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Monthly Archives: May 2014

Robots may take your job but it could lead to a more humane society


Many in the Artificial Intelligence and robotics professions clearly state that their work is toward what has come to be called “weak A.I.” — which is focused more on building tools for helping humans in their work rather than on replacing them. This is clearly the claim of robot manufacturers such as Rethink Robotics and Universal Robots. However weak A.I., or its associated technology, machine learning is becoming an integral component of automation – and it is this automation, something that previously may have been called Business Process Automation, that may explain the high rate of joblessness in many advanced countries some four years into the recovery from recession.

Yet, it is not inconceivable that in the near future current advances in robotics and automation technology will have a bigger impact on employment from the cashless supermarket checkout to security guards; we will have robot roofers’ helpers and A.I. receptionists, robots are increasingly used on farms for milking cows, picking peppers and drones for crop spraying. Advanced algorithms are ‘improving’ financial trading and providing more and more predictive analysis. Insurance and travel tickets are ordered via online automated systems and banks are reducing headcount (and physical sizes) of branches as online banking and ATM’s become pervasive – all created by automated technology. The list of jobs that soon could be, or already can be performed, by robotic and automated technologies is vast, but if you read on I will show how this is likely to greatly benefit humanity.

One of the key questions being asked by senior economists and others: “Is the threat of automation and robotics on employment the most pressing social issue?” This is not new — In his book published in 1995 The End of Work, Jeremy Rifkin examined the technological innovations and market-directed forces that were “moving us to the edge of a near workerless world.

Redefining opportunities and responsibilities for millions of people in a society absent of mass formal employment is likely to be the single most pressing social issue of the coming century. (Introduction page XV)

More recently, the economist Larry Summers who is President Emeritus and Professor at Harvard University, said that the big concern in the economy and split between capital and inequality will be the “devastating consequences of robots, 3-D printing, artificial intelligence, and the like for those who perform routine tasks.” Adding that all sectors of the workplace are at risk of the advances in “artificial intelligence to replace white-collar as well as blue-collar work will increase rapidly in the years ahead.”

Despite many highlighting the gloom few have spoken of the benefits and offered up good solutions, until now.

Who owns the robots?

One of Larry Summers Harvard colleagues, the economist Professor Richard Freeman, a leading labor economist who also directs the National Bureau of Economic Research, presented a paper in early May with the title: Who owns the robots rules the world.

Freeman is also convinced that robots will displace many from the workplace, offering up the advances in technology from IBM’s Watson preparing recipes (Chef’s beware), to the improvements of robots as anesthetists. He warns:

Behind the headlines are advances in artificial intelligence that create machines that are far better substitutes for human intelligence than seemed possible just a few years ago

Robots can increasingly substitute for workers, even highly skilled professionals.

The main message of Professor Freeman is that ‘workers (you and me) need to ensure that they have some other income from capital and not just income from work. To own equity stakes, in companies that will thrive, so as to receive dividends and increased wealth, to own the land or properties to receive rent:

As companies substitute machines and computers for human activity, workers need to own part of the capital stock that substitutes for them to benefit from these new “robot” technologies. Workers could own shares of the firm, hold stock options, or be paid in part from the profits. Without ownership stakes, workers will become serfs working on behalf of the robots’ overlords. Governments could tax the wealthy capital owners and redistribute income to workers, but that is not the direction societies are moving in. Workers need to own capital rather than rely on government income redistribution policies.

He points to the fact that Chief Executive Officers (CEO’s) and other executives are paid stock options, restricted stock grants, and bonuses tied to capital income:

It is telling that the persons with the greatest power in corporations prefer to be paid as owners rather than as wage and salary workers.

