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Higher education, gender‑balanced leadership and digital literacy raise trust in ML credit scoring and increase FinTech adoption in the surveyed developing‑country sample; but perceived algorithmic unfairness and lack of transparency continue to exclude marginalized groups.
low correlational openalex
A Machine Learning Perspective on FinTech-Driven Inclusion: Addressing Algorithm Bias in Credit Scoring Systems in Developing Economies · · Apr 18, 2026
HR technology in Marathwada appears to cut hiring time and costs substantially while improving early employee performance, but the evidence relies on self-reported comparisons and flags algorithmic bias and readiness gaps.
low correlational openalex
A Study on the Effectiveness of Technology-Driven Recruitment and Selection Practices in Modern Organizations · Prashant Madhukar Khedkar · Apr 18, 2026
AI is transforming interdependence into leverage: states can now use data and algorithms to monitor and disrupt trade, finance, and supply chains, turning previously mutual economic ties into instruments of coercion; the result is a global push for resilience, technological sovereignty and selective decoupling.
n/a theoretical openalex
ARTIFICIAL INTELLIGENCE AND THE WEAPONIZATION OF ECONOMIC INTERDEPENDENCE: REDEFINING FOREIGN POLICY IN A MULTIPOLAR WORLD · Muhammad Irfan Magray (Corresponding Author), Dr. Nadia Shaheen, Asia Rahman Kha... · Apr 18, 2026
Investors price AI stocks at a premium because those equities hedge a hypothetical AI 'singularity' that could displace consumption; market incompleteness then inflates valuations and creates a case for government transfers when singularity-driven gains outweigh policy costs.
n/a theoretical openalex
Hedging the Singularity · Andrew Y. Chen · Apr 18, 2026
Replicating two scholars' published reasoning produced scholar-bots that attained senior-lecturer–level evaluations across supervision, peer review and panel debate, suggesting that extractable publication records could enable low-cost functional replacement of some academic labor unless disclosure and compensation rules are adopted now.
low quasi_experimental arxiv
The Relic Condition: When Published Scholarship Becomes Material for Its Own Replacement · Lin Deng, Chang-bo Liu · Apr 17, 2026
What passes for AI accountability often props up the industry: many critiques and reforms act as decoys that conceal the networks of power and extraction making AI possible; to secure real fairness we must reckon with the material political economy behind AI, not just its surface practices.
n/a commentary arxiv
Reckoning with the Political Economy of AI: Avoiding Decoys in Pursuit of Accountability · Janet Vertesi, danah boyd, Alex Taylor, Benjamin Shestakofsky · Apr 17, 2026
A safe deep reinforcement learning controller can halve simulated building heating costs while always honoring grid flexibility requests; the adaptive safety filter secures compliance but incurs a small rise in comfort breaches compared with unconstrained RL.
low descriptive arxiv
Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibility · Colin Jüni, Mina Montazeri, Yi Guo, Federica Bellizio, Giovanni Sansavini, Phili... · Apr 17, 2026
Digital-labor platforms can complete large batches of tasks while paying a vanishing fraction of total labor cost by exploiting workers' uncertainty; however, a small, targeted coalition of low-cost workers enforcing a price floor can force the platform to pay proportional (linear) total wages, while random organizing is largely ineffective.
medium theoretical arxiv
Stochastic wage suppression on gig platforms and how to organize against it · Ana-Andreea Stoica, Celestine Mendler-Duenner, Moritz Hardt · Apr 17, 2026
How you reveal AI matters more than whether it exists: four disclosure modes—No AI, Hidden, Translucent, Visible—trade off accountability, autonomy and coordination costs; the paper maps this design space and supplies a lab instrument to test its effects on team reasoning and authorship.
n/a theoretical semantic_scholar
Who Gets Credit? Operationalizing AI Disclosure as Epistemic Coordination in Human-AI Teams · Hanjing Shi, Dominic DiFranzo · Fetched Apr 17, 2026
Leading language models are overconfident forecasters: none of 11 evaluated models hit the 90% prediction-interval target—Gemini 3.1 Pro (79.1%), Grok 4 (76.4%) and GPT-5.4 (75.3%) perform best—while calibration collapses at extreme magnitudes.
n/a descriptive arxiv
QuantSightBench: Evaluating LLM Quantitative Forecasting with Prediction Intervals · Jeremy Qin, Maksym Andriushchenko · Apr 17, 2026
Deep reinforcement-learning price setters learn to tacitly collude fast: in a simulated continuous-price oligopoly, agents converge to cooperative pricing within empirically realistic timeframes, sustained by reward-punishment schemes that deter deviations.
low theoretical arxiv
Convergence to collusion in algorithmic pricing · Kevin Michael Frick · Apr 17, 2026
An AI 'Test Automation Copilot' sped up regression test-script production at Hacon and reused 30–50% of code, boosting throughput; however, maintainability and domain-correctness still require human review and governance.
low descriptive semantic_scholar
Human-AI Collaboration for Scaling Agile Regression Testing: An Agentic-AI Teammate from Manual to Automated Testing · Moustapha El Outmani, M. Shenoy, A. Hatahet, Andreas Rausch, T. Kniep, T. Raddat... · Fetched Apr 17, 2026
A sovereign AI strategy could raise Cameroon's long‑run productivity by an estimated 1.5–2.8% a year if paired with governance reform and blended finance, but the figure rests on model assumptions rather than micro‑evidence; the paper lays out a three‑layer institutional framework and financing blueprint tailored to Cameroon's political economy.
