Future of Work

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FUTURE OF WORK | 03 RACONTEUR | 06 / 12 / 2015 raconteur.net COGNITIVE COMPUTING CHARLES ARTHUR T he marriage of computing pow- er and data is finally bearing fruit in the field of cognitive computing, sometimes called machine learning or, more controversially, artificial intelligence. In its most everyday form, we see it in tools such as Google Translate or Microsoft's Bing Translate, which can translate phrases and documents effortlessly across multiple lan - guages. More futuristically, the promise of self-driving vehicles, which can complete entire road journeys without driver interven- tion, is already being realised. Yet the biggest revolution in work is hap- pening at some of the most basic levels, such as reading and dissecting legal doc- uments to extract meaning and useful in- formation. The tedious slog of work can be transformed by computers which are able to read and parse legal phrases, and sum- marise them or enter relevant details into a database or spreadsheet. Are these thinking machines? The idea has fascinated philosophers and tech - nocrats for ages. But with every advance that machines make into space normally thought of as "thinking", the goal posts re- treat. Until IBM's Deep Blue defeated then world champion Garry Kasparov in 1997, chess had been thought of as a redoubt for human thinking. More recently, the British company Deep- Mind created a computer program which can learn to play 1980s arcade games, such as Space Invaders and Breakout, by trial and error, based on what it sees on the screen, but without being told any rules or given any objective except to maximise its score. It's a classic conundrum: is the DeepMind system "thinking" or "learn - ing"? Certainly, it improves its score, and discovers neat ways to play games better. Google acquired DeepMind for £400 mil- lion in 2014. Yet the impressive feats of translation tools don't indicate that the machines behind them can actually "think", nor even understand what it is that they are translating. Instead, they rely on a huge resource of data, principally documents containing the same content, which have been translated simultaneously into mul - tiple languages. Publications from the United Nations and the European Union are highly favoured, for example, which may explain why machine translations can sound so remarkably stilted and formal. But to a company using such a translation service, it doesn't matter whether the com - puter can "think", what matters is whether it gets the job done as well or better than a human. And a growing number of stud- ies suggest that more and more jobs are susceptible. A recent study by the Bank of America forecast that the market for robots and artificial intelligence (AI) solu - tions will be worth $153 billion by 2020, of which AI solutions will be worth $70 bil- lion. In ten years, there could be $9 trillion of cuts in employment costs as AI systems take over knowledge work, as self-driving vehicles and drones make $1.9 trillion of efficiency savings compared with having the work done by people, and robots and AI could boost productivity by 30 per cent, while cutting manufacturing costs by be - tween 18 and 33 per cent. The broad wave of cognitive computing is thus ready to break over the world of employment. But it's not a single, simple implementation. "The area splits into two fields," explains Andrew Martin, who is studying for a PhD in cognitive comput - ing at the Tungsten Centre for Intelligent Data Analytics at the University of London. "There are people trying to make more and more complex systems with more and more data, hoping against hope that the problem will solve itself through big com - plex systems. And the other group is sitting back and going to the philosophical draw- ing board trying to work out what intelli- gence actually is, and how it emerges." So which group is the Tungsten Centre in? "Sort of both. We're making big sys- tems, but aware of the limits of what com- puters can and can't do," says Mr Martin. Share this article and infographic on social media via raconteur.net "We have a view of the things that won't be solvable." Some problems look as though they're beyond solution by one approach, but that doesn't mean it can't be done. In self-driv - ing cars, Mr Martin says, "you have a machine that has to act in very complex situations, but it will never have the full situational awareness that a human driver does". Yet this sounds like some of the argu- ments that used to be used about chess: a computer could never win at chess, some used to argue, because it wouldn't be able to understand the nuances of certain moves or understand