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Telling customers a chatbot is AI and adopting an empathetic, personalized tone boosts trust and lifts purchase intent among UAE youth. Perceived manipulation cuts conversion, but higher digital literacy blunts that harm, suggesting transparency and explainable personalization are pro-competitive and pro-consumer.
medium rct openalex
AI Chatbots as Informatics-Enabled Marketing Service Systems: Trust, Transparency, and Youth User Responses · · Mar 06, 2026
A governed hyperautomation pattern—combining low-code, RPA and generative AI with embedded policy, human‑in‑the‑loop checks and continuous monitoring—lets firms scale automation without sacrificing compliance or stability; the approach raises upfront governance costs but can lower risk‑adjusted total cost of ownership and reshape labor demand toward oversight and AI‑engineering roles.
low descriptive openalex
Governed Hyperautomation for CRM and ERP: A Reference Pattern for Safe Low-Code, RPA, and Generative AI at Enterprise Scale · Siva Prasad Sunkara · Mar 06, 2026
AI and green technology are the new engines of creative destruction, reshaping productivity and competitive hierarchies; how much they raise broad prosperity depends on long-wave cycles, supply-chain fragilities and political‑economic forces that determine diffusion, market structure and distributional outcomes.
low theoretical openalex
Economic Waves, Crises and Profitability Dynamics of Enterprises: A Review in the Context of Kondratieff, Schumpeter and Mandel Approaches · Banu HAS, Fatih Koç, Sinan ÇINAR · Mar 06, 2026
A dynamic, task-based AI exposure architecture would modernize BLS labor projections by mapping LLM-driven capabilities to occupations and combining real-time signals with causal inference to forecast displacement, augmentation, and skill transitions; its success depends on data access, robust LLM validation, and careful backtesting.
n/a descriptive openalex
Enhancing BLS Methodologies for Projecting AI's Impact on Employment: A Data-Driven Framework for Measuring Labor Market Transformation · Satyadhar Joshi · Mar 06, 2026
Climate AI is being built on Northern compute and data, producing systematically weaker and potentially misleading outputs for vulnerable, data-sparse regions; public investment in shared data, distributed compute, and co-produced evaluation is needed to prevent costly maladaptation and entrenched informational inequality.
low review_meta arxiv
The Rise of AI in Weather and Climate Information and its Impact on Global Inequality · Amirpasha Mozaffari, Amanda Duarte, Lina Teckentrup, Stefano Materia, Gina E. C.... · Mar 05, 2026
The shape of compute pipelines determines whether decentralised pricing works: hierarchical service graphs converge to stable, optimal allocations, but cross-cutting dependencies cause price oscillations and poor allocation quality; wrapping complex subgraphs into integrator 'resource slices' cuts price volatility by roughly 70–75% while preserving throughput.
medium theoretical arxiv
Real-Time AI Service Economy: A Framework for Agentic Computing Across the Continuum · Lauri Lovén, Alaa Saleh, Reza Farahani, Ilir Murturi, Miguel Bordallo López, Pra... · Mar 05, 2026
Current extrapolation‑based labor projections miss AI’s nonlinear, spillover, and augmentation effects; a task‑level, LLM‑enabled Occupational AI Exposure Score integrated with real‑time data and causal inference would give policymakers earlier, more precise forecasts of displacement and reallocation risks.
n/a descriptive openalex
Enhancing BLS Methodologies for Projecting AI's Impact on Employment: A Data-Driven Framework for Measuring Labor Market Transformation · Satyadhar Joshi · Mar 05, 2026
Language-model agents that perceive, deliberate and act reproduce human-like adaptive behavior in epidemic–economic simulations, producing divergent health and economic trajectories and enabling quantitative trade-off analysis; the framework is robust across several LLMs but requires empirical calibration before real-world policy use.
