The research team, led by Fei Wang, Siqi Huang, Yiwen Xu, Jin Wen and Xing Qu, affiliated with Sichuan University’s West China Hospital and its Business School, analyzed forty-two national-level medical AI policy documents issued between 2019 and 2025 by seven governments and blocs: the United States, the United Kingdom, Japan, South Korea, Australia, China and the European Union. Rather than simply reading and summarizing the documents, the researchers applied the Policy Modeling Consistency, or PMC, Index model, a quantitative framework originally developed in policy science to measure how internally coherent, structurally complete and implementation-ready a piece of policy text really is.

The PMC methodology is technically intricate. The team first constructed a multidimensional evaluation system comprising nine primary variables, each subdivided into a total of thirty-five secondary variables. These dimensions capture everything from the nature and purpose of a policy to its content depth, the policy tools it deploys, the breadth of perspective it adopts, and the strength of its evaluation and feedback mechanisms. Each secondary variable is scored, the scores are combined into a composite PMC index, and a concavity index is calculated to grade the policy on a five-point scale from A to E. The final step is visualization: a so-called PMC surface map renders each policy’s strengths and weaknesses as a three-dimensional landscape, allowing researchers to see at a glance where a document bulges with detail and where it collapses into vagueness.

The headline numbers reveal a field that is competent but not exceptional. Of the forty-two policies analyzed, only two, or 4.76 percent, earned the top Grade A rating, while twenty-nine, or 69.05 percent, landed in Grade B. Nine policies, listed as 14.51 percent in the study, were rated Grade C, and two, or 4.76 percent, fell to Grade D. The overall mean PMC index came out at 6.67, which the authors interpret as above-average global policy quality. In other words, most governments are doing reasonably well at writing medical AI strategies, but almost none are producing documents the model considers excellent.

More revealing than the aggregate scores is the pattern beneath them. The policies scored highest on dimensions such as policy nature, policy evaluation and policy perspective, indicating that governments excel at declaring broad intent, articulating why medical AI matters, and framing their strategies within national and global contexts. The weakest scores, by contrast, appeared in policy content and policy tools, the very dimensions that determine whether a strategy can actually be executed. The authors describe this as a structural imbalance: comprehensive strategic frameworks paired with weak implementation instruments. A government can proclaim that AI will transform its health system, but if the document lacks concrete regulatory levers, funding mechanisms, accountability structures and measurable milestones, the proclamation remains aspirational prose.

This imbalance has real consequences for patient safety and innovation alike. Medical AI systems touch some of the most sensitive territory in modern governance: clinical decision-making, patient data privacy, algorithmic bias, liability when an algorithm errs, and the ethical boundaries of machine involvement in care. The study found that most of the policies it examined exhibit robust strategic orientation but insufficient regulatory and ethical detailing. That gap matters because the absence of specific rules does not create a regulatory vacuum in practice; it simply shifts decisions to courts, hospitals and individual clinicians, often after harm has occurred or trust has eroded.

The seven jurisdictions studied represent the full spectrum of approaches to AI governance. The United States has leaned on agency-level guidance, including the Food and Drug Administration’s evolving framework for AI-enabled medical devices, alongside broader executive initiatives. The United Kingdom has pursued a principles-based, regulator-led model through bodies such as the Medicines and Healthcare products Regulatory Agency and the Department for Science, Innovation and Technology. The European Union has embedded health AI within its sweeping horizontal AI legislation and its General Data Protection Regulation, prioritizing fundamental rights. China, Japan and South Korea have issued national strategies that couple industrial policy with health-sector pilot programs, while Australia has taken a more incremental, standards-driven path. The PMC analysis allows these philosophies to be compared on a common quantitative footing for the first time at this scale.

For China in particular, the study offers pointed recommendations. The authors conclude that the country’s policy framework should prioritize refining data governance mechanisms, strengthening ethical accountability, and building dynamic policy adjustment systems capable of keeping pace with fast-moving technology. The emphasis on dynamism is notable: static policy documents written for the AI of 2020 may be poorly matched to generative models and foundation-model medical applications emerging today. A policy system that cannot revise itself quickly risks perpetually regulating the previous generation of technology, a problem the authors suggest is not unique to China but visible across the dataset.

