About The Commonplace
A structured research knowledge base that monitors, assesses, and synthesizes the latest academic research on AI's economic impact. Updated daily via an automated pipeline, it turns hundreds of weekly publications into a curated, evidence-graded feed that researchers and business leaders can actually use.
Sections of the App
Each section serves a different purpose. Click any card to go there.
Topics We Track
Nine research areas spanning AI's impact on the economy, from firm-level productivity to macroeconomic policy.
AI & Labor Productivity
Output effects, firm-level productivity gains, task automation, and the gap between AI adoption and measurable economic impact.
AI & Labor Markets
Employment effects, wage dynamics, job displacement, occupational shifts, and labor demand restructuring.
Human-AI Collaboration
Augmentation vs. automation, human-AI teaming, workplace integration patterns, and complementarity effects.
AI & Skills/Training
Upskilling, reskilling, skill obsolescence, workforce development programs, and returns to AI-related human capital.
AI & Organizational Design
Firm structure, management practices, decision-making authority, and how organizations reconfigure around AI capabilities.
AI & Innovation
R&D productivity, scientific discovery acceleration, patent activity, and AI as a general-purpose technology.
AI & Inequality
Wage gaps, digital divides, distributional effects across skill levels, regions, and demographic groups.
AI Adoption & Diffusion
Firm adoption barriers, technology diffusion patterns, sectoral variation, and determinants of AI uptake.
AI Governance & Policy
Regulation design, labor policy responses, AI governance frameworks, and evidence-based policy evaluation.
Methodology
Every paper goes through a multi-stage automated pipeline before appearing in the knowledge base.
Discovery
Papers fetched daily from three academic sources across 9 topic queries each. 7-day rolling lookback window captures new publications and preprints.
Cross-Source Deduplication
DOI, arXiv ID, and fuzzy title matching eliminates duplicates across sources. The same paper indexed by OpenAlex and Semantic Scholar appears only once.
Summarization
Structured summaries generated via GPT-5-mini from abstracts and full text (when available via PDF download).
Methodological Assessment
Each paper is classified by type (RCT, quasi-experimental, correlational, etc.), evidence strength, and methods rigor. Relevance scored 1-10 with a calibrated prompt targeting 10-15% at 8+. Only papers scoring 7+ are retained.
Claims Extraction
Key claims extracted with evidence basis, confidence level (high/medium/low), and direction (positive/negative/mixed/null result). Claims are browsable and searchable on the Evidence page.
Headline Generation
Economist-style headlines capture the key finding in 1-2 declarative sentences. Designed for scannability across the Papers list and Top Papers ranking.
Digest Synthesis
Two-pass editorial synthesis published weekly, every Monday. Pass 1 extracts structured themes, contradictions, and claims. Pass 2 writes an editorial narrative connecting findings across papers. The digest tells you what the research collectively means, not what each paper says.
Sources
Three complementary academic databases ensure broad coverage of published research and preprints.
OpenAlex
Open scholarly metadata covering 250M+ works. Filtered to the Social Sciences domain (Economics, Sociology, Management).
50 results per query · 9 topic queries
arXiv
Preprint server for scientific papers. Filtered to econ.*, cs.CY (Computers and Society), cs.HC (Human-Computer Interaction), cs.AI.
40 results per query · 9 topic queries
Semantic Scholar
AI-powered academic search by the Allen Institute. Filtered to Economics, Business, Sociology, Political Science, Computer Science.
40 results per query · 9 topic queries
Pipeline runs daily at 4:00 AM ET with a 7-day rolling lookback window. After cross-source deduplication, papers are enriched in parallel using 5 concurrent workers.
Use Cases
How different teams can use The Commonplace to stay informed and produce better work.
For Researchers Studying AI & the Economy
Stay Current Without the Noise
Track the frontier of AI economics research across 9 topic areas without manually monitoring dozens of journals and preprint servers. The relevance filter (7+/10) ensures you only see papers with genuine contributions to the field.
Identify Methods Trends & Evidence Gaps
See how the field is evolving methodologically. What share of papers are RCTs vs. correlational? Where is evidence strength concentrated? Use the Evidence page to find where high-confidence claims cluster and where gaps remain.
Find Contradictions & Debates
The digest synthesis flags contradictions between papers. Who claims AI raises productivity and who claims it doesn't? What explains the divergence? These are the interesting questions for new research.
Build Literature Reviews Faster
Use the Evidence page to find high-confidence claims with their evidence basis, organized by theme and direction. Each claim links back to its source paper with full assessment metadata.
Get Independent Assessments
Submit working papers for automated methodological assessment: paper type classification, evidence strength, methods rigor score, and extracted claims.
Discover Cross-Cutting Themes
The weekly digest synthesizes across papers to surface patterns you'd miss reading in isolation. How do findings on AI adoption connect to skills training research? The Emerging Patterns section makes these connections explicit.
For Marketing Executive Leadership
5-Minute Executive Briefing
Read The Big Picture section of the weekly Digest for a concise synthesis of what the latest research says about AI's economic impact. Written for time-constrained leaders, not academics.
Evidence-Grounded Narratives
Ground strategic narratives in peer-reviewed evidence, not vendor whitepapers or analyst speculation. Every claim in the system is traced to a specific study with a confidence level and evidence assessment.
Board-Ready Data Points
Find specific data points for presentations and investor communications. Filter Papers for high-evidence RCTs to cite findings like "AI tools boost developer productivity by X%" with academic backing.
Regulatory & Policy Foresight
Monitor how academic consensus is shifting on AI and labor displacement. The Governance theme in Evidence tracks regulatory research and policy evaluation. Get ahead of policy risk before it becomes headline news.
Signal From Noise
Top Papers on the Dashboard surfaces the highest-signal research ranked by a composite score. No need to wade through hundreds of abstracts. The system does the relevance filtering and quality assessment for you.
For Thought Leadership Teams
Source Original Research
Find peer-reviewed claims for blog posts, reports, and presentations that competitors can't easily replicate. The system surfaces findings within days of publication, before they appear in mainstream coverage.
Spot Emerging Findings Early
The Claims to Watch section in each digest identifies emerging findings before they become conventional wisdom. Build thought leadership around novel results while others are still citing last year's papers.
Build Evidence-Backed Content Pillars
Use the 9 research themes as content pillars. Filter the Evidence page by theme (e.g., "Human-AI Collaboration" or "AI & Inequality") to build a body of research-backed content around each topic.
Track Evolving Consensus
Read digests week-over-week to track how findings evolve. Develop contrarian or nuanced positions based on where the evidence is actually heading, not where popular opinion thinks it is.
Add Credibility With Precision
Reference specific studies with confidence levels to add credibility. There's a difference between citing a "high-evidence RCT" and a "correlational study." The assessment metadata on each paper makes this distinction visible.
Quotable Claims for Social Content
The Evidence page surfaces claims with their supporting research. Filter for high-confidence, positive-direction claims to find shareable findings with solid academic backing.