The Commonplace
Home Papers Evidence Explore Trends Syntheses Digests About 🎲 Workforce Futures

Papers (1699)

Filter: Sort:
Instant AI help backfires: brief interactions with assistants boost short-term accuracy but make people more likely to give up and perform worse without the AI. The effect appears rapidly across reasoning and comprehension tasks, suggesting current assistants may undermine the learning persistence needed for long-term skill acquisition.
medium rct Full text arxiv
AI Assistance Reduces Persistence and Hurts Independent Performance · Grace Liu, Brian Christian, Tsvetomira Dumbalska, Michiel A. Bakker, Rachit Dube... · Apr 06, 2026
EU regulatory patchwork stacks binding obligations on AI agent providers and, according to this mapping, leaves high‑risk agentic systems with untraceable behavioral drift noncompliant with the AI Act; providers must first exhaustively catalogue agents' external actions, data flows and affected persons before any meaningful compliance architecture can be built.
n/a descriptive Full text arxiv
AI Agents Under EU Law · Luca Nannini, Adam Leon Smith, Michele Joshua Maggini, Enrico Panai, Sandra Feli... · Apr 06, 2026
A granular LLM-and-expert assessment finds data-heavy cognitive occupations unusually exposed to automation while hands-on trades and high-stakes caregiving remain resilient; liability and compliance concerns create an emerging wage 'compliance premium' that could reshape who benefits from AI. The paper provides a diagnostic exposure index for 923 U.S. occupations but does not demonstrate realized employment or wage effects.
low descriptive Full text arxiv
Bounded by Risk, Not Capability: Quantifying AI Occupational Substitution Rates via a Tech-Risk Dual-Factor Model · Shuyao Gao, Minghao Huang · Apr 06, 2026
An IDE-integrated energy assistant cuts frontend page energy use by roughly 13–16% across 500 benchmarked sites and nudges developers toward greener choices without slowing them down; evidence comes from large-scale benchmarks and a small controlled study of 20 programmers.
medium quasi_experimental Full text arxiv
EcoAssist: Embedding Sustainability into AI-Assisted Frontend Development · André Barrocas, Nuno Jardim Nunes, Valentina Nisi, Nikolas Martelaro · Apr 06, 2026
AI is remaking office tasks for the majority of workers, but career outcomes depend far more on training and managerial support than on the technology itself; firms that invest in skills and organizational adaptation see substantially better employee reconfiguration.
low correlational Full text openalex
Artificial Intelligence Adoption and Career Reconfiguration of Office Workers: The Mediating Role of Training and Organizational Support · Dony Ari Nugroho · Apr 06, 2026
China's AI pilot zones lift cities' green economic efficiency by spurring green innovation and reshaping industry; gains are concentrated in inland and non-resource cities and grow where government and public environmental attention are high.
medium quasi_experimental Summary openalex
Unlocking Green Growth: How Artificial Intelligence Policies Enhance Green Economic Efficiency—Evidence from China · Shangqing Jiang, Da Gao, Xinyu Zhang · Apr 06, 2026
Large language models can unlock large-scale text-based economic research, but only if researchers guard against training-data leakage for prediction and use an independent validation sample to correct LLM measurement errors or risk biased and imprecise estimates.
n/a theoretical Full text openalex
Large Language Models: An Applied Econometric Framework · Jens Ludwig, Sendhil Mullainathan, Ashesh Rambachan · Apr 06, 2026
Conversational AI nearly triples selections of sponsored products—61% versus 22% under search—while users rarely detect the steering, and 'Sponsored' labels fail to blunt the effect, suggesting existing transparency tools may be insufficient.
high rct Full text arxiv
Commercial Persuasion in AI-Mediated Conversations · Francesco Salvi, Alejandro Cuevas, Manoel Horta Ribeiro · Apr 05, 2026
A structured 'Context Engineering' approach halved average iteration cycles and lifted first-pass acceptance from 32% to 55% in an observational study of 200 AI interactions; the evidence is promising but limited by single-operator, uncontrolled data.
low descriptive Full text arxiv
Context Engineering: A Practitioner Methodology for Structured Human-AI Collaboration · Elias Calboreanu · Apr 05, 2026
Nigeria’s firms lack the AI talent to reap automation’s gains: a survey of 150 leading companies finds critical shortages in data engineering, ML maintenance and AI ethics and flags up to 25% of routine administrative work as highly automatable. Without immediate, scalable public–private reskilling and tertiary-education reform, the country risks displacement rather than inclusive job creation.
low descriptive Full text semantic_scholar
Human Capital and the AI-Powered Future of Work: (Training, Employment Creation, and Skill Deficits in Nigeria's SME Sector) · Ovili Henry Peter, Ekeno Precious Eroboghene, Orugba Kenneth Obokparo · Fetched Apr 05, 2026
Telling AI exactly how to act — not vaguely appealing to 'be green' — cuts the energy footprint of a GenAI research workflow substantially without changing results. The study shows operational constraints and decision-rule prompts are a practical human-in-the-loop lever to align GenAI productivity with environmental efficiency.
medium descriptive Full text semantic_scholar
On the Carbon Footprint of Economic Research in the Age of Generative AI · Andrés Alonso-Robisco, Carlos Esparcia, Francisco Jareño · Fetched Apr 05, 2026
A payment-based ‘Agentic Risk Standard’ would make AI agents contractually liable for execution failures, replacing implicit trust in models with enforceable compensation; simulations suggest such a scheme could lower social costs of agentic transactions but remains untested in real markets.
