Hai-Bo Yu, a theoretical physicist at the University of California, Riverside, has received a $260,000 grant from the John Templeton Foundation to investigate how supermassive black holes were “seeded” in the early universe.

In a new paper published in the journal Psychological Review, Cory Cobb, PhD, assistant professor in the Department of Health Behavior at the Texas A&M University School of Public Health, and colleagues from the University of Texas at Austin, proposed a cultural continuity hypothesis stating that humans are universally motivated to retain and preserve key parts of their cultures across time and space.

Although there is no direct case law on liability using medical AI, the recent products liability case Dickson v. Dexcom Inc. may hold some lessons on future liability risk for manufacturers incorporating AI or machine learning (ML) technologies, according to Sara Gerke and David Simon. This legal finding could influence which products in this space are developed and marketed, with impacts on research and development and resulting benefits to the public. In this Policy Forum, Gerke and Simon discuss the case, which is the first to hold that federal law can preempt personal injury lawsuits under state law when the Food and Drug Administration codifies regulations applicable to a Class II medical device authorized through its De Novo pathway. De Novo classification requests are made for devices that cannot seek the FDA’s Premarket Notification or 510(k) approval pathway – because there are no devices substantially equivalent to it on the market – but are not deemed risky enough to require FDA Premarket Approval (PMA). New technologies such as digital therapeutics are often approved under the De Novo pathway, and Gerke et al. note that “AI/ML-enabled device manufacturers are utilizing the De Novo pathways over three times more than most device manufacturers.” Dickson may shed light on how courts address liability issues with these devices in the future, the authors conclude.

Discovering and studying gravitationally lensed explosions using multiple types of signals will help to answer big questions about the history and structure of the universe.