A rare policy consensus emerges as AI’s impact moves beyond innovation into governance and societal risk
Updated
May 5, 2026 5:42 PM
A mechanical hand reaching for the hand of flesh. PHOTO: UNSPLASH
A new survey from Povaddo, a policy research firm, suggests that concern about artificial intelligence is no longer limited to industry or academia. It is now firmly present within the policy community.
The survey draws on responses from 301 public policy professionals across the United States and Europe, including lawmakers, staffers and analysts involved in shaping and evaluating public policy. A majority of respondents—61%—say governments are falling short in addressing the negative impacts of AI.
There is also broad agreement that regulation needs to increase. In the United States, 92% of respondents support stronger AI regulation, compared to 70% in Europe. At a time when consensus is often difficult, the findings point to a shared view across policy circles that current frameworks are not keeping pace with technological development.
Differences emerge when looking at how AI is affecting national contexts. In the U.S., 57% of policy experts believe AI is already harming the labor market. In Europe, 34% say the same. U.S. respondents are also more likely to see AI as a greater threat to jobs than immigration, with 63% holding that view compared to 47% in Europe.
On misinformation, responses are closely aligned. A large majority of policy experts in both regions expect an AI-driven misinformation crisis within the next one to two years—87% in the U.S. and 82% in Europe. Many also believe that AI-generated or AI-amplified misinformation could affect elections and public health information.
Some respondents frame the risks in more fundamental terms. In the United States, 41% of policy experts say AI poses an existential threat to humanity. In Europe, 29% share that view. U.S. respondents are also more likely to believe that advances in AI could harm global security and stability.
The findings come as policymakers begin to respond more actively. In the U.S., Senators Josh Hawley, Richard Blumenthal and Mark Warner have introduced bipartisan legislation focused on AI accountability, including measures aimed at protecting workers and children.
In Europe, the introduction of the EU AI Act marks a more advanced regulatory approach. The framework sets out rules based on levels of risk and is widely seen as the first comprehensive attempt to govern AI at scale.
William Stewart, President and Founder of Povaddo, said: "What makes these findings so significant is who is saying it. These are the practitioners who work inside the policy process every day, spanning every corner of the policy world from defense to healthcare to finance, not activists or everyday citizens. These findings foreshadow real action. The current path of governments accelerating AI deployment while falling short on governance is not sustainable, and the people who know that best are the ones in this survey. You cannot have nine-in-ten policy insiders demanding more regulation and four-in-ten calling AI an existential threat without that eventually moving the needle in Washington and Brussels in terms of legislative or regulatory action".
Taken together, the survey reflects a shift in how AI is being discussed within policymaking circles. Concern is no longer limited to future risks. It is increasingly tied to current gaps in governance and the pace of deployment.
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A closer look at how machine intelligence is helping doctors see cancer in an entirely new light.
Updated
January 8, 2026 6:33 PM
Serratia marcescens colonies on BTB agar medium. PHOTO: UNSPLASH
Artificial intelligence is beginning to change how scientists understand cancer at the cellular level. In a new collaboration, Bio-Techne Corporation, a global life sciences tools provider, and Nucleai, an AI company specializing in spatial biology for precision medicine, have unveiled data from the SECOMBIT clinical trial that could reshape how doctors predict cancer treatment outcomes. The results, presented at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting, highlight how AI-powered analysis of tumor environments can reveal which patients are more likely to benefit from specific therapies.
Led in collaboration with Professor Paolo Ascierto of the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, the study explores how spatial biology — the science of mapping where and how cells interact within tissue — can uncover subtle immune behaviors linked to survival in melanoma patients.
Using Bio-Techne’s COMET platform and a 28-plex multiplex immunofluorescence panel, researchers analyzed 42 pre-treatment biopsies from patients with metastatic melanoma, an advanced stage of skin cancer. Nucleai’s multimodal AI platform integrated these imaging results with pathology and clinical data to trace patterns of immune cell interactions inside tumors.
The findings revealed that therapy sequencing significantly influences immune activity and patient outcomes. Patients who received targeted therapy followed by immunotherapy showed stronger immune activation, marked by higher levels of PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells. Those who began with immunotherapy benefited most when PD-1+ CD8 T-cells engaged closely with PD-L1+ CD4 T-cells along the tumor’s invasive edge. Meanwhile, in patients alternating between targeted and immune treatments, beneficial antigen-presenting cell (APC) and T-cell interactions appeared near tumor margins, whereas macrophage activity in the outer tumor environment pointed to poorer prognosis.
“This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology”, said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.
The collaboration between the two companies underscores how AI and high-plex imaging together can help decode complex biological systems. As Avi Veidman, CEO of Nucleai, explained, “Our multimodal spatial operating system enables integration of high-plex imaging, data and clinical information to identify predictive biomarkers in clinical settings. This collaboration shows how precision medicine products can become more accurate, explainable and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone”.
Dr. Ascierto described the SECOMBIT trial as “a milestone in demonstrating the possible predictive power of spatial biomarkers in patients enrolled in a clinical study”.
The study’s broader message is clear: understanding where immune cells are and how they interact inside a tumor could become just as important as knowing what they are. As AI continues to map these microscopic landscapes, oncology may move closer to genuinely personalized treatment — one patient, and one immune network, at a time.