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Smart power reframes influence: states and non‑state actors now marry coercion and attraction into a legitimacy‑based strategic model, using diplomacy, development and digital technologies — especially AI — to shape global economic and political orders. This shifts economic levers (trade, investment, standards, industrial policy) and raises coordination, market-structure and distributional risks for global AI ecosystems.
n/a theoretical Full text openalex
Smart Power and the Transformation of Contemporary International Relations: Connecting Coercion and Persuasion in Global Politics · Johnson Kayode Ayeni, Agaba Halidu · Mar 07, 2026
Federated advertising architectures can preserve much of targeted personalization while cutting centralized data custody risks, but doing so requires cryptographic aggregation, calibrated differential privacy, algorithmic fixes for non‑IID and delayed feedback, and explicit cross‑party governance; without these measures, performance, fairness and security trade‑offs remain substantial.
low theoretical Summary openalex
Privacy-Aware AI Advertising Systems: A Federated Learning Framework for Cross-Platform Personalization · Ethan Caldwell, Sofia Bennett · Mar 07, 2026
Treating privacy as a commodity produces distinctive harms that prices can’t fix: markets for personal data enable exploitation, erode autonomy and concentrate platform power, so policymakers should restrict or redesign data markets rather than simply 'fill' a missing market.
n/a theoretical Full text openalex
Data and privacy: Putting markets in (their) place · Reetika Khera · Mar 07, 2026
A traceable, compliance-ready curriculum framework promises better alignment between qualifications and labor-market needs and richer datasets for measurement and AI tooling; its benefits, however, come with high upfront costs, continuous audit burdens, and risks of concentrating advantages among well-resourced providers.
low descriptive Full text openalex
Curriculum engineering: organisation, orientation, and management volume 8 · tshingombe tshitadi, tshingombe tshitadi · Mar 07, 2026
Fragmented vocational certification and administrative backlogs in South Africa are obstructing artisans’ career progression to engineering roles; migrating records to cloud repositories and adding automated compliance checks could restore credential continuity and unlock data for AI-driven matching and upskilling—but rural infrastructure gaps and governance risks could limit benefits.
low descriptive Full text openalex
<i>Electrotechnical education, institutional compliance, and engineering career progression in Southern Africa</i> · tshingombe tshitadi, tshingombe tshitadi · Mar 07, 2026
THETA uses LoRA-tuned hybrid embeddings and a structured human-in-the-loop agent workflow to extract more coherent, domain-aware topics from massive social-text corpora than conventional topic models, enabling scalable, auditable narrative and policy analysis for economists and regulators.
medium descriptive Full text arxiv
THETA: A Textual Hybrid Embedding-based Topic Analysis Framework and AI Scientist Agent for Scalable Computational Social Science · Zhenke Duan, Xin Li · Mar 06, 2026
Introducing AI into design workflows is not just a productivity upgrade but a reconfiguration of responsibility and power: UX designers weigh efficiency against skill, autonomy and trust, and outcomes hinge on team norms and organizational governance. Adoption therefore redistributes who benefits and who bears accountability, with implications for incentives, human capital and firm policy.
low descriptive Full text arxiv
The Values of Value in AI Adoption: Rethinking Efficiency in UX Designers' Workplaces · Inha Cha, Catherine Wieczorek, Richmond Y. Wong · Mar 06, 2026
A lightweight 'FutureBoosting' pipeline that uses a frozen time‑series foundation model to generate forecasted features and feeds them into an interpretable regressor cuts electricity price forecasting MAE by more than 30% across multiple markets. The approach is plug‑and‑play, computationally modest, and retains model interpretability, making it attractive for market participants seeking better bids and risk management.
medium descriptive Full text arxiv
Regression Models Meet Foundation Models: A Hybrid-AI Approach to Practical Electricity Price Forecasting · Yunzhong Qiu, Binzhu Li, Hao Wei, Shenglin Weng, Chen Wang, Zhongyi Pei, Mingshe... · Mar 06, 2026
Task-level approaches reveal that low-skilled tasks face the largest displacement risk while high-skilled work is more likely to be augmented, but much of the literature rests on static, pre-2020 mappings and limited causal evidence that rapid LLM advances have already outpaced.
