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AI risks eroding low-cost labor advantages and reshaping global supply chains, pushing production closer to advanced or allied economies; governments must integrate trade, industrial and digital policies to manage the geopolitical and development consequences.
n/a theoretical Full text openalex
Yapay Zekâ ve Küresel Değer Zincirleri: Ticaret Politikası ve Rekabet Gücü Açısından Bir Değerlendirme · Yunus Ediz, Seçkin Kabak · May 16, 2026
A new task-level atlas finds automation exposure ranges from about 3% of tasks in the poorest countries to over 60% in China, rising strongly with income; low-income countries face relatively more labour-substituting and low-tech automation, whereas AI is more prevalent and more often labour-augmenting in richer economies.
medium descriptive Full text openalex
Global Automation Atlas · Prashant Garg, Tommaso Crosta, Jasmin Baier · May 16, 2026
Rising AI rack power densities risk 'stranding' datacenter power — installed megawatts can vastly overstate usable capacity. Simulations using Azure data show multi-resource stranding cuts deployable capacity and inflates effective capital costs, so long-run planning must prioritize deployable capacity across generations, not simply installed power.
medium descriptive Full text arxiv
Designing Datacenter Power Delivery Hierarchies for the AI Era · Grant Wilkins, Fiodar Kazhamiaka, Alok Gautam Kumbhare, Chaojie Zhang, Ricardo B... · May 15, 2026
Programmatic state abstraction delivers the biggest performance-per-cost gains in a cyber-defense POMDP (up to 76% higher mean return per token), whereas scattering deliberation tools across hierarchical sub-agents backfires—cutting mean return by up to 3.4× and raising token use 1.8–2.7×; clean modular design, not deeper per-agent reasoning, tends to win.
medium quasi_experimental Full text arxiv
Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDP · Igor Bogdanov, Chung-Horng Lung, Thomas Kunz, Jie Gao, Adrian Taylor, Marzia Zam... · May 15, 2026
Simple pricing algorithms that ignore rivals can drive persistent supra-competitive pricing — and under symmetric exploration can reach monopoly levels. Calibrated simulations show these collusive-like outcomes arise robustly even with finite horizons and product heterogeneity.
medium theoretical Full text arxiv
Misspecified Explore-then-Exploit Leads to Supra-Competitive Prices · Jackie Baek, Vivek F. Farias, Farrell Wu · May 15, 2026
Palliative care generally reduces families' medical bills and unpaid caregiving time across Europe, but for the most vulnerable and non‑cancer cases it can expose households to catastrophic costs and time poverty, especially in underfunded systems.
medium quasi_experimental Full text semantic_scholar
The Broken Shield of European Palliative Care: Evidence from Synthetic Counterfactuals on Financial Toxicity and Informal Care · P. Grassi, Edoardo Paperi, Chiara Seghieri, D. Vignoli · Fetched May 15, 2026
AI-driven skill volatility is generating 'reskilling fatigue' among mid-career knowledge professionals, eroding confidence and mastery; organizations can blunt the cycle through role-linked learning, protected learning time, skill prioritization, and phased AI adoption.
n/a theoretical Summary semantic_scholar
AI-driven skill volatility and the emergence of re-skilling fatigue: the human cost of perpetual learning · T. Biju, Anusree Ambady, T. K. V. · Fetched May 15, 2026
A 320-worker survey links AI adoption to job restructuring and pay shifts: firms reporting AI use show higher demand for skilled workers and declines in routine roles, with widening wage gaps driven by uneven skill adaptation.
low correlational Summary semantic_scholar
ARTIFICIAL INTELLIGENCE, AUTOMATION, AND LABOR MARKET TRANSFORMATION: EVIDENCE ON EMPLOYMENT, SKILLS, AND WAGE DYNAMICS · Khair Bux Mangrio, Sara Zaidi, Saeed Ahmed · Fetched May 15, 2026
A continuous, simulation-driven prompt engineering system slashes median prompt authoring time from two days to under 30 minutes and maintains 99% reliability across 35 enterprise chatbots, while detecting and repairing LLM behavioral drift within 24 hours.
