AI

Who will benefit from AI? | MIT News

5 Mins read


What if we’ve been thinking about artificial intelligence the wrong way?

After all, AI is often discussed as something that could replicate human intelligence and replace human work. But there is an alternate future: one in which AI provides “machine usefulness” for human workers, augmenting but not usurping jobs, while helping to create productivity gains and spread prosperity.

That would be a fairly rosy scenario. However, as MIT economist Daron Acemoglu emphasized in a public campus lecture on Tuesday night, society has started to move in a different direction — one in which AI replaces jobs and rachets up societal surveillance, and in the process reinforces economic inequality while concentrating political power further in the hands of the ultra-wealthy.

“There are transformative and very consequential choices ahead of us,” warned Acemoglu, Institute Professor at MIT, who has spent years studying the impact of automation on jobs and society.

Major innovations, Acemoglu suggested, are almost always bound up with matters of societal power and control, especially those involving automation. Technology generally helps society increase productivity; the question is how narrowly or widely those economic benefits are shared. When it comes to AI, he observed, these questions matter acutely “because there are so many different directions in which these technologies can be developed. It is quite possible they could bring broad-based benefits — or they might actually enrich and empower a very narrow elite.”

But when innovations augment rather than replace workers’ tasks, he noted, it creates conditions in which prosperity can spread to the work force itself.

“The objective is not to make machines intelligent in and of themselves, but more and more useful to humans,” said Acemoglu, speaking to a near-capacity audience of almost 300 people in Wong Auditorium.

The Productivity Bandwagon

The Starr Forum is a public event series held by MIT’s Center for International Studies (CIS), and focused on leading issues of global interest. Tuesday’s event was hosted by Evan Lieberman, director of CIS and the Total Professor of Political Science and Contemporary Africa.

Acemoglu’s talk drew on themes detailed in his book “Power and Progress: Our 1000-Year Struggle Over Technology and Prosperity,” which was co-written with Simon Johnson and published in May by PublicAffairs. Johnson is the Ronald A. Kurtz Professor of Entrepreneurship at the MIT Sloan School of Management.

In Tuesday’s talk, as in his book, Acemoglu discussed some famous historial examples to make the point that the widespread benefits of new technology cannot be assumed, but are conditional on how technology is implemented.

It took at least 100 years after the 18th-century onset of the Industrial Revolution, Acemoglu noted, for the productivity gains of industrialization to be widely shared. At first, real earnings did not rise, working hours increased by 20 percent, and labor conditions worsened as factory textile workers lost much of the autonomy they had held as independent weavers.

Similarly, Acemoglu observed, Eli Whitney’s invention of the cotton gin made the conditions of slavery in the U.S. even worse. That overall dynamic, in which innovation can potentially enrich a few at the expense of the many, Acemoglu said, has not vanished.

“We’re not saying that this time is different,” Acemoglu said. “This time is very similar to what went on in the past. There has always been this tension about who controls technology and whether the gains from technology are going to be widely shared.”

To be sure, he noted, there are many, many ways society has ultimately benefitted from technologies. But it’s not something we can take for granted.

“Yes indeed, we are immeasurably more prosperous, healthier, and more comfortable today than people were 300 years ago,” Acemoglu said. “But again, there was nothing automatic about it, and the path to that improvement was circuitous.”

Ultimately what society must aim for, Acemoglu said, is what he and Johnson term “The Productivity Bandwagon” in their book. That is the condition in which technological innovation is adapted to help workers, not replace them, spreading economic growth more widely. In this way, productivity growth is accompanied by shared prosperity.

“The Productivity Bandwagon is not a force of nature that applies under all circumstances automatically, and with great force, but it is something that’s conditional on the nature of technology and how production is organized and the gains are shared,” Acemoglu said.

Crucially, he added, this “double process” of innovation involves one more thing: a significant amount of worker power, something which has eroded in recent decades in many places, including the U.S.

That erosion of worker power, he acknowledged, has made it less likely that multifaceted technologies will be used in ways that help the labor force. Still, Acemoglu noted, there is a healthy tradition within the ranks of technologists, including innovators such as Norbert Wiener and Douglas Engelbart, to “make machines more useable, or more useful to humans, and AI could pursue that path.”

Conversely, Acemoglu noted, “There is every danger that overemphasizing automation is not going to get you many productivity gains either,” since some technologies may be merely cheaper than human workers, not more productive.

Icarus and us

The event included a commentary from Fotini Christia, the Ford International Professor of the Social Sciences and director of the MIT Sociotechnical Systems Research Center. Christia offered that “Power and Progress” was “a tremendous book about the forces of technology and how to channel them for the greater good.” She also noted “how prevalent these themes have been even going back to ancient times,” referring to Greek myths involving Daedalus, Icarus, and Prometheus.

Additionally, Christia raised a series of pressing questions about the themes of Acemoglu’s talk, including whether the advent of AI represented a more concerning set of problems than previous episodes of technological advancement, many of which ultimately helped many people; which people in society have the most ability and responsibility to help produce changes; and whether AI might have a different impact on developing countries in the Global South.

In an extensive audience question-and-answer session, Acemoglu fielded over a dozen questions, many of them about the distribution of earnings, global inequality, and how workers might organize themselves to have a say in the implementation of AI.

Broadly, Acemoglu suggested it is still to be determined how greater worker power can be obtained, and noted that workers themselves should help suggest productive uses for AI. At multiple points, he noted that workers cannot just protest circumstances, but must also pursue policy changes as well — if possible.

“There is some degree of optimism in saying we can actually redirect technology and that it’s a social choice,” Acemoglu acknowledged.

Acemoglu also suggested that countries in the global South were also vulnerable to the potential effects of AI, in a few ways. For one thing, he noted, as the work of MIT economist Martin Beraja shows, China has been exporting AI surveillance technologies to governments in many developing countries. For another, he noted, countries that have made overall economic progress by employing more of their citizens in low-wage industries might find labor force participation being undercut by AI developments.

Separately, Acemoglu warned, if private companies or central governments anywhere in the world amass more and more information about people, it is likely to have negative consequences for most of the population.

“As long as that information can be used without any constraints, it’s going to be antidemocratic and it’s going to be inequality-inducing,” he said. “There is every danger that AI, if it goes down the automation path, could be a highly unequalizing technology around the world.”


Source link

Related posts
AI

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 2: ModelBuilder

7 Mins read
In Part 1 of this series, we introduced the newly launched ModelTrainer class on the Amazon SageMaker Python SDK and its benefits,…
AI

Meet Ivy-VL: A Lightweight Multimodal Model with Only 3 Billion Parameters for Edge Devices

2 Mins read
The ongoing advancement in artificial intelligence highlights a persistent challenge: balancing model size, efficiency, and performance. Larger models often deliver superior capabilities…
AI

Answer questions from tables embedded in documents with Amazon Q Business

4 Mins read
Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on…

 

 

Leave a Reply

Your email address will not be published. Required fields are marked *