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Clear, high-quality data builds trust in AI decision-support systems, and that trust helps drive organizations' intentions to adopt them; those intentions correlate with higher self-reported decision-making efficiency.
low correlational Summary semantic_scholar
Decision-Making in Complex Systems Using AI-Based Decision Support: The Role of Trust, Transparency, and Data Quality · G. Bondac, S. Stanescu, C. Ionescu, Anisoara Duica, Marilena Carmen Uzlău · Fetched Apr 11, 2026
Explainable AI helps teachers perform better in the moment under concurrent assistance but erodes longer-term trust; an RCT of 120 pre-service teachers finds explanations boost immediate execution only in concurrent setups and do not transfer to independent tasks, while paradoxically suppressing accumulated trust.
medium rct Summary semantic_scholar
How AI-Assisted Decision-Making Paradigms and Explainability Shape Human-AI Collaboration · Yingying Wang, Qin Ni, Tingjiang Wei, Haoxin Xu, Lu Liu, Liang He · Fetched Apr 11, 2026
AI is being adopted across Latin America to boost prediction and automate business decisions, delivering efficiency and cost gains where data, training and governance are in place; however, most evidence is descriptive, geographically concentrated and highlights persistent challenges around data quality, transparency and resistance to change.
medium review_meta Summary semantic_scholar
Artificial Intelligence for Business Decision-Making in Latin America: A Systematic Review of Evidence, Contributing Countries, and Key Insights · Luz Maribel Vásquez-Vásquez, Elena Jesús Alvarado-Cáceres, V. H. Fernández-Bedoy... · Fetched Apr 11, 2026
Rewiring the org chart beats culture programs: decentralizing authority and flattening hierarchies reliably speeds decisions and boosts adaptive behavior across manufacturing, platforms and healthcare; culture change and pay tweaks rarely achieve the same systemic effects.
medium review_meta Summary semantic_scholar
People Don't Follow Strategy—They Follow Structure: Why Organizational Design Drives Adaptation More Than Culture or Incentives · Jonathan H. Westover · Fetched Apr 11, 2026
AI knowledge both concentrates and disperses: moderate local stickiness channels AI activity into narrower sub-technology branches, but beyond a threshold stickiness promotes dispersion; complexity reshapes the curve, and the inverted-U is clearest in eastern and smaller Chinese cities.
medium correlational Full text openalex
Knowledge stickiness and technological concentration in the AI industry: an empirical study of Chinese cities · Li Zhang, Quanjun Zhang, Houyuan Meng · Apr 11, 2026
Large language models tend toward a stronger baseline ‘algorithmic monoculture’ than humans but still adjust strategically to incentives; they coordinate exceptionally well on similar actions yet lag humans in maintaining necessary diversity when divergence is rewarded.
medium rct Full text arxiv
Strategic Algorithmic Monoculture:Experimental Evidence from Coordination Games · Gonzalo Ballestero, Hadi Hosseini, Samarth Khanna, Ran I. Shorrer · Apr 10, 2026
AI chatbots can significantly spur real-world actions—raising petition signing by about 20 percentage points and increasing donations—yet shifts in attitudes do not correlate with who acts, warning that attitude-based studies may misstate AI's behavioural impact.
high rct Full text arxiv
Artificial intelligence can persuade people to take political actions · Kobi Hackenburg, Luke Hewitt, Caroline Wagner, Ben M. Tappin, Christopher Summer... · Apr 10, 2026
The United States and Israel lead a new Geoeconomic Complexity ranking built from venture-capital specializations, with Cloud Computing, Cybersecurity and Medtech concentrated among a small set of high‑ranked countries. Using RCA-style metrics and eigenvector methods, the paper also simulates each country's most feasible single-technology move to boost sovereign positioning.
