Humans and AI: Rivals or Romance?

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Artificial intelligence (AI) has been developing at a frightening pace. It is debatable to what extent it has improved our lives – being able to use geolocation and search for the best restaurants or places of interest is great; however, AI is, at the same time, eliminating plenty of jobs, fast. A frequently cited report points out that a staggering 47 per cent of jobs in the US will be automated soon [1]. Another study suggests that 45 per cent of the daily tasks currently done by humans could be automated if current trends continue [2]. These numbers are inconceivable, considering that the worst case of unemployment to be recorded was during the Great Depression, in 1929, where an estimated 25 per cent of the population was out of work.

In our most recent book, we mentioned the case of a CFO at an investment bank. Last year, he was given the task of reducing the size of his staff by 80 per cent because off-the-shelf digital technologies could be doing the jobs that were currently occupied by humans [3]. And, in 2017, we have seen large banks close record numbers of physical branches, making thousands redundant in the process. Judging by this, humans are starting to look like horses before the arrival of automobiles.

The (human) empire strikes back

It’s certain that we will hear more and more alarmist accounts. However, we have seen it before – many times, in fact. Back in 1963, it was J F Kennedy who said, “We have a combination of older workers who have been thrown out of work because of technology and younger people coming in […] too many people are coming into the labor market and too many machines are throwing people out” [4]. Going further back, when the first printed books with illustrations started to appear in the 1470s in Germany, wood engravers protested as they thought they would no longer be needed [5].

But this all begs one question: If technological progress represents a comprehensive threat to humans, then why do we still have jobs left? In fact, many of us are still working, probably much harder than before. The answer: machines and humans excel in different activities. For instance, machines are frequently no match for our human minds, senses and dexterity. For example, even though Amazon’s warehouses are automated, humans are still required to do the actual shelving.

And this doesn’t only apply to physical jobs. The real story behind today’s AI is that it cannot function without humans in the loop. Google is thought to have 10,000 ‘raters’ who look at YouTube videos or test new services. Microsoft, on the other hand, has a crowdsourcing platform called Universal Human Relevance System to handle a great deal of small activities, including checking the results of its search algorithms [6]. And this blend of AI and humans, who follow through when the AI falls short, is not going to disappear any time soon [7]. Indeed, the demand for such on-demand human interventions is expected to continue to grow. The ‘human cloud’ is set to boom.

Closer together

The above illustrates a very important lesson – humans will be needed. The key is how to integrate humans and machines in various activities and how to steer AI towards the creation of new economic interfaces, rather than towards the mere replacement/displacement of existing ones. At the moment, the probability of AI getting things right is between 85 and 95 per cent. Humans, on the other hand, generally score 60 to 70 per cent. On this basis alone, we need only machines and not humans.

Yet, in some highly data-driven industries such as financial and legal services, there can be no error – any mistake can result in huge financial costs in the form of economic losses or expensive lawsuits. Machines by themselves are not enough. Furthermore, AI can only run an algorithm that is predefined and trained by a human, and so a margin of error will always exist. When mistakes take place, AI will not be able to fix them. Humans, by contrast, are able to create solutions to problems. We believe that the best solution is to use machines to run production up to the level of 95 per cent accuracy, and supplement this with human engineers to mitigate risks if not to strive to improve accuracy.

Humans and machines will – and must – work together. As business consultants, educators and policy advisors, we all strongly believe that, ultimately, what really matters is how to prepare people to work increasingly closely with machines.

 

References:
[1] Frey, Carl Benedikt and Osborne, Michael. The Future of Employment: How susceptible are jobs to computerisation? Oxford Martin School, 2013. http://www.oxfordmartin.ox.ac.uk/publications/view/1314
[2] Chui, Michael, Manyika, James, and Miremadi, Mehdi. How Many of Your Daily Tasks Could Be Automated?, Harvard Business Review, 14 December 2015. (https://hbr.org/2015/12/how-many-of-your-daily-tasks-could-be-automated)
[3] Tse, Terence and Esposito, Mark. Understanding How the Future Unfolds: Using Drive to Harness the Power of Today’s Megatrends. Lion Crest, 2017.  
[4] John F Kennedy interview by Walter Cronkite, 3 September 1963, https://www.youtube.com/watch?v=RsplVYbB7b8
[5] The Economist. Artificial intelligence will create new kinds of work, 26 August 2017. https://www.economist.com/news/business/21727093-humans-will-supply-digital-services-complement-ai-artificial-intelligence-will-create-new
[6] Ibid.
[7] Gray, Mary L. and Suri, Siddharth. “The humans working behind the AI curtain,” Harvard Business Review, 9 January 2017.

