More News from IWER

MIT Sloan placed first in this ranking of international MBA programs.

A handful of so-called hyperscalers are investing huge amounts of money to build AI data centers. While the hyperscalers plan to spend trillions, total AI revenues will be around $150 billion to $200 billion this year, says professor of the practice Gary Gensler. "The challenge is that the spending does not have commensurate revenues yet. That's a fact," he said. "And then the question is, is that an investment that will be paid off in the future?"

A rate increase would throw another sharp shift into a volatile period for the economy and financial markets. With the Iran war flaring up again and causing sharp increases in oil and gas prices, inflation is likely to remain higher than the Fed's 2% target for even longer. "I don't see any end to the war in Iran right now," said professor Kristin Forbes. "Given what everyone has been through in the last few years of high inflation, consumers are more sensitive, companies are more sensitive, and they raise prices faster. The risks are much more on more persistent inflation than on it falling quickly."

Professor John Sterman has called AI both "promising and problematic." He's skeptical that the industry can adequately regulate itself and sees dangers with AI. Sterman does see outcomes where AI can be harnessed to solve societal problems such as climate change, but, he said, that will take smarter government policies and incentives. A simulator he helped develop, En-ROADS, allows users to explore AI's potential impacts on climate change.

The closure of an industrial site, the bankruptcy of a large group, or a massive restructuring plan can simultaneously affect several thousand households, suppliers, subcontractors, and sometimes an entire region. It is precisely this risk that senior lecturer Paul Cheek puts back at the center of the debate. According to him, large, innovative companies are generally perceived as beneficial to the economy because they concentrate a high volume of jobs. However, this concentration can also produce a systemic risk when the economic health of a region depends on a limited number of actors.

People consistently rated human advisers as more competent than AI advisers when evaluating who could best solve their problem across domains that included financial, technological, medical, and career advice, according to a study by professor Eric So and co-authors. But that situation changed once shame entered the picture. That preference reversed when a client's problem would require them to reveal embarrassing information.

As the share of wealth workers take home through wages is shrinking, corporate profits have exploded. This trend has been about 50 years in the making, according to assistant professor Anna Stansbury. Fewer workers in the U.S. are represented by unions, giving them fewer opportunities to bargain for salaries and benefits, she noted. But more so, Stansbury blames the fissuring of the workplace, or the breakdown of the employer-employee relationship. In the past, the typical employer-employee relationship would be that of direct employment. But "in more and more cases, that's not actually people's experience of the workplace, particularly in lower middle-income jobs," Stansbury said.

Principal research scientist Neil Thompson joined Yahoo Finance's "Market Domination" to discuss the real threats AI could pose, following public claims by Jacob Coxon, a former Anthropic researcher, who said AI could lead to the extinction of all humans by 2030.

Associate professor Taha Choukhmane believes that artificial intelligence can be especially useful at the beginning of the documentation process. He recommends using AI to explain concepts like the stock market, mutual funds, or index funds, followed by verifying the information with trusted sources. One problem is that AI responses can vary depending on how questions are phrased. Choukhmane also recommends asking for references to verify the information received.

Assistant professor Chara Podimata and MIT professors Adam Berinsky and Charles Stewart III have designed a public dashboard called the LLM Election Observatory for tracking how A.I. models are responding to questions about prominent midterm candidates and political issues. "A.I. is becoming part of the way people encounter and make sense of political information, and yet we know relatively little about what that information environment actually looks like, and how it differs for different user demographics, political identities and geographies," said Podimata.