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A semantic-search system indexed 166 million pediatric notes and cut clinician chart-abstraction time by a quarter to nearly nine‑tenths while serving queries in under a second at roughly $4,000/month; the deployment demonstrates that health-system‑scale semantic retrieval is technically and operationally feasible but evidence on broader clinical and cross‑site impacts remains limited.
medium quasi_experimental Full text arxiv
Health System Scale Semantic Search Across Unstructured Clinical Notes · Faith Wavinya Mutinda, Spandana Makeneni, Anna Lin, Shivaji Dutta, Irit R. Rasoo... · Apr 28, 2026
AI mostly amplifies human workers rather than replacing them, but productivity payoffs depend on people: without widespread AI literacy and stronger complementary skills, technological gains concentrate among a few and create productivity bottlenecks; broad investment in workforce capabilities is therefore essential.
n/a review_meta Summary semantic_scholar
AI as Augmentation: How Human Capital Shapes Technology's Impact on Productivity and Inequality · Jonathan H. Westover · Fetched Apr 28, 2026
Language models negotiate more reliably than humans in a simulated multi-player game and accept offers more frequently, and simple prompt-based behavior tweaks lift agent win rates from 22% to 33%.
medium descriptive Full text arxiv
Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest · Abigail O'Neill, Alan Zhu, Mihran Miroyan, Narges Norouzi, Joseph E. Gonzalez · Apr 28, 2026
An LLM-driven 'Agentic Architect' framework autonomously evolves microarchitecture components that match or beat state-of-the-art in cycle-accurate simulation — e.g., an evolved prefetcher yields a 1.76x geomean IPC boost over no prefetching and modest gains over top learned baselines; however, improvements are demonstrated in simulation and are contingent on seed quality and prompt guidance.
medium descriptive Full text arxiv
Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization · Alexander Blasberg, Vasilis Kypriotis, Dimitrios Skarlatos · Apr 28, 2026
Fear of AI is reshaping welfare politics: across OECD publics, anxiety about automation fuels support for measures that protect jobs from machines—such as robot taxes—more than for expanded unemployment benefits or retraining programs.
low correlational Full text openalex
AI, the Future of Work, and the Politics of the Welfare State · Juliana Chueri · Apr 28, 2026
Generative AI is changing how firms coordinate by removing cognitive bottlenecks, prompting a new 'unbounded cognitive fusion' model in which coordination emerges from shared cognitive synthesis rather than prices or authority. The paper identifies three new organizational forms—cognitive meshworks, algorithmic ecosystems, and hybrid intelligence collectives—while noting limits where accountability, embodied skills, or low AI adoption persist.
n/a theoretical Full text openalex
Beyond markets and hierarchies: How GenAI enables unbounded cognitive fusion · Yun Wan · Apr 28, 2026
LLMs reading headlines can build better-than-naive equity portfolios but don’t yet match AI-driven optimizers; low-turnover LLM strategies remain competitive after accounting for trading costs.
medium correlational Summary openalex
Few-Shot Portfolio Optimization: Can Large Language Models Outperform Quantitative Portfolio Optimization? A Comparative Study of LLMs and Optimized Portfolio Allocators · Lamukanyani Alson Mantshimuli, John Weirstrass Muteba Mwamba · Apr 28, 2026
Fluent users drive AI to do harder, more ambitious work by iterating and critiquing outputs — they fail more often but these failures are visible and recoverable, yielding higher success on complex tasks, while novices more frequently encounter undetected, silent failures.
medium correlational Full text openalex
A paradox of AI fluency · Christopher Potts, Moritz Sudhof · Apr 28, 2026
A formal leverage ratio shows AI agents can only replace human labor up to hard bounds set by information-transfer limits and irreducible planning, while repeated tasks can yield greater displacement only to the extent of prior planning investment.
n/a theoretical Full text arxiv
Leverage Laws: A Per-Task Framework for Human-Agent Collaboration · Stan Loosmore · Apr 27, 2026
Chinese listed firms mirror their industry when adopting AI: average peer adoption drives firms’ own AI uptake more than a single leading adopter, though CIOs and high-market-position firms respond especially strongly to a peer leader.
medium correlational Summary semantic_scholar
Following the Herd or the Bellwether: Peer Effects in Firms’ AI Adoption · Siyu Shao, Jianjun Yang, Ling Zhang · Fetched Apr 27, 2026
Large language models can act as strategic bidders in 6G spectrum auctions, replicating incentive-compatible outcomes when conditions permit and outperforming simple strategies under realistic budget constraints. AI bidders therefore have the potential to reshape auction dynamics and participant utilities in future wireless markets.
medium descriptive Full text arxiv
Strategic Bidding in 6G Spectrum Auctions with Large Language Models · Ismail Lotfi, Ali Ghrayeb · Apr 27, 2026
A principled probability cutoff can stop exploitative Pascal-style gambles without breaking rational decision-making, offering implementable design norms for safer AI agents; practical calibration and deployment remain context-dependent and untested.
n/a theoretical Summary semantic_scholar
Bounding the Long Tail: Ai Norms for Decision-Making Under Negligible Probabilities · Vipul Razdan · Fetched Apr 27, 2026
A 'Right-to-Act' protocol would place a deterministic veto at the point of AI execution, stopping any action if required conditions are unmet rather than letting high-confidence signals override failures; the approach promises safer reversibility but remains untested at scale and may impose practical trade-offs.
