State of Large-Scale Technological Underemployment
A State of Large-Scale Technological Underemployment is a state of large-scale underemployment of underemployed workers who are in a state of technological underemployment (that is largely attributed to technological underemployment causes).
- Context:
- It can be associated with low Labor Participation Rate.
- It can be preceded by:
- a shrinking Job Opening Rate.
- a shrinking Median Income and a Middle Class Hollowing-Out.
- a growing Corporate Cash Level.
- an increasing Capital-Labor Substitutability Ratio.
- a shrinking Labor's Share of National Income.
- It can be succeeded by a State of Large-Scale Technological Unemployment.
- It can range from being a State of Large-Scale Technological Underemployment in Rural Communities of Developed Countries (rural communities of developed countries), to being ...
- ...
- Example(s):
- as hypothesized in (Susskind, 2020).
- State of Large-Scale Technological Underemployment in the U.S..
- ...
- …
- Counter-Example(s):
- See: Structural Unemployment, Capital-based Technological Change.
References
2022
- https://www.nytimes.com/2022/10/07/opinion/machines-ai-employment.html
- QUOTE: I’ve been thinking about this a lot recently. In part it’s because I was among the worriers — I started warning about the coming robotic threat to human employment in 2011. As the decade progressed and artificial intelligence systems began to surpass even their inventors’ expectations, evidence for the danger seemed to pile up. In 2013, a study by an Oxford economist and an A.I. scientist estimated that 47 percent of jobs are “at risk” of being replaced by computers. In 2017, the McKinsey Global Institute estimated that automation could displace hundreds of millions of workers by 2030, and global economic leaders were discussing what to do about the “robocalypse.” In the 2020 campaign, A.I.’s threat to employment became a topic of presidential debates.
Even then, predictions of robot dominance were not quite panning out, but the pandemic and its aftermath ought to radically shift our thinking. Now, as central bankers around the world are rushing to cool labor markets and tame inflation — a lot of policymakers are hoping that this week’s employment report shows declining demand for new workers — a few economic and technological truths have become evident.
First, humans have been underestimated. It turns out that we (well, many of us) are really amazing at what we do, and for the foreseeable future we are likely to prove indispensable across a range of industries, especially column-writing. Computers, meanwhile, have been overestimated. Though machines can look indomitable in demonstrations, in the real world A.I. has turned out to be a poorer replacement for humans than its boosters have prophesied.
What’s more, the entire project of pitting A.I. against people is beginning to look pretty silly, because the likeliest outcome is what has pretty much always happened when humans acquire new technologies — the technology augments our capabilities rather than replaces us. ...
- QUOTE: I’ve been thinking about this a lot recently. In part it’s because I was among the worriers — I started warning about the coming robotic threat to human employment in 2011. As the decade progressed and artificial intelligence systems began to surpass even their inventors’ expectations, evidence for the danger seemed to pile up. In 2013, a study by an Oxford economist and an A.I. scientist estimated that 47 percent of jobs are “at risk” of being replaced by computers. In 2017, the McKinsey Global Institute estimated that automation could displace hundreds of millions of workers by 2030, and global economic leaders were discussing what to do about the “robocalypse.” In the 2020 campaign, A.I.’s threat to employment became a topic of presidential debates.
2022
- Michael J. Handel. (2022). "Growth trends for selected occupations considered at risk from automation." In: BLS MLR July 2022
- QUOTE: ... Fears that automation will cause widespread job losses have been raised repeatedly in the past, which, in retrospect, usually greatly overestimated the scale of actual displacement. Recent experience and projections suggest a similar pattern may be occurring with recent developments in AI and robotics. For various reasons, technological change seems to be generally more gradual than commonly recognized. Prior waves of computing may be too familiar to receive much attention from observers of emerging trends, but their immediate effects are probably smaller than anticipated and their full impact unfolds gradually over a longer timeframe than recognized. None of this is to minimize the hardships experienced by displaced workers. However, rapid leaps in technology in the early 2010s prompted many to envision a future scenario of massive disruption. This article has examined specific occupations that are most favorable to the automation thesis and found little support for this view. It is entirely possible that robotics and AI are simply another in a long line of waves of innovation whose effects on employment will unfold at rates comparable to those in the past. ...
2017
- (Grace et al., 2017) ⇒ Katja Grace, John Salvatier, Allan Dafoe, Baobao Zhang, and Owain Evans. (2017). “When Will {AI} Exceed Human Performance? Evidence from {AI} Experts.” In: CoRR, abs/1705.08807.
- QUOTE: ... Researchers predict AI will outperform humans in many activities in the next ten years, such as translating languages (by 2024), writing high-school essays (by 2026), driving a truck (by 2027), working in retail (by 2031), writing a bestselling book (by 2049), and working as a surgeon (by 2053). Researchers believe there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years, with Asian respondents expecting these dates much sooner than North Americans. These results will inform discussion amongst researchers and policymakers about anticipating and managing trends in AI.
