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The parts of large language models that make them economically valuable are not simply 'rules in disguise'—they are tacit, practice‑derived competences that resist full human‑readable extraction, boosting rents for model providers and shifting policy toward outcome‑based auditing and behavioral testing.
low theoretical arxiv
Why the Valuable Capabilities of LLMs Are Precisely the Unexplainable Ones · Quan Cheng · Mar 16, 2026
A retrospective, time-split test finds retrieval-augmented AI idea generators produce roughly 2.5× more ideas that later become influential papers than vanilla models — a difference missed by LLM judges, which tend to overvalue novel-sounding but ultimately unmaterialized ideas.
medium quasi_experimental arxiv
HindSight: Evaluating LLM-Generated Research Ideas via Future Impact · Bo Jiang · Mar 16, 2026
Tasks that give workers agency and happiness are more likely to be exposed to AI, raising concerns about erosion of meaningful work; meanwhile, developers design systems around politeness and imagination, whereas workers want straightforward, tolerant, practical tools.
medium descriptive arxiv
Are We Automating the Joy Out of Work? Designing AI to Augment Work, Not Meaning · Jaspreet Ranjit, Ke Zhou, Swabha Swayamdipta, Daniele Quercia · Mar 16, 2026
AI is becoming a research productivity layer that speeds idea-to-publication workflows and tends to raise research outputs and quality; institutions that adopt and integrate these tools effectively may widen their competitive lead while unequal access risks amplifying academic stratification.
medium review_meta openalex
Artificial Intelligence for Improving Research Productivity and Knowledge Creation in Higher Education Institutions: Nano Review · Horn Sarun, In Nara, Him Hun · Mar 16, 2026
Delivering development in Cameroon Pidgin sharply raised comprehension and uptake—health-message comprehension rose by over 30 percentage points and agricultural techniques were nearly universally adopted—while vernacular-speaking volunteers were socially integrated and granted traditional legitimacy; the study argues that linguistic sovereignty, not mere translation, is central to effective, sustainable aid and should reshape data, modeling, and governance priorities for AI-enabled development.
low descriptive openalex
From Linguistic Hybridity to Development Sovereignty: Pidgin English, the American Peace Corps, and the Decolonization of African Development · Eric Dzeayele Maiwong · Mar 16, 2026
AI automates managers' information-processing chores while elevating strategic, relational and ethical tasks into hybrid decision zones, forcing firms to redesign roles, governance and upskilling; without human‑in‑the‑loop checkpoints and clear accountability, algorithmic optimisation risks misaligned decisions and coordination failures.
n/a theoretical openalex
Comparative analysis of strategic vs. computational thinking in management · Iryna Nyenno · Mar 16, 2026
Chinese publicly listed firms that emphasize big-data use see higher firm value, and that payoff becomes stronger after China's landmark data-protection law; the result suggests robust privacy rules can amplify corporate gains from data-driven operations.
medium quasi_experimental openalex
How Big Data Enhances Firm Value Under Data Privacy Regulation · Zekai Yan, Xuan Cai · Mar 16, 2026
Consensus can mask fragility: organizations that suppress divergent reports create the illusion of agreement and miss accumulating tail risks until abrupt correction. Simple governance diagnostics—recorded dissent patterns, voting-anonymous gaps, and method/pipeline diversity—can distinguish healthy integration from dangerous exclusion.
n/a theoretical openalex
Cohesion as Concentration: Exclusion-Driven Fragility in Financial Organizations · Foong Soon Cheong · Mar 16, 2026
Deep reinforcement learning can outperform static portfolio rules but also concentrates risk and consumes large compute; regulators and firms must impose interpretability, crowding safeguards and sustainability standards before wide deployment.
n/a review_meta openalex
Deep Reinforcement Learning for Dynamic Portfolio Optimization in Financial Markets · Helena J. Sterling, Marcus V. Thorne · Mar 16, 2026
Countries with greater diffusion of cognitive technologies saw measurable gains in entrepreneurial opportunities: a one-standard-deviation rise in a Cognitive Tools Index is associated with a 0.33 increase in a composite Market Opportunity Index between 2020 and 2024. The result—from a dynamic panel with instrumental variables—points to the value of digital infrastructure, human capital and open data to sustain innovation.
medium quasi_experimental openalex
Innovative Cognitive Tools for Studying Market Opportunities for Entrepreneurship · Taliat Bielialov, Maryna Salun, Alina Lytvynenko, Halyna Yamnenko, Olha Romanko · Mar 16, 2026
Generative AI can reliably spot employment-law claims and draft investigatory plans comparable to junior associates, potentially saving firms many hours of research; but frequent incorrect case citations mean human lawyers must still verify and supervise outputs.
low descriptive openalex
Robot Wingman: Using AI to Assess an Employment Termination · Perritt, Henry H., Jr. · Mar 16, 2026
A shared AI professional vocabulary crystallized quickly in early 2024, but practitioners never coalesced into a distinct occupation; instead, AI skills diffused into existing jobs rather than creating a new 'AI Engineer' class.
medium descriptive openalex
NLP Occupational Emergence Analysis: How Occupations Form and Evolve in Real Time -- A Zero-Assumption Method Demonstrated on AI in the US Technology Workforce, 2022-2026 · David Nordfors · Mar 16, 2026
A hybrid AI hiring engine combining Transformer embeddings and a skills knowledge graph improves candidate retrieval and provides factor-level explanations compared with traditional keyword search on the JobSearch-XS benchmark; the system is released with a demo and installable package.