He does not believe it is far fetched that robots and associated technologies will increasingly take more of the jobs, dismissing the hype claim and indicating this is a reality. He encourages people to own the robots, or at least have their capital in someway invested so that it provides an income, failing to do so will leave those with no ‘robot ownership’ behind:

The “who-owns-the-robots-rules-the-world” thesis is simple: Regardless of whether technological advance is labor-saving or capital-saving, skill-biased or not, and regardless of the speed with which robots or other machines approach or exceed human skill sets, the key to the effect of the new technologies on the well-being of people around the world is who owns the technologies.

Is it any wonder so many tech companies have good stock options? Tech employees see first hand the impact on jobs as their solutions are rolled out. Freeman emphasizes the need for all employees to be stock-owners in their companies (or maybe have John Lewis style partnerships?).

There is only one solution to the challenge posed by computerizing skill through machines. That is for you, me, all of us to have a substantial ownership stake in the robot machines that will compete with us for our jobs and be the vehicle for capital’s share of production. We must earn a substantial part of our incomes from capital ownership rather than from working. Unless workers earn income from capital as well as from labor, the trend toward a more unequal income distribution is likely to continue, and the world will increasingly turn into a new form of economic feudalism. We have to widen the ownership of business capital if we hope to prevent such a polarization of our economies.

Freeman is right, the factor that potentially has the greatest economic benefit in dealing with robotization and the falling share of labor income is employee ownership, as we help build the business we work for — the more skin (equity) we have in the game the better.

A new paradigm

My own thoughts are that we are at the cusp, or in fact quite advanced, in a techno-economic paradigm, which is breaking the organizational habits in technology, the economy, management and social institutions.

In addition to Freeman’s call for us to seek to ‘own the robots,’ I also see a great positive, and as I have written before: I believe the attempt to better the world for all humanity is hidden somewhere within the automated robotic economy.

The robot overlords will need to ensure there is still a flow of finance to people or the goods they make with their automated machines will have no buyers. Organizations (and indeed individuals) that increasingly see vast profits from the machine economy are creating more and more jobs in the Not For Profit sector. Bill Gates has possibly created thousands of jobs as he uses his wealth for humanitarian and educational purposes. Other tech beneficiaries, and billionaires are putting their money to work in ways that help others — and creating jobs in the process.

It is said the Not For Profit (NFP) sector worldwide already surpasses US$ 2 trillion. This will grow considerably and I believe it will become a major sector of job growth. Already we see this playing out as NFP’s such as Google.org seeks to solve humanities problems and bring together brain and brawn, creating jobs and giving hope to many.

Whilst technology will be a big factor in tearing jobs apart, the wealth stream created by the robot owners will likely also put society back together, and in so doing help build a better, stronger, more resilient and altruistic society.

Picture credit Google.org

5 Monday reads in Robotics, Artificial Intelligence and Economics 

Ben Goertzel believes we are just years away from having a robot read the news (South China Morning Post)

Artificial intelligence techniques such as natural-language processing and computer vision will someday revolutionize our world – at least they will help advertisers sell us more: (Gigaom)

The ultra lethal drones of the future and some we have now: (New York Post)

Rodney Brooks cuts through the hype, what robots can and can’t do – people and robots working together; but don’t underestimate the robots: (Wired – Video)

Frances Coppola discusses the “Wastefullnes of automation:” If a small number of people own machines, how will capitalism survive? (Pieria)

Larry Summers gets it wrong on Piketty and Robots

Piketty and robotsFirst of all I think Larry Summers gets much right, especially with respect to how many people are unemployed and have been displaced by a multiple of factors, of which robotics is one of them, albeit not a major factor (yet). I’m not quite sure why Summers mentions disability insurance – would be grateful if he would clarify that.

He also considers that robotics will have a major impact on future employment and indicates that Thomas Piketty does not emphasize the threat of robotics and associated technologies enough. Here’s what Summers writes:

I am not sure that Piketty’s theory emphasizes the right aspects. Looking to the future, my guess is that the main story connecting capital accumulation and inequality will not be Piketty’s tale of amassing fortunes. It will be the devastating consequences of robots, 3-D printing, artificial intelligence, and the like for those who perform routine tasks. Already there are more American men on disability insurance than doing production work in manufacturing. And the trends are all in the wrong direction, particularly for the less skilled, as the capacity of capital embodying artificial intelligence to replace white-collar as well as blue-collar work will increase rapidly in the years ahead.

