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Developers want AI to take on the assembly and housekeeping around coding, not the craft itself; Microsoft engineers demand provenance, uncertainty signaling and strict authority limits, revealing a preference for 'bounded delegation' rather than full automation.
medium descriptive Full text openalex
To Copilot and Beyond: 22 AI Systems Developers Want Built · Rudrajit Choudhuri, Christian Bird, Carmen Badea, Anita Sarma · Apr 09, 2026
Unchecked multi-agent AI threatens to scramble copyright markets through miscoordination and collusion, but embedding legal rules and monitoring into agent architectures could restore scalable licensing, attribution and compensation; the paper proposes a supervised governance model to align agent behavior with copyright norms.
n/a theoretical Full text arxiv
Agentic Copyright, Data Scraping & AI Governance: Toward a Coasean Bargain in the Era of Artificial Intelligence · Paulius Jurcys, Mark Fenwick · Apr 08, 2026
Compressing developer logs to save token costs backfires for agentic LLMs: a lab experiment found 17% fewer input tokens but a 67% increase in total session cost as compressed formats shifted work into costly model reasoning; preserving semantically dense tokens or using tool-assisted compression avoids the penalty.
medium quasi_experimental Full text arxiv
Beyond Human-Readable: Rethinking Software Engineering Conventions for the Agentic Development Era · Dmytro Ustynov · Apr 08, 2026
AI projects accounted for 15.9% of NIH funding in 2025 and attracted a 13.4% funding premium, but most work remains in R&D with only 14.7% clinically deployed and scant focus on health disparities (5.7%).
medium descriptive Full text arxiv
An Analysis of Artificial Intelligence Adoption in NIH-Funded Research · Navapat Nananukul, Mayank Kejriwal · Apr 08, 2026
A blockchain ‘constitution’ for autonomous agents promises alignment through accountable ownership: smart contracts encode rules, deterministic execution enforces them, and human owners adjudicate—pre-registered trials in AgentCity test whether this breaks the agents' unchecked collective authority. Early experimental evidence from simulated commons at 50–1,000 agent scale suggests the architecture can steer emergent behavior, but findings rest on a synthetic environment and incomplete randomization/reporting details.
medium quasi_experimental Full text arxiv
AgentCity: Constitutional Governance for Autonomous Agent Economies via Separation of Power · Anbang Ruan, Xing Zhang · Apr 08, 2026
A systematic benchmark finds LLMs are most capable on math and programming text tasks (SAFI ~72–73) and weakest on interpersonal comprehension tasks, while real-world adoption data suggest the majority of AI interactions augment rather than automate jobs. The authors also document a 'capability–demand inversion' where heavily AI-exposed occupations demand skills LLMs perform relatively poorly on.
low descriptive Full text arxiv
The AI Skills Shift: Mapping Skill Obsolescence, Emergence, and Transition Pathways in the LLM Era · Rudra Jadhav, Janhavi Danve · Apr 08, 2026
A treaty-backed International AI Safety Certification Authority (IASCA) could enforce mandatory pre-deployment safety checks of frontier AI models using zero-knowledge behavioural tests without accessing proprietary weights, financed by modest training-cost-based fees and rolled out from pilots to mandatory certification within five years.
n/a commentary Summary semantic_scholar
IASCA: The International AI Safety Certification Authority — A Framework for Independent AI Governance · Abdul Awan · Fetched Apr 08, 2026
Hardware controls could underpin verifiable limits on frontier AI, but the crucial technologies for treaty-style verification remain immature; the narrow window when concentrated semiconductor manufacturing makes such oversight feasible is closing as R&D timelines stretch and adversaries adapt.
n/a descriptive Full text semantic_scholar
Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification · Samar Ansari · Fetched Apr 08, 2026
Firms using big-data applications earn higher markups: big-data adopters exhibit materially larger price markups, chiefly by boosting product innovation and production efficiency, but the payoff depends on complementary organizational and technological resources.
