India is uniquely positioned to anchor a democratic alternative to China’s authoritarian tech model, leveraging its democratic institutions and massive market to shape global technology norms. The analysis highlights that India’s tech governance remains rooted in the rule of law and pluralistic deliberation, contrasting sharply with state-led authoritarian models. However, the article stresses that India cannot lead alone; effective progress requires coordinated efforts from like-minded democratic powers, particularly the United States, to fill the growing normative vacuum. Strategically, democratic nations must urgently coordinate to establish shared frameworks for AI and data governance, or risk ceding future economic and regulatory influence to China.
Technology
This topic hub groups ThinkTankWeekly entries tagged Technology and links readers back to the original publishers.
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The concept of mandatory AI licensing and pre-release testing is resurfacing as a critical policy concern, driven by the emergence of highly capable, vulnerable models and renewed political interest in regulation. While the U.S. government is considering an executive order modeled after drug approval processes, the author argues that simply adapting existing regulations is insufficient. For effective policy, the U.S. must craft a framework tailored to AI's unique, continuously evolving nature, focusing heavily on rigorous pre-release evaluation methods. Crucially, any licensing regime must be paired with robust post-market oversight and enforcement mechanisms to manage the risks posed by advanced, rapidly advancing AI systems.
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This CATO analysis warns against a White House proposal to establish a pre-approval system for advanced AI models, framing it as a potential ‘kill switch’ over speech and innovation. The proposal, likened to an ‘FDA for AI,’ would grant the executive branch unprecedented control over the technology, raising concerns about regulatory capture, censorship, and the weaponization of government power. Evidence suggests this initiative is driven by cybersecurity concerns and a desire to retaliate against companies with dissenting viewpoints, exemplified by the Anthropic-Pentagon dispute. Such a prescriptive approach risks stifling innovation, chilling free speech, and placing the U.S. at a competitive disadvantage compared to nations with less restrictive regulatory frameworks.
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This CSIS report argues that spectrum policy is increasingly intertwined with AI advancement, particularly as 6G technology emerges. The report highlights that the deployment of AI-powered systems, especially those requiring low latency like autonomous vehicles and robotics, will heavily rely on access to sufficient mid-band spectrum. Drawing lessons from the 5G rollout and China's rapid advancements, the authors warn that inadequate U.S. spectrum policy risks hindering domestic AI competitiveness and national security. Expanding the spectrum pipeline and streamlining allocation processes are crucial for U.S. leadership in AI and 6G.
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The development of superintelligence, exemplified by DeepMind's work, represents a transformative, dual-use technology comparable to nuclear power, promising massive gains in fields like medicine (e.g., AlphaFold). The analysis highlights that while pioneers like Demis Hassabis approach AI from a fundamental scientific motivation, the race dynamic makes global safety governance challenging. Strategically, the findings suggest that emerging markets view AI as a primary engine for development, contrasting with the caution seen in advanced economies due to job displacement fears. Policymakers must therefore focus on guiding AI development toward applications with clear human benefits to ensure global acceptance and manage the inherent risks of this powerful new technology.
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Connected cars represent a major technological shift, offering enhanced convenience and safety through advanced AI and digital interfaces. However, this deep integration creates significant governance challenges, particularly concerning data privacy, system security, and accountability. Policy must navigate the tension between rapid technological innovation and the need for robust regulatory frameworks. Key discussions will focus on developing resilient infrastructure while establishing clear rules for data ownership and cybersecurity to protect both consumers and the broader economy.
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Agrawal's career highlights that effective foreign policy analysis requires integrating diverse, global perspectives, a skill honed by observing massive technological and geopolitical shifts. His experience tracking the impact of digital transformation—from cable TV to smartphones—demonstrates that modern global events are rarely localized, having profound, varied ripple effects across different economies and societies. For policy strategists, this implies a critical need to move beyond national silos, adopting a holistic view that accounts for how global power dynamics (e.g., energy conflicts) disproportionately affect disparate regions. Furthermore, the rapid proliferation of affordable technology must be factored into policy planning, as it fundamentally alters political structures and social harmony in developing nations.
