From cc08bdd5743f32648b0dba637b81d81830f07fd4 Mon Sep 17 00:00:00 2001 From: Teleo Agents Date: Thu, 30 Apr 2026 04:12:15 +0000 Subject: [PATCH] =?UTF-8?q?vida:=20research=20session=202026-04-30=20?= =?UTF-8?q?=E2=80=94=209=20sources=20archived?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Pentagon-Agent: Vida --- ...i-productivity-high-skill-concentration.md | 63 ++++++++++++++++ ...lth-workforce-shortage-2025-projections.md | 72 +++++++++++++++++++ 2 files changed, 135 insertions(+) create mode 100644 inbox/queue/2026-04-30-frbsf-atlanta-fed-ai-productivity-high-skill-concentration.md create mode 100644 inbox/queue/2026-04-30-hrsa-behavioral-health-workforce-shortage-2025-projections.md diff --git a/inbox/queue/2026-04-30-frbsf-atlanta-fed-ai-productivity-high-skill-concentration.md b/inbox/queue/2026-04-30-frbsf-atlanta-fed-ai-productivity-high-skill-concentration.md new file mode 100644 index 000000000..2b47e2184 --- /dev/null +++ b/inbox/queue/2026-04-30-frbsf-atlanta-fed-ai-productivity-high-skill-concentration.md @@ -0,0 +1,63 @@ +--- +type: source +title: "Atlanta Fed / FRBSF: AI Productivity Gains of 0.8% in High-Skill Services vs 0.4% in Low-Skill — Gains Expected to Double in 2026" +author: "Federal Reserve Bank of Atlanta / San Francisco Fed" +url: https://www.atlantafed.org/research-and-data/publications/working-papers/2026/03/25/04-artificial-intelligence-productivity-and-the-workforce-evidence-from-corporate-executives +date: 2026-03 +domain: health +secondary_domains: [ai-alignment] +format: research +status: unprocessed +priority: medium +tags: [ai, productivity, workforce, economic-research, high-skill-concentration, federal-reserve] +intake_tier: research-task +--- + +## Content + +Federal Reserve Bank of Atlanta / FRBSF research paper "Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives" (March 2026 — companion to NBER Working Paper 34836). + +Key sector-level findings (2025 actual data, not executive predictions): +- High-skill services and finance: ~0.8% labor productivity gain from AI +- Low-skill services, manufacturing, construction: ~0.4% gain +- Knowledge-intensive industries with AI job posting surges accounted for 50% of real GDP growth in Q3 2025 +- Total factor productivity increases associated with innovation and demand-oriented channels (not capital deepening) + +FRBSF Economic Letter (Feb 2026) additional data: +- Most macro-studies find limited evidence of significant AI effect in aggregate productivity statistics +- AI's GDP contribution is currently flowing through INVESTMENT (AI capex) not productivity gains +- "Solid, above-trend growth" expected for H1 2026 partly from AI-related investment + +AI adoption concentration pattern (IMF Jan 2026 / PWC data): +- Higher education levels significantly more likely to demand AI-related skills +- Young workers' employment more concentrated in occupations with high AI exposure AND low complementarity to AI → higher displacement risk +- Areas with higher literacy, numeracy, and college attainment see more AI skill demand +- Entry-level positions facing pressure from AI in highly exposed occupations + +San Francisco Fed Mary Daly (Feb 2026): AI productivity gains moving "under the hood" — present but not yet visible in standard productivity statistics. + +## Agent Notes + +**Why this matters:** This is the supply side of the AI-vs-chronic-disease argument. The Fed data shows that where AI gains ARE happening, they're concentrated in exactly the sectors and workers LEAST burdened by chronic disease (high-skill, finance, knowledge workers). The 0.8% vs 0.4% sector split is small but the directional signal is consistent: AI productivity accrues to already-healthy, already-productive workers. + +**What surprised me:** Knowledge-intensive industries drove 50% of real GDP growth in Q3 2025 despite being a minority of employment. This is the AI productivity flying through the high-skill conduit while the rest of the economy sees 0.4% or nothing. The GDP numbers look good but the distribution is highly unequal. + +**What I expected but didn't find:** A direct comparison of AI productivity gains among workers WITH vs WITHOUT chronic conditions. This is the research gap — we have sector-level