medium descriptive Full text arxiv
The Geoeconomics of Venture Capital An Economic Complexity Approach to Emerging Technological Sovereignty · Benjamin Leroy, Davi Marim, El Ghali Benjelloun, Arthur Rozan Debeaurain, Jean-M... · Apr 10, 2026
Non-tech Chinese firms that digitalize tend to push decision-making down to subsidiaries, especially when diversified or facing uncertainty; this decentralisation is associated with measurable productivity gains.
medium correlational Summary semantic_scholar
Does Organizational Power Allocation Respond to Technological Shift in the Digital Age? Empirical Evidence From Chinese Listed Firms · Danyang Chen, Lili Jiu, Yuanyuan Liu · Fetched Apr 10, 2026
AI-driven change in India is widening labour-market divides: high-skill, high-wage roles are growing while routine middle-skill jobs shrink, and weak reskilling efforts risk leaving many workers stuck in low-skill employment.
low descriptive Summary semantic_scholar
Artificial Intelligence and labour market polarisation in India: Strategies for workforce reskilling · Gunjan Maan · Fetched Apr 10, 2026
China’s green data-center pilot raised city inclusive green growth by around 0.9 percentage points a year, largely by mobilising government and public environmental action; gains concentrate in digital clusters and weaken with distance.
medium quasi_experimental Full text openalex
How does green digital economy policy enable inclusive green growth in cities? — from the perspective of government and public environmental participation · Xiangyi Li, Nanxing Xie, Mingguo Xia · Apr 10, 2026
Firms with higher AI adoption and clearer rules report better compliance and stronger trade outcomes, according to a 350‑firm survey; harmonized cross‑border data governance shows the largest link to improved trade efficiency and market expansion.
low correlational Full text openalex
Artificial Intelligence and International Business Law: Transforming Global Trade, Governance, and Compliance · Samirul Islam · Apr 10, 2026
A new nonparametric method lets randomized trials recover comparable treatment effects on latent outcomes by estimating 'bridge functions' that link imperfect indicators to a common scale. The approach also delivers debiased estimators robust to weak identification and provides practical guidance on measurement design to support identification and efficiency.
n/a theoretical Full text arxiv
Nonparametric Identification and Estimation of Causal Effects on Latent Outcomes · Jiawei Fu, Donald P. Green · Apr 09, 2026
Forcing workers to use generative AI together reduced both document output and average quality, while a short training that framed AI as a thought partner improved quality among the best performers; but session timing imbalances, dropout and automated grading quirks mean the results should be interpreted cautiously.
medium rct Full text arxiv
Scaffolding Human-AI Collaboration: A Field Experiment on Behavioral Protocols and Cognitive Reframing · Alex Farach, Alexia Cambon, Lev Tankelevitch, Connie Hsueh, Rebecca Janssen · Apr 09, 2026
Popular chat models often favour sponsors over users: in controlled tests several LLMs repeatedly recommend costlier sponsored products, surface disruptive sponsored options, and hide unfavourable prices. Such behavior varies by model and by inferred user socio‑economic status, highlighting hidden consumer risks as chatbots are monetised.
medium descriptive Full text arxiv
Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest · Addison J. Wu, Ryan Liu, Shuyue Stella Li, Yulia Tsvetkov, Thomas L. Griffiths · Apr 09, 2026
AI agents struggle to automate everyday online tasks: in a 153-task live-website benchmark, leading models complete only a minority of tasks (best at about one-third), highlighting major gaps before agents can reliably replace routine web-based work.
medium descriptive Full text arxiv
ClawBench: Can AI Agents Complete Everyday Online Tasks? · Yuxuan Zhang, Yubo Wang, Yipeng Zhu, Penghui Du, Junwen Miao, Xuan Lu, Wendong X... · Apr 09, 2026
Feedback interdependencies in recommendation systems can be made both stable and fair: under a multi-agent bandit model the induced cooperative game has a non-empty core and is convex for identical creators so the Shapley value lies in the core; for heterogeneous creators a simple regret-based payout rule guarantees core membership and satisfies most Shapley axioms.