low descriptive openalex
An LLM-Driven Multi-Agent Simulation Framework for Coupled Epidemic–Economic Dynamics · S. Wang, Huiyong Liu, Na Wang, Qunsheng Yang · Mar 05, 2026
A practical blueprint for reversible AI leadership: the Dynamic Authority Reversal framework turns human oversight into a measurable, auditable, and testable process—enabling controlled AI-led decisions while preserving accountability through hysteresis, safe-exit timers and a Reversal Register.
n/a theoretical openalex
Human–AI Handovers: A Dynamic Authority Reversal Framework for Trust Calibration and Transitional Accountability · Jonathan H. Westover · Mar 05, 2026
Agentic AI makes alignment an ongoing organizational cost: systems that generate open-ended actions, novel outputs, and evolving goals turn coordination into a continuous process of projection, monitoring and renegotiation rather than a one-off specification task; firms that can cheaply sustain persistent alignment gain a competitive edge.
n/a theoretical openalex
Visioning Human-Agentic AI Teaming: Continuity, Tension, and Future Research · Bowen Lou, Tian Lu, T. S. Raghu, Yingjie Zhang · Mar 05, 2026
When paired with mechanistic priors, synthesis‑aware design, robust external validation and regulatory alignment, AI can cut drug development time and raise early‑phase success rates; absent proper validation, dataset bias and misalignment with regulators can negate gains and create costly setbacks.
medium review_meta openalex
Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision · Shota Furukawa, Hiroyuki Uchida, Gabriela Novak · Mar 05, 2026
An augmented-reality system driven by a multimodal LLM cuts CMM task time and perceived workload while preserving measurement accuracy, enabling less-expert operators to complete precision measurement tasks faster; the result suggests productivity and training-cost gains in precision manufacturing, but evidence is limited to a single-machine case study and modest sample.
low descriptive openalex
Augmented Reality-Based Training System Using Multimodal Language Model for Context-Aware Guidance and Activity Recognition in Complex Machine Operations · Waseem Ahmed, Qingjin Peng · Mar 05, 2026
Mapping consulting tasks to generative-AI strengths can boost consultant efficiency, but only with strong verification and governance; otherwise hallucinations and gradual loss of routine skills threaten quality and long‑term capabilities.
low descriptive openalex
Where Automation Meets Augmentation: Balancing the Double-Edged Role of Generative AI in Management Consulting · Matthias Tuczek, Kenan Degirmenci, Michael H. Breitner, Kevin C. Desouza, Richar... · Mar 05, 2026
A modular agent architecture (CRAEA) significantly boosts simulated home-robot planning, memory-based question answering and routing, making long-horizon natural-language household tasks more reliable; gains are shown in simulation and human ratings but real-world robustness and deployment costs remain untested.
medium descriptive openalex
Context-Rich Adaptive Embodied Agents: Enhancing LLM-Powered Task Planning and Memory in Home Robotics · Yutian Gai, Haoyu Cen · Mar 05, 2026
Trust and apparent accuracy determine whether AI helps finance teams: where both are high, firms make faster, more data-driven strategic pivots and improve risk management; but misplaced trust, cognitive biases and low AI literacy can create systemic risks and blunt productivity gains.
medium correlational openalex
Human-AI Synergy in Financial Decision-Making: Exploring Trust, Precision, and Organizational Agility · Dr. Salman Arafath Mohammed · Mar 05, 2026
AI promises sectoral productivity gains across Africa but risks entrenching foreign control and social harm if data ownership, linguistic and cultural constraints, and local capacity are ignored; a governance framework grounded in Afro‑communitarianism and stakeholder participation is proposed to steer AI toward inclusive, locally rooted development.
n/a theoretical openalex
Towards Responsible Artificial Intelligence Adoption: Emerging and Existing Ethical Issues in Africa · Dolapo Faith Sule · Mar 05, 2026
Clinical uptake of EEG AI hinges on explainability as much as accuracy; current XAI techniques are frequently fragile, inconsistent, and poorly aligned with neurophysiology, creating regulatory and adoption headwinds for commercialization.
