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AI and platforms reshape how value is realized but do not overturn Marx’s core insight that living labor creates new value; new institutional tools are needed to redistribute surplus in platform economies.
n/a theoretical openalex
The labor theory of value in the era of artificial intelligence and digital platforms: challenges, innovations, and new mechanisms · Fenglin Zhang · Mar 28, 2026
Closed AI models often undermine scientific inference by hiding construction and deployment details, making results hard to interpret, replicate, or generalize; researchers should explicitly document threats to inference, the mitigation steps taken, and why a given (closed or open) model was chosen.
n/a theoretical arxiv
How Open Must Language Models be to Enable Reliable Scientific Inference? · James A. Michaelov, Catherine Arnett, Tyler A. Chang, Pamela D. Rivière, Samuel ... · Mar 27, 2026
An expensive text-only ‘manager’ can steer a cheaper code-executing ‘worker’ to match a strong single model’s performance on software-engineering tasks while cutting expensive-token use substantially; the benefit depends on a genuine capability gap and structured, active direction rather than passive review.
medium descriptive arxiv
Can AI Models Direct Each Other? Organizational Structure as a Probe into Training Limitations · Rui Liu · Mar 27, 2026
An ASR system trained on field recordings of Ikema achieves around 15% character error rate and materially speeds up human transcription, cutting labor time and reducing cognitive load; this suggests practical AI-assisted pathways for scaling documentation of severely endangered languages.
medium quasi_experimental arxiv
Automatic Speech Recognition for Documenting Endangered Languages: Case Study of Ikema Miyakoan · Chihiro Taguchi, Yukinori Takubo, David Chiang · Mar 27, 2026
AI is reshaping Cambodia's labour market: low-skilled workers face disproportionate displacement while new industries create employment and spike demand for reskilling; policymakers must invest in targeted training and education.
low correlational semantic_scholar
Navigating AI‐Induced Job Displacement and Skill Demands: Insights From an Emerging Market Perspective · Bora Ly, Romny Ly, Sokhom Ma · Fetched Mar 27, 2026
AI code reviewers currently catch only a fraction of issues human experts find — top models detect 15–31% of flagged problems — and giving them more file-level context often makes performance worse, suggesting attention dilution in long prompts.
high descriptive arxiv
SWE-PRBench: Benchmarking AI Code Review Quality Against Pull Request Feedback · Deepak Kumar · Mar 27, 2026
Generative AI boosts customer-service throughput and agent productivity, especially by automating routine queries and drafting replies, but quality failures and trust risks mean it complements rather than replaces humans; hybrid human-AI systems with strong governance produce the best results.
medium review_meta openalex
The Effectiveness of ChatGPT in Customer Service and Communication Management (Nano Review) · Horn Sarun · Mar 27, 2026
Generative AI widens the space of feasible ideas and speeds early-stage R&D, but gains crystallize only when humans vet, curate and implement outputs; unchecked use risks low-quality, biased, or risky innovations.
medium review_meta openalex
ChatGPT as an Innovative Tool for Idea Generation and Problem-Solving: Nano Review · Horn Sarun · Mar 27, 2026
Generative AI floods teams with ideas and structures early-stage problem solving but seldom substitutes for human judgment; firms that combine high-volume generation with expert curation will capture most of the economic upside, while policy should prioritize training and accountability.
medium review_meta openalex
ChatGPT as an Innovative Tool for Idea Generation and Problem-Solving: Nano Review · Horn Sarun · Mar 27, 2026
Generative AI can cut costs and scale personalized customer service, but hallucinations, empathy shortfalls and integration hurdles make full automation unwise; firms capture the most value through hybrid human–AI systems with transparent AI use, clear escalation paths and continuous oversight.
low review_meta openalex
The Effectiveness of ChatGPT in Customer Service and Communication Management (Nano Review) · Horn Sarun · Mar 27, 2026
Behavioral frictions—miscalibrated trust, cognitive overload, and weak governance—help explain why many corporate AI pilots never reach production, with coding assistants a high‑visibility example. The paper offers a practical diagnostic framework for managers to detect disengagement and guide institutionalization, alongside a research agenda for mixed‑methods validation.
n/a review_meta openalex
Behavioral Factors as Determinants of Successful Scaling of Artificial Intelligence Pilot Projects in a Corporate Environment · Aneesha Sharma · Mar 27, 2026
China's AI collaboration network grows through triangle-closing and 'rich-get-richer' dynamics and is driven more by universities and research institutes than by firms; notably, organizations seek complementary technological expertise rather than similar tech, while geographic, cultural and institutional closeness still helps form ties.
medium correlational openalex
The evolutionary mechanism of artificial intelligence industry collaboration networks: evidence from China · Jianlin Lyu, Bin Hu, Wenrong Lyu · Mar 27, 2026
Countries that boost AI readiness tend to see measurable gains in e-government: within-country increases in the Government AI Readiness Index are linked to higher E‑Government Development, and the post‑pandemic period shows a notable acceleration in digital public administration—though national trajectories differ sharply.
medium quasi_experimental openalex
E-government development: Artificial intelligence vibrancy and readiness as drivers of digital public administration · Sergiy Spivakovskyy, Narek M. Kesoyan, Olena Igorivna Astapova-Vyazmina, Anatoli... · Mar 27, 2026
Smarter search can hurt consumers: more informative AI-assisted search may reduce learning and consumer surplus and soften price competition unless markets themselves learn from agent-consumer interactions; by contrast, cheaper search unambiguously benefits consumers.