medium descriptive Full text arxiv
PRISM: Prompt Reliability via Iterative Simulation and Monitoring for Enterprise Conversational AI · Keshava Chaitanya, Jahnavi Gundakaram · May 15, 2026
AI is changing the nature of work by automating tasks, not entire occupations: about 9% of jobs are fully automatable, yet almost every role will be affected. Who wins or loses will hinge on firms' training choices and public policy, with displacement concentrated among older and lower-mobility workers.
medium commentary Summary openalex
7. AI and the Future of Work · Bianca de Teffé Erb · May 15, 2026
AI systems and vendor consolidation have turned parts of the academic library into a franchise model: a few suppliers control roughly 84% of ARL market share while automated cataloguing performs poorly (≈26% F1), leaving librarians accountable for opaque, vendor-controlled systems that prioritize cost-cutting over information access.
medium descriptive Full text openalex
Operating the franchise: vendor consolidation, algorithmic mediation, and the remaking of academic librarians as platform administrators for digital capitalism · Mike Olson · May 15, 2026
Behavioural testing and red‑teaming cannot guarantee the absence of hidden objectives or long‑horizon agentic behaviour, creating an 'audit gap' between what regulators demand and what can be verified; regulators should limit reliance on behavioural evidence and require deeper mechanistic access such as probes, activation patching, and pre/post‑training comparisons.
n/a commentary Full text arxiv
Position: Behavioural Assurance Cannot Verify the Safety Claims Governance Now Demands · Pratinav Seth, Vinay Kumar Sankarapu · May 14, 2026
A new staggered DiD method separates direct and spillover effects by comparing units with identical exposure profiles and estimating spillovers from never‑treated units; applied to Community Health Centers, spillovers explain a substantial share of the observed decline in older‑adult mortality, and ignoring them biases standard DiD estimates.
medium theoretical Full text arxiv
Identification and Estimation of Staggered Difference-in-Differences with Network Spillovers · Hayato Tagawa · May 14, 2026
How you collect data determines how well you can evaluate AI: concentrating logging on high-reward actions cuts variance but risks missing signals a target policy will take, and this paper derives optimal and practical logging policies to minimize off-policy evaluation error under different knowledge regimes.
low theoretical Full text arxiv
Logging Policy Design for Off-Policy Evaluation · Connor Douglas, Joel Persson, Foster Provost · May 14, 2026
Better models can make property taxes both fairer and more accurate: across nearly all U.S. counties, adding property attributes and public Census data to assessment models reduces valuation errors and the regressivity of tax burdens, undermining the assumed inevitability of a fairness–accuracy trade-off.
medium correlational Full text arxiv
Tradeoffs are Domain Dependent: Improving Accuracy and Fairness in Property Tax Assessments · Evelyn Smith, Emma Harvey, Christopher Berry, Jacob Goldin, Daniel E. Ho · May 14, 2026
A system that pairs LLM-written C code with automatically generated, machine-checked assertions helps people understand code faster and more accurately; in a study of 400+ participants across 18 tasks, these annotations improved code-comprehension performance.
medium quasi_experimental Full text arxiv
Viverra: Text-to-Code with Guarantees · Haoze Wu, Rocky Klopfenstein, Keith Farkas, Nina Narodytska · May 14, 2026
A visual, executable workflow system recorded a 97.08% completion rate over 8,728 clinical runs in a year-long pilot, but the core formal verification promised by the design has not yet been tested and most errors traced to external integrations.
low descriptive Full text arxiv
GraphFlow: An Architecture for Formally Verifiable Visual Workflows Enabling Reliable Agentic AI Automation · Drewry H. Morris, Luis Valles, Reza Hosseini Ghomi · May 14, 2026
Agentic AI trims customer-service handling time but chips away at satisfaction: Taobao's experiment shows faster chats and improved attention to non-AI cases, yet customer ratings fall for AI-resolved conversations. Human interventions patch technical failures effectively, but struggle to assuage emotionally escalated customers unless engaged early and intensively.