ideas such as control of the centre of the board. Those arguments went by the board when IBM's Deep Blue defeated Kasparov. Being able to do lots of calculations very quickly turned out to be a sufficient substitute for a human's full situational awareness of the chess board. Indeed, Google's cars have driven mil - lions of miles in the United States and the only accidents have been the fault of other, human drivers. In fact, a police officer re- cently flagged down a Google car because its driving seemed over-cautious. Mr Martin says that with cognitive com- puting, "some things are instantly solv- able because they're constrained – the problems have clearly defined limits – and some people might think that solving the quickest route to somewhere isn't cogni - tive computing". But that used to be the ambit of taxi drivers with huge experi- ence; now it's available to anyone with a smartphone. So which are the fields that will be most affected by advances in cognitive com- puting? Analysis of legal documents is a key one. London-based law firm Berwin Leighton Paisner recently made substan- tial time-savings by using such a system to analyse the content of hundreds of Land Registry documents automatically, rather than getting the same work done by interns and paralegals. "The real value that you add as a lawyer is about anomalies," says Wendy Miller, a partner at the firm. "If clients have a huge number of contracts and want to under - stand them, it's useful to have these data extraction tools. It's applicable to a surpris- ing number of tasks and we're working to put it to work in other areas of law." At the Tungsten Centre, Mr Martin says the areas of work which will be most af - fected are those which "don't need much human inspiration". The centre is already studying the world of finance. He points to vehicle manufacture as one which could easily be done by such sys - tems and more prosaically to supermarket self-service checkouts. "The road haulage industry is at the biggest threat of being se- riously disrupted by AI," he says, "because motorways and motorway driving are rela- tively constrained environments." There have already been tests of self-driv- ing trucks in the US, Germany, Holland and Japan by Daimler, Scania, Ford and others. The potential for employment dis- ruption is huge, since there are 3.5 million professional truck drivers in the US alone, whose income generates support for mil- lions more people, whether in their fami- lies or the truck stops they visit as part of their work. What then will they move on to? How will the world of work be affected? At its core, this is the same question as that faced by horse and stable owners at the end of the 19th century as motor cars arrived. The as - sumption is that grooms and bridlemakers all found new work. But what's never clear is whether they found better-paid work or subsistence. That tends to be the concern around the march of the new world of AI, which can also be deployed far faster than the car factories of the early-20th century could ramp up production. "The way to think of cognitive computing is that it gives us very fast and obedient, but extremely stupid, slaves," says Mr Martin. "The parts of industries that will remain are those which require knowledge." But what parts are those? How do we define "knowledge" so that we can be sure it won't be accessible to a machine-learn - ing system in five or ten years? Mr Martin says it's easier to think of the tasks that will be susceptible, "things that you can think of as mostly rule-following and rote behaviour, repetitive, with no creativity, or where there's only a small amount of independent thought and a lot of people doing it". The contrast is with fields which require deep knowledge and experience, such as the law and medicine. Even though IBM's Watson is being used to analyse scans and data from cancer patients in a number of hospitals in the US, the expectation is you will still need doctors and lawyers to de - liver the final decisions on what to do and where to focus. Can the machines 'learn' or 'think'? Computing power and data have given birth to artificial intelligence, which is set to transfer labour pains to the world of work CASE STUDY: BERWIN LEIGHTON PAISNER London-based law firm Berwin Leighton Paisner had a very specific challenge: analyse more than 700 Land Registry documents for a client, to extract details about land ownership such as the name and address of the overall owner, and related interests such as outstanding mortgages and other debts tied to them, plus any third-party interests in the title. And the answers had to be 100 per cent accurate. In the past, the only way to do that would be to