n/a descriptive arxiv
JobMatchAI An Intelligent Job Matching Platform Using Knowledge Graphs, Semantic Search and Explainable AI · Mayank Vyas, Abhijit Chakraborty, Vivek Gupta · Mar 15, 2026
AESP lets AI agents transact at machine speed on crypto rails while preventing them from gaining unilateral control over funds by combining deterministic policy checks, tiered human review, cryptographic dual-signing and escrow, context-isolated privacy, and a hardened crypto substrate; the protocol is released as an open-source TypeScript SDK with a formal evaluation plan but lacks field validation.
low descriptive semantic_scholar
AESP: A Human-Sovereign Economic Protocol for AI Agents with Privacy-Preserving Settlement · Jian Wang · Fetched Mar 15, 2026
AI could substantially raise social welfare in health, education, environment and civic services, but those gains will not be automatic — governments must couple procurement, standards and risk frameworks with international cooperation to prevent bias, unequal access and systemic harm.
low review_meta semantic_scholar
AI for Good: Societal Impact and Public Policy · Dr.Madhulika Sonawane, Mr. Nilesh Sapkale · Fetched Mar 15, 2026
Psychological readiness, not just technical capability, is the main obstacle to AI adoption in U.S. firms; a new organizational-psychology framework prescribes a five-phase HR and governance roadmap to unlock productivity benefits.
n/a theoretical semantic_scholar
Developing Organizational Psychology Frameworks to Prepare the U.S. Workforce for Artificial Intelligence Integration and Competitiveness · Anita Naa Adoley Badoo · Fetched Mar 15, 2026
Hybrid human–AI translation substantially improves employment outcomes for limited-English immigrants—up to 40% better job-placement accuracy and ~20% higher retention—while reductions in public translation services push workers toward informal, inequitable solutions.
low correlational semantic_scholar
Translation Models Empowering Immigrant Workforce Integration in the US Policy and Economic Implications · Haytham Othman Hassan Abdalla, Manal ELtayeb Mohamed Idris, Nawal Mosa Mohammed ... · Fetched Mar 15, 2026
AI is not just a technology but a tool of geopolitical power: the United States, China and the European Union are shaping three distinct AI orders that concentrate economic value and lock other countries into dependency through control of models, data and standards; regulatory divergence and standards competition will reconfigure trade, investment and market access.
low theoretical semantic_scholar
The Geopolitics of Artificial Intelligence: Power, Regulation, and Global Governance · Cuneyt Yilmaz · Fetched Mar 15, 2026
AI appears to deliver the biggest macro gains in weaker or early-regime conditions within G7 countries, but shows no measurable benefit in high-performing regimes; by contrast, FinTech and financial development deliver larger payoffs in upper-tail regimes, and high governance scores correlate negatively at the top quantile—a pattern the authors interpret as institutional rigidity limiting advanced-system gains.
low correlational semantic_scholar
Towards Smart, Economic Performance and Sustainable Monetary Policy: The Role of AI and FinTech in G7 Economies · M. Ageli · Fetched Mar 15, 2026
India frames AI as a key engine for future growth and smarter government, yet policy currently rests on a fragmented legal patchwork; without clear, enforceable data governance and competition rules, AI risks concentrating gains, eroding privacy, and widening regional and skill‑based inequalities.
n/a descriptive semantic_scholar
Regulation and governance of artificial intelligence in India · Malte Jauch · Fetched Mar 15, 2026
Academic economics on AI is clustered around supply chains, labor markets and large language models, with a sharp rise in LLM studies after ChatGPT; crucial policy questions—measuring AI-driven growth, evaluating industrial policy, and assessing regulatory and cross-border effects—remain underexplored.
n/a review_meta semantic_scholar
Mapping the Landscape of the Economics of AI Literature: Gaps and Opportunities for Research and Policy · Lucy Hampton, J. L. Poquiz · Fetched Mar 15, 2026
Information, not experience, shifts public support for government AI: learning about AI markedly changes citizens' attitudes—even overriding prior beliefs and personal experience working under an AI manager—whereas being managed by an AI alters task performance but leaves views on public-sector AI largely unchanged.
high rct semantic_scholar
The Politics of Using AI in Policy Implementation: Evidence from a Field Experiment · Yotam Margalit, Shir Raviv · Fetched Mar 15, 2026
AI-enabled forecasting and intelligent dispatch can materially raise revenues, extend life and cut emissions for grid-scale batteries, improving levelized cost of storage and payback times; however, most claimed gains stem from simulations and isolated demos, and scaling them requires better data, lighter algorithms and market rules that reward speed and degradation-aware operation.
n/a review_meta semantic_scholar
Grid-Scale Battery Energy Storage and AI-Driven Intelligent Optimization for Techno-Economic and Environmental Benefits: A Systematic Review · N. Ketjoy, Y. Muna, M. Kaewpanha, Wisut Chamsa-ard, Tawat Suriwong, C. Termritth... · Fetched Mar 15, 2026
Strong governance turns AI and other technologies into sustainable development gains, while weak governance systematically blocks progress—especially in developing and transition economies. Investments in transparency, rule of law, and interoperable information systems are prerequisites for AI to deliver equitable, climate‑resilient benefits.
low descriptive semantic_scholar
Good Governance and Sustainable Development: Pathways, Principles, and Policy Imperatives · Pradip Kumar Das · Fetched Mar 15, 2026
Across several Central and Eastern European economies, AI adoption rarely boosts output unless firms already have standardized processes, management systems and skilled workers; without these complements, AI gets filtered out in a 'productivity funnel'. Policy and investment should prioritize organizational readiness and skills alongside AI tools to realize productivity gains.
medium correlational semantic_scholar
The complementarity trap: AI adoption and value capture · G. Pitić, Mihajlović Čolić, Teodora Ilić, Milica Simić · Fetched Mar 15, 2026