In a Policy Forum, Nizan Packin and Sharon Rabinovitz highlight the social, political, and economic risks of rapidly growing commercial prediction market (PM) platforms, such as Polymarket and Kalshi, and call for informed regulatory action. “The window for precautionary action is closing: Each week of billion-dollar PM activity, integrated into core information infrastructure without oversight comparable to that of regulated gambling, prolongs a large uncontrolled experiment on users,” write the authors. For many years, economists and computer scientists praised PMs as refined tools of collective intelligence, particularly within academic and institutional settings where they were used to generate accurate forecasts. However, a 2024 U.S. court decision permitting event-based political contracts on commercial platforms marked a turning point, accelerating the rise of large-scale, gamified markets designed for mass participation. Unlike their research-focused predecessors, these modern platforms often prioritize user engagement and profit, and by late 2025, PMs were handling more than $2 billion in transactions each week, with major events attracting wagers totaling in the hundreds of millions. According to the authors, these rapidly growing platforms raise growing concerns, including the potential for democratic manipulation, the incorporation of gambling-like mechanics, and risks to public health stemming from addictive design features.

Here, Packin and Rabinovitz discuss these concerns in detail and highlight the need for evidence-based regulatory attention. “This public health risk flourishes through systematic regulatory failure,” write the authors. “PM platforms function as ‘regulatory entrepreneurs,’ designing products to leverage legal ambiguities between gambling and financial law.” The authors note that commercial PMs can undermine democratic integrity by enabling manipulation, unequal participation, and distorted political signals. Foreign actors may legally trade on election outcomes, while thinly traded markets allow relatively small bets to shift probabilities and create misleading impressions of consensus, influencing voters, media narratives, and campaign dynamics. Weak oversight also enables insider trading risks tied to sensitive government information, which creates the ability to profit from real-world events and may even create incentives to influence the outcomes themselves. Moreover, these platforms increasingly resemble gambling systems, despite being framed as tools for forecasting, which may drive broader social and economic risks for those who use them, particularly individuals with addictive tendencies. According to Packin and Rabinovitz, PMs now occupy a pivotal juncture; they could remain valuable tools for informed decision-making if responsibly governed – or, if unchecked, they could become sources of behavioral and democratic harm. The scientific community, having contributed to their development, bears a responsibility to guide their ethical boundaries, advocate for evidence-based regulation, and ensure that innovation does not outpace accountability.

For reporters interested in topics of research integrity, author Sharon Rabinovitz notes, “One of the most underacknowledged integrity issues in addiction science is structural: stigma and implicit moral judgment constrain funding for the very research needed to ground policy and regulation in evidence. This is especially acute for behavioral addictions, where powerful financial interests consistently outpace the science and actively shape the regulatory landscape. Gambling, despite its well-documented public health impact, remains chronically under-researched relative to its regulatory urgency; trading platforms and prediction markets present an even more pressing gap, aggressively normalized yet almost entirely unexamined for addiction liability. Without greater public investment in independent research, regulation will continue to lag behind industry, repeating the mistakes of sectors that shaped the evidence base in their own favor before oversight could catch up.”

Podcast: A segment of Science's weekly podcast with Nizan Packin, related to this research, will be available on the Science.org podcast landing page [http://www.science.org/podcasts] after the embargo lifts. Reporters are free to make use of the segments for broadcast purposes and/or quote from them – with appropriate attribution (i.e., cite "Science podcast"). Please note that the file itself should not be posted to any other Web site.

A new analysis of individual brain cells across several human brain regions reveals subtle but widespread differences in gene activity between male and female brains. This may help explain why some psychiatric and neurological disorders appear to affect the biological sexes differently, researchers report. Males and females, as defined by individuals with an XY and XX chromosomes, respectively, show marked differences in risk, prevalence, and progression of many psychiatric and neurological disorders. While these disparities likely arise from the interplay of biological and social influences, their consistency across cultures and predictable timing over development suggest that sex-determined differences in gene transcription in the brain may play an important role. To investigate this possibility, Alex DeCasien and colleagues conducted a high-resolution analysis of gene expression in the human brain using single-nucleus RNA sequencing (snRNA-seq) on tissue samples from 30 adult individuals (15 male and 15 female). They specifically focused on six cortical regions – some known to exhibit sex differences in brain structure and others not known to – allowing the authors to more precisely compare between molecular and anatomical variation.

DeCasien et al. found that biological sex explained only a very small fraction of variation in gene expression across the brain. Nevertheless, the analysis revealed more than 3,000 genes that exhibited some degree of sex-biased transcription in at least one cortical region, and 133 with consistent effects across brain regions and cell types. While the strongest differences were found in genes located on the sex chromosomes, most sex-related variation occurred in autosomal genes not linked to sex chromosomes and driven predominantly by sex steroid hormones. Notably, many of these genes showing sex-biased expression overlap with genetic variants associated with neuropsychiatric and neurodegenerative disorders, including ADHD, schizophrenia, depression, and Alzheimer’s disease. “[DeCasien et al.] explicitly acknowledge that sex-related differences reported in their study may originate from differences in socialization and experience,” write Jessica Tollkuhn and Marc Breedlove in a related Perspective. “A role for such social influences could be ruled out if sex differences in gene expression are present before birth, and future studies could address this question.”