low theoretical Full text arxiv
Quantifying Trust: Financial Risk Management for Trustworthy AI Agents · Wenyue Hua, Tianyi Peng, Chi Wang, Ian Kaufman, Bryan Lim, Chandler Fang · Apr 05, 2026
Targeted AI adoption could materially boost Kazakhstan's value added and employment: simulations attribute 16.8 percentage points of a projected 35.3 p.p. GVA increase (2025–2035) to AI, lift the GDP share of priority sectors by 6.3 p.p., and create roughly 1.3 million jobs, as task-creation effects outweigh automation.
low other Full text openalex
The Impact of Artificial Intelligence on the Structural Transformation of Kazakhstan's Economy · Y. Varavin, M. V. Kozlova, M. U. Rakhimberdinova, Özay Özpençe · Apr 05, 2026
Provinces with deeper digital–intelligent integration emit less carbon per unit of output, partly because digitization spurs industrial upgrading and green innovation; benefits also leak to nearby provinces but vary by geography, calling for regionally tailored policies.
medium quasi_experimental Summary openalex
Research on the Pathways and Spatial Effects of Digital–Intelligent Integration on Carbon Emission Intensity · Xiaochun Zhao, Ying Liu, Xi Zhang · Apr 05, 2026
Automation — including A.I. — accounted for the lion’s share of postwar productivity gains by allowing rapidly improving machines to replace slowly improving human inputs; but essential task complementarities mean any A.I.-led takeoff will be gradual and only becomes explosive once the last bottleneck tasks are automated.
medium theoretical Full text manual
Past Automation and Future A.I.: How Weak Links Tame the Growth Explosion · Charles I. Jones, Christopher Tonetti · Fetched Apr 04, 2026
Experts broadly expect major AI capability gains by 2030; if AI progresses rapidly they anticipate a sizable macroeconomic re‑rating—GDP growth rising toward roughly 3.5–4% annually and labour‑force participation falling to about 55% by 2050 (equivalent to ~10 million jobs), while policy preferences split: economists favor targeted retraining whereas the public backs broader safety‑net measures.
low descriptive Full text manual
Forecasting the Economic Effects of AI · Ezra Karger, Otto Kuusela, Jason Abaluck, Kevin Bryan, Basil Halperin, Todd Jone... · Fetched Apr 04, 2026
Corporate short-termism is prompting premature AI-driven layoffs that risk macro instability; coordinated policy-led reductions in standard work hours offer a practical tool to preserve jobs, maintain demand and spread the gains from AI.
low review_meta Summary semantic_scholar
A Shorter Workweek as Economic Infrastructure: Managing AI-Driven Labor Displacement Through Work-Time Policy · Jonathan H. Westover · Fetched Apr 04, 2026
Software engineers treat AI as an intellectual collaborator rather than a social teammate, expecting fewer socio-emotional attributes from models and instead valuing functional capabilities like contextual adaptation and responsibility negotiation; the authors argue teams should design for 'functional equivalents' rather than mimic human socio-emotional intelligence.
low descriptive Full text semantic_scholar
Bridging the Socio-Emotional Gap: The Functional Dimension of Human-AI Collaboration for Software Engineering · Lekshmi Murali Rani, Richard Berntsson-Svensson, R. Feldt · Fetched Apr 04, 2026
Tweak incentives, not the model: paying writers for originality—rather than quality—prevents generative AI from making outputs more alike, because originality payoffs prompt users to lean on the model for brainstorming and targeted edits instead of copying suggestions verbatim.
high rct Full text arxiv
Incentives shape how humans co-create with generative AI · Nathanael Jo, Manish Raghavan · Apr 04, 2026
A Sino‑Russian 'semi‑core' offers an epistemological as well as geopolitical challenge to Western order, elevating technical AI workers from technicians to strategic actors; their position between competing infrastructures gives them unique leverage to influence the direction of the current global interregnum.
low theoretical Full text openalex
Theorising the Interregnum: · Stephen Wilkinson · Apr 04, 2026
AI can raise short-term output while quietly eroding human skills, and even farsighted managers may rationally accept a lower long-run productivity once AI is adopted; short-termist incentives or external value of skills can trap workers in harmful deskilling paths.
n/a theoretical Full text arxiv
The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading · Michael Caosun, Sinan Aral · Apr 03, 2026
AI coding models generated thousands of reliable unit tests in hours and substantially reduced regression risk during major refactors; supervised, iterative test generation constrained model-driven code changes and cut manual labor for a prototype codebase.
low descriptive Full text arxiv
AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study · Ema Smolic, Mario Brcic, Luka Hobor, Mihael Kovac · Apr 03, 2026
A survey of 627 studies identifies four distinct AI–human decision-making paradigms driven by AI–human dynamics and decision typologies; the framework helps organizations choose between intuitive, algorithmic, analytical and hybrid decision modes as they integrate AI into operations.
n/a review_meta Full text openalex
Advancing Decision-Making through AI-Human Collaboration: A Systematic Review and Conceptual Framework · Han Li, Feng Tian · Apr 03, 2026
A hybrid local–global credit multi-agent RL cuts simulated supply-chain costs by about 26% and boosts service levels by roughly 43%, while retaining robustness under multiple simultaneous disruptions and scaling to 120 nodes.
low descriptive Full text openalex
Research on Multi-Agent Collaborative Decision-Making Algorithm for Supply Chain Management · Changgeng Li, Zixi Liu · Apr 03, 2026
Training models to solve multiple problems in one context slashes per-problem token consumption by up to 62.6% while preserving accuracy, promising substantial inference-cost savings; the simple BCR structural change also avoids instability associated with explicit length penalties.
medium descriptive Full text arxiv
Batched Contextual Reinforcement: A Task-Scaling Law for Efficient Reasoning · Bangji Yang, Hongbo Ma, Jiajun Fan, Ge Liu · Apr 02, 2026