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Professor Emeritus Paul Osterman wrote: "People who have [disposable jobs] work at an employer's site, but their employer makes no commitment to them regarding career prospects or job security. My research shows that employers treat more than 1 in 3 U.S. workers as disposable. That comes to just under 57 million full- or part-time workers out of the nation's workforce of 162 million."

Professor Emeritus Paul Osterman wrote: "Employers have strong financial incentives to classify workers as independent contractors rather than employees even where the practical reality of the work relationship closely resembles traditional employment. The disputes that have followed reveal not just a legal ambiguity but a policy system struggling to keep pace with how work has actually changed. A straightforward [solution] would be federal adoption of the ABC rule, already in use by over thirty states to define employee status for state employment rules and for programs related to minimum wages, unemployment insurance, and workers' compensation."

In a recent study, professor Kate Kellogg and co-authors focused on a university medical center, NE Health (fictitious name), and a law firm, LegalCo (also fictitious name). They conducted dozens of individual interviews and observed work meetings. The aim was to see how employees used generative AI and the individual and collective consequences of these uses. The observation was unanimous: the adoption of AI invariably led to an intensification of work. 

Research scientist Ranjan Pal and co-author wrote: "AI will not slow down to accommodate insurance; insurance must accelerate to keep up with AI. The prize is not just a new premium pool. It is the creation of incentives that make the use of AI safer: Discounts for robust governance, higher limits for firms that can prove provenance and performance, and quicker payouts that keep operations afloat while engineers fix the model."

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.

A study by associate professor Taha Choukhmane and co-authors found that AI-generated financial advice moves people closer to sound long-term financial behavior, but the benefits are not distributed equally. "Regular people are not writing their prompts the way a finance professor is," said Choukhmane. AI systems tend to produce stronger financial recommendations when users provide richer context about their circumstances, he explained.