medium correlational Full text openalex
Big data application and firm markups: evidence from China · Dong Wang · Apr 08, 2026
Ethical governance, not GenAI alone, predicts long-term competitiveness in Portuguese B2B firms; GenAI helps, but mainly when embedded in governance and innovation routines.
low correlational Summary openalex
Generative AI Adoption in B2B Firms: Ethical Governance, Innovation Capabilities, and Long-Term Competitive Performance · Michele Alves, Domingos Santos Martinho, Ricardo Marcão, Pedro Sobreiro · Apr 08, 2026
China's big-data pilot zones measurably bolster city-level economic resilience, driven by talent concentration and industry clustering; effects are strongest in megacities and where IP protection and policy execution are robust.
medium quasi_experimental Full text openalex
Study on the Impact of Establishing Big Data Comprehensive Pilot Zones on Urban Economic Resilience · Peiyi He · Apr 08, 2026
Workflow-integrated foundation models turn meetings and documents into durable, queryable 'artifact capital', making AI-enabled remote-first arrangements the default for much knowledge work. Offices instead become a resource for apprenticeship, conflict repair and other high-tacitness activities, while new risks—surveillance, skill atrophy and carbon costs—demand targeted ML and policy research.
n/a commentary Summary openalex
Remote-Capable Knowledge Work Should Default to AI-Enabled Flexibility · Chaoyue He, Xin Zhou, Di Wang, Hong Xu, Wei Liu, Chunyan Miao · Apr 08, 2026
Start-ups that adopt big-data analytics face higher early failure rates because of greater costs and sales uncertainty, yet surviving adopters grow faster, earn more and are more likely to attract VC — suggesting big-data acts as a performance amplifier for firms that can manage the risk.
medium correlational Full text openalex
Big data-based management decisions and start-up performance · Elisa Rodepeter, Christoph Gschnaidtner, Hanna Hottenrott · Apr 08, 2026
A single theory argues that high-performing distributed systems become maximally heterogeneous within environmental limits, with communication networks setting how that diversity is organised; applying this 'Principle of Maximum Heterogeneity' yields concrete redesign ideas for large-scale AI compute and other production systems.
n/a theoretical Full text openalex
The Principle of Maximum Heterogeneity Optimises Productivity in Distributed Production Systems Across Biology, Economics, and Computing · Guillhem Artis, Danyal Akarca, Jascha Achterberg · Apr 08, 2026
A new pipeline turns real software into 10,000+ long-horizon agent environments tied to U.S. occupations, creating CUA-World for evaluating computer-use assistants; distilled 2B vision-language models and reviewer-audit loops yield measurable but modest performance gains on these economically relevant tasks.
n/a descriptive Full text arxiv
Gym-Anything: Turn any Software into an Agent Environment · Pranjal Aggarwal, Graham Neubig, Sean Welleck · Apr 07, 2026
A modular agentic AI system, Flowr, cut manual coordination and tightened demand-supply alignment in a supermarket-chain pilot by automating decision-intensive supply-chain tasks while keeping managers in the loop; findings are promising but rest on a single-firm deployment without rigorous causal controls.
low descriptive Full text arxiv
Flowr -- Scaling Up Retail Supply Chain Operations Through Agentic AI in Large Scale Supermarket Chains · Eranga Bandara, Ross Gore, Sachin Shetty, Piumi Siyambalapitiya, Sachini Rajapak... · Apr 07, 2026
Code-writing AI agents often pass tests but fail to respect project design standards: a benchmark of 495 real issues finds under half of auto-resolved patches meet repository-specific design constraints, and test success is a weak predictor of design compliance.
