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Re-evaluating EVMbench finds AI agents fall short of replacing human auditors: expanded, contamination-free tests show unstable rankings, scaffold sensitivity and no end-to-end exploit success on post-release incidents, implying AI is best used for breadth and triage within human-in-the-loop workflows.
high descriptive Full text arxiv
Re-Evaluating EVMBench: Are AI Agents Ready for Smart Contract Security? · Chaoyuan Peng, Lei Wu, Yajin Zhou · Mar 11, 2026
A new philosophical framework argues that neurotechnology and AI risk expanding capabilities while hollowing out lived experience unless designers prioritize 'temporal quality'; XChronos offers symbolic units to bridge first‑person temporality with neural readouts and to shape product, regulatory and valuation choices.
n/a theoretical Summary openalex
XChronos and Conscious Transhumanism: A Philosophical Framework for Integrating Consciousness, Subjective Time, and Neurotechnology · JACONAAZAR SOUZA SILVA · Mar 11, 2026
Ibero‑American SMEs are likely to capture value from AI only when strategy, leadership, sensing and institutional links align; targeted managerial training, sensing subsidies and intermediary networks raise adoption and returns. The paper provides a structured framework—and eight testable propositions—for economists and policymakers to model diffusion, complementarities and heterogeneous returns among resource‑constrained firms.
n/a review_meta Summary openalex
Beyond resource constraints: how Ibero-American SMEs leverage AI for competitive advantage through strategic capability development · Martin Sposato, Eduardo Carlos Dittmar · Mar 11, 2026
Academic ML intrusion-detection systems for IoT often report high detection rates in lab settings but rarely become production-ready. Heterogeneous devices, constrained compute/energy, dataset shortcomings and ML pipeline failures raise deployment costs and create commercial opportunities for firms that deliver lightweight, privacy-preserving, and operationally robust IDS solutions.
n/a review_meta Full text openalex
International Journal on Cybernetics & Informatics · Vishal Karanam · Mar 11, 2026
AI-powered digital finance platforms expand access and cut costs in emerging markets, lifting efficiency and growth prospects; but without interoperable infrastructure and updated regulation they risk consumer harm, market concentration and systemic fragility.
n/a review_meta Full text openalex
DIGITAL FINANCIAL ECOSYSTEMS AND FINANCIAL INCLUSION: AN INTEGRATED FRAMEWORK FOR SUSTAINABLE ECONOMIC GROWTH · Saydkhodjaeva Nigorakhon Ibaydullayevna · Mar 11, 2026
National‑security concerns yield three contrasting AI regimes: the EU enforces rights‑forward, risk‑based rules; Algeria pursues capacity and independence; Pakistan prioritizes economic governance while leaving military AI largely opaque. These regulatory gaps threaten market fragmentation, complicate export controls and procurement transparency, and heighten dual‑use risks.
low descriptive Full text openalex
<b>Regulating AI in National Security: A Comparative Study of European, Algerian, and   Pakistani Approaches</b> · Ehsanullah Khan, Syed Rizwan Haider Bukhari, Tourkia Rebhi · Mar 11, 2026
The EU's Digital Omnibus could either deepen regulatory fragmentation or unlock harmonized rules for platform AI — much depends on design and institutional coordination; unclear boundaries with the DSA risk higher compliance costs and uneven enforcement that favor large incumbents.
low commentary Full text openalex
The Digital Omnibus and the Future of EU Regulation: Implications for Policy Coherence and Enforcement · Alejandro Flores Moleon · Mar 11, 2026
Firms that invest in AI-skilled staff achieve measurably better tax planning and modest gains in after-tax returns; the benefits concentrate in complex organizations and where tax teams have strategic influence.
medium quasi_experimental Full text openalex
The use of artificial intelligence in decision-making: evidence from the effectiveness of corporate tax strategies · Trent Krupa, Michele Mullaney · Mar 11, 2026
A reinforcement‑learning agent trained on the FRB/US macro model discovers fiscal strategies that raise simulated US GDP and lower unemployment across 2000–2024 versus standard FRB/US scenarios, but the improvements are earned inside the assumptions of the model and a growth‑focused objective.
