PHILADELPHIA — Public resistance to new data centers has risen sharply across the United States, even as Americans’ overall views of artificial intelligence remain largely unchanged, according to a nationally representative survey from the Annenberg Public Policy Center at the University of Pennsylvania. The findings reveal a growing divide between public attitudes toward AI as a technology and attitudes toward the physical infrastructure required to operate it. While many people continue to see potential benefits from AI, particularly in medical research, opposition increases substantially when the technology is associated with a large industrial facility being built near their homes.

The survey found that 61% of U.S. adults somewhat or strongly oppose the construction of new data centers in their communities. That figure is 12 percentage points higher than the 49% recorded in an earlier APPC survey conducted in February and March. Support fell during the same period, from 21% to 14%. The change comes as communities across the country debate the environmental, economic, and social consequences of rapidly expanding computing infrastructure used to train and operate advanced AI systems.

Data centers are specialized facilities filled with servers, networking equipment, cooling systems, backup power supplies, and security infrastructure. AI applications can require enormous amounts of computational power because they process vast datasets and perform calculations across billions of model parameters. Training a large AI model may require thousands of processors operating simultaneously, while everyday use also depends on data centers to generate responses, analyze images, translate languages, and carry out other tasks. These facilities can consume substantial amounts of electricity and water, making their construction a highly visible local issue even when the software they support is used remotely.

Opposition to local data centers crosses political boundaries. Majorities of Democrats, Republicans, and independents said they opposed new facilities in their areas, although the proportions differed: 69% of Democrats, 54% of Republicans, and 53% of independents expressed opposition. Resistance was strongest among adults younger than 30, reaching 70%, and declined to 57% among people 65 and older. The pattern is notable because younger adults are often assumed to be more comfortable with emerging technologies and are more likely to use AI-powered services in education, work, entertainment, and communication.

Despite the shift in views about local infrastructure, broader opinions about AI have remained stable. Thirty-nine percent of respondents said they expected AI’s impact on the United States over the next decade to be somewhat or very negative, compared with 18% who expected a positive impact. The result was statistically unchanged from the spring survey. In addition, 68% said the federal government has done “too little” to regulate AI, a view shared by majorities of Democrats, Republicans, and independents. The results suggest that concerns about AI regulation have become persistent rather than being driven solely by short-term news events.

Respondents distinguished sharply between areas where AI might produce public benefits and areas where it could create risks. Among 13 sectors examined, medical research and scientific discovery was the only category receiving a net-positive assessment, with anticipated benefits exceeding expected harms by 41 percentage points. AI systems are increasingly being used to identify patterns in biological data, predict molecular structures, assist with medical imaging, and help researchers screen potential treatments. These applications may accelerate work that would otherwise require years of laboratory experiments, although they still depend on human validation and carefully controlled clinical studies.

The most negative assessments involved personal privacy and data security, which registered a net score of minus 63 points. Children’s online safety followed at minus 50 points, while employment and jobs reached minus 46 points. These concerns reflect the technical and social consequences of deploying AI at scale. Models may be trained on or exposed to sensitive information, automated systems can make decisions that are difficult to explain, and workplace applications may alter or eliminate certain tasks. The survey does not measure whether these risks will materialize in specific industries, but it indicates that many Americans view them as more immediate than AI’s possible benefits outside medicine.

Personal experience with AI was associated with more favorable opinions about its national impact. Among respondents who said they had never used AI during the previous month, 54% expected its effect on the country to be negative. That proportion fell to 40% among light users and to 29% among those who used AI many times or almost every day. However, frequent use did not make people more supportive of data centers. Opposition to building new facilities near respondents’ homes remained essentially flat across different levels of AI use. This distinction suggests that familiarity may influence perceptions of digital tools, while concerns about electricity demand, water consumption, noise, traffic, land use, and local utility costs may remain regardless of personal experience with AI software.

“The people who use AI the most are the most optimistic about what it will do for the country, and that has been consistent across our surveys,” said Matt Levendusky, a University of Pennsylvania political science professor and the Stephen and Mary Baran Chair in the Institutions of Democracy at APPC. He said that optimism had clear limits, particularly when questions involved privacy, employment, or the construction of a data center nearby. The survey was conducted by SSRS for APPC’s Institutions of Democracy division among 1,320 U.S. adult citizens from June 16 through July 19, 2026. Respondents were surveyed primarily online, with a small telephone sample, and weighted to match population benchmarks. The margin of error for the full sample was plus or minus 3.5 percentage points, with larger margins for subgroups. Together, the findings indicate that the next phase of the AI debate may be shaped less by abstract promises about intelligent software than by negotiations over the highly physical systems that make it possible.

