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Simulations of small edge-AI populations show that smarter, diverse agents can make shared-resource congestion worse when capacity per device is low, while the same sophistication improves outcomes when capacity is ample; the capacity-to-population ratio C/N predicts which regime a deployment will fall into.
medium quasi_experimental Full text arxiv
Increasing intelligence in AI agents can worsen collective outcomes · Neil F. Johnson · Mar 12, 2026
Clinical AI works in Indonesian hospitals but flounders outside them: promising diagnostic and telemedicine results are undermined by patchy broadband, fragmented regulation and limited workforce readiness, risking foreign vendor dependence and lost economic gains unless coordinated policy and investment follow.
medium review_meta Full text semantic_scholar
Artificial Intelligence in Healthcare in Indonesia: Are We Ready to Race for Golden Indonesia 2045? · Wayan Sadwika · Fetched Mar 12, 2026
Open-source AI offers transparency, customization and privacy advantages while proprietary systems dominate on reliability and vendor support; policymakers should adopt a hybrid, tiered governance and certification regime to capture complementary benefits without entrenching inequities or market concentration.
n/a review_meta Full text semantic_scholar
Framework for Government Policy on Agentic and Generative AI in Healthcare: Governance, Regulation, and Risk Management of Open-Source and Proprietary Models · Satyadhar Joshi · Fetched Mar 12, 2026
Synthetic patient data can lower barriers to building clinical AI in Africa, but only when paired with real local data and robust governance; without hybrid training, domain adaptation, and stronger validation infrastructure, fidelity gaps risk biased care and wasted investment.
medium review_meta Summary semantic_scholar
On the use of synthetic data for healthcare AI in Africa: Technical performance, governance challenges, and policy readiness · Ally Nyamawe, D. Shao · Fetched Mar 12, 2026
An AI-powered Skill Gap Intelligence Hub can probabilistically forecast where and which skills will be in shortage, spotlighting regional opportunity hubs and quantifying how automation and policy choices reshape future workforce readiness; however, its usefulness hinges on data quality and transparent validation.
low descriptive Full text semantic_scholar
AI-Based Predictive Skill Gap Analysis for Workforce Planning · Jacob Tom, J.Noor Ahamed · Fetched Mar 12, 2026
Indonesia promotes mobile-AI as an engine of growth while relying on soft‑law ethics and guidelines; that mismatch leaves low‑wage, rural and otherwise marginalised groups disproportionately exposed and undermines equitable economic outcomes.
low descriptive Full text semantic_scholar
Promising Protection, Producing Exposure: AI Ethics and Mobile Communication Regulation in Indonesia · Rustini Floranita, Diamitra Darius, Irwansyah Irwansyah · Fetched Mar 12, 2026
Generative web-search and reasoning models deployed in 2025 impose substantially higher cumulative environmental costs even as reporting declines; existing rules—focused on facilities and training—miss model-level and inference emissions. The paper recommends mandatory model-level energy disclosures, consumer opt-outs, and coordinated international reforms, with concrete amendments proposed for EU laws to operationalize these changes.
medium review_meta Full text semantic_scholar
The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI · Kai Ebert, Boris Gamazaychikov, Philipp Hacker, Sasha Luccioni · Fetched Mar 12, 2026
AI is already boosting productivity across multiple sectors but also amplifies bias, privacy and distributional risks; tailored, ethics‑based governance—from standards and sandboxes to workforce training and competition policy—is required to preserve innovation while protecting fairness and accountability.
low descriptive Full text semantic_scholar
AI Governance and Data Privacy: Comparative Analysis of U.S., EU and African Frameworks · Oyeyemi Akinrele · Fetched Mar 12, 2026
The Pentagon's new AI memo speeds procurement by turning oversight into an exception: expanded waiver powers and vague standards, combined with a shrinking acquisition workforce, raise the odds of unsafe or unvetted AI deployments and shift legal and operational risk onto the government.
