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Nigerian multinationals report big gains from AI–IoT supply‑chain networks — waste falls 30–50% and carbon emissions 20–35% while costs remain competitive, but the findings come from limited non-randomized case evidence.
low correlational openalex
Green Supply Chain Optimization: AI and IoT for Ethical Resource Management in Nigeria · Surulere Omosuyi Julius, Omofolasaye Omobolanle Adegoke, Anuoluwapo Felicia Alab... · May 04, 2026
Human live-streaming anchors generally inspire more trust and purchase intent than AI counterparts, but AI anchors win over efficiency-minded shoppers: intimacy drives trust for hedonic consumers, while responsiveness converts utilitarian buyers only under specific conditions.
medium rct openalex
Conditional trust pathways in live-streaming commerce: how consumer motivation influences responses to human and AI anchors · Yujia Lin, Yue Zou, Xin Wang · May 04, 2026
Nigerian retailers using AI plus IoT to personalize green engagement report 25–40% higher customer loyalty and measurable cuts in energy and waste; however, improvements are observationally linked to AI-driven insights rather than established through randomized evaluation.
low correlational openalex
AI and Iot-Based Customer Behaviour Analysis for Business Enhancement in Nigeria · Omofolasaye Omobolanle Adegoke, Surulere Omosuyi Julius, Sunmola Kayode Fashola ... · May 04, 2026
Conflicting forecasts about which jobs AI will threaten leave public opinion divided, but AI’s capital- and compute-heavy development is concentrating wealth and political influence in tech firms; without gradual policy reforms, these economic shifts risk straining democratic institutions.
low commentary openalex
AI’s Economy and Its Political and Institutional Consequences · Carles Boix, Michael Becher, Valentina González‐Rostani, Daniel Stegmueller · May 04, 2026
A unified standard for AI evaluation RCTs: five validity principles and 33 operational guidelines to ensure causal credibility, repeatability and equitable assessment when measuring how AI affects human performance.
n/a theoretical arxiv
Principles and Guidelines for Randomized Controlled Trials in AI Evaluation · Christopher Kelly, Angelica Chowdhury, Alexandra Campili, Bimpe Ayoola, Devin Ba... · May 03, 2026
AI learns valuable but unverifiable 'implicit' knowledge, creating a persistent reliability gap; instituting structured 'Knowledge Objects' for human validation would make verification economically feasible and let trustworthiness accumulate over time.
n/a commentary arxiv
Reliable AI Needs to Externalize Implicit Knowledge: A Human-AI Collaboration Perspective · Hengyu Liu, Tianyi Li, Zhihong Cui, Yushuai Li, Zhangkai Wu, Torben Bach Pederse... · May 03, 2026
Balanced AI use boosts perceived team effectiveness, but both under-use and over-reliance erode outcomes; active e-leadership — framing, validation checkpoints and human authorship — determines whether AI augments or undermines collaboration.
low descriptive semantic_scholar
E-leadership and human-AI collaboration: socio-technical alignment in project-based teams · Geshwaree Huzooree · Fetched May 03, 2026
Large language models struggle to reach jointly optimal agreements in multi-turn negotiations not for lack of reasoning but because they fail to establish and repair shared meaning; giving them more information or talk does not fully close the coordination gap.
medium descriptive arxiv
Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation · Yiheng Yao, Chelsea Zou, Robert D. Hawkins · May 03, 2026
Lab-style benchmarks and common NLP scores miss systemic failures when AI agents run continuously in production: four of seven production-specific failure modes were invisible to ROUGE, BERTScore and standard agentic benchmarks, and the authors offer PAEF, a continuous, production-oriented evaluation framework and open-source implementation to close the detection gap.
medium descriptive arxiv
Evaluating Agentic AI in the Wild: Failure Modes, Drift Patterns, and a Production Evaluation Framework · Mukund Pandey · May 02, 2026
Cheaply copied, easily deployed AI can aggregate decision-making power into single highly efficient nodes, creating a one-stop source of irreversible system-level harm; safety should therefore prioritize institutional and technical boundary stabilization — layered control, authorization, and externally reviewable limits — not solely perfect alignment.
n/a theoretical arxiv
AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries · Wesley Shu, Peng Wei · May 02, 2026
AI agents could sever the centuries-old link between population trends and GDP growth by acting as economic actors in their own right, creating an expanding 'algorithmic' population and new pressures on pensions, taxation and international competitiveness. Policymakers must measure agent productivity (cFTE), energy use (AEP) and reconsider fiscal and market rules to manage the geoeconomic and social consequences.
n/a theoretical semantic_scholar
DIGITAL AGENTS AS FUNCTIONAL EQUIVALENTS OF ECONOMIC ACTORS: THE DECOUPLING OF DEMOGRAPHICS AND ECONOMIC GROWTH · N. Reznikova, V. Panchenko, M. Grod · Fetched May 02, 2026
Digital-health technologies—including EHRs, telemedicine, AI and IoT—are improving efficiency in Indian hospitals, but benefits are concentrated in cities; lack of funding, poor infrastructure and regulatory gaps prevent widespread adoption in rural areas.
medium review_meta semantic_scholar
A Comprehensive Review of Technology Adoption and Its Impact on Organisational Productivity in the Healthcare Industry in India · Manali Gupta, Dr. Garima Bharadwaj, Dr. Pooja Tiwari · Fetched May 02, 2026
AI development at Chinese listed firms widens wage gaps: firms with more AI-related patents exhibit higher skill premiums and lower labor income shares, with stronger effects in non-state firms, more digitalized firms, and less concentrated industries.