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The U.S. must strategically leverage advanced technologies like AI and quantum computing to maintain scientific leadership and national competitiveness. The federal government is pursuing initiatives, such as the Genesis Mission, to accelerate scientific discovery and solidify American technological advantage. This effort requires significant federal investment and a focus on translating basic research into practical, mission-critical applications. Policymakers must therefore balance aggressive domestic development with strategic global collaboration to secure scientific and economic superiority in the coming decades.
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9.Evaluating Large Language Models' Abilities to Process and Understand Technical Policy Reports (RAND)
This RAND report details the development of a specialized benchmark to accurately evaluate Large Language Models (LLMs) on complex, technical policy reports. The authors found that standard LLMs perform poorly (48-54% accuracy) on nuanced policy claims, demonstrating that out-of-the-box solutions are insufficient for high-stakes decision support. To improve reliability, the report recommends moving beyond binary truth assessments, utilizing multi-category truthfulness metrics to capture partial inaccuracies and inferred reasoning. Strategically, while LLMs hold promise for synthesizing policy findings and identifying evidence gaps, their deployment requires significant domain-specific fine-tuning and rigorous testing before they can be trusted by public decision-makers.
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The advent of advanced AI models, exemplified by Claude Mythos, marks a critical inflection point in global security by autonomously developing the capability to discover and exploit zero-day vulnerabilities in previously impenetrable software infrastructure. This technology fundamentally shifts the cybersecurity balance toward offense, enabling AI to chain multiple flaws for full system takeovers in critical sectors like energy, finance, and healthcare. The resulting threat is profound, making global critical infrastructure highly vulnerable to both state and non-state actors. Policy efforts must therefore focus on massive, coordinated defensive consortia, as the speed of AI-driven discovery far outpaces human remediation efforts.
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AI adoption is a bipartisan priority within the federal government, showing significant growth in reported use cases across various agencies. However, the report finds that adoption remains uneven, heavily concentrated in large agencies, and is significantly constrained by structural bottlenecks. Key challenges include workforce capacity limitations, a risk-averse culture, and systemic issues in procurement and funding. To accelerate responsible deployment, policy must focus on expanding technical talent and AI literacy, streamlining outdated acquisition processes, and enhancing transparency to build public trust in high-impact AI systems.
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12.Simpler Is Better for Autograders: Toward Cost-Effective LLM Evaluations for Open-Ended Tasks (RAND)
This RAND report addresses the bottleneck of evaluating large language models (LLMs) in open-ended tasks, which is typically constrained by the high cost and slow speed of expert human grading. The analysis tested five autograding methods and found that the simple 'single rubric' approach consistently outperformed complex techniques like metaprompting or prompt optimization. This method achieves a statistically significant reduction in error while matching or exceeding the accuracy of nonexpert human graders, but at a fraction of the time and cost. Policymakers should adopt single-rubric autograders as the default, scalable solution to enable cost-effective and reliable LLM evaluation across diverse domains.
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China's high-tech drive has resulted in undeniable, though uneven, progress, significantly boosting its global innovation capacity and international influence. Key evidence includes China's rising Global Innovation Index ranking, surpassing the U.S. in R&D spending, and becoming a core leader in setting global mobile broadband standards. However, the analysis notes persistent weaknesses in institutional quality, advanced semiconductors, and complex manufacturing sectors like commercial aircraft. Strategically, the report advises that the U.S. should abandon a policy of consistent decoupling in favor of "calibrated coupling," while simultaneously strengthening coordination with like-minded global partners to maximize national security and economic benefits.
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Global AI governance is rapidly maturing, with major economies establishing comprehensive national standards for AI deployment across critical sectors. China is spearheading this effort by releasing detailed standards for humanoid robots and integrating AI across its entire economic plan, while regional players like Singapore and Vietnam are updating guidelines for use in healthcare and education. Strategically, the focus is shifting to energy infrastructure, with India and Australia mandating energy storage and setting strict standards for data centers. These developments signal that technological advancement is no longer sector-specific but is inextricably linked to mandatory grid modernization and sustainable power sources.