low commentary Summary semantic_scholar
FEATURE COMMENT: Governance as a "Blocker": How the Pentagon's New AI Strategy Trades Oversight for Speed · Jessica Tillipman · Fetched Mar 12, 2026
U.S. AI policy is fragmented and in flux: export controls coexist with a permissive domestic stance while worker-protection initiatives falter, increasing legal uncertainty that will shape where and how firms adopt AI and likely strengthen employer bargaining power.
n/a commentary Full text semantic_scholar
AI governance under the second Trump administration: implications for labour · Catriona Gray · Fetched Mar 12, 2026
Common AI tools in research workflows are shrinking researcher control and raising ethical costs, particularly in lower‑capacity jurisdictions; policymakers should prioritize data‑sovereignty, procurement rules and public research infrastructure to rebalance power and lower hidden transaction costs.
low descriptive Summary semantic_scholar
Emerging ethical duties in AI-mediated research: A case of data sovereignty in applying cross-national regulation. · Ricardo A. Ayala, P. Hervé-Fernández · Fetched Mar 12, 2026
Russia’s extractive industries trail the US, China and EU in AI investment and digitalization; the shortfall is structural — fragmented data access, talent shortages, weak infrastructure and institutional failures, not just low spending, are blocking scaling and call for coordinated institutional reforms.
medium descriptive Summary semantic_scholar
ADOPTION OF ARTIFICIAL INTELLIGENCE IN THE RUSSIAN EXTRACTIVE INDUSTRY: ANALYSIS OF BARRIERS AND INSTITUTIONAL CONSTRAINTS · Danil S. Krasovskikh, Diana Yu. Boboshko · Fetched Mar 12, 2026
On-premise RAG is a viable alternative for SMEs: it matches cloud RAG on accuracy, delivers more contextually useful answers in specialized manufacturing, and converts recurring API fees into fixed costs—but requires upfront capex, technical staff, and accepts higher latency.
medium descriptive Summary semantic_scholar
An Empirical Study on the Feasibility Analysis of On-Premise RAG for AI Diffusion in Manufacturing · Jaeseok You, Ahreum Hong · Fetched Mar 12, 2026
Big Data and AI can make governments proactive rather than reactive, improving resource allocation where institutions, infrastructure and trust exist. But adoption is uneven: realizing economic and social returns depends on interoperable, ethical‑by‑design platforms, sustained investment in skills and governance, and stronger accountability mechanisms.
medium review_meta Full text semantic_scholar
Models, applications, and limitations of the responsible adoption of big data and artificial intelligence in public policy · José David Vallejo Manzur, E. L. Álvarez-Aros · Fetched Mar 12, 2026
AI can materially raise productivity and enable new services for SMEs in developing economies, but adoption in places like Botswana is held back by skills shortages, poor infrastructure, financing gaps and weak data governance. Policymakers should pair phased, firm-level capability building with ecosystem financing and pragmatic data rules to make benefits broad and inclusive.
low review_meta Full text semantic_scholar
Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies · J. Holland · Fetched Mar 12, 2026
AI systems reliably perform narrow clinical tasks and speed routine workflows, but physicians remain indispensable: near-term automation will reallocate tasks rather than replace clinicians, with regulatory, robustness, and liability hurdles slowing widespread substitution.
medium review_meta Summary semantic_scholar
Will AI Replace Physicians in the Near Future? AI Adoption Barriers in Medicine · R. Obuchowicz, Adam Piórkowski, Karolina Nurzyńska, B. Obuchowicz, Michał Strzel... · Fetched Mar 12, 2026
AI and digital investments can speed up government services and improve targeting, but benefits rarely materialize at scale without fixing infrastructure, skills and institutional incentives. Lasting public‑sector productivity gains depend as much on procurement, interoperability and governance reforms as on the technology itself.
