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June 27, 2017

Fourth Industrial Revolution: Calling For A 'Growth Mindset' Over A 'Task Mindset'

Posted by Carly Cooper (View Profile | View All Posts) at 6:20 AM



Make to learn: Building your first robot [Source: https://www.youtube.com/watch?v=gGOWaKmQ51U]

The World Economic Forum predicts five million jobs will be automated by 2020 (The Future of Jobs, Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution, 2016). Furthermore, research by Frey and Osborne (2013) predicts, 47 percent of the total jobs in the US are in the high-risk category and could be automated or computerized within the next 20 years. Some of the facts, figures, predictions, as well as Hollywood productions (Westworld, Transcendence, Interstellar), have many of us fearful of the impact of artificial intelligence on the future. However, never underestimate the power of human potential.

The debate about technology impacting work is one that goes back hundreds of years. In 1776, Adam Smith wrote 'The Wealth of Nations' in which he described the division of labor - a separation of different tasks for different people in order to improve efficiency (1776). During the (first) Industrial Revolution (1760-1820), jobs were being 'automated'. Productivity increased with the invention of the steam engine and by allocating specialized tasks to workers. Now, one can only imagine the fear in the 1800s of "what will happen to me with this new technical advancement?" But indeed, society survived and even thrived. In the Second Industrial Revolution (1870-1914), the railroad, telegraph and machine tools were invented. In 1930, John Maynard Keynes noted, "The increase of technical efficiency has been taking place faster than we can deal with the problem of labor absorption" (Keynes, 1933). Keynes predicted "widespread technological unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor".

And yet, here we are approaching the Fourth Industrial Revolution. Scholars (Levy & Murname) pose four questions for this new age:

  • What kinds of tasks do humans perform better than computers?
  • What kinds of tasks do computers perform better than humans?
  • In an increasingly computerized world, what well-paid work is left for people to do both now and in the future?
  • How can people learn the skills to do this work?

Key skills, the World Economic Forum has identified will be in demand in 2020 are: complex problem solving, critical thinking, cognitive flexibility, mathematical reasoning, and active learning. And I would add, beyond skillsets the need to bring about a shift in the mindset, encourage a 'growth mindset' over a 'task mindset', and increase an individual's agility to learn. But how? How do we all become learners? One of the ways is to actively experiment, make, and create. The mindset and behavior of design thinkers are geared to focus on human values, have a bias towards action, embrace experimentation, to show and not merely tell, craft for clarity, be mindful of the process, and be radically collaborative.

With the understanding of the trends on the future of work and impact of AI, and an invitation to make with robots at the World Economic Forum - Annual New Champions Meeting in Dalian, China, I set out with a Hummingbird kit to build a robot with the help of my 10 year old niece. The Hummingbird Kit by Carnegie Mellon that I will use to coach executives in China is 'child's play'. Although children often learn by experimentation, we adults like to have a plan. (Spaghetti and Marshmellow challenge anyone?) But it's through experimentation, in a safe place, that we can actually learn. When we first opened our Hummingbird kit, the directions were not included, and so we installed every sensor, server, LED light and turned them all on to figure out how it worked. We googled 'hummingbird robots' to gain inspiration on what others had developed, and then together set out to develop a robot designed for and by a 10 year old girl, with the help and awe of a leader in tech. After several ideations and iterations, we have the robot ready for you to see in the video above. #YayRobots

Change is always a bit scary - imagine seeing the first steam engine. The invention of the switchboard, electronic typewriter, spellcheck, home computer, etc. You may have been one of the individuals that crossed the technology chasm as an early adopter, or you may have waited and watched the on others and then joined in. Innovation and invention happen because of people, our unique creative abilities to grasp change, and improve upon it. As we enter the Fourth Industrial Revolution, may we all reach our own next level of potential - let the robots do some of the routine work and let us be creative and have a bit more fun. #YayRobots.

Comments

Dear Carly,

In your essay you suggest that we will address the problem of technological displacement if we can effectively encourage a 'growth mindset' over a 'task mindset' and increase each individual's ability to learn. You ask the question “How do we all become learners?”

In response I want to posit the idea that it’s not a “growth mindset” or increased learning capabilities that we need when dealing with the issue of technological displacement, rather we need to ask much better questions than the ones we’re asking now. In fact, I think we’re suffering from a ‘design thinking deficit’ when it comes to the issue of technological displacement and this deficit is going to make our transition to an automated economy much more difficult than it needs to be.

Whether we are aware of it or not, we’re all engaged in a process of designing an economy that’s great for machines and not so great for people – in just the same way that we’ve designed modern cities to suit automobiles rather than pedestrians. I don’t believe that anyone means for this to happen, it’s just an unintended consequence of technology vendors designing and delivering products and services in a competitive environment. When it comes to design thinking around the problem of technological displacement we can choose to address the intended consequences of our technologies (I call these the easy questions) or we can address the unintended consequences of our technologies (the hard questions). But whichever ones we choose, our success at transitioning to a radically different future will be inversely proportionate to the effort we expend in asking and answering the right questions.

The ‘Easy Questions’ and the ‘Hard Questions’ of Technological Displacement
The ‘easy’ questions around technological displacement are directed towards individuals and pertain to skillsets, mindsets and retraining. They include questions like ‘what skills do our employees need for the future?”, or “how do we turn a network engineer or a system programmer into a roboticist?” Such questions have easy and obvious answers but such answers are easy and obvious because they don’t address the root cause of the problem. To a large extent the easy answers to technological displacement – those that focus on technical skills, attitudes and mindsets - are designed to shift the blame for technological unemployment away from our economic system and onto its victims. Solutions to ‘easy’ questions are the sort of things recommended by the World Economic Forum. Such solutions include; training people to be competent in complex problem solving, critical thinking, cognitive flexibility, mathematical reasoning, and active learning. While these things might be useful in the short-term, the trouble with all of them is that they promote exactly the skills we’re training our machines to become expert at – and we all know what happens when humans race against machines.