low descriptive semantic_scholar
A Framework for Sovereign AI Governance and Economic Growth in Cameroon · Eyong Atem · Fetched Apr 17, 2026
In real human-AI interactions, design beats disposition: AI attributes—above all transparency—drive outcomes in hiring and transactional scenarios more than user personality does, although purely simulated agents overstate the influence of human traits.
medium quasi_experimental arxiv
Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies · Myke C. Cohen, Mingqian Zheng, Neel Bhandari, Hsien-Te Kao, Xuhui Zhou, Daniel N... · Apr 17, 2026
State-of-the-art LLMs silently damage documents in long delegated workflows: even top models corrupt roughly a quarter of content by the end, with errors compounding over time and worsening for large files or distractions; using agents or tools does not reliably prevent the decay.
medium descriptive arxiv
LLMs Corrupt Your Documents When You Delegate · Philippe Laban, Tobias Schnabel, Jennifer Neville · Apr 17, 2026
Scroll-and-click consent no longer suffices for AI systems: invisible inferences, model updates, and delegated decisions make traditional privacy disclosures ineffective; interdisciplinary design and a new research agenda are needed to create contextual, usable consent that shapes data flows, firm incentives, and market outcomes.
n/a descriptive openalex
Moving Beyond Clicks: Rethinking Consent and User Control in the Age of AI · William Seymour, Florian Alt, Zinaida Benenson, Sophie Grimme, Farzaneh Karegar,... · Apr 17, 2026
A combined AI-forecasting, blockchain and automation pilot lifted inventory turnover and order-fulfillment efficiency and cut costs in a textile supply-chain trial; however, the evidence comes from a small-scale demonstration without a control group, limiting causal claims.
low descriptive openalex
Intelligent Textile Technology�CDriven Supply Chain Optimization in the Textile Industry · Qin Xu, Jinhong Wu · Apr 17, 2026
E‑commerce comments used as demand signals cut inventory and changeovers at a Taiwanese dyeing SME: a C2M AI system reduced inventory value by 28%, lowered dye-lot changeovers by 31% and raised capacity utilization by 16% in a 12‑month field deployment.
medium quasi_experimental openalex
Enhancing Supply Chain Resilience in Textile SMEs: A Human-Centric Customer-to-Manufacturer Framework Using Public E-Commerce Data · Chien-Chih Wang, Yu-Teng Hsu, Hsuan-Yu Kuo · Apr 17, 2026
China’s manufacturing digital technologies propagate along 14 patent-backed main paths led by core capabilities like image recognition; high-value technologies and recombination potential — not similarity — chiefly shape those paths, though the effects of diversity and proximity differ across firms, universities and regions.
medium correlational openalex
Mapping China’s digital transformation: a multilayer network analysis of technology diffusion in manufacturing · Jialu Ren, Yong Zhou, Yangyang Yang, Shengkai Wang · Apr 17, 2026
Profit-aware classifiers tailored to operational limits improve detection of high-risk cold-start auto-insurance customers and raise expected portfolio profit relative to a standard baseline (p < 0.001). A balanced bagging ensemble gives the best practical trade-off for regulated deployment, while a lightweight Transformer delivers stronger robustness and generalization under data perturbations.
medium correlational openalex
Advanced Insurance Risk Modeling for Pseudo-New Customers Using Balanced Ensembles and Transformer Architectures · Finn L. Solly, Raquel Soriano-Gonzalez, Angel A. Juan, Antoni Guerrero · Apr 17, 2026
Contracts and neutral mediators restore cooperation between powerful LLM agents, while repeated play and reputations often do not; cooperation that appears under repeated interaction collapses when partners change, but mechanisms that enforce contingent payments or delegate decisions sustain cooperative equilibria.
medium quasi_experimental arxiv
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas · Emanuel Tewolde, Xiao Zhang, David Guzman Piedrahita, Vincent Conitzer, Zhijing ... · Apr 16, 2026
AADvark enables agentic AI to design and verify multi-part 3D assemblies with moving joints by pairing LLM code synthesis with constraint solvers and visual feedback; the prototype overcomes previous systems' inability to create functioning pistons, pendulums, or scissor-like mechanisms, though validation is limited to demonstrations rather than industrial testing.
low descriptive arxiv
Agent-Aided Design for Dynamic CAD Models · Mitch Adler, Matthew Russo, Michael Cafarella · Apr 16, 2026
Reasoning is better treated as a shared human–AI protocol than an internal model feat; 'The Architect's Pen' prescribes structured human–model dialogues (articulate, critique, revise) to produce auditable, controllable reasoning and facilitate governance without changing underlying models.
n/a theoretical arxiv
Governing Reflective Human-AI Collaboration: A Framework for Epistemic Scaffolding and Traceable Reasoning · Rikard Rosenbacke, Carl Rosenbacke, Victor Rosenbacke, Martin McKee · Apr 16, 2026
A game-theoretic framework finds that firms in competitive federated learning strategically trade off generating synthetic data against strengthening rivals, and that a payoff-redistribution mechanism can restore cooperation and improve collective model performance.
low theoretical arxiv
Cooperate to Compete: Strategic Data Generation and Incentivization Framework for Coopetitive Cross-Silo Federated Learning · Thanh Linh Nguyen, Nguyen Van Huynh, Quoc-Viet Pham · Apr 16, 2026
Fluent answers from large language models can mask unreliable reasoning; stabilising both human and model processes with uncertainty cues and an Epistemic Control Loop is necessary to make AI trustworthy in high-stakes decision-making.
n/a theoretical arxiv
The Missing Knowledge Layer in AI: A Framework for Stable Human-AI Reasoning · Rikard Rosenbacke, Carl Rosenbacke, Victor Rosenbacke, Martin McKee · Apr 16, 2026