n/a review_meta Summary openalex
Recent Methodologies on AI and Labour - a Desk Review · Elena Papagiannaki, Joana Geisler · Mar 06, 2026
AI tools speed routine coding and prototyping at Netlight but create errors, context gaps and integration costs that increase the value of human supervision and orchestration. Firms that build effective orchestration and tooling layers — and hire for system-design and coordination skills — are likely to capture disproportionate productivity gains.
low descriptive Summary openalex
Rethinking How IT Professionals Build IT Products with Artificial Intelligence · Florian J. Meier, Florian Gatzlaff, Sven Laumer · Mar 06, 2026
Data‑driven HRM strengthens workforce resilience and operational performance by improving talent matching, forecasting turnover, and enabling real‑time monitoring; however, privacy, algorithmic bias and capability gaps limit adoption and leave causal long‑term impacts on employment and wages unresolved.
medium review_meta Full text openalex
Data-Driven Strategies in Human Resource Management: The Role of Information Science in Workforce Resilience – A Systematic Review · Stephen Taduvana, Thubelihle Moyo, Rhinos Kombedzai · Mar 06, 2026
Children bear outsized risks from antimicrobial resistance, climate change and emerging zoonoses because immaturity, behaviour and ecosystem dependence concentrate exposure; yet One Health surveillance and policy remain fragmented and adult‑centric. Building integrated, child‑labelled datasets and equity‑aware AI/economic models—with targeted governance reforms—will improve forecasting and resource allocation, particularly in low‑ and middle‑income countries.
low review_meta Full text openalex
Safeguarding future generations: a One Health perspective on children, climate change, and infectious threats · Marco Masetti, Francesca Lato, Martina Menoni, Susanna Esposito · Mar 06, 2026
China pursues centralized, state‑led data governance to mobilize large, sovereign data projects; the United States relies on decentralized, rights‑based institutions emphasizing transparency and accountability. Rather than strict opposites, openness and security are treated as layered, adaptable governance processes with distinct implications for data access, innovation and competition.
low descriptive Full text openalex
Balancing openness and security in scientific data governance: Institutional logics in China and the United States · Ling Chen, Lianjian Deng · Mar 06, 2026
Cities more exposed to AI cut energy intensity: a one-standard-deviation rise in AI exposure increases regional total factor energy efficiency by roughly 3.2%, driven by shifts toward 'green' jobs and skills and amplified where environmental rules and digital networks are strong.
medium quasi_experimental Full text openalex
Artificial intelligence, greening of occupational structure and total factor energy efficiency · Tianren Li, Yao Hu, Jiachao Peng, Fushun Zhang · Mar 06, 2026
AI has transformed ad personalization from a prediction problem into platform infrastructure: who controls data, identity, and governance—not just model accuracy—now determines rents, welfare impacts and market structure. Durable, welfare-aligned personalization will require interpretable models, privacy-by-design, causal impact measurement and new audit/regulatory regimes.
n/a review_meta Full text openalex
Artificial Intelligence for Personalized Digital Advertising: Methods and Applications · Ethan J. Mercer, Daniel R. Holloway · Mar 06, 2026
Telling customers a chatbot is AI and adopting an empathetic, personalized tone boosts trust and lifts purchase intent among UAE youth. Perceived manipulation cuts conversion, but higher digital literacy blunts that harm, suggesting transparency and explainable personalization are pro-competitive and pro-consumer.
medium rct Full text openalex
AI Chatbots as Informatics-Enabled Marketing Service Systems: Trust, Transparency, and Youth User Responses · · Mar 06, 2026
A governed hyperautomation pattern—combining low-code, RPA and generative AI with embedded policy, human‑in‑the‑loop checks and continuous monitoring—lets firms scale automation without sacrificing compliance or stability; the approach raises upfront governance costs but can lower risk‑adjusted total cost of ownership and reshape labor demand toward oversight and AI‑engineering roles.
