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Large language models can act as 'brains' for modern microscopes, automating protocol design, instrument control and data analysis to speed experiments and raise the value of software and data; yet their deployment creates reproducibility, safety and concentration risks that demand standards, benchmarks and public interventions.
n/a review_meta openalex
ChatMicroscopy: A Perspective Review of Large Language Models for Next-Generation Optical Microscopy · Giuseppe Sancataldo · Mar 05, 2026
Treating EdTech firms as recipients of federal education funding would make vendors directly liable for discriminatory AI tools, forcing firms to internalize nondiscrimination obligations. The shift would reshape procurement, raise compliance costs, and alter market incentives for innovation and entry in the EdTech sector.
n/a commentary openalex
Civil Rights and the EdTech Revolution · Kirsten Mettler · Mar 05, 2026
Treating AI systems like patients could create a market for diagnostics, certification and remediation: 'Model Medicine' lays out taxonomies, imaging tools and reporting standards (Neural MRI, M-CARE) that would let purchasers, insurers and regulators assess model ‘health’ — but empirical support so far comes mainly from a single experimental corpus (Agora-12) and four case studies.
low theoretical openalex
Model Medicine: A Clinical Framework for Understanding, Diagnosing, and Treating AI Models · Jihoon Jeong · Mar 05, 2026
A model-agnostic pipeline using LLM-driven semantic normalization and density-based clustering uncovers coherent research themes in ML and NLP conference abstracts. The method scales to large corpora and generates interpretable topic maps that can be used to track research frontiers and build indicators for economic analysis, though results require robustness checks across models and prompts.
n/a descriptive openalex
Soft-Prompted Semantic Normalization for Unsupervised Analysis of the Scientific Literature · Ivan Malashin, Dmitry Martysyuk, Vadim Tynchenko, Andrei Gantimurov, V. A. Nelyu... · Mar 05, 2026
AI-guided microbial ‘factories’ are shortening design cycles and promising cheaper, greener routes to complex chemicals, but most successes are confined to the lab or pilot scale and persistent scale-up and regulatory hurdles will shape who benefits and how fast.
n/a review_meta openalex
Harnessing Microbial Factories: Biotechnology at the Edge of Synthetic Chemistry · Dr. S. Mohamed Rabeek · Mar 05, 2026
Digital finance widens access and slashes transaction costs, but risks amplifying inequality and systemic fragility; without data governance, competition safeguards and algorithmic oversight, platformization can lock in exclusion as well as convenience.
n/a review_meta openalex
Financial Inclusion in the Age of FinTech Platforms: Opportunities, Inequalities, and Regulatory Dilemmas · Kumaraswamy M, D. Swapna Devi · Mar 05, 2026
A ten-minute onboarding session substantially raised voluntary use of an LLM and produced measurable performance gains on a law-school exam: training increased usage from 26% to 41% and improved scores by 0.27 grade points, whereas untrained access delivered no score benefit.
medium rct openalex
Training for Technology: Adoption and Productive Use of Generative AI in Legal Analysis · Benjamin Minhao Chen, Hong Bao · Mar 05, 2026
AI-enhanced robotics patenting took off after 2010, marking a structural shift in innovation dynamics; China shows the tightest integration between AI and robotics with substantial university/public-sector patenting, while the U.S. remains more market-driven and less integrated.
medium descriptive openalex
The "Gold Rush" in AI and Robotics Patenting Activity. Do innovation systems have a role? · Giovanni Guidetti, Riccardo Leoncini, Mariele Macaluso · Mar 05, 2026
Generative AI equalizes individual task performance but shifts economic value to owners of complementary assets; unless AI is broadly accessible or labor institutions share rents, firms capture gains and inequality can rise.
low theoretical openalex
When AI Levels the Playing Field: Skill Homogenization, Asset Concentration, and Two Regimes of Inequality · Xupeng Chen, Shuchen Meng · Mar 05, 2026
Charging levies on AI 'tokens'—a usage tax applied at the point of inference—could give governments a practical way to tax AI-generated value and blunt automation-driven revenue and wage shocks; the approach hinges on robust cryptographic receipts, norm-based rates, white-box audits, and difficult international cooperation.
n/a commentary openalex
Token Taxes: mitigating AGI's economic risks · Lucas Irwin, Tung-Yu Wu, Fazl Barez · Mar 04, 2026
Countries with stronger AI readiness record notably better progress on the Sustainable Development Goals, and FinTech and Blockchain activity also predict higher SDG performance; when nations develop multiple digital technologies together, the combined sustainability gains exceed the sum of individual effects.
low correlational openalex
Digital Technologies and Sustainable Development: Evidence from FinTech, AI, and Blockchain Adoption in G20 Economies · Nesrine Gafsi, Amina Hamdouni, Aida Smaoui · Mar 04, 2026
Consumer complaints forecast short-term stock drops at U.S. financial firms: rising complaint volumes and more negative narrative sentiment are linked to near-term abnormal return declines, and topic-level complaint trends add predictive power for investors and risk managers.
medium correlational openalex
More than words: valuation of words for stock price by using the combination of natural language processing, time-series panel and gradient boosting · Wookjae Heo, Yeonseo Jo, Keewon Moon · Mar 04, 2026
China’s cultural-zone program created jobs by spawning platform-mediated gigs, not new firms; however, fiscal spending only translated into employment where digital infrastructure was sufficiently developed, otherwise it failed or backfired.
medium quasi_experimental openalex
Redefining Policy Effectiveness in the Digital Era: From Corporate Scaling to Inclusive Employment Growth—Evidence from China’s National Cultural Demonstration Zones · Yuanming Wang, Mu Li, Y. Chen, Yuting Xue · Mar 03, 2026
Human-authored procedural 'Skills' lift LLM agent success by 16.2 percentage points on average—gains vary sharply by domain and sometimes harm performance—while model-generated Skills add no net value; narrowly targeted Skills let smaller models match larger ones, suggesting firms can substitute curated knowledge for compute.
medium quasi_experimental manual
SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks · Xiangyi Li, Wenbo Chen, Yimin Liu, Shenghan Zheng, Xiaokun Chen, Yifeng He, Yubo... · Feb 13, 2026