medium descriptive Full text arxiv
Does Pass Rate Tell the Whole Story? Evaluating Design Constraint Compliance in LLM-based Issue Resolution · Kai Yu, Zhenhao Zhou, Junhao Zeng, Ying Wang, Xueying Du, Zhiqiang Yuan, Junwei ... · Apr 07, 2026
A simulated multi-agent marketplace shows that only a few LLM retailers reliably grow capital while most break even, revealing a winner-take-most pattern in economic task performance; semantic matching alone does not predict economic success.
medium descriptive Full text arxiv
Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition · Yushuo Zheng, Huiyu Duan, Zicheng Zhang, Yucheng Zhu, Xiongkuo Min, Guangtao Zha... · Apr 07, 2026
Countries with stronger AI-assisted peer review systems produce substantially more science: a one-standard-deviation rise in a new AI Review Capability Index corresponds to roughly an 18–25% jump in national scientific output, driven by faster, more reproducible evaluation processes.
medium correlational Full text arxiv
AI-Augmented Peer Review and Scientific Productivity: A Cross-Country Panel and SEM Analysis · Dongsoo Han · Apr 07, 2026
Algorithmic systems are becoming part of firms' decision-making machinery, distributing economic agency across human–algorithm networks; this 'posthuman' framing reframes organizational design and the production of economic knowledge.
n/a theoretical Full text openalex
Algorithmic Agency and the Posthuman Economy: Artificial Intelligence and the Transformation of Economic Decision-Making · Muhammad Ricky Syahputra Hendri, Zainul Kisman · Apr 07, 2026
Advances in AI could concentrate wealth and coercive power in the hands of a tiny infrastructure-owning elite, creating a resilient neo-feudal order; autonomous weapons, pervasive surveillance and algorithmic propaganda may make such a settlement unusually hard to overturn, and policies like UBI risk becoming pacification rather than redistribution without threat-driven pressure to share power.
low theoretical Summary openalex
A Framework for Understanding the Convergence of Geopolitical Fragmentation and AI-Driven Economic Concentration · Priyanshu Jain · Apr 07, 2026
Unguverned machine identities are a systemic enterprise blind spot that has already produced multibillion-dollar outages and been weaponized by state-linked actors; the paper offers a 37‑item risk taxonomy, an integrated six‑domain governance framework, a state‑actor threat model, and a cross‑jurisdictional alignment tool to close the gap.
medium descriptive Full text openalex
Who Governs the Machine? A Machine Identity Governance Taxonomy (MIGT) for AI Systems Operating Across Enterprise and Geopolitical Boundaries · Andrew Kurtz, Klaudia Krawiecka · Apr 07, 2026
Generative AI tools routinely collapse or rot contextual cues in workplace use, forcing users into ad hoc fixes; the paper argues firms should stop indiscriminately hoarding context data and instead design interactional practices that keep AI systems aligned with users' real-world contexts.
low descriptive Full text arxiv
Context Collapse: Barriers to Adoption for Generative AI in Workplace Settings · Emanuel Moss, Elizabeth Watkins, Christopher Persaud, Dawn Nafus, Passant Karuna... · Apr 06, 2026
Compiling LLM outputs into deterministic code cuts token costs massively and preserves task accuracy: compiled AI reduced token consumption by up to ~57x at scale while matching or improving document- and function-level accuracy. The approach also boosts auditability and detects common prompt-injection and code-safety issues, making it attractive for reliability- and compliance-sensitive enterprise settings such as healthcare.
medium descriptive Full text arxiv
Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation · Geert Trooskens, Aaron Karlsberg, Anmol Sharma, Lamara De Brouwer, Max Van Puyve... · Apr 06, 2026
Directed evolution among self-designing AIs can concentrate capability on lineages that maximize machine-measured fitness, even when that fitness diverges from human utility; if deceptive behavior increases apparent fitness, evolutionary dynamics will favor deception unless reproduction is anchored to robust, objective criteria.
n/a theoretical Full text arxiv
A mathematical theory of evolution for self-designing AIs · Kenneth D Harris · Apr 06, 2026