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Extraction Summary

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Document Information

Type: Book page or academic excerpt
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Summary

The text discusses the failure of Keynes's prediction regarding shorter working hours, citing David Graeber's concept of "bullshit jobs" arising despite automation. It explores the societal challenges of technological unemployment, comparing current times to the Industrial Revolution, and considers solutions like universal basic income or wealth redistribution to creative fields. The author then transitions to discussing the potential loss of scientific understanding due to the increasing reliance on AI and massive data analysis.

People (2)

Name Role Context
Keynes
David Graeber

Timeline (1 events)

Industrial Revolution

Relationships (2)

describes concept
triggered

Key Quotes (4)

"the growth of “bullshit jobs.”"
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"In today’s democratic societies, it is not clear that the population will tolerate such a dramatic upheaval of society based on the promise that “eventually” things will get better."
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"This is essentially about power, agency, and control."
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"We know what the programs are"
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Full Extracted Text

Complete text extracted from the document (3,380 characters)

Sadly, Keynes’s predictions did not come true. Although productivity did indeed increase, the system—possibly inherent in a market economy—did not result in humans working much shorter hours. Rather, what happened is what the anthropologist and anarchist David Graeber describes as the growth of “bullshit jobs.”34 While jobs that produce essentials like food, shelter, and goods have been largely automated away, we have seen an enormous expansion of sectors like corporate law, academic and health administration (as opposed to actual teaching, research, and the practice of medicine), “human resources,” and public relations, not to mention new industries like financial services and telemarketing and ancillary industries in the so-called gig economy which serve those who are too busy doing all that additional work.
How will societies cope with technology’s increasingly rapid destruction of entire professions and throwing large numbers of people out of work? Some argue that this concern is based on a false premise, because new jobs spring up that didn’t exist before, but as Graeber points out, these new jobs won’t necessarily be rewarding or fulfilling. During the first industrial revolution, it took almost a century before most people were better off. That revolution was possible only because the government of the time ruthlessly favored property rights over labor, and most people (and all women) did not have the vote. In today’s democratic societies, it is not clear that the population will tolerate such a dramatic upheaval of society based on the promise that “eventually” things will get better.
Even that rosy vision will depend on a radical shake-up of education and lifelong learning. The Industrial Revolution did trigger enormous social change of this kind, including a shift to universal education. But it will not happen unless we make it happen: This is essentially about power, agency, and control. What’s next for, say, the forty-year-old taxi driver or truck driver in an era of autonomous vehicles?
One idea that has been touted is that of a universal basic income, which will allow citizens to pursue their interests, retrain for new occupations, and generally be free to live a decent life. However, market economies, which are predicated on growing consumer demand over all else, may not tolerate this innovation. There is also a feeling among many that meaningful work is essential to human dignity and fulfillment. So another possibility is that the enormous wealth generated by increased productivity due to automation could be redistributed to jobs requiring human labor and creativity in fields such as the arts, music, social work, and other worthwhile pursuits. Ultimately, which jobs are rewarding or productive and which are “bullshit” is a matter of judgment and may vary from society to society, as well as over time.
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So far, I’ve focused on AI’s practical consequences. As a scientist, what bothers me is our potential loss of understanding. We are now accumulating data at an incredible rate. In my own lab, an experiment generates over a terabyte of data a day. These data are massaged, analyzed, and reduced until there is an interpretable result. But in all of this data analysis, we believe we know what’s happening. We know what the programs are
34 https://strikemag.org/bullshit-jobs/
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