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Race Against The Machine

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“Race Against The Machine: How The Digital Revolution is Accelerating Innovation, Driving Productivity and Irreversible Transforming Employment and The Economy”
by Erik Brynjolfsson and Andrew McAfee

The authors based this article on their book entitled The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. When I checked on 3/8/17, it had 4.5 Amazon stars based on 510 customer reviews.The article points out that while other measures of economic health have rebounded quite well since the official end of the Great Recession in June, 2009, employment has lagged. The authors make a strong case for the slow growth in employment being due to technological advances outpacing labor’s ability to adjust to such advances.

They point to two related concepts. First is Moore’s Law, named after Gordon Moore, co-founder of Intel who said back in 1965 that computing power will double every 12 months. (History has shown that the doubling occurs closer to every 18 months.)

The second concept is the power of exponential series, as demonstrated by an ancient story which I will let the authors tell in their own words:

“….the inventor of the game of chess shows his creation to his country’s ruler. The emperor is so delighted by the game that he allows the inventor to name his own reward. The clever man asks for a quantity of rice to be determined as follows: one grain of rice is placed on the first square of the chessboard, two grains on the second, four on the third, and so on, with each square receiving twice as many grains as the previous. The emperor agrees, thinking that this reward was too small. He eventually sees, however, that the constant doubling results in tremendously large numbers.”

The inventor winds up with 9,223,372,036,854,775,808 grains of rice (i.e. 263), on the 64th square alone. If you sum the number of grains of rice on all 64 squares, you get a very large number of grains of rice. (precisely 18,446,744,073,709,551,615 grains of rice). If placed end to end and assuming each grain of rice is .2 inches long, all the rice would stretch approximately 60,000,000,000,000 miles which is twice as far as the nearest star (Alpha Centauri which is 25,000,000,000,000 miles from Earth).  This is a great illustration of how an exponential series accelerates with each term. That is what is happening with technology. We are in the equivalent of the second half of the chess board.

Experts have shown that computers should reach the physical limits of Moore’s Law sometime in the 2020s. If the limit is reached in 2028, that is the equivalent of the 64th square on the chess board. But whenever the limit is reached is beside the point. Technology has dramatically changed our lives up to now and will continue to do so in an even more dramatic fashion over the next few decades.

The authors conclude that in order to keep up with the rapid change in technology, improvements need to be made in two areas: (a) improving the rate and quality of organizational innovations and (b) increasing human capital.

Another way of expressing this goal would be that we need to focus on (a) entrepreneurship and (b) education. I completely agree on the entrepreneurship part but think that the education part needs some clarification. There are several existing jobs that will be performed by the computers and robots in the future. Other existing jobs will become more important. Plus new jobs will be created. We need to educate young people so as to prepare them for the future jobs which will exclude many of the existing jobs.

Math, entrepreneurship, communication, leadership and marketing are the core areas that will only become more important for humans in the future, in my opinion.

Basic Study

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The Future of Employment: How Susceptible Are Jobs to Computerisation – by Carl Benedikt Frey and Michael A. Osborne

http://www.oxfordmartin.ox.ac.uk/downloads/academic/future-of-employment.pdf

Over the next 6-12 months, I expect to review all of the academic articles referenced in the basic study and summarize, in easy to read terms, what I think are the most pertinent and interesting parts.

Interesting on topic interviews

In my research I am finding so much content about robots and the future of our workforce. My previous post contains interesting robot videos. In this post I will add interviews that involve discussions about the impact technology will have on our future workforce.  They will be added chronologically with the most recent interview on top.

April 2017

4/21/2017 – Workforce disruption and threatened jobs were the topic of discussion in Tucker Carlson’s interview with Mark Cuban:

http://video.foxnews.com/v/5407045297001/

4/20/17 – In this interview published in Emarketer.com,  Guido Campello, the CEO and Creative Director at Cosabella, a fashion company, talks about how artificial intelligence being used to help with creative decisions such as predicting fashion trends.

https://retail.emarketer.com/article/how-ai-changing-chief-marketers-role-cosabella/58fa69b2ebd4000a54864b29

4/2/2017 – In this interview with Sheena Alexandra, I discuss what motivated me to create this blog and how the next generation can take steps now to future proof themselves from the vastly changing workforce.

Interesting Robot Videos

In my research I continue to come across interesting robot videos and so this post will contain the growing number of those interesting robot videos I’d like to share.

Robots may eliminate the need for humans labor in the wine country. This autonomous grapevine pruner can do what is currently being done by humans

More robots designed to work in the fields. This video shows Harvest Automation’s 4-robot team moving plants around. 

In this video from WIRED, you’ll see that Tesla relies heavily on robots to build their Model S car.  

This robot is sophisticated enough to steer and balance itself while riding a bicycle.

Lousy and Lovely Jobs: The Rising Polarization of Work in Britain

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Lousy and Lovely Jobs: The Rising Polarization of Work in Britain
By Maarten Goos and Alan Manning

This is one of several articles referenced by the Oxford University study that analyzes the effect of technology on employment. While the article has several graphs, charts and tables, it is the bar graph showing how the distribution of jobs has changed in Britain over the period from 1979 to 1999 that most impressed me and is reproduced on an approximate basis above this summary. The starting point for the construction of this graph was to categorize all jobs in the study into their decile based on the mean wage in 1979. Thus, the base number of jobs for each decile would be 10% of the total number of jobs in the study. With time, the number of workers in each job changes. A second tally was based on the number of workers in 1999 in each of the occupations. Such second tally was compared with the base tally. The bar graph is the result of this comparison and shows the following:

  • a substantial increase in the number of jobs at the highest end of the wage spectrum
  • a more moderate increase in the number of jobs at the lowest end of the wage spectrum
  • a decrease in the number of jobs in the middle of the wage spectrum

A common theory of economists is that technology affects labor markets in a way that is skill biased. One way to apply the “skill biased” theory would be to contend that skilled workers are better able to use technology to increase their productivity which would lead to higher wages. This would explain the percentage increase in the nine and ten deciles in the above graph.

However, this theory would not explain the percentage increase in the number of workers at the lowest end of the wage spectrum.

For this explanation the authors introduced the routine / non-routine characteristics of jobs and theorized that it is the computerization of routine jobs in the middle of the wage spectrum (“middling” jobs) that led to the increase in the number of workers in the service jobs that typically are both non routine and lower paying jobs. The assumption is that routine jobs are more susceptible to being computerized than are non-routine jobs.

What I find most interesting is that this article appeared in the February, 2007 issue of The Review of Economics and Statistics. It was only three years later, in October, 2010, that Google announced that it had fully automated several Toyota Priuses. Such announcement demonstrated that while routine jobs may be the first to be lost to computerization, non-routine jobs may not be far behind.