up to the hype.
‘Machine learning has created the biggest business opportunity in history,’ said Pedro Domingos, The University of Washington professor of computer science and engineering, in a recent talk. ‘This opportunity is going to be open for maybe three to five years, and after that massive lock-in will set in. The time to act is now.’
In April, when Google DeepMind’s machine learning algorithm defeated a grandmaster at Go (the world’s most complex boardgame) Google’s CEO, Sundar Pinchai, was equally effusive. ‘The implications for this victory are, literally, game changing, and the ultimate winner is humanity. This is another important step toward creating artificial intelligence that can help us in everything from accomplishing our daily tasks and travels, to eventually tackling even bigger challenges like climate change and cancer diagnosis.’
As you can see, it’s quite some hype.
It wasn’t until our most recent issue, however, that we started to genuinely see the extent of this potential. When we started piecing together the publication, we realised that machine learning was inadvertently underpinning pretty much the entire magazine. It was the technology behind some of the most highly awarded marketing campaigns in our Cannes Lions round-up; it powered five of the six startups that we chose to profile (in sectors as diverse as automotive, FMCG, banking and retail) and it was a recurrent theme in many of our extended features.
For example, in our piece on predictive fulfilment, we profiled a New York food delivery service called Maple, which uses machine learning algorithms to plot delivery routes, plan menus, forecast how many ingredients to buy and tell its chefs what (and when) to cook. The system knows exactly how long it takes to prepare each dish and which ones are likely to be popular at different times of the day, or during specific weather conditions. In a 10-month period, the machine learning system had improved itself to the point that the restaurant’s output increased more than twentyfold.
Elsewhere, too, there are more signs of this prevalence. Research firm Venture Scanner revealed in March that it’s currently tracking 957 startups, 383 of which specialise in machine learning, with a combined funding total of over $2bn. And the White House is closely monitoring this trend: a subcommittee was established in May to ‘monitor state-of-the-art advances in machine learning within the Federal Government, in the private sector and internationally’.
Is creativity safe?
In our industry, we’re already starting to see evidence of machine learning being employed to improve customer service, generate more meaningful insights and — shock horror — produce creative work. Twentieth Century Fox, for example, partnered with IBM Watson to generate an advert for Morgan, the company’s latest AI thriller. The machine learning algorithm analysed the movie — modelling each scene to determine whether it was happy, sad, tense or scary — and then determined the 10 best moments to stitch into a promotional film. The most spine-chilling thing? The trailer was actually good.
We are, of course, miles away from operating in an industry where creativity is driven principally by machines, not humans. And there’s certainly no guarantee that algorithms will ever be able to master the irrational world of ideas. But early signs indicate that some kind of impact is surely inevitable.
So perhaps machine learning can be best described as being ‘the next wave of digital’. Currently the technology feels a bit siloed — there are specialist companies and teams using the tech — just like there were specialists in ‘digital’ back in 2001. But as it continues to diffuse throughout all sectors and into all companies, it is likely to become as all-encompassing as digital is today.
As that gradually happens, the excitement around machine learning will start to die down. But — unlike so many other trends — the impact won’t disappear with the hype.
Contagious offers an extended Trend Briefing on machine learning — offering insight and analysis on why the technology has evolved, where it’s going and how it’s beginning to impact jobs, companies and sectors. For more information, please contact our head of trends, Patrick Jeffrey, (firstname.lastname@example.org).
Next Practice is Contagious’ home for thinking on the future of creativity in marketing. It features original essays from the advertising industry and beyond, and the editors and strategists of Contagious. Read more about Next Practice and how to submit your own op-ed here.
Originally published at www.contagious.com.