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AI widens firms' reach into distant knowledge but can hollow out radical discovery once automation is pervasive; beyond a threshold of AI automation firms shift from riskier, radical recombinations to safer incremental tweaks, and full automation risks eliminating originality altogether.
n/a theoretical Full text arxiv
Bridging Distant Ideas: the Impact of AI on R&D and Recombinant Innovation · Emanuele Bazzichi, Massimo Riccaboni, Fulvio Castellacci · Apr 02, 2026
Adaptive, GPT-powered life-insurance questionnaires cut the number of questions and win user preference, but conventional forms still slightly outperform them on risk-assessment accuracy in two field experiments; further development could close the accuracy gap and streamline underwriting.
medium quasi_experimental Full text arxiv
AI in Insurance: Adaptive Questionnaires for Improved Risk Profiling · Diogo Silva, João Teixeira, Bruno Lima · Apr 02, 2026
A prototype payment gateway lets autonomous agents spend fiat while enforcing programmatic spend policies: lab tests show policy rules cut total spending by 27.3% and security checks blocked all replay and token misuse with ~20ms latency overhead.
medium descriptive Full text arxiv
APEX: Agent Payment Execution with Policy for Autonomous Agent API Access · Mohd Safwan Uddin, Mohammed Mouzam, Mohammed Imran, Syed Badar Uddin Faizan · Apr 02, 2026
Large language models give fairly accurate point estimates but are wildly overconfident — their nominal 95% credible intervals contain the truth only 9–44% of the time; a simple statistical recalibration (conformal prediction) expands intervals to recover the intended coverage.
medium descriptive Full text arxiv
Bayesian Elicitation with LLMs: Model Size Helps, Extra "Reasoning" Doesn't Always · Luka Hobor, Mario Brcic, Mihael Kovac, Kristijan Poje · Apr 02, 2026
AI-made videos match humans in total attention by flooding the feed: AIGC creators win aggregate engagement through sheer volume even though viewers prefer human-made clips, and the platform’s recommendation algorithm largely determines how much AI content viewers actually see — suggesting platforms should adopt AIGC-aware distribution and governance rules.
medium correlational Full text arxiv
Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology · Tianhao Shi, Yang Zhang, Xiaoyan Zhao, Fengbin Zhu, Chenyi Lei, Han Li, Wenwu Ou... · Apr 02, 2026
A role-separated multi-agent LLM system cut curation effort to a single operator completing campus-scale datasets in two days and stopped a coordinate-transformation error affecting 2,452 stations before publication; audited handoffs detected the issue within 10 minutes and resolved it in 80 minutes.
medium descriptive Full text arxiv
Exploring Robust Multi-Agent Workflows for Environmental Data Management · Boyuan Guan, Jason Liu, Yanzhao Wu, Kiavash Bahreini · Apr 02, 2026
A new industrial PHM benchmark finds leading LLM agents complete just 68% of realistic diagnostics and prognostics tasks, plagued by tool-orchestration errors and poor generalization; top configurations show 23% incorrect sequencing, a 14.9 percentage-point drop on multi-asset reasoning, and only 42.7% success on held-out datasets.
medium descriptive Full text arxiv
PHMForge: A Scenario-Driven Agentic Benchmark for Industrial Asset Lifecycle Maintenance · Ayan Das, Dhaval Patel · Apr 02, 2026
A benchmark built from real production coding sessions finds current foundation models solve roughly 53–72% of fail-to-pass tasks, and those that execute tests and static analysis perform substantially better, suggesting that exposing codebase-specific verification tools materially improves externally trained agents' effectiveness.
medium descriptive Full text arxiv
ProdCodeBench: A Production-Derived Benchmark for Evaluating AI Coding Agents · Smriti Jha, Matteo Paltenghi, Chandra Maddila, Vijayaraghavan Murali, Shubham Ug... · Apr 02, 2026
Chinese manufacturers that invest in AI show materially lower carbon intensity, largely by reshaping governance, decarbonizing production and redirecting investment to green assets; the emission gains are concentrated in firms with dispersed supply chains, in environmentally sensitive industries and in regions with underdeveloped factor markets.
