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AI Insights & Research

Empirical working paperStanford Digital Economy Lab·

Young workers’ hiring as an early AI employment signal

Using US payroll data through June 2026, the revision finds no economy-wide displacement but weaker employment growth among young workers in AI-exposed occupations, primarily through reduced hiring. The authors describe early indicators rather than causal estimates; education, pre-existing trends and sample differences affect interpretation.

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Public-service prototype announcementGoogle DeepMind·

AI-assisted planning with human final decisions

UK councils and partners are co-developing an assistant that extracts policy and site information, summarizes consultations and drafts assessments. Planning officers retain review and final decisions. Halving processing time and national availability in 2027 are stated goals, not demonstrated nationwide outcomes.

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Institutional research and product releaseGoogle DeepMind / Google Research·

WeatherNext 3 connects live observations with hourly forecasts

WeatherNext 3 incorporates live satellite and station observations into hourly forecasts at variable-dependent resolutions, including 5-km grids for some near-surface fields. This targets rapidly changing local conditions. Performance claims depend on variables, regions and evaluation methods and do not imply accurate prediction of every weather event.

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Institutional research article | Internal usage data and practice observationsOpenAI·

When AI enters research workflows, what remains human-led?

OpenAI reports growing internal use of coding agents alongside increased coding and experimentation. Complex tasks still need human guidance, while people set priorities and make research and deployment decisions. These are preliminary institutional observations, not independent causal evidence; activity measures do not directly establish scientific progress.

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Institutional research article | Economic model and interactive scenariosAnthropic Institute·

If AI grows the economy, will knowledge workers share the gains?

Anthropic models how AI capabilities, adoption, autonomy and job-switching frictions could shape US growth, wages and employment through 2030. Across three illustrative scenarios, output rises while knowledge workers may face wage and employment pressure, and capital captures a larger share of income. These are conditional scenarios, not forecasts or probability estimates. The framework omits policy responses and business cycles, among other forces, and cannot be directly generalized to other countries.

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Research report | Observational platform analysisAnthropic Research·

Why domain expertise still matters with coding agents

Analysis of roughly 400,000 Claude Code sessions finds people usually plan while AI executes. Greater domain expertise is associated with more work per instruction, while users across occupations achieve similar coding-task success rates. Transcript classifications do not establish whether resulting artifacts are deployed or economically valuable.

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Research overview | Developer randomized trialAnthropic Research·

When AI writes the code, what does the learner retain?

In a randomized study of 52 developers learning a Python library, immediate quiz scores averaged 50% with AI versus 67% without it; completion-time differences were not statistically significant. Concept-focused interaction was associated with better comprehension, without establishing causality between usage styles. The small, short-term study cannot determine long-term skill development.

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Engineering practice | Institutional progress reportGoogle DeepMind·

AI-generated algorithms need meaningful evaluation

DeepMind reports AlphaEvolve applications in sequencing, grid optimization and computing infrastructure. Candidate algorithms are iteratively evaluated and selected, illustrating how testable objectives can guide automated search. Reported gains are institutional disclosures and should not be treated as independently established effects across all settings.

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Journal paper | Computational genomics model evaluationNature·

From DNA sequence to regulatory effects with AlphaGenome

AlphaGenome combines long DNA contexts with predictions across regulatory modalities, matching or exceeding compared external models on 25 of 26 variant-effect evaluations. It can help prioritize and interpret variants for investigation. Molecular predictions still require experimental validation and do not independently establish clinical diagnoses or treatment decisions.

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Journal paper | Preregistered field experimentOrganization Science·

How AI changes expertise sharing in product-development teams

A preregistered experiment with 791 P&G professionals found that individuals using AI matched teams without it on product-innovation tasks and produced more balanced technical and commercial proposals. The journal version distinguishes improved idea generation from the continuing value of human selection. It does not establish replacement of durable team relationships.

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