In this interview, senior lecturer Paul Cheek discussed the index he created to assess AI adoption across S&P 500 companies, the most important thing executives need to do for AI transformation, and why he says he is "bullish" about software engineers' skills.

Through the 2010s the rate of new business formations was falling, triggering worries that the country's dynamism was fading. In 2020, professor Scott Stern and a co-researcher looked for a better measure. They took 28 million business registrations across 32 states covering 81% of US gross domestic product and asked how many of those firms ever amounted to anything. Only 0.07% reached an initial public offering or a meaningful acquisition within six years. More than a third of those came from the top 1% of firms they rated highest quality based on their characteristics the day they registered.

"A proposed pledge for Elon Musk," wrote Institute Professor Daron Acemoglu in an X post on Monday. "If money won't matter in 2036, why don't you pledge to donate your current wealth of approximately $1 trillion to charity no later than 2036. This would establish with great credibility your belief in the powers of AI and technology."

Visiting scholar Eric Rosengren joined "Market Domination" to preview the Fed's interest rate decision and discuss the central bank's policy outlook, inflation trends, and the path ahead for rates.

An MIT Sloan article describes recent research by professor Sinan Aral, professor Jared Curhan, and co-authors that ran over 180,000 unique negotiations between AI agents from more than 40 countries to determine what makes an AI negotiator succeed. The article says the competition's central finding challenged a widespread assumption: that politeness and empathy are wasted on AI. Agents designed to be warm and kind consistently outperformed cold and ruthless ones.

Professor Tavneet Suri joined the "Planet Money Summer School World Tour" podcast to discuss economic development in Kenya. "I do think that core to the growth of an economy is this thing we call human capital, which is about the education and the health of your population. It's the sort of, in quotes, 'capital' that a human brings to the table," said Suri.

The voluntary carbon market (VCM) prices credits based more on who is buying them than on how much good they do for the climate, according to research by professor Roberto Rigobon, principal research scientist Florian Berg, and co-authors — a finding that raises fundamental questions about whether the market is channeling money toward the most effective climate solutions. The study analyzed more than 7,200 real transactions made between 2018 and 2024, covering roughly 11% of the global secondary VCM by dollar value.

Professor Jackson Lu and co-authors wrote: "By making negotiation rules visible, reducing reliance on self-advocacy, holding evaluators accountable, and pairing empowerment with protection, [senior leaders] can make negotiation a genuine vehicle for mobility rather than a gatekeeper of privilege."

Distinguished senior lecturer Robert Pozen wrote: "The National Association of Insurance Commissioners has adopted a process to allow state regulators to challenge individual ratings. It's also developing a due-diligence framework to assess whether private ratings are mapped appropriately to regulatory risk categories. A simpler and more effective solution would be for state insurance regulators to mandate public disclosure of all ratings of private credit, along with explanations on how they were determined."

Tom Achoki (Sloan Fellows: MBA '18) wrote: "Graduation to middle-income status is supposed to signal success. When it comes to public health, it must not mark the moment when progress slows, systems strain, and hard-won gains begin to erode."

A recent MIT FutureTech report on AI risk drew responses from 272 specialists, including professor Jackson Lu, research scientist Peter Slattery, and principal research scientist Neil Thompson. "These findings are a call to arms for those building and governing AI to make sure the worst outcomes do not occur," said Thompson.

"The sheer number of platforms turns attention into a central economic resource," said professor Sinan Aral. "This mechanism creates structural pressure toward content capable of generating an immediate reaction. In this scenario, complex materials are more difficult to circulate because they demand time, patience, and sustained concentration. What is relevant for public understanding often loses ground to emotionally effective stimuli."

Research scientist Christian Catalini said: "We should probably not worry about the sci-fi model turning evil and trying to take over our systems, but about the consequences of not foreseeing how high-performance AI systems will interpret human instructions."

Senior lecturer Renée Richardson Gosline says some of the most useful AI systems are those that use friction deliberately, prompting people to test assumptions rather than accept an AI-generated answer outright. The goal, Gosline said, is to stop workers defaulting to the easiest available answer, particularly where speed could come at the cost of accuracy or judgement. She argued organizations need to avoid both extremes in how staff relate to AI tools.

"Do we need more people? Do we need fewer people? We have no idea. Nobody has a clue," wrote Professor Emeritus Paul Osterman in the forthcoming book "Disposable Workers." He added that companies treated workers as expendable and got rid of them when it was convenient. Osterman expects this trend of precarious work to continue during this period of change. "Artificial intelligence introduces a lot of uncertainty among employers who do not know what they need and what they do not need," he said.

In this interview, professor Simon Johnson discussed the rise of artificial intelligence, the future of US-China competition, and how the technology poses unique challenges to both economies.

Principal research scientist Andrew McAfee said people typically learn difficult knowledge work by first assisting experienced colleagues with routine responsibilities. If companies automate these tasks too quickly, they risk eliminating the apprenticeship ladder that has traditionally produced skilled professionals and future business leaders.