This is very similar to many critiques that wonder whether Piketty is right to think the future will look like the past.

But the critiques fail to appreciate that Piketty does look to the future, in fact he specifically states in his book the extreme example is a society where robots produce the entire output, and that in this case the returns will go entirely to the owners of robots and factoral income distribution would be 100% capital, 0% labor.

In Capital in the Twenty-First Century Piketty talks of an “entirely robotized economy in which one can increase production at will.” (Page 217). He sees this as techno optimism (or pessimism depending upon which side of the fence you sit).

He talks about how capital will always find new and useful things to do, such as producing “ever more sophisticated robots,” and the impact this will have on inequality. (Page 221)

And he refers his readers to his online technical slides where he speaks of the “extreme case” being a “pure robot-economy.” And the people to worry about are those “that own the robots.”

I’m in agreement with Noah Smith who writes: “If robots are to blame, then Piketty is right:” If R, the rate of return on capital (which is different than the safe interest rate “r”) is greater than g, the rate of economic growth, and that this fact can be expected to continue into the indefinite future, resulting in an ever-rising capital share of income and an ever-falling labor share.

Yes we should take the threat of robots and potential mass unemployment seriously as Summers says and I believe Piketty emphasizes this, in fact Piketty also states that “education and technology are the decisive determinants in wage levels,” although maybe he could have expanded upon this. But more importantly we should consider Piketty’s warning on who owns the robots, or as he says:

It is too soon to warn readers that by 2050 they may be paying their rent to the Emir of Qatar (or Norwegian sovereign fund).” And he later adds: “Nevertheless it would be a mistake to ignore the issue.”

US Army to test robots that “think – look – move – talk – work”

A report issued by the U.S. Defense shows that the army intends testing robots that “think – look – move – talk and work.” Figure 24 summarizes the Army’s vision for these five problem domains, barriers to achieving its vision, and work to be done to advance toward the vision.

US Army 24

The Robotic Collaborative Technology Alliance (RCTA) plans a Capstone Experiment in during 2014. The U.S. Defense robot provides the following example as shown in Figure 25.

The Capstone Experiment is centered around a notional cordon-and-search operation: during urban transit by a small unit (i.e., four to five soldiers), a fugitive is reported to have entered a building the unit is approaching. A man-transportable robot is instructed to “cover the back door” of the building by the unit commander because he cannot safely split up his limited resources. The robot must understand and acknowledge the order, associate the order with its perceived environment, move safely and securely to an appropriate vantage point, observe activity behind the building, and report any salient events to the unit commander. As needed, it enters the building and negotiates stairs or other mobility obstacles. It then returns to its unit, maintaining situational awareness, and is ready for another assignment. While this narrative occurs in the context of a cordon-and-search operation, its underlying capabilities support a broad range of potential operational missions.

Effectively the Military consider that a truly useful robot should have the ability to learn on its own from interactions with the physical and social environment. It should not rely on a human programmer once it is purchased. It must be trainable.

Figure 25

Unfortunately, the report goes further by indicating that work will continue to move to fully autonomous robots, something I am personally very much against:

Similar to the other Services, middle- and long-term work by the RCTA will continue to evolve and improve capabilities to increase the level of autonomy in systems from the current, remotely operated systems to autonomous systems.

Botsourcing – Robots Are Starting to Make Offshoring Less Attractive

My latest Harvard Business Review article is now live.

The hype around robots taking jobs is reaching a crescendo, in response to an insightful new book The Second Machine Age by Erik Brynjolfsson and Andrew McAfee, as well as an Oxford Martin School study: The Future of Employment: How susceptible are jobs to computerization? The former states that digital technology and robotics are advancing at such a pace that: “Professions of all kinds — from lawyers to truck drivers — will be forever upended. Companies will be forced to transform or die.”

