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Examples of this alternative abound. For instance, research by economists at Stanford University and MIT found that a generative AI conversational assistant substantially increased the productivity of customer support agents (measured in cases resolved per hour) and improved consumer satisfaction. The gains were greatest among the most novice workers.
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On the other end of the wage spectrum, computer programmers have also been found to benefit from AI help. In an experiment by researchers at Microsoft, GitHub and MIT, coders who used the AI tool GitHub Copilot completed programming tasks 56 percent faster.
It’s hard to understate how much human enhancement via AI tools could reshape society. The vast inequalities in income and opportunity that automation has given us so far could be significantly reduced.
Computers didn’t just automate routine, blue-collar work. By vastly expanding access to information, computers plugged into the internet empowered the expert white-collar workers who could profitably use it. Doctors, programmers, lawyers — broadly, workers with college degrees — reaped the rewards, leaving behind a host of less-educated workers whose jobs have progressively been taken over by the machines.
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AI could narrow the opportunity gap by helping lower-ranked workers take on decision-making tasks currently reserved for the dominant credentialed elites.
Consider how old-school IT tools such as electronic medical records have allowed nurse practitioners to make more complex decisions encroaching on doctors’ turf — much to the chagrin of the American Medical Association. Generative AI could take this further, allowing nurses and medical technicians to diagnose, prescribe courses of treatment and channel patients to specialized care.
As Autor put it, “AI, if used well, can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization.”
Can the deployment of artificial intelligence be nudged in this direction? It would require a different approach to technology, both by policymakers and the corporate class. “The human-complementary approach is not likely to prevail based on current investments and corporate attitudes,” Acemoglu, Autor and Johnson say.
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Corporate managers today itch to bring in the robots, even when the machines often don’t do much to improve productivity. Perhaps it’s because they don’t agitate to join unions? In any event, policy could rejigger corporate incentives. Changing the tax code, which vastly favors capital investment over hiring new workers, would level the playing field and temper incentives to automate.
Acemoglu, Autor and Johnson argue for giving unions a voice on how to deploy the new technologies in the workforce. Regulations could stop companies from deploying untested AI in tasks like hiring or surveillance — areas where technology already is degrading and devaluing work. Incentives could be provided to change the research agenda, which today is acutely focused on automation, to explore complementary uses of AI instead.
This requires a conceptual challenge: a paradigm of technological development that has long focused on replacing human capabilities must cede its place to a mind-set concentrated on how to expand human potential.
The stakes are high. As Stanford’s Erik Brynjolfsson wrote, AI could well generate enormous wealth and vastly enhance our understanding of the world. But if technology continues to replace people, the end game includes a working class of no economic or political power, unable to improve its lot, left to live off whatever universal basic income the Silicon Valley plutocrats are willing to provide.
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There is good reason to believe that artificial intelligence is coming for our jobs. That’s, after all, what information technology has been doing for decades. The tech plutocrats apparently agree that human employment will become the stuff of folklore. They probably don’t mind that all wealth in this world will accrue to the lucky few who own the AI patents. They seem willing to share some of it with regular people through some universal basic income scheme.
Artificial general intelligence, the end goal Silicon Valley technologists are striving for, is defined in the charter of OpenAI, the outfit that developed ChatGPT and DALL-E, as “highly autonomous systems that outperform humans at most economically valuable work.” Elon Musk has concluded that “there will come a point where no job is needed.”
But work as we know it doesn’t have to end this way. The sense of inevitability about our technological future stems from a misunderstanding of how technologies emerge and become embedded in the economy. The process is not driven by the laws of nature. It hinges on political decisions that can lead to vastly different outcomes. North Korea devoted its nuclear knowledge to weapons; Japan deployed it to produce electric power.
So far, the march of computers into the workplace has furthered Musk’s vision. Automation powered by information technology has spread to take over every task that could be decomposed into a defined set of precise instructions, displacing swaths of blue-collar workers.
AI could feasibly push automation even further. But it could also reshuffle opportunity in a different direction. As Daron Acemoglu, David Autor and Simon Johnson of MIT have pointed out, it could be deployed not to replace human workers but to augment them, enabling them to perform more complex tasks.
Examples of this alternative abound. For instance, research by economists at Stanford University and MIT found that a generative AI conversational assistant substantially increased the productivity of customer support agents (measured in cases resolved per hour) and improved consumer satisfaction. The gains were greatest among the most novice workers.
On the other end of the wage spectrum, computer programmers have also been found to benefit from AI help. In an experiment by researchers at Microsoft, GitHub and MIT, coders who used the AI tool GitHub Copilot completed programming tasks 56 percent faster.
It’s hard to understate how much human enhancement via AI tools could reshape society. The vast inequalities in income and opportunity that automation has given us so far could be significantly reduced.
Computers didn’t just automate routine, blue-collar work. By vastly expanding access to information, computers plugged into the internet empowered the expert white-collar workers who could profitably use it. Doctors, programmers, lawyers — broadly, workers with college degrees — reaped the rewards, leaving behind a host of less-educated workers whose jobs have progressively been taken over by the machines.
AI could narrow the opportunity gap by helping lower-ranked workers take on decision-making tasks currently reserved for the dominant credentialed elites.
Consider how old-school IT tools such as electronic medical records have allowed nurse practitioners to make more complex decisions encroaching on doctors’ turf — much to the chagrin of the American Medical Association. Generative AI could take this further, allowing nurses and medical technicians to diagnose, prescribe courses of treatment and channel patients to specialized care.
As Autor put it, “AI, if used well, can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization.”
Can the deployment of artificial intelligence be nudged in this direction? It would require a different approach to technology, both by policymakers and the corporate class. “The human-complementary approach is not likely to prevail based on current investments and corporate attitudes,” Acemoglu, Autor and Johnson say.
Corporate managers today itch to bring in the robots, even when the machines often don’t do much to improve productivity. Perhaps it’s because they don’t agitate to join unions? In any event, policy could rejigger corporate incentives. Changing the tax code, which vastly favors capital investment over hiring new workers, would level the playing field and temper incentives to automate.
Acemoglu, Autor and Johnson argue for giving unions a voice on how to deploy the new technologies in the workforce. Regulations could stop companies from deploying untested AI in tasks like hiring or surveillance — areas where technology already is degrading and devaluing work. Incentives could be provided to change the research agenda, which today is acutely focused on automation, to explore complementary uses of AI instead.
This requires a conceptual challenge: a paradigm of technological development that has long focused on replacing human capabilities must cede its place to a mind-set concentrated on how to expand human potential.
The stakes are high. As Stanford’s Erik Brynjolfsson wrote, AI could well generate enormous wealth and vastly enhance our understanding of the world. But if technology continues to replace people, the end game includes a working class of no economic or political power, unable to improve its lot, left to live off whatever universal basic income the Silicon Valley plutocrats are willing to provide.
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