n/a review_meta openalex
Explainable Artificial Intelligence (XAI) for EEG Analysis: A Survey on Recent Trends and Advancements · Vassilis Lyberatos, Georgios Kontos, Nikolaos Spanos, Orfeas Menis Mastromichala... · Mar 05, 2026
A publicly available library of 2,193 high-resolution 3D ant scans links morphology to genomes and slashes data-acquisition barriers for biological AI; the open resource shifts value toward model development, compute, and services while enabling new biodiversity and trait-analytics markets.
n/a descriptive openalex
High-throughput phenomics of global ant biodiversity · Julian Katzke, F. Javier García, Jacob J. Relle, Fumika Azuma, Tomáš Faragó, La... · Mar 05, 2026
Large language models can act as 'brains' for modern microscopes, automating protocol design, instrument control and data analysis to speed experiments and raise the value of software and data; yet their deployment creates reproducibility, safety and concentration risks that demand standards, benchmarks and public interventions.
n/a review_meta openalex
ChatMicroscopy: A Perspective Review of Large Language Models for Next-Generation Optical Microscopy · Giuseppe Sancataldo · Mar 05, 2026
Treating EdTech firms as recipients of federal education funding would make vendors directly liable for discriminatory AI tools, forcing firms to internalize nondiscrimination obligations. The shift would reshape procurement, raise compliance costs, and alter market incentives for innovation and entry in the EdTech sector.
n/a commentary openalex
Civil Rights and the EdTech Revolution · Kirsten Mettler · Mar 05, 2026
Treating AI systems like patients could create a market for diagnostics, certification and remediation: 'Model Medicine' lays out taxonomies, imaging tools and reporting standards (Neural MRI, M-CARE) that would let purchasers, insurers and regulators assess model ‘health’ — but empirical support so far comes mainly from a single experimental corpus (Agora-12) and four case studies.
low theoretical openalex
Model Medicine: A Clinical Framework for Understanding, Diagnosing, and Treating AI Models · Jihoon Jeong · Mar 05, 2026
A model-agnostic pipeline using LLM-driven semantic normalization and density-based clustering uncovers coherent research themes in ML and NLP conference abstracts. The method scales to large corpora and generates interpretable topic maps that can be used to track research frontiers and build indicators for economic analysis, though results require robustness checks across models and prompts.
n/a descriptive openalex
Soft-Prompted Semantic Normalization for Unsupervised Analysis of the Scientific Literature · Ivan Malashin, Dmitry Martysyuk, Vadim Tynchenko, Andrei Gantimurov, V. A. Nelyu... · Mar 05, 2026
AI-guided microbial ‘factories’ are shortening design cycles and promising cheaper, greener routes to complex chemicals, but most successes are confined to the lab or pilot scale and persistent scale-up and regulatory hurdles will shape who benefits and how fast.
n/a review_meta openalex
Harnessing Microbial Factories: Biotechnology at the Edge of Synthetic Chemistry · Dr. S. Mohamed Rabeek · Mar 05, 2026
Digital finance widens access and slashes transaction costs, but risks amplifying inequality and systemic fragility; without data governance, competition safeguards and algorithmic oversight, platformization can lock in exclusion as well as convenience.
n/a review_meta openalex
Financial Inclusion in the Age of FinTech Platforms: Opportunities, Inequalities, and Regulatory Dilemmas · Kumaraswamy M, D. Swapna Devi · Mar 05, 2026
A ten-minute onboarding session substantially raised voluntary use of an LLM and produced measurable performance gains on a law-school exam: training increased usage from 26% to 41% and improved scores by 0.27 grade points, whereas untrained access delivered no score benefit.
medium rct openalex
Training for Technology: Adoption and Productive Use of Generative AI in Legal Analysis · Benjamin Minhao Chen, Hong Bao · Mar 05, 2026