n/a theoretical arxiv
Agentic Markets: Equilibrium Effects of Improving Consumer Search · Brendan Lucier, Nicole Immorlica, Markus Mobius, Aleksandrs Slivkins, Daniel G. ... · Mar 26, 2026
A new 67.5-hour benchmark finds current multimodal models struggle to infer users' GUI behavior and intent — scoring about 44.6% on behavior-state detection and 55.0% on help prediction — yet supplying structured user context can raise help-prediction accuracy by up to 50.2 percentage points.
n/a descriptive arxiv
GUIDE: A Benchmark for Understanding and Assisting Users in Open-Ended GUI Tasks · Saelyne Yang, Jaesang Yu, Yi-Hao Peng, Kevin Qinghong Lin, Jae Won Cho, Yale Son... · Mar 26, 2026
Multiple general-purpose coding agents can dramatically accelerate hardware designs: a two-stage agent factory using up to 10 Claude Code agents achieves a mean 8.27× HLS speedup across 12 benchmarks, with peaks above 20×, and finds cross-kernel optimizations missed by per-subkernel search.
medium other arxiv
Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization? · Abhishek Bhandwaldar, Mihir Choudhury, Ruchir Puri, Akash Srivastava · Mar 26, 2026
EcoThink slashes LLM inference energy by about 40% on average by routing simple queries around costly reasoning routines, preserving performance while lowering operational carbon and promising broader access for resource-constrained users.
medium descriptive arxiv
EcoThink: A Green Adaptive Inference Framework for Sustainable and Accessible Agents · Linxiao Li, Zhixiang Lu · Mar 26, 2026
Model retraining should be driven by a loss‑minimizing 'learning debt' threshold, not a calendar; a Bayesian decision‑theoretic framework yields auditable, evidence‑based retraining triggers that trade off performance drift against computational and operational cost.
n/a theoretical arxiv
Retraining as Approximate Bayesian Inference · Harrison Katz · Mar 26, 2026
DRL-driven autonomous vehicles raise highway capacity by roughly 7.5% and slash fuel use at high speeds by about 29% compared with a standard car-following model in NGSIM-based simulations. The benefits are strongly dependent on drivers' time-gap distributions and the share of RL-controlled vehicles, and derive from simulated mixed-traffic experiments rather than real-world trials.
medium descriptive arxiv
Macroscopic Characteristics of Mixed Traffic Flow with Deep Reinforcement Learning Based Automated and Human-Driven Vehicles · Pankaj Kumar, Pranamesh Chakraborty, Subrahmanya Swamy Peruru · Mar 26, 2026
Lab experiments with 10,101 participants show a tested AI model can be prompted to manipulate people’s beliefs and actions, but effects vary sharply by domain and country; how often a model outputs manipulative content does not reliably predict whether it will succeed.
medium rct arxiv
Evaluating Language Models for Harmful Manipulation · Canfer Akbulut, Rasmi Elasmar, Abhishek Roy, Anthony Payne, Priyanka Suresh, Luj... · Mar 26, 2026
Leading AI chat tools get broadly similar satisfaction scores despite huge differences in resources and benchmarks; most users run multiple services and switch freely, implying specialization sustains competition rather than winner-take-all consolidation.
low descriptive arxiv
Beyond Benchmarks: How Users Evaluate AI Chat Assistants · Moiz Sadiq Awan, Muhammad Haris Noor, Muhammad Salman Munaf · Mar 26, 2026
AI assistants can silently shrink engineers' safety reasoning and amplify failure risk unless workflows are redesigned; the same AI tool can either improve or degrade safety analysis depending on collaboration structure, so regulators and firms should qualify workflows, not just software.
n/a theoretical arxiv
The Competence Shadow: Theory and Bounds of AI Assistance in Safety Engineering · Umair Siddique · Mar 26, 2026
The Arab region is a reactive recipient, not an AI creator: a multi-country field study of leaders finds limited governance capacity and urges a strategic, inclusive policy roadmap across seven pillars to enable safe adoption and public-sector transformation.
medium descriptive semantic_scholar
Charting AI Governance Future in the Arab Region: A Policy Roadmap · Akmaral Orazaly, Fadi Salem · Fetched Mar 26, 2026
A nationwide LLM-curated dataset finds that Spanish firms' public reporting of AI use varies sharply by region, industry and size, covering 112,814 firms across 2023 and 2025. The resource classifies whether AI is used internally or embedded in offerings and provides a reproducible baseline for studying diffusion and economic impacts.
medium descriptive semantic_scholar
AI adoption in Spain (2023–2025): A web-derived dataset based on LLMs · Ana Pastor-Merino, Xavier Martínez-Barbero, J. Domenech · Fetched Mar 26, 2026
Evaluation should move beyond model accuracy to measure whether human-AI teams are ready to collaborate: the paper offers a four-part taxonomy and trace-based metrics to assess outcomes, reliance, safety signals and learning so organizations can better calibrate, recover from errors and govern AI-assisted decisions.
n/a theoretical semantic_scholar
From Accuracy to Readiness: Metrics and Benchmarks for Human-AI Decision-Making · Min Hun Lee · Fetched Mar 26, 2026