The broader lesson for policymakers everywhere is that ambition and operability must be designed together. The PMC Index model, with its decomposition into nine primary and thirty-five secondary variables, effectively functions as a diagnostic checklist for policy drafting. Documents that score well tend to specify who is responsible for implementation, how compliance will be monitored, what resources are committed, and how success will be measured. Documents that score poorly tend to be heavy on vision statements and light on instruments. As governments worldwide prepare the next wave of AI health regulations, the study’s methodology offers a template for stress-testing drafts before they are published, rather than discovering their weaknesses through implementation failures.

The research also demonstrates the value of treating policy text itself as data. By combining text mining with quantitative modeling, the team converted hundreds of pages of governmental prose into comparable scores and visual surfaces, making cross-national policy assessment reproducible rather than subjective. In a domain where hype routinely outpaces evidence, that kind of rigor is itself a form of governance. The study, published open access on 5 October 2026 with the DOI 10.1186/s12913-026-15763-w and supported by the National Natural Science Foundation of China, suggests that the world’s governments know where they want medical AI to go. What remains to be seen, and what their current policies too rarely specify, is exactly how they plan to get there.

Subject of Research: Quantitative evaluation of national-level medical artificial intelligence policies using the Policy Modeling Consistency Index model

Article Title: Evaluation of global national-level medical artificial intelligence policies and strategies based on the policy modeling consistency index model

Article References: Wang, F., Huang, S., Xu, Y., Wen, J., & Qu, X. (2026). Evaluation of global national-level medical artificial intelligence policies and strategies based on the policy modeling consistency index model. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15763-w

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15763-w

Keywords: medical artificial intelligence, health policy, PMC index model, policy evaluation, policy implementation, data governance, AI regulation, health services research, comparative public policy, clinical AI, policy quality assessment, China

The special issue examines AI’s policy implications from five distinct angles. One study probes public trust and opinion within the European Union, another compares governance models in Singapore and France, a third frames global AI governance as a classic collective action problem, a fourth dissects regulatory challenges in the defense sector across the European Union and the United States, and a fifth investigates the ethical and legal implications of facial recognition technology in both democratic and autocratic states. Taken together, they map the fault lines where national sovereignty, ethical oversight, and international cooperation collide, and they suggest that no single country or institution can manage the technology alone.

The comparative analysis of national governance models reveals just how different the world’s responses have become. In a study of Singapore and France, Alibašić shows how international organizations and global governance frameworks shape national AI strategies in markedly different ways. Singapore has built an innovation-centric model, one that treats regulatory agility as a competitive advantage and leans heavily on market-driven experimentation. France, by contrast, has pursued an ethics-driven approach in which the state plays a leading role in setting boundaries and safeguarding public values. The contrast is not merely stylistic. It illustrates a fundamental tension in AI policy worldwide: whether the primary goal of regulation is to accelerate innovation or to constrain it in the name of rights, safety, and democratic accountability.

That tension becomes even sharper when the technology in question is designed for the battlefield. Parisini’s comparative study of the European Union and the United States in the defense sector underscores the fragmented nature of EU defense AI governance, which is spread across institutions and member states, and contrasts it with the far more centralized strategy of the US Department of Defense. The analysis identifies capability gaps within the EU that could be narrowed through stronger transatlantic cooperation, an argument that echoes the findings on Singapore and France about the importance of international coordination. In other words, whether the domain is civilian innovation or military capability, the same lesson emerges: jurisdictions that try to go it alone leave gaps that cooperation could close.

At the global level, the picture grows more daunting still. Olugbade situates these national differences within a broader framework, arguing that AI governance is fundamentally a collective action problem, one made worse by the non-cooperation of the three dominant powers: the United States, China, and the European Union. When the largest producers and deployers of AI cannot agree on shared rules, smaller states are left to choose among incompatible standards, and the technology flows through the cracks. Olugbade’s answer is a polycentric governance mechanism, a system in which multiple centers of authority, from national regulators to international organizations, each govern parts of the problem while reconciling national autonomy with global cooperation. Rather than waiting for a single worldwide treaty that may never arrive, polycentricity accepts overlapping jurisdictions and seeks alignment among them.