For managers, the trend toward botsourcing will require a shift in thinking. Rather than moving operations to wherever work costs the least, think about which pieces can be automated, and how best to combine human and robotic expertise.

Read the full article at Harvard Business Review…

Cobots – people and robots working together

When people talk about the displacement of jobs brought about by the development of robotics, Artificial Intelligence (A.I.) and automation, they have a tendency to leave out the capabilities and flexibility of people and to impute a certain amount of agency to the technology itself. The technology becomes the focal point. The deeper problem is the idea that we just need more technology (robots, automation or petaflops) — as if technology is something you pour on grass like water to help growth — whereas in our businesses it is not technology alone that is the answer to increased productivity and efficiency, it is technology combined with people and knowhow that makes the big difference.


As sophisticated as these machines are, they are, at most, semi-autonomous. I don’t believe I will see a robot or computer have an original thought, the Holy Grail of Artificial General Intelligence, in my lifetime. Robots and computerized machines are tools, albeit remarkably sophisticated tools, used by humans.

Many organizations are beginning to see the advantages of cobots. Large corporations like Apple and General Electric and smaller companies such as C & S Wholesale Grocer are beginning or increasing manufacturing within the US through a combination of people and robots. Flextronics, a manufacturer of consumer electronics utilizing robots and automation, is famed for displaying a banner outside its factory in Milpitas, south of San Francisco proudly proclaiming: “Bringing Jobs & Manufacturing Back to California.”

Europe is seeing similar trends in banking, financial services and in the industrial and other service sectors. The European Union is investing heavily to help businesses build and adopt robots and forecasts robotics and related services will contribute an extra $80 billion in GDP per year by 2020.

Whilst sales of robots is growing, figures released by the Robotic Industries Association (RIA), the industry’s trade group, indicate a growing demand for industrial robots in the US with a total of 5,938 robots valued at $338 million ordered by companies in North America in the first quarter of 2014, coming in just shy of the all-time record set at the end of 2012. This increase in robot sales is having a positive impact on jobs, either creating them or sustaining existing jobs and helping to increase productivity and profitability. Jim Stogdill at O’Reilly Media emphasizes where I believe co-working is going:

“As automation takes the next layer of jobs at the current bottom, we humans are asked to do more and more complex stuff, higher up the value hierarchy.”

The potential uses for robotics, AI, and automation in business are great and ever expanding and helping to move jobs locally. But we must remember technology is here to serve us, not the other way around. It is the tech savvy company that successfully unites robots, automation and humans that will thrive in the ‘second machine age.’

Photo: ABB’s FRIDA (Friendly Robot for Industrial Dual-arm Assembly).

Four reads in Artificial Intelligence, Robots and their Economical Impact

  1. BHP to use autonomous trucks in Australia – the autonomous trucks, cut costs by reducing the need to house, feed and employ drivers (The Australian)
  2. Computers will never replicate the human brain and the technological Singularity is “a bunch of hot air.” (MIT Technology Review)
  3. How robotic surgery ‘saved my life’ (Irish Independent)
  4. Andrew McAfee believes in his lifetime (he is in his mid 40’s now) robots will displace many in the workforce. This time the robots really are going to take our jobs (Slate)

Reigniting the economy with computational thinking

I first saw psychologist Daniel Kahneman in 2001, the year before he won the Nobel Prize for Economics. Dan has since become known as the grandfather of Behavioral Economics and a big influence on computer programmers and researchers developing Artificial Intelligence, smartphones and cognitive computing.

In nine words Dan changed how I think. Those 9 words are:

“We think much less than we think we think.” 

Dan’s most important achievements are in his research into human decision making under uncertainty, showing how human decision making behaviors deviate systematically from standard predicted results following economic theories. How we use biases and heuristics — the mental shortcuts we take to make decisions and form opinions.

