Jeffrey D Sachs is Professor of Economics at Columbia University, a leader in sustainable development, senior UN advisor, bestselling author and syndicated columnist. (Source: Devex Journal,

On October 2nd, 2017, I listened to Jeffrey Sachs lecture:  Man and Machine: the macroeconomics of the digital revolution. Roughly  450 students and several faculty members of the community gathered into the LSE Old Building, expected with excitement or doubts a forecast of the next 50 years. Before relating his words, it is important to mention that Jeffrey Sachs is a famous American economist who works with the United Nations (UN) as an advisor and teaches at Columbia University. “Wow” was also what I thought when I read his professional titles for the first time.


The Core of the Lecture

Jeffrey Sachs started with a tribute to the academic work, or science fiction novel,  of author John Maynard Keynes, who, some 90 years ago, predicted that machines will replace labour. The visionary book is called “Economic Possibilities for our Grandchildren” and  it is directly addressed to us.

Then, the core of his lecture was a long stretch of graphs and statistics, from the industrial revolution to the digital revolution. He demonstrated that each revolution raised national output, disrupted production processes, restructured the labour market, and most importantly shifted the distribution of income and wealth.


What does Jeffrey Sachs mean by distribution of wealth?

For Sachs, distribution of wealth  is not about the rich getting richer and the poor getting poorer. Distribution of wealth is bigger than that. As Keynes, before Sachs argues, it is multi generational, and its implications are considerable. Wealth is owned by the older generation through the stock market. In the USA, young people start working and paying off debts for a significant  majority of their life.


In order to get rich, young people need to work while they still can.

In the near future, Sachs predicts that machines, which don’t need benefits such as work-life balance and a competitive wage, will replace labour. Why would a recruiter train a human-worker when they can program a machine? Also why not replace the recruiter and have a machine do all the recruiting instead?

By Sachs’ calculations, the decrease in human labour required by companies will drive down wages and will allow companies to retain about 70% of national income.  In other words, profits will continue to rise for companies, since they won’t have to pay as much vacation time or salaries.

Watch his lecture:


Sachs reaches his discourse apotheosis

“In 50 years, the young worker, full of hope for a better future, will be crushed with debts and not able to find a decent job.” As much as I expected the curtains to close and the crowd to cheer for his theatrical performance, I was quickly reminded that this was LSE, not Broadway.


Let’s look at the facts again

His main argument is based on data all the way from 1900 to , his favourite book, which inspired that beautiful theatrical plead, is the one previously mentioned, written in 1930. From this outdated material, he is making predictions on the year 2020.  Does that sound alright to you? Shouldn’t we be making extrapolations about the world in the future based on current data? Because based on current data, the job market is still expanding and now we are seeing that technology is not necessarily correlated with higher productivity – consider the amount of time people spend at work surfing the internet where previously they would have had a typewriter with no Google or Facebook.


Still, there are some positive takeaways from the lecture:

Being more knowledgeable gives a competitive edge, so we have to keep learning, for free or through the education system. Sachs predicts (or wishes) that older generations (the capital holders) and the big data companies (Apple, Amazon, etc.) will distribute capital to the next generation through free education and tax credit. Otherwise,  for those who want to start learning now,  Coursera or EdX are free education platform, accessible to anyone.

In conclusion, just like predicting the weather forecast for a London summer day, or estimating a stock price six months in advance, forecasts are ultimately a random walk in the park. Whether Jeffrey Sachs’s predictions ultimately turn out to be true or not, we must remind ourselves today that we have a chance, by gaining skills and knowledge, to  positively influence the future for our current generation and those to come.

Charlotte J. Caron is a first year MPA student, originally from France. She holds a Business Administration degree from the BC Institute of Technology , Canada and a Psychology degree from Université de Champagne Ardenne, France . Before starting her graduate studies at LSE, Charlotte worked as a Labour Market Advisor for Educacentre, a Non-Profit Organization in Canada.

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