#research-transparency

#research-transparency

As Big Tech faces criticism for the environmental impact of artificial intelligence, companies have said the technology will actually help solve climate change. But those claims often lack scientific evidence, a new report finds. And when touting the climate benefits of AI, tech companies conflate "traditional AI" with the more environmentally harmful generative AI, a form of "bait-and-switch" that amounts to greenwashing.

Many researchers are surprised and relieved over an unusual step taken by the US National Institutes of Health (NIH): the agency is rolling back the red tape on a host of basic-science experiments that involved human participants and had been classified as clinical trials. The decision, which was announced on 29 January and is part of a broader NIH effort to reduce administrative burden, should free such research from the heavy bureaucratic requirements that are designed for clinical trials but are sometimes ill-suited to other fields, such as basic psychology and behavioural studies.

I vividly remember the first experiment I conducted for my PhD in economics, investigating the conditions under which trust forms between strangers. I had built a solid theoretical framework, designed the experiment - in which students played a trust game - carefully, and optimistically named my database 'AwesomeData'. But when I ran my first sessions, the results made no sense. My participants weren't behaving as theory - or even common sense - would suggest, because my set-up made the task too confusing.