With AlphaGo, DeepMind demonstrated the power of machine-learning to beat humans. And it is not only in games where we come up short
Put simply, AI refers to technologies that try to replicate core human functions. Peet van Biljon, formerly of McKinsey and now one of the leading innovation specialists engaging with the topic, sums it up neatly: “It’s about computers doing things ever smarter than we used to expect of machines, and ever closer to what we thought only humans could do.” The resemblance to human intelligence is no coincidence, he says, as “recent advances all involve some sort of neural network, which is modelled on how we think the human brain works.”
At the heart of the excitement over AI is the concept of machine learning: computers working things out for themselves without being explicitly programmed to do so. Instead, they progress by processing and analysing huge amounts of data, identifying patterns and improving their performance as they do so.
The classic example is the AlphaGo system, developed by Google-owned DeepMind, which in 2017 beat the reigning (human) world champion of the game Go. Impressive in itself, this became more so when a second machine, AlphaGo Zero, which had merely been programmed with the game’s rules, trained itself to play without any human prompting at all, and within six weeks had learned to beat AlphaGo – by 100 games to nil. AI had enabled it to become the best Go player in the world, well beyond the level of human performance, even though this had been honed over the little matter of 2,500 years of the game’s history. A further AlphaGo version is now teaching humans how to play the game better.
DeepMind’s CaseCruncher Alpha beat UK lawyers in a competition to predict outcomes of court cases
It isn’t just games where AI has the edge on humans. DeepMind’s CaseCruncher Alpha beat a team of UK lawyers in a competition to predict the outcomes of court cases. And AI-enabled machines are starting to outperform specialist radiographers at detecting early signs of cancer.
For the tech industry, AI is the future. As Google CEO Sundar Pichai commented in 2016: “Machine learning is a core, transformative way by which we are rethinking how we’re doing everything.” It’s an approach shared by Ginni Rometty, IBM CEO, who said that it will form the basis for the company’s future strategy.
Strictly speaking, it isn’t AI alone that is causing such seismic upheaval, but rather its impact in combination with the rapid evolution of other technologies. This, says PwC, amounts to nothing short of a “fourth industrial revolution” (4IR). It defines this as “the current explosion of technological innovations characterised by connectivity, speed, breadth and depth of transformation ... The rapid advances in AI [along with] the internet of things, robots, autonomous vehicles, the cloud and big data, to name but a few, are rapidly transforming industries and societies across the world.”
The tech industry’s ability to capture and store massive amounts of data is crucial to AI’s success. It feeds on data; the more it has to work with, the better it performs. So it’s just as well that our increasingly connected lives are generating the stuff as never before – everything from video uploads to GPS records to the vast trail of social media updates that we leave behind us. More than 90% of the data floating around the cloud has been generated in the last two years alone. And as the Royal Society observes in Machine learning: the power and promise of computers that learn by example, data is “the new oil; holding incredible economic potential, but requiring refinement in order to realise this.”
Data is the new oil; holding incredible economic potential, but requiring refinement
Much of it is available in crude form for commercial use (thanks in part to all those “I agree” boxes we tick without thinking when downloading a new app). And it’s starting to be applied. You know those personalised recommendations? Those nudges to buy this, that or the other depending where you are and what you bought yesterday? That’s early-stage AI in action.
As Oliver Rowlands, software innovation specialist and studio director for WIPRO’s BuildIt division, comments: “Facebook has so much data on me that it probably knows who I am better than I do.” And in that data lie vast potential riches for those who can mine it. Ever wonder why so much of the net remains free to use? AI’s why.
This is part of our in-depth briefing on AI. See also:
Can we turn AI into a force for good?
How AI and robotics can transform CSR
Comment: 'We can't leave Silicon Valley to solve AI's ethical issues'
Machine learning: how firms from Danone to Sodexo are integrating AI
First, do no harm: regulators and tech industry scramble to tame the AI tiger
'With AI polluters will have nowhere to hide'
Apocalypse soon? Tech giants warn of risks of 'AI arms race'
Rise of the sewbots: Asian factory workers feel chill winds of automation
'Our problem with automation is a labour shortage, not surplus'