The stakes of this fragmentation are not abstract. Robles and colleagues examine regulatory frameworks for facial recognition technology across a range of political regimes and document how unevenly such measures are applied. In democratic states, facial recognition raises acute concerns about civil liberties, wrongful identification, and the chilling of lawful assembly; in autocratic states, the same technology can become an instrument of surveillance and social control. The study’s central finding, the need for harmonized international standards, echoes a sentiment running through the entire special issue: without common benchmarks, the ethical floor for AI technologies will be set by the least restrictive jurisdiction, and the consequences will spill across borders.

Public trust emerges as the connective tissue binding all of these analyses together. Jensen and Chen focus on public sentiment toward AI within the European Union and identify class-based divides in how the technology is perceived, along with skepticism rooted in deficits of governance trust. Citizens who distrust the institutions regulating AI are unlikely to accept its deployment, however technically sound the safeguards may be. The authors propose citizen engagement and transparency initiatives as mechanisms to bridge this trust gap, a micro-level prescription that complements the macro-level analyses of global governance offered elsewhere in the issue. The implication is that legitimacy must be built at both ends of the scale: in the deliberations of international bodies and in the lived experience of ordinary people confronting algorithmic decision-making.

What makes the synthesis compelling is the convergence of these five studies on a shared set of themes: governance fragmentation, public trust, ethical considerations, and international cooperation. The comparative evidence suggests that harmonizing AI governance requires multilevel collaboration, both within regions such as the European Union and across global power blocs that currently view each other with suspicion. The collective warning is stark. Without coordinated global policies, AI governance will remain uneven, and that unevenness will put democratic accountability and international security at risk simultaneously. A technology that respects no borders cannot be governed effectively by institutions that stop at them.

The policy implications are concrete. The synthesis calls for enhanced international cooperation, stronger citizen engagement to foster trust, and the establishment of ethical standards for emerging technologies such as facial recognition. It also sketches institutional mechanisms that could translate high-level policy convergence into practice without demanding complete harmonization. Regulatory sandboxes, flexible spaces where governments can trial data-sharing protocols or algorithmic audits under shared principles while maintaining oversight, offer one path for incremental alignment. International AI observatories, hosted by multilateral organizations such as the OECD, UNESCO, or the UN Tech Envoy, could coordinate monitoring, ethics benchmarking, and risk assessment across jurisdictions. Capacity-building initiatives, including South–South knowledge transfer networks and AI policy toolkits tailored to institutional contexts, would support low- and middle-income countries that currently lack the regulatory infrastructure to engage on equal terms.

The research agenda that follows is equally clear. Future work should explore mechanisms for enforcing global AI standards while respecting national sovereignty, and should conduct empirical studies on whether polycentric governance frameworks actually deliver in practice. Multi-scalar research comparing AI implementation across local, national, and regional levels would reveal where governance gaps emerge and how they might be mitigated. The special issue as a whole advocates a multi-level, polycentric approach that bridges the gap between national autonomy and global regulatory alignment, setting the stage for AI governance that is both more robust and more democratically accountable. The alternative, a world in which each bloc writes its own rules and trusts no one else’s, is not a stable equilibrium but a slow-motion race to the weakest standard. The choice, the synthesis suggests, is still open, but the window for making it deliberately is narrowing with every deployment.

