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Early studies of the effects of AI have found it can often lead to a 20 to 80 percent improvement in productivity across a wide variety of job types, from coding to marketing. By contrast, when steam power, that most fundamental of General Purpose Technologies, the one that created the Industrial Revolution, was put into a factory, it improved productivity by 18 to 22 percent. And despite decades of looking, economists have had difficulty showing a real long-term productivity impact of computers and the internet over the past twenty years.
Productivity effect of AI
AI is surprisingly good at this, as you can see when I prompted it by saying, I was thinking of writing a book about generative AI, but I am very busy and don’t think I want to make such a large commitment. Can you reframe my failure to write a book as a loss rather than a default option? Make the framing vivid. In a world brimming with knowledge, you stood at the precipice of innovation, holding the torch of understanding about generative AI. Yet, when the world looked to you for illumination, the torch remained unlit. Not because the world wasn’t ready, but because you let the whispers of
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AI moto
whatever AI you are using right now is going to be the worst AI you will ever use.
The worst AI you will use
We are playing Pac-Man in a world that will soon have PlayStation 6s. And that is assuming that AI improves according to the normal pace of technology development. If the possibility of developing AGI turns out to be real and achievable, the world will be even more transformed in the coming years.
Pacman vs playstation
Large Language Models are excellent at writing, but the underlying Transformer technology also serves as the key for a whole set of new applications, including AI that makes art, music, and video. As a result, researchers have argued that it is the jobs with the most creative tasks, rather than the most repetitive, that tend to be most impacted by the new wave of AI.
Creatives at risk
Until July 28, 2022. That is when I first got access to the AI art program Midjourney. I was almost instantly hooked by its power and spent that day creating artistic bar charts (look, I am an academic, charts are in our blood). I started posting them on Twitter. By the next day, over 20,000 people had liked the tweet thread. Academics told me that they printed out copies and hung them on their walls. I had made something other people enjoyed.
Artistic bar chrts
Work that was boring to do but meaningful when completed by humans (like performance reviews) becomes easy to outsource—and the apparent quality actually increases.
Performance reviews
We start to create documents mostly with AI that get sent to AI-powered inboxes, where the recipients respond primarily with AI. Even worse, we still create the reports by hand but realize that no human is actually reading them.
AI for AI
This kind of meaningless task, what organizational theorists have called mere ceremony, has always been with us. But AI will make a lot of previously useful tasks meaningless. It will also remove the facade that previously disguised meaningless tasks. We may not have always known if our work mattered in the bigger picture, but in most organizations, the people in your part of the organizational structure felt it did. With AI-generated work sent to other AIs to assess, that sense of meaning disappears.
Meaningless work
Research by economists Ed Felten, Manav Raj, and Rob Seamans concluded that AI overlaps most with the most highly compensated, highly creative, and highly educated work.
Type of work AI displces
Today, billions of people have access to Large Language Models and the productivity benefits they bring. And from decades of research in innovation studying everyone from plumbers to librarians to surgeons, we know that, when given access to general purpose tools, people figure out ways to use them to make their jobs easier and better. The results are often breakthrough inventions, ways of using AI that could transform a business entirely. People are streamlining tasks, taking new approaches to coding, and automating time-consuming and tedious parts of their jobs. But the inventors aren’t
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Closet AI
All this shadow use leads to the final concern, the justified worry that workers might be training their own replacements by figuring out how to work with AI. If someone has figured out how to automate 90 percent of a particular job, and they tell their boss, will the company fire 90 percent of their coworkers? Better not to speak up.
Shadow user get fired
We could imagine how LLMs might supercharge this process, creating an even more comprehensive panopticon: in this system, every aspect of work is monitored and controlled by AI. AI tracks the activities, behaviors, outputs, and outcomes of workers and managers. AI sets goals and targets for them, assigns tasks and roles to them, evaluates their performance, and rewards them accordingly. But, unlike the cold, impersonal algorithm of Lyft or Uber, LLMs might also provide feedback and coaching to help workers improve their skills and productivity. AI’s ability to act as a friendly adviser could
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AI overlord
Accountants once were in charge of calculating numbers by hand; now they use a spreadsheet—they are still accountants, but their bundles of tasks have changed.
Accountants still
So it may not be a big surprise that over two-thirds of a panel of economists expect, on average, for AI to have very little effect on overall jobs in the next few years, even as AI boosts the economy overall.
Economists exp
By the 1920s, 15 percent of all American women had worked as operators, and AT&T was the largest employer in the United States. AT&T decided to remove the old-school telephone operators and replace them with much cheaper direct dialing. Operator jobs dropped rapidly by 50 to 80 percent. As might be expected, the job market overall adjusted quickly, as young women found other roles, like secretarial positions, that offered similar or better pay. But the women with the most experience as operators took a larger hit to their long-term earnings, as their tenure in a now extinct job did not
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Operators
Knowledge work is famous for very large differences in abilities among workers. For example, repeated studies found that differences between the programmers in the top 75th percentile and those in the bottom 25th percentile can be as much as 27 times along some dimensions of programming quality.
Diffs in ability
This suggests the potential for a more radical reconfiguration of work, where AI acts as a great leveler, turning everyone into an excellent worker. The effects of this could be as profound as the automation of manual labor. It didn’t matter how good you were at digging, because you still couldn’t dig as well as a steam shovel. In this case, the nature of jobs will change a lot, as education and skill become less valuable.
Education less value
With lower-cost workers doing the same work in less time, mass unemployment, or at least underemployment, becomes more likely, and we may see the need for policy solutions, like a four-day workweek or universal basic income, that reduce the floor for human welfare.
UBI
Amara’s Law, named after futurist Roy Amara, says: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” The
Amara's law
Benjamin Bloom, an educational psychologist, published a paper in 1984 called “The 2 Sigma Problem.” In this paper, Bloom reported that the average student tutored one-to-one performed two standard deviations better than students educated in a conventional classroom environment.
Personal tutoring
For example, we know that in-class lectures are not the most effective way to teach and that topics need to be interwoven together in order for students to retain what they know.
Interweaving
Even before generative AI, 20,000 people in Kenya earned a living writing essays full time.
Kenyan essayists
This difference in approach and outcome illustrates the gap between mere repetition and deliberate practice. The latter, with its elements of challenge, feedback, and incremental progression, is the true path to mastery.
Reps.vs deliberate practice
If you were in the bottom half of the skill distribution for writing, idea generation, analyses, or any of a number of other professional tasks, you will likely find that, with the help of AI, you have become quite good.
From bad to great
Humans, walking and talking bags of water and trace chemicals that we are, have managed to convince well-organized sand to pretend to think like us.
Bags of water vs well ordered sand