Subject of Research: People

Article Title: Opposition to Local Data Centers Rises Sharply as Views on AI Hold Steady

Web References: Annenberg Public Policy Center news release; Reuters; The New York Times; Associated Press

References: Annenberg Public Policy Center Institutions of Democracy national survey, June 16–July 19, 2026; APPC AI topline survey data; APPC survey methodology

Image Credits: Annenberg Public Policy Center

Keywords: Artificial intelligence, data centers, public opinion, AI regulation, medical research, privacy, data security, employment, social surveys, political science

The nature of the surveys to which Phil Halper appeals is that they measure what physicists believe. They cannot measure what the evidence actually supports.

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In recent years, glucagon-like peptide-1 (GLP-1) receptor agonists have emerged primarily as breakthrough medications targeting metabolic disorders such as type 2 diabetes and obesity. Medications like Ozempic and Wegovy have revolutionized treatment protocols by improving glycemic control and promoting weight loss through mechanisms involving appetite regulation and insulin modulation. However, intriguing new research spearheaded by scientists at Rutgers University suggests that the influence of GLP-1 receptor agonists may extend well beyond metabolic pathways, potentially modulating complex behaviors associated with violence and aggression.

The Rutgers study, published in the esteemed journal Criminology, delves into the behavioral ramifications of GLP-1 receptor agonist usage among adults in the United States. This groundbreaking investigation focused on whether these medications could attenuate the well-documented links between impulsivity, alcohol consumption, and violent behavior—an intersection of psychological and physiological domains rarely explored in pharmacological research. Given the increasing prevalence of GLP-1 usage, understanding these potential secondary effects holds substantial public health significance.

Researchers employed data gathered from a 2025 nationwide survey encompassing over 7,500 U.S. adults, narrowing their primary analysis to a subgroup of 821 individuals who had a history of GLP-1 medication use. This cohort was meticulously categorized into current versus former users to discern if ongoing GLP-1 receptor activity correlates with measurable differences in violent behavior frequency. Violent behavior metrics were derived from validated self-reported scales encompassing acts ranging from physical fights and assaults to more severe offenses like robbery, allowing for a comprehensive behavioral profile aligned with criminological standards.

A pivotal discovery from the analysis was the pronounced moderation of the relationship between impulsivity and violent conduct among current GLP-1 users. The data revealed that the association strength between impulsivity—a critical psychological trait linked to poor decision-making and aggression—and violent actions was reduced by approximately 62% in active GLP-1 users compared to those who had discontinued use. Such a substantial attenuation suggests that GLP-1 receptor agonists may exert neurobehavioral effects that temper impulsive drives which frequently precipitate violent acts.

Complementing these results, the study also examined the interplay between alcohol consumption, impulsivity, and violence. Alcohol’s role as a disinhibitor and amplifier of aggressive tendencies is well established. Among current GLP-1 medication users, the correlation between alcohol intake and violent behavior was notably diminished, showing around a 52% reduction in association strength relative to former users. While these findings were somewhat less consistent across different analytic models, they broadly indicate that GLP-1 receptor agonists might mitigate alcohol’s exacerbation of violent impulses, potentially via neurochemical or systemic pathways that modulate inhibitory control.

The underlying neural mechanisms posited by researchers revolve around the interplay of GLP-1 receptor activation within the central nervous system. GLP-1 receptors are expressed not only peripherally but also in brain regions implicated in impulse control, reward processing, and executive functions, such as the prefrontal cortex and limbic structures. Activation of these receptors could conceivably influence neurotransmitter systems including dopamine and serotonin pathways, which are integral to regulating mood, impulse control, and aggression. This neuropharmacological modulation may resemble cognitive behavioral therapy in effect — attenuating the translation of impulsive urges into violent actions without necessarily eradicating impulsivity itself.