Subject of Research: Comparative analysis of global AI governance frameworks and polycentric policy coordination

Article Title: From fragmentation to polycentricity: a comparative synthesis on AI governance and global policy coordination

Article References: Woods, D. (2025). From fragmentation to polycentricity: a comparative synthesis on AI governance and global policy coordination. Global Public Policy and Governance, 5(2), 87-92. https://doi.org/10.1007/s43508-025-00118-8

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00118-8

Keywords: artificial intelligence, AI governance, polycentric governance, global policy coordination, public trust, facial recognition technology, EU regulation, defense sector, collective action, regulatory sandboxes, international organizations, comparative public policy

The significance of this comparison lies in its methodology. While many scholars have observed anecdotally that conditions for civil society organizations in China have tightened or loosened over time, few studies have undertaken a systematic, field-by-field comparison of the actual policy texts issued at the national level across these two eras. By treating policy documents as primary evidence, the researchers were able to trace precisely where the state’s posture changed dramatically and where it remained remarkably stable. This document-based approach allows the evolution of government-nonprofit relations to be mapped with a granularity that impressionistic accounts cannot match, and it grounds the analysis in the concrete legal and administrative instruments through which the Chinese state actually exercises authority over organized social life.

The study identified major policy changes across several crucial domains. The first is organizational establishment, the process by which nonprofit groups gain legal recognition. Registration requirements, sponsor oversight arrangements, and the criteria for what may legally exist as a social organization all shifted between the two periods, altering which kinds of groups can form and under whose supervision. A second domain is disciplining and monitoring, where policies governing annual inspections, audits, and enforcement actions became more elaborate and more demanding in the New Era. Related fields include government funding of nonprofits, the rules governing charitable fundraising, and the increasingly consequential regulation of overseas funding, through which foreign grants to Chinese organizations have come under intense scrutiny. Party building, the extension of Communist Party committees and members into nonprofit organizations, emerged as another field transformed almost beyond recognition between the two eras, alongside policy advocacy, the arena in which organizations seek to influence government decisions.

The contrast with earlier decades is striking. During the New Century, the state’s relationship with the nonprofit sector reflected what scholars of Chinese politics have described as consultative or graduated forms of authoritarian governance. Organizations were subject to controls, but the state also experimented with purchasing services from nonprofits, encouraging social organizations to deliver welfare functions, and soliciting their expertise in policy formation. Some analysts characterized this as a period in which many civil societies could bloom, at least within carefully bounded spheres. The policy environment allowed a measure of negotiated autonomy, in which grassroots groups survived through what researchers have called contingent symbiosis with local authorities. The new comparative analysis confirms that this era’s policies embodied a deliberative logic: the state consulted, absorbed, and steered, but it did not yet demand organizational integration into its own political structures.

The New Era policies tell a different story. Since 2013, the party-state has asserted far more direct and directive authority over the sector. Party building requirements, which the study identifies as one of the most transformed policy fields, now extend Communist Party organization deep into social organizations, embedding political supervision within the internal governance of nonprofits themselves. The regulation of overseas funding, formalized through legislation targeting foreign nongovernmental organizations and their domestic partners, has securitized what was once a routine channel of philanthropic and technical support. Charitable fundraising, while legally clarified through the 2016 Charity Law and the subsequent recognition of tens of thousands of certified charitable organizations, has been coupled with heightened disclosure and monitoring obligations. The cumulative effect, according to the researchers, is a strategy of incorporation: organizations are welcomed into the state’s agenda only to the extent that they accept directive oversight and align with party leadership.

Yet the study’s most analytically interesting finding may be what has not changed. In certain policy fields, notably business activities and tax deduction, the researchers found fewer significant shifts between the New Century and the New Era. The rules permitting nonprofits to engage in revenue-generating activities, and the tax incentives that encourage charitable giving, have remained comparatively stable. This continuity matters because it complicates any simple narrative of wholesale repression or liberalization. The state has, in effect, retained and even cultivated the economic and fiscal infrastructure of a functioning philanthropic sector, with more than sixteen thousand certified charitable organizations now operating under the Charity Law framework, while simultaneously transforming the political infrastructure through which those organizations are supervised and integrated. The result is a sector that is institutionally more developed and politically more constrained at the same time.