low review_meta Full text semantic_scholar
Digital Transformation and AI Adoption in Government: Evaluating the Productivity Gains, Implementation Barriers, and Governance Risks · Kofi Asante Aninakwah · Fetched Mar 12, 2026
When wages are lognormal, tiny skill or AI upgrades pay off exponentially at the top, prompting costly arms races in education and AI deployment; such overinvestment lifts GDP and widens inequality but can leave society worse off as private costs outweigh social gains.
n/a theoretical Full text semantic_scholar
Janus-Faced Technological Progress and the Arms Race in the Education of Humans and Chatbots · Wolfgang Kuhle · Fetched Mar 12, 2026
AI adoption reallocates work and concentrates wage gains: routine cognitive jobs fall 2.3% per standard-deviation in adoption while complex problem-solving and interpersonal roles rise 1.8%. Wage gains accrue to the top quintile (+3.8%) as middle‑income wages slip (−1.4%), though countries with robust ALMPs and portable benefits experience much smoother transitions.
medium quasi_experimental Summary semantic_scholar
Artificial Intelligence and Labor Market Transformation: Employment Effects, Wage Inequality, and Policy Responses in the Era of Generative AI · A. T. D. · Fetched Mar 12, 2026
A machine‑learning system is reported to raise retained food after harvest by 3.42% on Indian farms at no extra cost and claims near‑perfect prediction (R²=0.999); however, opaque data provenance and absent out‑of‑sample or field validation make the result fragile and potentially misleading.
low correlational Summary semantic_scholar
AI in food inequality: Leveraging artificial intelligence to predict food waste in agriculture and post-harvesting · Akshit Erukulla, Swanish Baweja, Amol Sriprasadh, A. Paul, Aaron Sethi · Fetched Mar 12, 2026
Foreign direct investment can boost jobs and productivity in Sub‑Saharan Africa, but gains are uneven: when FDI is concentrated in extractive or capital‑intensive activities or when institutions and skills are weak, it often produces enclave growth and widens wage inequality; whether AI embodied in foreign investment helps or harms depends critically on sector, absorptive capacity and policy design.
medium review_meta Full text semantic_scholar
Foreign Direct Investment, Labor Markets, and Income Distribution in Sub-Saharan Africa: A Conceptual Review · Isaac Armah, Patience Yamoah · Fetched Mar 12, 2026
AI that lowers coordination costs lets managers supervise more workers, boosting output and compressing hierarchies while widening manager–worker pay gaps; whether gains are shared or concentrated into superstars hinges on who captures the coordination rents.
n/a theoretical Full text semantic_scholar
AI as Coordination-Compressing Capital: Task Reallocation, Organizational Redesign, and the Regime Fork · Alex Farach · Fetched Mar 12, 2026
Calibrated dynamics for China suggest AI capital spurs both investment and wages: AI drives physical-capital accumulation and boosts the wage bill, while feedback from capital and labor onto AI is weak; equilibria are stable rather than cyclic.
low theoretical Full text semantic_scholar
Governance of Technological Transition: A Predator-Prey Analysis of AI Capital in China's Economy and Its Policy Implications · Kunpeng Wang, Jiahui Hu · Fetched Mar 12, 2026
Managers and school administrators who trust AI make quicker, more evidence-aligned decisions and run more data-driven organizations; building trust through transparency, reliability demonstrations and training appears to unlock measurable managerial and institutional performance gains.
low correlational Full text semantic_scholar
Algorithmic Trust and Managerial Effectiveness: The Role of AI-Driven Decision Culture in Digital Organizations and Educational Institutions · Kunal Samanta, S. Singh · Fetched Mar 12, 2026
A cross-model audit of 70+ LLMs on ~26,000 real queries finds outputs have become strikingly similar, creating an 'Artificial Hivemind' that erodes stylistic and cognitive diversity; firms must invest in governance, process redesign and multi-model strategies to avoid correlated errors and loss of creative value.
medium descriptive Summary semantic_scholar
The Artificial Hivemind: Rethinking Work Design and Leadership in the Age of Homogenized AI · Jonathan H. Westover · Fetched Mar 12, 2026