medium correlational Summary openalex
Artificial Intelligence Innovation, Internal Structure Optimization and Corporate Carbon Emission Reduction: Experience from China · Xingxing Lu, Lianying Liao, Xiaojuan Luo, Bing Zhao · Apr 02, 2026
Democratic decline and concentrated AI capability risk producing a new neo‑feudal order: a tiny class of infrastructure owners could capture economic value and coercive power, leaving most people politically and economically disenfranchised; standard policy fixes such as UBI may serve as pacification unless confronted by redistributive pressure.
low theoretical Summary openalex
The Great Compression: Geopolitical Fragmentation, AI, and the Coming Neo-Feudal Order · Priyanshu Jain · Apr 02, 2026
Multimodal GeoAI can diagnose transport inequalities across cities but current studies are thin, uneven and poorly validated; the field needs equity-aware models, participatory workflows and stronger data governance such as urban data trusts to translate technical advances into inclusive mobility outcomes.
n/a review_meta Summary openalex
GeoAI and Multimodal Geospatial Data Fusion for Inclusive Urban Mobility: Methods, Applications, and Future Directions · Atakilti Brhanu Kiros, Y. Ribakov, Israel Klein, Achituv Cohen · Apr 02, 2026
Organizing work around people — not just buying technology — unlocks value from automation: the authors show theoretically and document in Colombian firms that better workplace design amplifies returns to technology (management quality raises the marginal return by about 30%), and they introduce a 36‑item index to diagnose firms' human-centric readiness.
medium theoretical Full text arxiv
From Automation to Augmentation: A Framework for Designing Human-Centric Work Environments in Society 5.0 · Cristian Espinal Maya · Apr 01, 2026
Large language models are broadly getting better across text tasks rather than suddenly mastering narrow task clusters: measured success rose from roughly 50% in mid‑2024 to 65% by mid‑2025 and is projected to reach 80–95% for most text tasks by 2029. That suggests gradual, economy‑wide automation (‘rising tide’) rather than imminent, concentrated disruptions, although actual labor impacts will depend on organizational adoption and quality requirements.
medium descriptive Full text arxiv
Crashing Waves vs. Rising Tides: Preliminary Findings on AI Automation from Thousands of Worker Evaluations of Labor Market Tasks · Matthias Mertens, Adam Kuzee, Brittany S. Harris, Harry Lyu, Wensu Li, Jonathan ... · Apr 01, 2026
AI raises wages for workers whose tasks are augmentable — but only in the formal sector; informal workers do not capture augmentation rents, implying labor market institutions, not technology access, are the binding constraint in the Global South.
medium correlational Full text arxiv
Augmented Human Capital: A Unified Theory and LLM-Based Measurement Framework for Cognitive Factor Decomposition in AI-Augmented Economies · Cristian Espinal Maya · Apr 01, 2026
Autonomous coding agents are increasingly active in open-source projects, but their patches are more fragile — agent-authored pull requests are rising in frequency yet are revised or removed at higher rates than human contributions, raising maintainability concerns.
medium correlational Full text arxiv
Investigating Autonomous Agent Contributions in the Wild: Activity Patterns and Code Change over Time · Razvan Mihai Popescu, David Gros, Andrei Botocan, Rahul Pandita, Prem Devanbu, M... · Apr 01, 2026
Generative AI can sharpen managerial performance — but only under emotionally intelligent leadership; without EI-driven trust calibration, AI-enabled delegation and communications risk amplifying errors and eroding team dynamics.
n/a theoretical Summary semantic_scholar
LEADER EMOTIONAL INTELLIGENCE IN THE GENERATIVE AI ERA: “HUMAN–AI LEADERSHIP” AS A NEW MANAGERIAL COMPETENCE · L. Golovkova, K. Hannouf · Fetched Apr 01, 2026
Adding a three-layer enterprise ontology to LLM agents cuts hallucinations and raises compliance and role fidelity: in a 600-run controlled test across five industries, ontology-grounded agents substantially outperformed ungrounded ones on accuracy, regulatory compliance and role consistency, with the biggest benefits in domains poorly covered by the LLM's training data.