medium quasi_experimental openalex
The Impact of Artificial Intelligence on the Labor Skill Premium: Evidence from Chinese Listed Companies · Hui Liang, Xuxia Zhang, Jingbo Fan · May 02, 2026
A theoretical model finds the AI computing-power industry moves through distinct stages—early 'natural monopoly', mid-period 'regulatory stalemate' traps, and a mature phase of co-opetition—shaped by downstream vertical integration and incumbents' choice to open interfaces, suggesting time-varying, targeted antitrust interventions are required.
n/a theoretical openalex
Evolutionary Dynamics of Openness, Dependence, and Regulation in AI Computing Power Innovation Ecosystem · Zhengrui Li, Qingjin Wang, Shuai Huang, Lan Tian · May 02, 2026
AI coding assistants often boost measurable developer activity but can undermine software reliability — a 'Productivity‑Reliability Paradox' driven by non-deterministic code generation and poor specification governance. A literature synthesis, taxonomy and a short pilot suggest strengthening specification discipline (not only improving models) is the key lever for dependable AI-augmented software development.
low review_meta arxiv
The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development · Sabry E. Farrag · May 01, 2026
Treat the controller, not the model, as Bayesian: applying Bayesian decision theory at the orchestration layer can make agentic AI systems better at choices under uncertainty—keeping beliefs calibrated and actions utility-aware—while avoiding the computational burden of fully Bayesian LLMs.
n/a theoretical arxiv
Position: agentic AI orchestration should be Bayes-consistent · Theodore Papamarkou, Pierre Alquier, Matthias Bauer, Wray Buntine, Andrew Daviso... · May 01, 2026
Retrieval-augmented chat assistants boost human task accuracy across small and large LLMs; but users don't rate larger models as more usable or satisfying, revealing a gap between technical performance gains and user perception.
medium rct arxiv
Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations? · Lennard C. Froma, Tom Kouwenhoven, Maaike H. T. de Boer, Catholijn M. Jonker, Ma... · May 01, 2026
Italian firms that adopt AI see higher productivity and profits and shift hiring toward white-collar roles, while overall employment remains unchanged; adoption is currently concentrated among larger, knowledge‑intensive firms.
medium quasi_experimental semantic_scholar
The economic impact of artificial intelligence: evidence from Italian firms · Tiziano Ropele, A. Tagliabracci · Fetched May 01, 2026
AI is restructuring labour markets: routine tasks are being automated while demand rises for complex cognitive and social skills, creating both productivity gains and transitional risks; targeted reskilling and policy frameworks are necessary to ensure inclusive outcomes.
n/a review_meta semantic_scholar
AI and the Transformation of Human Employment: Challenges, Opportunities and Future Prospects · B. Harshini, Dr.K.B. Ravindra, Dr. Suresh Kurumalla · Fetched May 01, 2026
AI-driven automation threatens semi- and unskilled jobs across Sub‑Saharan Africa, with the greatest risks in manufacturing; without targeted upskilling, labour-market reforms and equitable AI preparedness the technology may deepen unemployment and inequality.
low review_meta semantic_scholar
The Impact of AI-Driven Automation on Semi and Unskilled Workers in Sub-Saharan Africa's Manufacturing Sector: A Socio-Economic Analysis and Policy Perspective · Dr Vusi S. Mncube · Fetched May 01, 2026
Creators hide their use of generative AI to preserve authenticity, turning 'efficiency' gains into downstream repair and performance work; those with more education, money, or team support are better able to pass, widening trust-based inequality.
low descriptive semantic_scholar
AI passing and invisible authenticity labor: trust vulnerabilities and inequality in China's short-video creator economy · Xiaolong Su, Tingli Liu, Zhuoqi Ye, Yixue Mei · Fetched May 01, 2026
AI lifted Russia's potential GDP in 2023–2025, driven primarily by productivity gains and process optimisation; however, benefits were uneven across industries and limited by digital readiness, human-resource shortages and institutional constraints.
low descriptive semantic_scholar
THE IMPACT OF AI ON POTENTIAL GDP AND LONG-TERM ECONOMIC GROWTH · Karina Yu. Sherstyukova, V. S. Tormozov, S. Syurkova · Fetched May 01, 2026
A tokenized, self-devaluing commodity currency is proposed as a global 'honest money' for the AI era; the design aims to protect cross-border AI capital allocation from fiat depreciation but remains untested and faces legal, monetary-policy and adoption barriers.
n/a theoretical arxiv
RSDM: The Consensus Honest Money in the AI Era · Boliang Lin, Ruixi Lin · May 01, 2026
Smaller open-weight models can perform the bulk of routine agent tasks faster and cheaper than frontier models, but complex long-horizon planning still favors the largest systems; a hybrid design — small models for routine actions, big models for deep planning — is a practical way to build agentic pipelines.
medium descriptive arxiv
AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go? · Ranit Karmakar, Jayita Chatterjee · May 01, 2026
Endpoint-level differences — not just model families — drive large swings in accuracy, latency and cost: the same model served from different endpoints can vary by over 10 percentage points in accuracy, an order of magnitude in tail latency, and multiple-fold in energy and dollars per correct answer, changing which endpoints look best once realistic workloads are considered.
medium descriptive arxiv
Token Arena: A Continuous Benchmark Unifying Energy and Cognition in AI Inference · Yuxuan Gao, Megan Wang, Yi Ling Yu · May 01, 2026