A landmark study of 1.4 million real workplace interactions with artificial intelligence reveals teachable differences between routine and sophisticated AI use that offer organizations a concrete road map for identifying and scaling high-impact AI capability.

The joint study by KPMG LLP, the U.S. audit, tax, and advisory firm, and the McCombs School of Business at The University of Texas at Austin identifies distinct, observable patterns in how high‑impact users frame problems, guide AI reasoning, and apply AI across complex tasks that KPMG is applying internally and in its work for clients. The study is published today in Harvard Business Review.

A new study in Science Advances found that more than 155,000 US deaths between March 2020 and December 2021 were not officially recorded as COVID-19 deaths, which equates to 19 percent more deaths due to COVID-19 than federal records indicate. These unrecognized COVID-19 deaths disproportionately burdened certain populations more than others, including racial and ethnic minorities, as well as people who were low-income, had preexisting health conditions, lived in the South, or did not have a high school education. 

A new technique for assessing the reliability of a large language model’s predictions is better at identifying when the model is confident, but wrong. This more accurate method for uncertainty quantification could help users know whether to trust the model’s outputs.

Wave-Former is a new system that can complete the shape of a hidden 3D object or reconstruct the scene of an entire interior room using reflected wireless signals.