low theoretical Full text openalex
Fiscal Policy Towards Optimizing Macroeconomic Indicators by Integrating FRB/US with Reinforcement Learning · Quang Truong Dang, Huong Giang Hoang, Anh Son Ta · Mar 11, 2026
As AI takes over routine speed and pattern-matching, success should be redefined around distinctly human capacities—empathy, judgement and imagination—which firms should cultivate and reward rather than measured productivity alone.
n/a theoretical Summary openalex
Deconstructing success: why being human still matters · Andrew Woods, Benton Jones · Mar 11, 2026
Higher education has ballooned while vocational and lifelong learning lag, creating a shortage of intermediate, work-based skills needed for effective AI adoption; without stronger vocational pathways and targeted adult training, older and lower‑skilled workers face unequal risks from automation.
low review_meta Summary openalex
Balancing Higher Education, Vocational Training, and Lifelong Learning: Evidence on Skills Mismatch and Labor Market Outcomes · Ari Santoso, Arleiny Arleiny, Eka Wahyu Ardhi · Mar 11, 2026
Workers with clear career pathways, employer-sponsored reskilling and confidence in AI-related skills report markedly higher career optimism and stronger intentions to stay; by contrast, ambiguous progression and limited upskilling opportunities correlate with pessimism and turnover risk, suggesting investments in human‑centered learning infrastructures could ease AI-driven labor adjustments.
low correlational Summary openalex
Leveraging Career Optimism to Enhance Employee Well-Being · Pamayla Darbyshire · Mar 11, 2026
GeoAI sharpens urban decision-making—improving risk maps, informal settlement detection and targeted policy evaluation—yet its benefits concentrate where data, technical capacity and governance are strongest. Without investment in open data, transparency standards and local capacity, GeoAI risks reinforcing rather than reducing urban inequalities.
n/a review_meta Summary openalex
Advancing Urban Analytics: GeoAI Applications in Spatial Decision-Making and Sustainable Cities · Sorin Avram · Mar 11, 2026
Algorithmic controls are a double-edged sword for food-delivery riders: real-time tracking and punitive constraints heighten pressure, worsen mental health and raise risky riding, while standardized guidance reduces pressure and improves safety — effects depend on riders’ perceived autonomy.
low correlational Full text openalex
Not all algorithmic controls are equal: the double-edged impact of algorithmic control dimensions on mental health and risky riding behavior among food delivery riders · Jinnan Wu, Wenqian Yang, Juan Qi, Wenpei Zhang · Mar 11, 2026
Enterprise risk management is linked to stronger finances, steadier revenues and easier credit for MSMEs, but only when risk practices are mature and genuinely integrated into decision‑making rather than applied as superficial compliance.
medium review_meta Summary openalex
A Literature Review: Effect of Enterprise Risk Management (ERM) Implementation on Micro, Small and Medium Enterprises (MSMEs). · Ivan Malik · Mar 11, 2026
Medicaid’s buying power can be harnessed to cut healthcare emissions and promote equity by embedding ESG criteria into procurement; Section 1115 waiver pilots and NHS Net Zero offer practical templates, but meaningful deployment will hinge on data systems, algorithmic governance and support for smaller suppliers.
n/a theoretical Full text openalex
Greening the Medicaid Supply Chain: An ESG-Integrated Framework for Value-Based Procurement Anchored in Stakeholder Theory and the Triple Bottom Line · Helen Ayodimeji Alaba · Mar 11, 2026
Explainable-AI applied to HR records finds overtime, travel and promotion gaps drive resignations more than pay; simulation suggests eliminating overtime could cut predicted attrition by about 17% and retain roughly 31 staff in the analyzed dataset, outperforming modest salary hikes.