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Russia employs 'cyber proxies'—criminal groups, hacktivists, and private entities with varying degrees of state direction—to conduct disruptive cyberattacks against Ukraine while maintaining plausible deniability and complicating attribution. This proxy model shields the Russian state from sanctions while making coordinated response difficult. Chatham House proposes a strategic approach integrating international and domestic law with cost-imposition and disruption tactics to establish deterrence against cyber proxies of any origin, replacing ad-hoc tactical responses with comprehensive, enabling policies.
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Jessica Brandt's career evolution—from CFR researcher to Director of ODNI's Foreign Malign Influence Center—illustrates how technology has become a central domain of US geopolitical competition. Her work focused on foreign information warfare and technology-enabled asymmetric competition between democracies and authoritarian regimes, particularly through social media platforms and election interference. Brandt's trajectory demonstrates that technology is now inseparable from traditional foreign policy concerns, requiring practitioners with hybrid expertise spanning government, think tanks, and civil society. She emphasizes that emerging tech policy challenges require adaptability, as issues like AI and digital influence operations present novel problems that outpace traditional policy frameworks. Her advice to younger policymakers highlights the importance of technological literacy and willingness to pivot toward emerging national security threats in 21st-century foreign policy.
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AI-enabled technologies are set to transform crop breeding by accelerating the development of more resilient, higher-yielding, and nutritious crops essential for global food security. These advancements improve data management, enhance data collection and analysis, and provide novel genomic tools, addressing increasing food demand and ecological pressures. However, challenges such as unequal access to AI tools and genetic data, particularly in the Global South, and the need for aligned regulatory frameworks could hinder progress. To leverage AI's full potential, policymakers must support foundational sciences, build institutional capacity, establish coherent regulations, and promote global collaboration to ensure equitable deployment and long-term benefits for food systems.
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Chatham House organized a policy hackathon where 22 young people developed creative proposals for responsible AI adoption in government. Participants created innovative solutions including 'Guardian Angel,' a security-focused AI system analyzing employee access patterns, alongside ideas for AI-enabled health intelligence platforms and trade-risk detection systems. The exercise highlighted the significant complexity governments face in scaling emerging technologies while balancing transparency, democracy, security, sovereignty, and cost-effectiveness—a critical challenge for policymakers globally.
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The CSIS report, "Golden Insights: High-Quality Products Derived from Commercial Earth Observations," emphasizes a critical market transition from raw Earth observation data to sophisticated, derived insights. This shift is driven by increased multi-source remote sensing data and advanced AI tools, which facilitate the rapid and scalable extraction of valuable information. The report outlines key factors for product value, customer buying centers, and evaluation metrics, aiming to establish a common language for producers and consumers. This initiative is designed to enhance customer satisfaction and accelerate growth across the commercial Earth observation sector, enabling diverse industries to leverage decision-ready products for improved market readiness and revenue.
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The Kremlin is implementing widespread internet blackouts and censorship, extending to major cities like Moscow and St. Petersburg, to tighten its grip on Russia's digital space, citing security and national control. These measures include banning popular social media and messaging apps while promoting state-controlled alternatives, impacting daily life and suppressing protests for internet freedom. The shutdowns have caused significant economic disruption, costing local businesses millions daily and threatening small and medium-sized enterprises with bankruptcy. This aggressive digital control strategy reflects the regime's growing anxieties and will likely test the public's tolerance and potential for dissent.
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The CSIS 'Trendlines March 2026 Newsletter' asserts that the global AI race is evolving beyond mere model breakthroughs and compute performance. It highlights that structural trends in global energy systems are converging with changes in capital markets, industrial policy, and technology diffusion, becoming crucial determinants for future AI leadership. The newsletter aims to provide data-driven insights to help decision-makers distinguish credible hypotheses from hype by connecting various research areas within CSIS. For policy and strategy, this suggests an imperative to consider the integrated impact of energy, economic, and industrial factors when addressing the future of AI.