Daniel Semenza, lead author and director of research at the New Jersey Gun Violence Research Center, underscored the public safety implications of these findings. With GLP-1 drugs increasingly prescribed globally, it is paramount to deepen scientific understanding of their broader psychobehavioral consequences. Exploring how these medications might serve dual roles in metabolic regulation and behavioral modulation opens new vistas in the multidisciplinary fields of medicine, psychology, and criminology. Such knowledge could inform clinical decisions and policies aimed at reducing violence, a persistent societal challenge with profound public health ramifications.

Nevertheless, the authors caution that the study’s observational, cross-sectional nature precludes definitive causal inferences. While associations are compelling, longitudinal and experimental research designs are essential to elucidate temporal dynamics and confirm whether GLP-1 receptor agonists actively reduce violence risk or if the observed correlations reflect confounding factors. Future studies integrating neuroimaging, pharmacokinetics, and behavioral assessments could unravel the precise biological and psychological pathways mediating these effects.

Christopher Thomas, coauthor and assistant professor at Rutgers University-Camden, highlighted the similarity between the behavioral influences observed and therapeutic interventions like cognitive behavioral therapy. Such parallels suggest that GLP-1 receptor agonists may have untapped potential as adjunctive treatments for impulse control disorders or behavioral problems characterized by aggression. Their dual metabolic and psychobehavioral actions could redefine therapeutic strategies for complex patients with overlapping physiological and psychiatric needs.

Moreover, understanding these effects could broaden the scope of violence prevention frameworks. If GLP-1 receptor agonists contribute to weaker links between impulsivity, substance use, and violent behavior, integrating pharmacotherapy with social and psychological interventions might amplify public safety outcomes. This intersection of neurobiology and criminology exemplifies the innovative, interdisciplinary research needed to address entrenched societal issues.

In summary, the Rutgers study furnishes compelling preliminary evidence that GLP-1 receptor agonist medications, beyond their established metabolic benefits, may significantly dampen the behavioral pathways leading from impulsivity and alcohol consumption to violence. These findings urge a paradigm shift toward holistic evaluation of drug effects encompassing neural, behavioral, and social domains. As the prescribing landscape for GLP-1 medications continues to expand, vigilant research and nuanced understanding will be critical to harnessing their full therapeutic potential while safeguarding public health.

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Subject of Research: People
Article Title: GLP-1 receptor agonist use and violent crime among US adults
News Publication Date: 17-Jun-2026
Keywords: Violence, Drug therapy, Weight loss, Mental health

A recent comprehensive study published in PsyCh Journal casts significant doubt on the widespread application of an adult-derived framework for assessing social-emotional skills among children and adolescents across diverse cultures. The research critically evaluates the Organization for Economic Co-operation and Development’s (OECD) Survey on Social and Emotional Skills, a framework traditionally anchored in adult personality models, highlighting its inability to reliably capture the developmental nuances and cultural variations inherent in younger populations.

This study deployed an extensive dataset comprising over 60,000 children and adolescents aged 10 and 15 from 10 international urban centers spanning nine countries, including the United States, Canada, China, South Korea, Finland, Colombia, Russia, Portugal, and Turkey. The participants’ social-emotional competencies were assessed against the established framework that organizes 15 skills into five categories mapped onto the Big Five personality traits: openness, conscientiousness, extraversion, agreeableness, and emotional stability.

Findings indicate that the hypothesized functional zoning of these skills failed to emerge consistently across the diverse sample. Contrary to expectations, the adult-derived hierarchical structure did not hold true for younger individuals. The empirical data revealed that the configuration of social-emotional skills evolved significantly with age. Ten-year-olds exhibited a more blended and less differentiated pattern of skills, whereas fifteen-year-olds showed more refined distinctions, yet still diverged substantially from the adult framework that underpins the OECD survey.

Moreover, the study unveiled pronounced cultural heterogeneity in the organization of these skills. The way social-emotional skills clustered varied markedly across cities such as Houston, Helsinki, and Suzhou. This variance underscores the influence of local sociocultural factors, educational practices, and societal norms in shaping the development and interrelation of these competencies at both individual and community levels. The research suggests that universal, one-size-fits-all assessments are insufficient for capturing the complexity of social-emotional development across global contexts.

The methodological approach employed, Exploratory Graph Analysis (EGA), was pivotal in uncovering the latent structure of the assessed skills. EGA, a network psychometrics technique, models relationships among variables, offering a data-driven perspective on how different skills interconnect functionally. However, in this case, EGA failed to reproduce the pre-established functional zoning assumed by the survey framework, thereby challenging its applicability and prompting a call for re-evaluation and adaptation.

