Firms adjust to generative AI by reallocating hiring (52% of exposure decline) and redesigning tasks within jobs (39.5%), with senior roles shifting earlier via reallocation and junior roles using mixed channels.
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arXiv preprint arXiv:2507.07935 , year=
11 Pith papers cite this work. Polarity classification is still indexing.
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A new RL Feasibility Index based on task learnability via reinforcement learning diverges from prior AI exposure measures, rating operational jobs like power plant operators as highly feasible while rating creative and interpersonal roles as less so.
Preregistered behavioral study identifies a speedup illusion where users overestimate time savings from AI assistance on cognitive tasks despite no actual difference in completion times.
The authors propose a retrieval-augmented framework that grounds AI exposure labels for 18,796 O*NET occupation-task pairs in retrieved news and academic abstracts, outperforming zero-shot prompting in 72% of disagreements and aligning better with observed real-world usage.
AI writing distorts perceived writer personas across 29 dimensions in large experiments, and reward-model mitigation reduces but does not eliminate user preference for the AI.
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
Interviews reveal a four-stage vibe coding workflow that accelerates prototyping while introducing tensions between quick efficiency and reflective design intention, plus asymmetries in trust and ownership.
Language access managers express conditional optimism about AI implementations but emphasize strong risk awareness and the necessity of human oversight and value in translation services.
Survey of Italian adults finds generative AI adoption and capital-enhancing uses stratified by education, age, tech familiarity, and gender, with AI training as key predictor of purposeful engagement.
Chatbot AI systems often fail complex needs while projecting authority, contributing to deskilling, labor displacement, economic concentration, and high environmental costs, so alternative pluralistic and task-specific designs are needed.
citing papers explorer
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Generative AI and the Reorganization of Labor Demand
Firms adjust to generative AI by reallocating hiring (52% of exposure decline) and redesigning tasks within jobs (39.5%), with senior roles shifting earlier via reallocation and junior roles using mixed channels.
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What Jobs Can AI Learn? Measuring Exposure by Reinforcement Learning
A new RL Feasibility Index based on task learnability via reinforcement learning diverges from prior AI exposure measures, rating operational jobs like power plant operators as highly feasible while rating creative and interpersonal roles as less so.
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Cognitive offloading and the speedup illusion in human-AI interaction
Preregistered behavioral study identifies a speedup illusion where users overestimate time savings from AI assistance on cognitive tasks despite no actual difference in completion times.
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Jobs' AI Exposure Should Be Measured from Evidence, Not Model Priors
The authors propose a retrieval-augmented framework that grounds AI exposure labels for 18,796 O*NET occupation-task pairs in retrieved news and academic abstracts, outperforming zero-shot prompting in 72% of disagreements and aligning better with observed real-world usage.
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Measuring and Mitigating Persona Distortions from AI Writing Assistance
AI writing distorts perceived writer personas across 29 dimensions in large experiments, and reward-model mitigation reduces but does not eliminate user preference for the AI.
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"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
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Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration
Interviews reveal a four-stage vibe coding workflow that accelerates prototyping while introducing tensions between quick efficiency and reflective design intention, plus asymmetries in trust and ownership.
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AI Technologies in Language Access: Attitudes Towards AI and the Human Value of Language Access Managers
Language access managers express conditional optimism about AI implementations but emphasize strong risk awareness and the necessity of human oversight and value in translation services.
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Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context
Survey of Italian adults finds generative AI adoption and capital-enhancing uses stratified by education, age, tech familiarity, and gender, with AI training as key predictor of purposeful engagement.
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What if AI systems weren't chatbots?
Chatbot AI systems often fail complex needs while projecting authority, contributing to deskilling, labor displacement, economic concentration, and high environmental costs, so alternative pluralistic and task-specific designs are needed.
- Who Uses AI? Platform Selection and the Measurement of Occupational AI Exposure