There’s a joke going around:
“Person A to Person B: Artificial Intelligence can’t take your job if your job never required any intelligence to begin with.
Person B: I didn’t get that
Person A: You’re safe”

Irrespective of whether we like the brand of humour or not, it does seem contrary to popular perception that AI will most affect the low skilled amongst us. In this piece for MIT’s Technology Review, David Rotman highlights two pieces of recent research which suggests otherwise – that the generative AI tools such as ChatGPT will likely help bridge the gap between the low skilled and the high skilled than divide. Citing research from OpenAI (somewhat biased) and University of Pennsylvania:
“In contrast to what we saw in earlier waves of automation, higher-income jobs would be most affected, they suggest. Some of the people whose jobs are most vulnerable: writers, web and digital designers, financial quantitative analysts, and—just in case you were thinking of a career change—blockchain engineers.

“There is no question that [generative AI] is going to be used—it’s not just a novelty,” says David Autor, an MIT labor economist and a leading expert on the impact of technology on jobs. “Law firms are already using it, and that’s just one example. It opens up a range of tasks that can be automated.”
…Previously, AI had automated some office work, but it was those rote step-by-step tasks that could be coded for a machine. Now it can perform tasks that we have viewed  as creative, such as writing and producing graphics. “It’s pretty apparent to anyone who’s paying attention that generative AI opens the door to computerization of a lot of kinds of tasks that we think of as not easily automated,” he says.

…Autor also sees a more positive possible outcome: generative AI could help a wide swath of people gain the skills to compete with those who have more education and expertise.”

This is supported by another study:
“Two MIT economics graduate students, Shakked Noy and Whitney Zhang, ran an experiment involving hundreds of college-educated professionals working in areas like marketing and HR; they asked half to use ChatGPT in their daily tasks and the others not to. ChatGPT raised overall productivity (not too surprisingly), but here’s the really interesting result: the AI tool helped the least skilled and accomplished workers the most, decreasing the performance gap between employees. In other words, the poor writers got much better; the good writers simply got a little faster.”

This sounds encouraging from the point of reducing some of the inequities built over the past few decades. Yet, it depends on how we as a society choose to use the technology.

The author cites a new book Power and Progress: Our 1000-Year Struggle Over Technology & Prosperity, by MIT economists Daron Acemoglu and Simon Johnson, where the authors ‘provide a compelling walk through the history of technological progress and its mixed record in creating widespread prosperity. Their point is that it’s critical to deliberately steer technological advances in ways that provide broad benefits and don’t just make the elite richer.’

“From the decades after World War II until the early 1970s, the US economy was marked by rapid technological changes; wages for most workers rose while income inequality dropped sharply. The reason, Acemoglu and Johnson say, is that technological advances were used to create new tasks and jobs, while social and political pressures helped ensure that workers shared the benefits more equally with their employers than they do now.

In contrast, they write, the more recent rapid adoption of manufacturing robots in “the industrial heartland of the American economy in the Midwest” over the last few decades simply destroyed jobs and led to a “prolonged regional decline.” 

The book, which comes out in May, is particularly relevant for understanding what today’s rapid progress in AI could bring and how decisions about the best way to use the breakthroughs will affect us all going forward. In a recent interview, Acemoglu said they were writing the book when GPT-3 was first released. And, he adds half-jokingly, “we foresaw ChatGPT.”

Acemoglu maintains that the creators of AI “are going in the wrong direction.” The entire architecture behind the AI “is in the automation mode,” he says. “But there is nothing inherent about generative AI or AI in general that should push us in this direction. It’s the business models and the vision of the people in OpenAI and Microsoft and the venture capital community.”

Capitalism has rendered innovation profit driven and put the power of technology in the hands of businesses unlike the post WW-II breakthroughs, many of which were public funded including the internet which has democratised its benefits.

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