Bo Ning, PhD, corresponding author and professor at Shanghai Normal University, emphasized the implications of these results. She underscored that social-emotional skill assessments must be sensitive to developmental stages and cultural contexts to ensure fairness and accuracy. This stance invites a paradigm shift towards frameworks that are not only empirically validated for diverse populations but are also dynamic enough to adapt to the evolving socioemotional landscape of children and adolescents worldwide.

The study’s cross-national sample and robust analytic techniques bolster the credibility of its conclusions, signaling a crucial need for psychometric frameworks that accommodate developmental trajectories and cultural specificity. Such frameworks would enhance the validity of social-emotional skill measurement and guide the design of interventions tailored to the unique needs and contexts of younger populations globally.

This investigation also raises broader questions about the translatability of adult personality theories to child and adolescent populations. Since children are in critical developmental phases marked by rapid psychological, social, and cognitive changes, frameworks built on adult models may oversimplify or misrepresent their social-emotional realities. Consequently, researchers and policymakers must reconsider how social-emotional competencies are conceptualized and operationalized in international assessments.

Beyond academic inquiry, this research holds pragmatic significance. Social-emotional skills are increasingly recognized as crucial predictors of lifelong success, influencing educational outcomes, mental health, and social integration. Misalignment in assessment tools could lead to misguided policies, inadequate resource allocation, and ineffective educational programming, especially when applied in culturally or developmentally incongruent ways.

The study’s findings advocate for the creation of culturally nuanced measurement tools that incorporate indigenous concepts of social and emotional functioning. Such culturally congruent tools would respect local values and educational priorities, fostering more authentic and meaningful assessments. Additionally, they would facilitate international comparisons that are not merely nominal but grounded in culturally sensitive understanding.

Further research is needed to elucidate the mechanisms driving developmental and cultural variability in social-emotional skill organization. Longitudinal studies can capture dynamic developmental processes, while qualitative research may offer rich contextual insights. Combining these approaches with advanced quantitative methods like EGA can yield comprehensive frameworks capable of supporting equitable policies and practices in global education and child development.

The growing recognition of the complexity of social-emotional skills across developmental stages and cultures marks a pivotal advancement in psychological science. This study contributes a critical evidence base, urging the scientific community to transcend traditional adult-centric, culturally monolithic frameworks in favor of more sophisticated, inclusive paradigms that truly reflect the lived experiences of children and adolescents worldwide.

As the landscape of global education and psychological assessment continues to evolve, embracing culturally adaptive, developmentally informed frameworks will be essential. Doing so promises to improve the fairness and effectiveness of social-emotional skill measurement, ultimately promoting better outcomes for diverse populations of young people who will shape the future of societies around the world.

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Subject of Research: Social-emotional skill assessment across developmental stages and cultures

Article Title: Exploratory Graph Analysis Failed to Reproduce the Hypothesized Functional Zoning Framework in the OECD Survey on Social and Emotional Skills

News Publication Date: 17-Jun-2026

Web References: http://dx.doi.org/10.1002/pchj.70108

Keywords: personality development, social development, developmental psychology, psychological science, young people, adolescents, emotional development

Greetings, Arsians, and welcome to the great Ars Technica 2026 reader survey! It has been almost four years since we last ran a big site-wide survey like this, where we ask our readers—you!—what you like about the work we do and what we could perhaps improve on. This kind of check-in is absolutely vital to ensuring we're steering the ship properly, and we take the results very seriously. (The last time we did this, we got several thousand responses, and that's incredibly valuable data for us!)

You don't have to have been a reader since 1998 to weigh in, either. Whether you're a first-time reader, an old grizzled forum veteran, a front page comment maven, a newbie sysadmin, or a CEO, we want to hear what you have to say, no matter who you are. The only requirement is that you're a human! (Aliens are welcome as well, though we didn't really define any demographic categories for extraterrestrial beings. We'll tackle this issue if it comes up, I suppose.) There are a few text fields. Yes, we will read what you write there!

To assay, perchance to sing

Fortunately, this isn't a long survey—just a handful of targeted questions. We're not collecting any personally identifying information, and responses will only be viewed in aggregate. None of the data will be analyzed by anyone except us, and none of it will be sold or otherwise distributed outside of Ars. (We're using SurveyMonkey for our survey platform, the same as we have many times in the past.)

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