Ahead of the expected finalisation of an UN global plastics treaty [1], a group of international experts call for a greater focus on health impacts when considering plastic pollution. The Health Policy published in The Lancet reviews the current evidence on how plastics – including microplastics and plastic chemicals - impact health and announces the launch of a new project tracking these impacts: the Lancet Countdown on Health and Plastics.

Boston College researchers co-lead the launch of The Lancet Countdown on Health and Plastics, an online dashboard that will track the health and environmental impacts of plastic pollution and monitor UN-guided efforts to curb plastics’ use and mitigate their harms.

It's not always the issues: Over the last decade, people protest almost as much because they hate the opposing party.

The COVID-19 pandemic upended life for individuals and communities worldwide. Social isolation, health mandates, illness, and economic hardships took a toll on the well-being of families and children, but there were also silver linings to people’s experiences. A new study from the University of Illinois Urbana-Champaign looks at impacts of the pandemic among youth and parents across the U.S. Midwest. Their findings can help provide insights for future policy and public health measures.

Data story highlights disciplinary diversity in the second round of the German federal and state governments’ Excellence Strategy / “Analysis of great relevance to the research system”

In a Policy Forum, Rishi Bommasani et al. argue that successful artificial intelligence (AI) policy must be grounded in solid evidence and scientific understanding rather than hype or political expediency. “AI policymaking should place a premium on evidence: Scientific understanding and systematic analysis should inform policy, and policy should accelerate evidence generation,” write Bommasani et al. Although developing sound AI policy hinges on clearly defining and effectively using credible evidence, the authors note that what is considered to be valid or credible varies across AI policy domains, leading to uncertainty in governance. This uncertainty creates a policy challenge: act too soon and risk overregulation; wait too long and risk real harm. Here, Bommasani et al. call for developing mechanisms that allow AI policy to evolve alongside emerging scientific understanding, which would ensure that governance remains both effective and grounded in the current state of the technology. To achieve evidence-based AI policy, the authors suggest that governments should incentivize rigorous pre-release model evaluations, increase public transparency around safety practices, and establish systems to monitor post-deployment harms. Protecting independent researchers through safe harbor provisions is essential to expand the evidence base. Policies should also prioritize interventions supported by strong evidence across the broader sociotechnical landscape. Finally, fostering expert consensus through credible, inclusive scientific bodies will help guide responsible AI governance amid uncertainty and disagreement, say the authors.