medium quasi_experimental Full text arxiv
Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents · Thanh Luong Tuan · Apr 01, 2026
Personality determines who benefits from AI coaching: a theory-driven conversational coach helps overcontrolled negotiators, resilient users improve more from a traditional handbook, and undercontrolled users gain little, suggesting AI coaching should adapt support intensity to individual readiness.
medium rct Full text arxiv
Not My Truce: Personality Differences in AI-Mediated Workplace Negotiation · Veda Duddu, Jash Rajesh Parekh, Andy Mao, Hanyi Min, Ziang Xiao, Vedant Das Swai... · Apr 01, 2026
Code-aware conversational assistants are reshaping developer workflows: rather than giving complete instructions up front, programmers iteratively refine AI outputs, offload diagnosis and validation tasks to models, and steer AI autonomy by embedding context and constraints into ongoing chats.
medium descriptive Full text arxiv
Programming by Chat: A Large-Scale Behavioral Analysis of 11,579 Real-World AI-Assisted IDE Sessions · Ningzhi Tang, Chaoran Chen, Zihan Fang, Gelei Xu, Maria Dhakal, Yiyu Shi, Collin... · Apr 01, 2026
A five‑node value chain and 'Innovation Frontier' map how AI is reshaping legal work, arguing that targeted oversight can contain professional and systemic risks while enabling broader access and quality gains in legal services.
n/a commentary Summary openalex
Rewired: Reconceptualizing Legal Services for the AI Age · Lev Breydo · Apr 01, 2026
AI adoption initially boosts firms' electricity demand—suggesting energy needs outpace early efficiency gains—but the spike fades and is gone after about three years, with larger short-run increases in advanced regions, competitive industries, manufacturing firms, small and non-state firms, and low-tech or low-pollution firms.
medium quasi_experimental Summary openalex
The Impact of AI Adoption on Electricity Output Growth Gap: Evidence from Listed Chinese Firms · Guoyao Wu, Zhiqiang Lan, Yang Xu, Ye Guo · Apr 01, 2026
China's AI pilot zones measurably boost manufacturers' operational resilience: firms in designated AIIAPZ areas show significant gains in resilience driven by lower internal agency frictions and better supply‑chain allocation, with largest effects for coastal, growth-stage, tech- and capital‑intensive firms.
medium quasi_experimental Summary openalex
Does Artificial Intelligence Improve the Operational Resilience of Enterprises? Evidence from the AI Innovative Application Pioneer Zone Policy in China · Yiting Hu, Xu Yan, Chaofan Duan, Xiaodong Yang, Jiaoping Yang · Apr 01, 2026
Robotics manufacturing first raises then lowers urban carbon emissions in China: expansion initially boosts emissions, but once the industry attains moderate scale—especially via system integration—wider robot deployment and efficiency gains cut emissions, with stronger mitigation in central regions than in the east.
medium correlational Full text openalex
Exploring the nonlinear relationship between robotics manufacturing and urban carbon emissions · Jie Lin, Yizhi Xie, Jianfu Shen · Apr 01, 2026
Generative AI can quietly hollow out public knowledge archives by resolving problems privately and discouraging contributors, creating self-reinforcing low-archive traps; nudging users to share AI-assisted solutions can offset private diversion but cannot restore participation-driven declines without policies to sustain contributors.
n/a theoretical Full text openalex
When AI Improves Answers but Slows Knowledge Creation: Matching and Dynamic Knowledge Creation in Digital Public Goods · Keh-Kuan Sun · Apr 01, 2026
Agentic AI could put nearly all information-intensive occupations in major U.S. tech hubs at moderate displacement risk by 2030: a new ATE metric predicts 93% of 236 occupations in five regions cross the moderate-risk threshold, though the result rests on calibrated capability and adoption assumptions; the model also forecasts seventeen emerging human-AI and governance roles.
low theoretical Full text arxiv
Agentic AI and Occupational Displacement: A Multi-Regional Task Exposure Analysis of Emerging Labor Market Disruption · Ravish Gupta, Saket Kumar · Mar 31, 2026