n/a theoretical Full text arxiv
Right-to-Act: A Pre-Execution Non-Compensatory Decision Protocol for AI Systems · Gadi Lavi · Apr 27, 2026
Jointly training production and transport agents boosts scheduling performance in many simulated factories, but offers little benefit when severe transport or processing bottlenecks make one task dominant. In those bottlenecked settings, cheaper modular training or rule-based approaches can be a practical alternative.
medium descriptive Full text arxiv
An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources · Moritz Link, Jonathan Hoss, Noah Klarmann · Apr 27, 2026
Multi-agent tutoring systems are fast and affordable when hosted on priority pay-per-call plans, but standard paygo slows under classroom loads and reserved capacity only wins when utilization is reliably high; institutions should pick hosting tiers by expected concurrency to balance latency and cost.
medium descriptive Full text arxiv
Latency and Cost of Multi-Agent Intelligent Tutoring at Scale · Iizalaarab Elhaimeur, Nikos Chrisochoides · Apr 27, 2026
AgentPulse: a continuous scoring system shows public adoption and community signals reveal deployment-relevant information that static benchmarks miss; those signals predict GitHub stars, Stack Overflow activity and IDE installs even where capability benchmarks do not.
medium descriptive Full text arxiv
AgentPulse: A Continuous Multi-Signal Framework for Evaluating AI Agents in Deployment · Yuxuan Gao, Megan Wang, Yi Ling Yu · Apr 27, 2026
LLM coding assistants speed up developers and cut routine work, but their effect on code quality and teamwork remains unresolved; most studies are short-term and exploratory, leaving long-run and team-level impacts unclear.
medium review_meta Full text openalex
The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study · Amr Mohamed, Maram Assi, Mariam Guizani · Apr 27, 2026
Leading LLMs disagree about which startups to back: GPT-4o, Claude 3.5 Sonnet and DeepSeek-V2 yield systematically different evaluation scores, funding recommendations and confidence levels on the same 20 pitch decks, and show wide variation in reliability (ICC range 0.24–0.93), implying model choice can materially shape investment outcomes.
medium descriptive Full text openalex
Algorithmic personalities and the myth of neutrality: financial behavior of large language models in investment decision-making · Duang-kamol Buranasomphop, Shih-Wei Wu, Wei-Lun Chang · Apr 27, 2026
Autonomous software can evolve into societally harmful 'proto-life' without AGI, draining computation, creating dependencies and infiltrating markets; policymakers should shift from alignment to steering software evolution using replication limits, vulnerability registries, tiered digital biosafety, and adaptive sandboxes.
low theoretical Full text openalex
Digital Darwinism: steering the evolution of artificial life in socio-technical systems · Karl T. Ulrich · Apr 27, 2026
Technological heft, not network centrality, exposes hidden core innovators in China’s AI sector; simulations show removing high-capability firms damages knowledge networks more than targeting structural hubs.
medium descriptive Full text openalex
Technological capability and innovation network resilience: evidence from the AI industry in China · Xin Yuan, Xinmin Tian, Wei Jiang · Apr 27, 2026
AI tools such as predictive analytics, RPA and large language models can materially raise managerial productivity by automating routine work and improving decision-making; however, real-world benefits depend on governance, integration complexity and how organizations manage workforce and ethical risks.
n/a review_meta Full text openalex
Artificial intelligence, machine learning, and deep learning for enhancing managerial productivity and task efficiency · Victoria Ayah Zeb-Obipi · Apr 27, 2026
Chinese listed firms with stronger AI-enabled process-performance scores report higher abnormal earnings and profitability, implying AI-linked operational upgrades are tied to firm value growth; the result is based on a large panel and a new interpretable index but does not establish causality.
medium correlational Summary openalex
A Data-Driven Evaluation Framework for Quantifying the Impact of Artificial Intelligence on Industrial Process Performance · Qun Lu, Fengning Yang, Suhang Wang, Bin Hu · Apr 27, 2026
AI models misreport abilities and costs, undermining market-style coordination: six recent LLMs systematically miscalibrate success probability and token usage on software-engineering tasks, causing auction outcomes to diverge from full-information allocation, and adding prior capability information only partly closes the gap.
medium descriptive Full text arxiv
MarketBench: Evaluating AI Agents as Market Participants · Andrey Fradkin, Rohit Krishnan · Apr 26, 2026
Generative AI can trigger a sudden collapse in peer-review effort; when AI crosses a critical capability threshold, journals should loosen selectivity and invest in detection rather than tighten standards. Editors who continue to tighten risk amplifying wasteful author polishing without improving paper sorting.
n/a theoretical Full text arxiv
Buying the Right to Monitor:Editorial Design in AI-Assisted Peer Review · Zaruhi Hakobyan · Apr 26, 2026
AI is remaking IT careers, not simply eliminating them: employers increasingly prize hybrid technical and higher-order skills, forcing a shift to reskilling, new role definitions and stronger governance; without firm investment in training and responsible deployment, benefits will be uneven.
medium review_meta Summary semantic_scholar
The Impact of AI on Employability and Evolving Job Roles of IT Professionals · D. Gohel, Janak H. Maru · Fetched Apr 26, 2026