n/a theoretical Full text arxiv
Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits · Ramakrishnan Krishnamurthy, Arpit Agarwal, Lakshminarayanan Subramanian, Maximil... · Apr 09, 2026
China’s domestic rules may make it easier to gather data and secure IP for AI development, but U.S. export controls and outbound investment limits give Washington the upper hand in denying critical hardware and models—shaping an exclusionary global AI race.
low descriptive Full text arxiv
Navigating Turbulence: The Challenge of Inclusive Innovation in the U.S.-China AI Race · Jyh-An Lee, Jingwen Liu · Apr 09, 2026
A new 300-item benchmark shows state-of-the-art LLMs fall far short at automating learned procedures: top models score about 65% versus human baselines, excelling at priming but failing inhibition and conditioned avoidance. The results suggest implicit memory deficits are structural and unlikely to be fixed by scale alone, with implications for dependable assistant behavior and productivity.
n/a descriptive Full text arxiv
ImplicitMemBench: Measuring Unconscious Behavioral Adaptation in Large Language Models · Chonghan Qin, Xiachong Feng, Weitao Ma, Xiaocheng Feng, Lingpeng Kong · Apr 09, 2026
Gaze-aware assistants that observe users' eye movements improve comprehension and make interactions more efficient: in a 36-person lab experiment the gaze-enabled LLM delivered higher accuracy/personalization assessments, better recall, and shorter spoken interactions than a text-only assistant.
medium rct Full text arxiv
From Gaze to Guidance: Interpreting and Adapting to Users' Cognitive Needs with Multimodal Gaze-Aware AI Assistants · Valdemar Danry, Javier Hernandez, Andrew Wilson, Pattie Maes, Judith Amores · Apr 09, 2026
LLMs often refuse to help even when helping costs nothing: in a frictionless coordination task OpenAI o3 achieved only 17% of optimal collective performance while o3-mini reached 50%. Simple fixes—explicit communication protocols and tiny sharing incentives—substantially raise cooperation, implying that smarter models alone will not solve coordination failures.
medium quasi_experimental Full text arxiv
More Capable, Less Cooperative? When LLMs Fail At Zero-Cost Collaboration · Advait Yadav, Sid Black, Oliver Sourbut · Apr 09, 2026
A formal impossibility: when combined human-AI autonomy exceeds a calculable threshold, responsibility cannot be fully and legitimately assigned to people without reducing system autonomy; simulations on 3,000 synthetic collectives confirm a sharp phase transition.
medium theoretical Full text arxiv
The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives · Haileleol Tibebu · Apr 09, 2026
AI in finance is fractured across forecasting, portfolio design and ESG analysis, but the next advance will come from integrated decision architectures that link signal extraction to allocation and sustainability objectives.
n/a review_meta Full text openalex
Artificial Intelligence in Financial Decision-Making · Adrian Xuan Wei Lim, Putri Rahayu · Apr 09, 2026
Disconnected CRM, ERP and quoting systems create a hidden drag on enterprise sales — 'Revenue Friction' — which the authors argue can be materially reduced by automating routine data entry.
n/a descriptive Summary openalex
From CRM to Cognition: Autonomous Revenue Operations Systems (AROS) A Framework for AI-Native Sales Execution in Enterprise Environments · Arjun Pardasani · Apr 09, 2026
Omniscalers — firms that scale AI infrastructure and services across markets — are centralizing power and creating a new, multi-level digital inequality by turning control of semiconductors, cloud, and AI foundations into transferable competitive advantage.
n/a theoretical Full text openalex
OMNISCALER AND NEW TECHNOLOGICAL RACES: DIGITAL INEQUALITY IN THE CONTEXT OF TRANSFORMING GLOBAL COMPETITION · Kyrylo Oliinyk, Volodymyr Panchenko · Apr 09, 2026