assemble a team of interns and paralegals, give them the documents and leave them to slog through until they emerged with the answers. Together with training and necessary cross-check- ing to make sure that nobody had made any mistakes, this could consume huge amounts of time, as well as being boring. "I once had to do legal disclo- sure checking on a huge dispute where I was put in a room with documents piled to the ceiling and told to get on with it," recalls Wendy Miller, a partner at the firm and a litigator in commercial real estate disputes. This time the law firm turned to cognitive computing, which has begun to revolutionise much of the tedious work in legal analysis. The firm had already been looking for ways to improve efficiency. "What we do is very personnel-heavy," says Ms Miller. Also, the documents were likely to arrive in near-ran- dom groups, making resource planning difficult. "You don't want a team sitting around doing noth- ing, but it's tricky if you then find you need 200 documents analysed by tomorrow," she says. The company turned to a British company which specialises in cognitive computing systems for information-intensive businesses. It designed a system which could scan the PDFs generated from the Land Registry and generate a spreadsheet that could be queried by the law team. Compared with the 45 minutes it would take a human to examine each document, the RAVN system has already saved more than 500 work-hours. "The great efficiency of artificial intelligence is that we have complete flexibility because it's always there in the back- ground," says Ms Miller. So are the people who would have done that work out of a job? "Extracting data from documents isn't perceived as valuable, so we were using junior people on work that's hard to charge for," she says. "Instead, we've been able to use those people on later stages of the project which have more value." It doesn't matter whether the computer can 'think', what matters is whether it gets the job done as well or better than a human TECHNOLOGY: CHANGING THE WAY WE WORK FACTORS TRANSFORMING WORK OVER THE NEXT FIVE TO TEN YEARS Improved the customer experience Improved internal communications TECHNOLOGY BREAKTHROUGHS BENEFITS OF ADOPTING DIGITAL TECHNOLOGIES DON'T KNOW/ NOT SURE NONE OF THESE RAPID URBANISATION DEMOGRAPHIC SHIFTS SHIFTS IN GLOBAL ECONOMIC POWER RESOURCE SCARCITY AND CLIMATE CHANGE DIGITAL TECHNOLOGIES ARE CHANGING THE WAY BUSINESSES WORK WHICH DIGITAL TECHNOLOGIES HAVE HAD THE MOST IMPACT OVER THE PAST TEN YEARS? Enhanced the productivity of our workers Enhanced existing products and services Developed new business models Automated operational processes Expanded reach to new markets Launched new products and services GLOBAL TECH PREDICTIONS, 2015–2020 of IT decision- makers increase spending on cloud computing Source: Computerworld Source: Future of Work, Raconteur 2014 Source: PwC 2014 global software-as-a- service market, up 21 per cent on 2015 Source: Forrester of IT budgets will be deployed in mobile apps Source: IDC of business content will be authored by machines Source: Gartner employees will be required to wear health and fitness tracking devices as a condition of employment Source: Gartner will be spent on enterprise apps, up from $149.9 billion in 2015 Source: Gartner estimated size of the enterprise wearables, up from $218 million in 2015 Source: Tractica of organisations use advanced analytics to improve decision-making Source: Gartner TOP 10 DRIVERS BEHIND DIGITAL TRANSFORMATION FOR BUSINESSES CONTENT MANAGEMENT SYSTEMS RESPONDING FASTER TO CHANGING NEEDS OPTIMISING BUSINESS PROCESSES BETTER ENGAGED EMPLOYEES BY INCREASED ENABLEMENT INCREASING REVENUE AND PROFITS KEEPING UP WITH COMPETITORS VIDEO CONFERENCE TOOLS STIMULATING INNOVATION BETTER COMMUNICATION WITH THIRD-PARTY SUPPLIERS ATTRACTING THE BEST TALENT IN A COMPETITIVE MARKET IMPROVING COMMUNICATION BETWEEN EMPLOYEES CREATING AN INCREASING GLOBAL WORKFORCE Source: Future of Work, Raconteur 2014 Source: Future of Work, Raconteur 2014 CLOUD COMPUTING SOCIAL MEDIA WEARABLE TECHNOLOGY 17% The way to think of cognitive computing is that it gives us very fast and obedient, but extremely stupid, slaves WHICH DIGITAL TECHNOLOGIES WILL HAVE THE MOST IMPACT OVER THE NEXT FIVE YEARS? 26% WEB BROWSERS 23% 21% DESKTOP APPS 17% 16% SEARCH 14% 40% 30% 29% 28% 26% 22% 19% 19% 2015 2016 2017 2018 2018 2019 2020 2020 1 2 3 4 5 10 9 8 7 6 42% 25% 20% 75% $106bn $201bn $6.3bn 2m SMARTPHONES 31% SMARTPHONES 44% 39% TABLETS E-MAIL 45% CLOUD COMPUTING AND STORAGE 40% 25% MOBILE APPS 25% WEB COLLABORATION TOOLS 23% 20% SOCIAL MEDIA 39% 53% 36% 33% 26% 13% 4%

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