low correlational Summary openalex
Explainable AI for Employee Retention in Green Human Resource Management: Integrating Prediction, Interpretation, and Policy Simulation · Dinh Cuong Nguyen, Dan Tenney, Elif Kongar · Mar 11, 2026
AI diffusion appears linked to reduced work intentions among low-educated pre-retirement workers in high-adoption regions, while men and the highly educated are more willing to keep working; household financial pressure further suppresses employment intent, implying the need for targeted retraining and social supports.
low correlational Full text openalex
Analysis of the Impact of Artificial Intelligence on Middle-Aged Workers' Employment Willingness: Based on the Context of Delayed Retirement · Ming Fu · Mar 11, 2026
A shift to genuinely multi-hazard, multi-risk disaster management is both practicable and worthwhile, but meaningful uptake needs coordinated progress on methods, usable tools, equity, local coproduction and early-career capacity. Without standardized concepts, stronger spatio-temporal evidence, and operationally tested decision-support systems, benefits will remain patchy and context-dependent.
n/a review_meta Full text openalex
Reducing risk together: moving towards a more holistic approach to multi-hazard and multi-risk assessment and management · Philip J. Ward, Sophie Buijs, Roxana Ciurean, Judith Claassen, James Daniell, Ke... · Mar 11, 2026
Quantum computing could substantially raise productivity in simulation- and optimization-heavy sectors, but gains will likely concentrate among early, well-resourced adopters and depend on coordinated investments and policy; without complementary infrastructure, workforce development, and governance, broad economy-wide benefits may be delayed or unevenly distributed.
low theoretical Summary openalex
Modeling Macroeconomic Output Gains from Quantum-Driven Productivity: Scenario-Based Forecasts · Kaan Mert Cenkci · Mar 11, 2026
Academic research has barely touched NLP for bank marketing: only 8 of 109 peer‑reviewed studies directly examine it, and the literature clusters on retention rather than acquisition, personalization or external-data integration—pointing to large unrealised economic and managerial opportunities.
n/a review_meta Summary openalex
Natural language processing in bank marketing: a systematic review and strategic gap analysis · Christopher Gerling, Stefan Lessmann · Mar 11, 2026
Automation and AI are tilting production toward technological capital, shrinking labour’s share and eroding payroll‑based revenues; policymakers must rethink tax bases and pension designs or face mounting fiscal and social strain.
medium quasi_experimental Full text semantic_scholar
The Macroeconomic Transition of Technological Capital in the Age of Automation · Vladimir Mici, Ina Shehu, Armelina Lila, V. Hoxha, F. Bombaj · Fetched Mar 10, 2026
AI that automates tasks in India’s gig economy often destroys whole jobs rather than simply substituting tasks, because insecure contracts, opaque algorithms and weak social protections prevent workers from reallocating; reskilling alone will not suffice — policy must combine training with job protections, income supports and reforms to platform practices.
low review_meta Full text semantic_scholar
Who Loses to Automation? AI-Driven Labour Displacement and the Limits of Reskilling Policies in Platform-Based Informal Work in India · Anagha Ramteke, G. Hari · Fetched Mar 10, 2026
AI is shifting work from routine middle‑skill jobs toward high‑skill and AI‑complementary roles, widening wage dispersion and reshaping employment patterns; the scale and equity of these effects depend heavily on education, social protections and deployment choices.
medium review_meta Full text semantic_scholar
Intelligence and Labor Market Transformation: A Critical Analysis of Skill-Biased Technological Change, Task Displacement, and Economic Inequality in the Age of Generative AI · Hemanth Poothera Appaiah · Fetched Mar 10, 2026
Russian universities and alternative training channels supply less than half of the country's estimated AI personnel needs—covering only 43.9%—with large leakages from admission to employment. A small subset of institutions disproportionately place graduates into AI roles and secure higher wages, implying policy gains from targeting high-performing programs and strengthening university–industry links.
medium descriptive Full text semantic_scholar
Employment og Graduates of Educational Programs in the Field of Artificial Intelligence · А. О. Averyanov, V. Gurtov, I. Stepus · Fetched Mar 10, 2026