The ‘hard’ questions around technological displacement are directed toward the systems that govern our society and pertain to issues like incomes, wealth distribution and economic and political empowerment – precisely the things the World Economic Forum is designed to preserve for its members. In a world of machine-generated abundance where paid-work is largely unnecessary, the questions we need to ask are not “what work will people do?” but rather “how should we distribute the wealth we have created?” These questions are ‘hard’ because they are directed at our systems, not individuals. Systemic change is always hard. It is especially hard when there are deeply entrenched special interests at work with a keen desire to maintain the systemic sources of their privilege. In much the same way that victims of rape in primitive societies are blamed for their misfortune and often stoned to death while the perpetrator walks free, it’s easier for the economically powerful to blame the victims of technological displacement for their misfortune than the system that has sidelined them. I think we can do a lot better than this. I think we have to.

A Design Thinking Deficit
As IT professionals I believe we’re failing to grasp the magnitude of the change we are implementing. Intelligent machines will not merely augment work, they will do away with it entirely – along with our existing system of economic relations. We really need to think courageously about the questions we ask around technological displacement because as long as we’re asking the wrong questions, any answer will do. We need to stop thinking in worn out paradigms: jobs, skills, training, attitudes and mindsets, and start thinking in terms of social purpose, economic justice, contribution and impact.

To get an idea of just how ineffective the ‘easy’ questions are when it comes to dealing with technological unemployment let’s think back to 1908 when the first Model T Fords started rolling of the production line in Dearborn Michigan. If we take the logic deployed in CGP Grey’s excellent video Humans Need Not Apply and apply it to the Levy & Murname questions (which you refer to in your essay) - substituting horses for humans and automobiles for computers - we get the following questions and answers:

Question
• What kinds of tasks do horses perform better than automobiles? and
• What kinds of tasks do automobiles perform better than horses?
Answer
• In 1908 we might have answered: traversing rough, boggy terrain or steep mountain trails, but by 1950 there were no tasks horses could do better than automobiles.
Question
• In an increasingly motorised world, what well-paid work is left for horses to do both now and in the future?
Answer
• In 1908 we might have answered: Last mile delivery, domestic farm work and pony club, but by 1950 there were no well-paid jobs for horses. After 6,000 yrs of loyal service they had ceased to be part of our economic system.
Question
• How can horses learn the skills to do this work?
Answer
• In 1908 it was still possible for horses to leverage their natural advantage in certain limited respects but by 1950 all such advantage had been lost.

While the questions above might have made sense in 1908 when comparing horses to automobiles, it quickly became apparent to everybody in the early 20th Century that the future did not belong to horses. Eventually there was nothing horses could do that automobiles of one kind or another couldn’t do. It’s laughable to think that at one time people may have discussed ways in which horses were going to compete with automobiles and it’s just as laughable now to entertain such ideas when it comes to humans and strong narrow AI’s.

Our challenge, in fact our moral obligation, as individuals and as members of a company dedicated to bringing the benefits of automation to society, is that we ask the right questions about how our inventions and services will shape the future. We are living in a time as disruptive as the agricultural revolution was to 18th Century European feudalism. Between 1760 and 1830 mechanical threshing machines and steam-powered bailers displaced millions of agricultural workers and sent them into the cities as fodder for the new system of factory production. The old social and economic structures of feudalism that bound vassals to their lords gave way to a capitalist mode of production. In this new regime it made no sense to speak of a peasant’s loyalty to his liege, nor of a lord’s obligations to his serfs. Neither category of person existed anymore. In just the same way it doesn’t serve any good purpose for us to restrict our thinking to old concepts such as work, skills, wages and capital if these features and relations of our current economy will soon no longer apply.

Our task as a technology company is to design the future and we will only do that successfully if we ask the right questions - the ‘hard questions’. That to me is what Design Thinking is all about. I think Infosys has an obligation to encourage such thinking since we are at the forefront of the Fourth Industrial Revolution. As counterintuitive as it may seem, I think we would distinguish ourselves from everyone else in our industry if we were prepared to address the ‘hard questions’ of technological displacement candidly and courageously – with a view to making our transition to an ‘intelligent future’ as smooth and as equitable as possible.

Alan Hamilton

Thank you Carly for your post and Alan for the courageous and bold ideas.

wow!! what a deeply engaging view by Carly and an equally though provoking counterview by Alan. Thank you both. As a learner of this topic I'm largely absorbing the various ideas.

From my limited perspective I believe it may not be a matter of OR but AND. Both category of questions as described by Alan are important to address for the long term well-being of humankind.

It would be interesting to think about who is best positioned to address these questions.
Finding answers to the questions pertaining to reskilling of workforce can help businesses control anarchy in their organizations and even profit from it. This offers a business case or motivation for-profit organizations like ours to address these questions.

Addressing the questions pertaining to distribution of wealth may pose a conflict of interest for profit organizations. Organization that can see beyond profit will becomes the leaders of the new world (as has always been). However, humankind cannot fully depend on them to solve this problem. For that reason, the Non-profit organizations like World Economic Forum and the various countries governments may be best suited to address these questions to bring long term systemic changes. As citizens of the new world it will be our responsibility to raise these questions to them.

Wonderful blog Carly, very engaging ideas!

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