Terence Tse

Terence is a co-founder & managing director of Nexus Frontier Tech: An AI Studio. He is also an Associate Professor of Finance at the London campus of ESCP Europe Business School. Terence is the co-author of the bestseller Understanding How the Future Unfolds: Using DRIVE to Harness the Power of Today’s Megatrends. He also wrote Corporate Finance: The Basics. In addition to providing consulting to the EU and UN, Terence regularly provides commentaries on the latest current affairs and market developments in the Financial Times, the Guardian and the Economist, as well as through CNBC and the World Economic Forum. He has also appeared on radio and television shows and delivered speeches at the UN, International Monetary Fund and International Trade Centre. Invited by the Government of Latvia, he was a keynote speaker at a Heads of Government Meeting, alongside the Premier of China and Prime Minister of Latvia. Terence has also been a keynote speaker at corporate events in India, Norway, Qatar, Russia and the UK. Previously, Terence worked in mergers and acquisitions at Schroders, Citibank and Lazard Brothers in Montréal and New York. He also worked in London as a consultant at EY, focusing on UK financial services. He obtained his PhD from the Judge Business School at the University of Cambridge.

Mark Esposito

Mark Esposito is a member of the Teaching Faculty at the Harvard University's Division of Continuing, a Professor of business and economics, with appointments at Grenoble Ecole de Management and Hult International Business School. He is an appointed Research Fellow in the Circular Economy Center, at the University of Cambridge's Judge Busines School. He is also a Fellow for the Mohammed Bin Rashid School of Government in Dubai. At Harvard, Mark teaches Systems Thinking and Complexity, Economic Strategy and Business, Government & Society for the Extension and Summer Schools and serves as Institutes Council Co-Leader, at the Microeconomics of Competitiveness program (MOC) developed at the Institute of Strategy and Competitiveness, at Harvard Business School. He is Founder & Director of the Lab-Center for Competitiveness, a think tank affiliated with the MOC network of Prof. Michael Porter at Harvard Business School and Head of the Political Economy and Sustainable Competitiveness Initiative. He researches the "Circular Economy" inside out and his work on the topic has appeared on top outlets such as The Guardian, World Economic Forum, Harvard Business Review, California Management Review, among others. He is the co-founder of the concepts of "Fast Expanding Markets" and "DRIVE", which represent new lenses of growth detection at the macro, meso and micro levels of the economy. He is also an active entrepreneur and co-founded Nexus FrontierTech, an Artificial Intelligence Studio, aimed at providing AI solutions to a large portfolio of clients. ​He was named one of the emerging tomorrow's thought leaders most likely to reinvent capitalism by Thinkers50, the world’s premier ranking of management thinkers and inducted into the "Radar" of the 30 most influential thinkers, on the rise.

Danny Goh

Danny is a serial entrepreneur and an early stage investor. He is the partner and Commercial Director of Nexus Frontier Tech, an AI advisory business with presence in London, Geneva, Boston and Tokyo to assist CEO and board members of different organisations to build innovative businesses taking full advantage of artificial intelligence technology.
 
 Danny has also co-founded Innovatube, a technology group that operates a R&D lab in software and AI developments, invests in early stage start-ups with 20+ portfolios, and acts as an incubator to foster the local start-up community in South East Asia. Innovatube labs have a team of researches and engineers to develop cutting edge technology to help start-ups and enterprises bolster their operation capabilities. Danny currently serves as an Entrepreneurship Expert with the Entrepreneurship centre at the Said Business School, University of Oxford and he is an advisor and judge to several technology start-ups and accelerators including Startupbootcamp IoT London. Danny has lived in four different continents in the last 20 years in Sydney, Kuala Lumpur, Boston and London, and constantly finds himself travelling.