low descriptive Full text openalex
Governed Hyperautomation for CRM and ERP: A Reference Pattern for Safe Low-Code, RPA, and Generative AI at Enterprise Scale · Siva Prasad Sunkara · Mar 06, 2026
AI and green technology are the new engines of creative destruction, reshaping productivity and competitive hierarchies; how much they raise broad prosperity depends on long-wave cycles, supply-chain fragilities and political‑economic forces that determine diffusion, market structure and distributional outcomes.
low theoretical Full text openalex
Economic Waves, Crises and Profitability Dynamics of Enterprises: A Review in the Context of Kondratieff, Schumpeter and Mandel Approaches · Banu HAS, Fatih Koç, Sinan ÇINAR · Mar 06, 2026
A dynamic, task-based AI exposure architecture would modernize BLS labor projections by mapping LLM-driven capabilities to occupations and combining real-time signals with causal inference to forecast displacement, augmentation, and skill transitions; its success depends on data access, robust LLM validation, and careful backtesting.
n/a descriptive Summary openalex
Enhancing BLS Methodologies for Projecting AI's Impact on Employment: A Data-Driven Framework for Measuring Labor Market Transformation · Satyadhar Joshi · Mar 06, 2026
Climate AI is being built on Northern compute and data, producing systematically weaker and potentially misleading outputs for vulnerable, data-sparse regions; public investment in shared data, distributed compute, and co-produced evaluation is needed to prevent costly maladaptation and entrenched informational inequality.
low review_meta Full text arxiv
The Rise of AI in Weather and Climate Information and its Impact on Global Inequality · Amirpasha Mozaffari, Amanda Duarte, Lina Teckentrup, Stefano Materia, Gina E. C.... · Mar 05, 2026
The shape of compute pipelines determines whether decentralised pricing works: hierarchical service graphs converge to stable, optimal allocations, but cross-cutting dependencies cause price oscillations and poor allocation quality; wrapping complex subgraphs into integrator 'resource slices' cuts price volatility by roughly 70–75% while preserving throughput.
medium theoretical Full text arxiv
Real-Time AI Service Economy: A Framework for Agentic Computing Across the Continuum · Lauri Lovén, Alaa Saleh, Reza Farahani, Ilir Murturi, Miguel Bordallo López, Pra... · Mar 05, 2026
Current extrapolation‑based labor projections miss AI’s nonlinear, spillover, and augmentation effects; a task‑level, LLM‑enabled Occupational AI Exposure Score integrated with real‑time data and causal inference would give policymakers earlier, more precise forecasts of displacement and reallocation risks.
n/a descriptive Summary openalex
Enhancing BLS Methodologies for Projecting AI's Impact on Employment: A Data-Driven Framework for Measuring Labor Market Transformation · Satyadhar Joshi · Mar 05, 2026
Language-model agents that perceive, deliberate and act reproduce human-like adaptive behavior in epidemic–economic simulations, producing divergent health and economic trajectories and enabling quantitative trade-off analysis; the framework is robust across several LLMs but requires empirical calibration before real-world policy use.
low descriptive Summary openalex
An LLM-Driven Multi-Agent Simulation Framework for Coupled Epidemic–Economic Dynamics · S. Wang, Huiyong Liu, Na Wang, Qunsheng Yang · Mar 05, 2026
A practical blueprint for reversible AI leadership: the Dynamic Authority Reversal framework turns human oversight into a measurable, auditable, and testable process—enabling controlled AI-led decisions while preserving accountability through hysteresis, safe-exit timers and a Reversal Register.
n/a theoretical Summary openalex
Human–AI Handovers: A Dynamic Authority Reversal Framework for Trust Calibration and Transitional Accountability · Jonathan H. Westover · Mar 05, 2026
Agentic AI makes alignment an ongoing organizational cost: systems that generate open-ended actions, novel outputs, and evolving goals turn coordination into a continuous process of projection, monitoring and renegotiation rather than a one-off specification task; firms that can cheaply sustain persistent alignment gain a competitive edge.
n/a theoretical Full text openalex
Visioning Human-Agentic AI Teaming: Continuity, Tension, and Future Research · Bowen Lou, Tian Lu, T. S. Raghu, Yingjie Zhang · Mar 05, 2026