high rct Full text arxiv
Agentic AI and Human-in-the-Loop Interventions: Field Experimental Evidence from Alibaba's Customer Service Operations · Yiwei Wang, Chuan Zhu, Tianjun Feng, Lauren Xiaoyuan Lu, Bingxin Jia · May 14, 2026
Text-only policy prompts let LLMs produce plausibly compliant but uninformative rationales; adding mechanical enforcement outside the model halves hollow deferrals and more than doubles rationale information, lifting task accuracy from MCC ~0.43 to 0.88.
medium quasi_experimental Full text arxiv
Mechanical Enforcement for LLM Governance:Evidence of Governance-Task Decoupling in Financial Decision Systems · José Manuel de la Chica Rodríguez, Carlos Martí-González · May 14, 2026
A specialist virtual sales host, VerbalValue, fine-tuned on product knowledge and annotated live-commerce dialogs, outperforms leading LLMs—raising informativeness by 23% and factual accuracy by 18%—and produces more tactful, engaging responses. The results are promising for automated live commerce but rest on a small annotated dataset and proxy engagement metrics rather than measured purchase conversion.
medium quasi_experimental Full text arxiv
VerbalValue: A Socially Intelligent Virtual Host for Sales-Driven Live Commerce · Yuyan Chen · May 14, 2026
AI in engineering appears to lift team productivity by roughly 24% but threatens nearly one-in-five engineering tasks with obsolescence; firms that proactively integrate AI can more than halve that risk.
low descriptive Summary semantic_scholar
The AI-engineering imperative - Navigating synergy and obsolescence · Simon Suwanzy Dzreke, Semefa Elikplim Dzreke, Evans Dzreke, Franklin Manasey Dzr... · Fetched May 14, 2026
Integrated AI in marketing analytics is linked to large gains in campaign ROI—about 47% higher—yet raises labor concerns about obsolescence; combining human judgement with algorithms (augmented intelligence) is associated with substantially lower attrition than full automation.
low correlational Summary semantic_scholar
Augmented Intelligence: Resolving the AI integration-obsolescence dilemma in marketing operations · Simon Suwanzy Dzreke, Semefa Elikplim Dzreke · Fetched May 14, 2026
A new Intelligence Impact Quotient (IIQ) quantifies how deeply AI is embedded in work by combining time-decayed token stocks, usage frequency, recency gates and measures of leverage, task complexity and autonomy. Unlike raw usage counts, IIQ aims to separate repetitive low-leverage prompting from higher-consequence, autonomous AI-assisted tasks and offers bounded interpretations of efficiency and financial impact for deployment monitoring.
n/a descriptive Full text arxiv
Intelligence Impact Quotient (IIQ): A Framework for Measuring Organizational AI Impact · Chandan Rajah, Neha Sengupta, Federico Castanedo, Robin Mills, Amit Bahree, Rame... · May 14, 2026
Not all digital work is automatable: many computer-based tasks are socially and institutionally entangled in ways that defeat pure automation. Rather than chasing full automation, organizations should adopt centaur designs that keep humans in the lead and use AI as supportive tooling.
n/a theoretical Full text arxiv
Metis AI: The Overlooked Middle Zone Between AI-Native and World-Movers · Xiang Li · May 14, 2026
A simple, model-agnostic 'fusion–fission' signal can forecast when chatbots will flip from safe to harmful responses, correctly predicting shifts across multiple models and pre-empting a major delusion corpus by 11 months; the formula offers a real-time warning layer that sits beneath current alignment stacks.
medium theoretical Full text arxiv
Fusion-fission forecasts when AI will shift to undesirable behavior · Neil F. Johnson, Frank Yingjie Huo · May 14, 2026