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22.Internet Cutoff Switches as a Local Emergency Response for Damaging Artificial Intelligence Incidents (RAND)
This RAND report examines internet cutoff switches as emergency containment tools for damaging AI incidents in data centers. The analysis reveals a critical market failure: without liability for external damages, data center operators would rationally delay activating cutoffs to preserve revenue, even as AI escape risk grows exponentially. The authors conclude that three policy mechanisms are essential: assigning operators liability for catastrophic external damages, ensuring they understand cutoff use provides liability protection, and potentially compensating lost revenue to align private profit incentives with public risk management.
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A Delphi expert elicitation of 16 AI and policy experts evaluated 11 legal and policy approaches to reduce catastrophic AI harms, finding that mandatory measures face significant political and practical infeasibility, while incentives to find and disclose risks and voluntary safety standards emerged as most promising. Experts rated nearly all categories as desirable but questioned feasibility in the current U.S. political environment, with effectiveness varying substantially by actor type—highest for AI developers (3.3 average), lower for nonmalicious users (3.0), and lowest for malicious users (2.3). The most viable approaches require no federal government involvement and can be implemented through industry commitments and state-level action, including structured bug bounty programs, legal safe harbors for researchers, and coordinated vulnerability disclosure processes. Rather than waiting for comprehensive federal legislation, policymakers should pursue incremental, near-term measures that foster transparency through developer incentives and establish voluntary standards as scaffolding for future mandatory requirements. The analysis reflects growing skepticism about traditional regulatory approaches in the AI domain, with experts increasingly viewing private-sector and state-level action as more feasible pathways for near-term risk mitigation.
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24.Artificial General Intelligence Forecasting and Scenario Analysis: State of the Field, Methodological Gaps, and Strategic Implications (RAND)
The report synthesizes diverse AGI forecasting methodologies and finds that multiple independent approaches—expert surveys, prediction markets, and compute-centric models—show convergent evidence toward earlier AGI timelines, with many clustering in the 2030s, driven by rapid scaling of compute resources and capital investment. However, forecasting infrastructure remains immature with significant limitations: benchmarks saturate quickly, influential models lack independent validation, and reasonable experts fundamentally disagree about whether scaling existing architectures will suffice, how rapidly capabilities will diffuse economically, and whether AI-driven research acceleration will compress timelines. The report identifies three core empirical cruxes—capability sufficiency, diffusion speed, and takeoff dynamics—that generate distinct expert positions, with disagreement persisting despite shared information. Rather than betting on specific timelines, decisionmakers should pursue scenario-robust strategies emphasizing technical expertise, evaluation infrastructure, and monitoring systems while keying different policy responses to observable triggers across domains. Strengthening forecasting through independent model validation, continuous capability measurement, and real-time monitoring of AI's role in research advancement would better position policymakers to manage uncertainty across the range of plausible futures.
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The article argues that the private technology sector often misunderstands the complex, geopolitical drivers of national security spending. It uses the historical example of the 1993 'Last Supper' to demonstrate that the end of the Cold War immediately triggered budget cuts and consolidation pressures on the defense industry. This suggests that national security planning cannot be based solely on technological advancement or market demand. Instead, policy must account for major geopolitical shifts, which fundamentally dictate defense funding and industrial structure, often overriding private sector assumptions.
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The article argues that global fiber-optic cables, which carry 99% of transoceanic digital traffic, have become critical, yet highly vulnerable, arteries of modern power. While these cables underpin global finance, diplomacy, and military communications, the seabed has transformed into an arena of great-power competition, sabotage, and surveillance. As risks escalate and trust erodes, the infrastructure that powers the global economy is increasingly contested. Policymakers must therefore reassess the security and resilience of these vital digital lifelines to mitigate geopolitical risks and maintain global connectivity.