A new study addresses this problem by using generative AI to systematically classify thousands of everyday social interactions. In a new study, researchers analyzed thousands of textual descriptions of two-person social interactions, then used generative artificial intelligence (AI) to code the exchanges by features, resulting in a taxonomy of categories of social interactions. Then they related these groups to variables like conflict, power, and duty to provide a comprehensive, data-driven framework for quantifying the structure of interactions.

In a new study, “Who’s Afraid of the Minimum Wage? Measuring the Impacts on Independent Businesses Using Matched U.S. Tax Returns,” researchers examined how small and medium-sized firms accommodated minimum wage hikes along product and labor market margins. The study found that firms reacted to increases in minimum wage differently depending on their size, but most adapted well, and the effect on workers was also largely positive.

How a single word can make or break marketing messages, according to a new study from the University of Florida Warrington College of Business.

Linda Banda, a Malawi native, worked to help child marriage, a persistent problem in her native Malawi. After helping ensure a new law and constitutional amendment, she began research to evaluate ongoing efforts to stem the problem. She found agencies and others working on the issue often are put at odds with each other due to competition for international funding, and that local knowlege and culture is often overlooked, and she and co-researchers argue an African feminist lens could help more effectively employ local knowledge and culture to end the problem of child marriage.

Artificial intelligence could soon allow powerful companies to charge each customer a different price for the same product, based on what they think each individual is willing to pay.

Rising living costs, energy insecurity, widening inequality, and escalating climate impacts are fueling discussions on fairness and justice in climate policy. Yet, assumptions in global emission scenarios that determine who benefits and who bears the costs are often only made implicitly. A new IIASA-led study addresses this gap by offering a practical way to assess and design emission scenarios that explicitly account for distributive justice.