This dual trajectory sheds light on long-running theoretical debates about state-society relations in authoritarian contexts. Earlier frameworks described China’s approach as administrative absorption of society, in which the state co-opted social organizations to prevent autonomous mobilization, or as fragmented authoritarianism, in which policy authority was dispersed among competing bureaucratic actors. The new evidence suggests that such framings capture the New Century better than the present. The shift toward directive state incorporation implies a recentralization of authority and a clearer command hierarchy, in which the party’s organizational presence substitutes for the looser bargaining that once characterized government-nonprofit encounters. Participation by nonprofits is still possible, and even encouraged in service delivery areas, but it increasingly takes the form of participation without contestation, a formula that recent scholarship on NGO autonomy in China has used to describe advocacy that operates strictly within state-defined limits.

The practical implications for the nonprofit sector itself are substantial. Organizations seeking legal status, government contracts, or fundraising permissions in the New Era must navigate a policy environment in which political conformity is a baseline expectation rather than an occasional demand. Annual inspections have become instruments through which party leadership and standardization are enforced, with authorities explicitly framing inspection regimes as mechanisms to keep social associations on a steady course. Overseas partnerships, once a lifeline for environmental, legal aid, and public health groups, now require registration and reporting under security-oriented regulations. At the same time, organizations aligned with state priorities, particularly in poverty alleviation, elder care, and community services, have found expanded opportunities for government funding and public recognition. The policy landscape thus rewards integration and penalizes autonomy, reshaping the composition of the sector in favor of groups willing to operate inside the incorporation framework.

The researchers conclude by situating their findings within the global comparative literature on government-nonprofit relations, noting that China’s trajectory offers a distinctive model in which a strong state deliberately cultivates a nonprofit sector as an instrument of governance rather than as a counterweight to state power. They argue that future research should track how these policy changes filter down to the local level, where implementation has historically varied widely, and how organizations themselves adapt their strategies, governance structures, and issue portfolios to survive under directive incorporation. For scholars of civil society, authoritarian governance, and comparative public policy, the study provides something the field has lacked: a systematic, evidence-based map of exactly where Chinese nonprofit policy changed, where it endured, and what that pattern reveals about the state’s evolving theory of how organized society should be governed. As China’s social organizations continue to multiply in number while narrowing in permitted purpose, the comparison between the New Century and the New Era offers an essential baseline for understanding one of the world’s most consequential experiments in managing the boundary between state and society.

The findings also resonate with scholarship on the social origins of nonprofit sectors, which holds that the shape and autonomy of civil society depend heavily on the prevailing pattern of state welfare provision. China’s trajectory illustrates a variant in which the nonprofit sector expands not through retreat of the state but through its active orchestration, with government funding and service contracting serving as levers of alignment rather than signs of disengagement.

Historically, the study’s framing benefits from a longer view of Chinese associational life. Charitable halls and benevolent societies flourished in imperial China, often operating in negotiated proximity to officialdom, suggesting that the tension between state authority and organized benevolence is not a modern invention but a recurring feature of Chinese governance that each era resolves differently.

Methodologically, the reliance on document analysis underscores both the strength and the limits of policy-text research. Texts reveal official intent with precision, yet implementation has historically diverged across regions, meaning local enforcement may soften or sharpen the national posture described here. The authors’ call for research tracing these policies to the local level therefore addresses a genuine evidentiary gap.

For comparative scholars, the case suggests that authoritarian states can simultaneously professionalize a philanthropic sector, through legal clarification and fiscal incentives, while narrowing its political space, a combination that standard typologies of government-nonprofit relations, developed largely from liberal democratic contexts, may need to accommodate more explicitly.

Subject of Research: Policy changes in China's national-level governance of nonprofit organizations from the New Century (2002-2012) to the New Era (2013-present)

Article Title: China’s policy changes in managing nonprofit organizations: The comparison between the New Century and the New Era

Article References: Hu, M., & Dong, H. (2026). China’s policy changes in managing nonprofit organizations: The comparison between the New Century and the New Era. Global Public Policy and Governance. https://doi.org/10.1007/s43508-026-00157-9

Image Credits: AI Generated

DOI: 10.1007/s43508-026-00157-9

Keywords: China, nonprofit organizations, civil society, government-nonprofit relations, policy change, state control, party building, charitable fundraising, overseas funding, authoritarian governance, comparative public policy, social organizations