Kahneman has frequently confirmed the influence of Herbert Simon, a famous American computer scientist and psychologist, and one of the ‘founders’ of Artificial Intelligence and cognitive science, who won the Turing award in 1975 and the Nobel Prize in Economics in 1973. Like Kahneman, Herb Simon’s Nobel Prize in economics resulted for his work in decision-making.

Both Kahneman and Simon taught us how easy it is to make mistakes and fool ourselves through the way we think – or rather don’t think.

So how do we change this and change our way of thinking to get better results?

To thrive in this new world of human and machine collaboration and get the best out of the advances in technology requires a new way of thinking. Jeanette Wing, a Carnegie Mellon University professor, research analyst at Microsoft and currently assistant director of the US National Science Foundation’s computer programs calls this ‘computational thinking.’

Professor Wing has a vision of computational thinking becoming a fundamental skill, ranking alongside reading, writing and arithmetic. The Singapore Government say: “computational thinking should be taught to all Singaporeans and made a national capability.”

Businesses such as Boeing, Google (who are committed to expose everyone to this key 21st century skill), Microsoft and many others are adopting computational thinking to improve their decision-making. According to Jeanette Wing:

Computational thinking can be understood as a fundamental analytical skill that everyone can use to solve problems, design systems, and understand human behavior.

Earlier this week Chris Giles, the Economics Editor of the Financial Times, tweeted a chart showing the growth of demand in the job markets for people with computational thinking skills and the decline of jobs in financial services based on data from the Office of National Statistics:

Chris Giles tweet

But as Jeanette Wing states Computational Thinking should be a process everyone learns, not just those involved in computer sciences. As computation and information technology becomes more prevalent, individuals competent in computational thinking are better able to understand the ways which technology can improve the choices and decisions we make.

Computational Thinking is not programming, nor is it about more computer power. You can’t just throw more petaflops at a problem and expect it to be solved.  Likewise, you can’t expect machine learning by itself to learn deeply if it isn’t coupled to human debate, reasoning and knowledge.

According to Google specific Computational Thinking techniques include:

Problem decomposition — The ability to break down a task into minute details so that we can clearly explain a process to another person or to a computer, or even to just write notes for ourselves.

Pattern recognition — The ability to notice similarities or common differences that will help us make predictions or lead us to shortcuts. Pattern recognition is frequently the basis for solving problems and designing algorithms. According to some researchers: the secret of the human brain is pattern recognition.

Pattern generalization to define abstractions or models — The ability to filter out information that is not necessary to solve a certain type of problem and generalize the information that is necessary.

Algorithm design — The ability to develop a step-by-step strategy for solving a problem. An algorithm is a series of step-by-step instructions, designed to complete a certain task in a finite amount of time.

Data analysis and visualization

Dan Kahneman’s work is particularly relevant to Computational Thinking as we deal with more and more data and more computing power. He teaches that we see patterns in random data; that we are even more prone to see patterns in random data when in possession of a theory predicting such patterns; that we overweight outcomes we can imagine easily; that even though we prefer more information to less we are hopeless at processing it; that we are hopeless at gauging correlations until they are very obvious.

Economists such as Ricardo Hausmann, a Professor of Economics at Harvard University says:

One idea about which economists agree almost unanimously is that, beyond mineral wealth, the bulk of the huge income difference between rich and poor countries is attributable to neither capital nor education, but rather to ‘technology.’

But what is often missing from this discussion is a key component of technology – knowhow.

Computational Thinking puts that knowhow into the hands of those that choose to learn this important process. Knowhow is an ability to recognize patterns and respond with effective actions.

For those that want to improve their ability to understand and respond to the changing nature of technology, Computational Thinking can be a powerful way to bridge the gap between the problems of big data, robotics, artificial intelligence and cognitive assistants and improve practical decision making.