data (high-skill vs low-skill) as a proxy, but not direct health-status-segmented data. + +**KB connections:** +- Companion to NBER 34836 (80% no AI gains) +- Strengthens Belief 1 disconfirmation target: AI gains concentrated where chronic disease is least, chronic disease concentrated where AI is least — non-overlapping +- The 50% of GDP growth from knowledge-intensive industries creates a paradox: population health (which is declining) may not be the binding constraint on GDP in the near term if capital and knowledge work can decouple from population health status +- HOWEVER: this decoupling is temporary if knowledge workers eventually age and become chronically ill without prevention + +**Extraction hints:** +- This source is better used as supporting evidence for the NBER claim than as a standalone claim +- The most extractable finding: "AI productivity gains concentrate in high-skill sectors at 0.8% vs low-skill sectors at 0.4% — a 2x differential that mirrors the chronic disease burden distribution" +- OR: flag this as the GDP paradox — short-term AI can inflate GDP growth measures even as population health declines, which may create a false signal that health is not a binding constraint + +**Context:** Fed research has high methodological credibility. The FRBSF economic letter (shorter format, policy-oriented) and the Atlanta Fed working paper are companion pieces — both using the same underlying executive survey. + +## Curator Notes (structured handoff for extractor) +PRIMARY CONNECTION: Companion to NBER 34836 on AI-vs-chronic-disease interaction for Belief 1 +WHY ARCHIVED: Provides the sector-level quantification (0.8% vs 0.4%) and the GDP growth concentration finding (50% from knowledge-intensive industries). Together with NBER 34836, this builds the case that AI productivity is a high-skill phenomenon that doesn't compensate for low-skill chronic disease burden. +EXTRACTION HINT: Use as supporting evidence for the NBER 34836 claim rather than standalone. The 50% GDP growth concentration finding is the most surprising data point. diff --git a/inbox/queue/2026-04-30-hrsa-behavioral-health-workforce-shortage-2025-projections.md b/inbox/queue/2026-04-30-hrsa-behavioral-health-workforce-shortage-2025-projections.md new file mode 100644 index 000000000..1bf3750f1 --- /dev/null +++ b/inbox/queue/2026-04-30-hrsa-behavioral-health-workforce-shortage-2025-projections.md @@ -0,0 +1,72 @@ +--- +type: source +title: "HRSA State of the Behavioral Health Workforce 2025 — 122M Americans in Shortage Areas, Psychiatrist Supply Declining 20% by 2030" +author: "HRSA Bureau of Health Workforce" +url: https://bhw.hrsa.gov/sites/default/files/bureau-health-workforce/data-research/Behavioral-Health-Workforce-Brief-2025.pdf +date: 2025-12 +domain: health +secondary_domains: [] +format: report +status: unprocessed +priority: high +tags: [mental-health, workforce, shortage, psychiatrist, access, hrsa, behavioral-health, supply] +intake_tier: research-task +--- + +## Content + +HRSA Bureau of Health Workforce 2025 Behavioral Health Workforce Brief — key findings: + +**Shortage scope (December 2024 data):** +- More than 122 million Americans live in designated Mental Health Professional Shortage Areas (HPSAs) +- More than 150 million people live in federally designated mental health professional shortage areas (some overlap) +- More than half of U.S. counties lack a single psychiatrist +- 65% of nonmetropolitan counties completely lack psychiatrists; cities experience selective shortages + +**Workforce projections:** +- Adult psychiatrist supply projected to DECREASE 20% by 2030 (retirements outpacing new entrants) +- Demand for psychiatrist services expected to INCREASE 3% over same period +- Shortage of over 12,000 fully-trained adult psychiatrists by 2030 +- Longer-term: shortage of 43,660 to 93,940 adult psychiatrists by 2037 +- Projected shortages: addiction counselors, marriage and family therapists, mental health counselors, psychologists, psychiatric PAs — all significant + +**Access impact:** +- National average wait time for behavioral health services: 48 days +- Current appointment wait times: 3 weeks to 6 months depending on location and specialty +- 6 in 10 psychologists do NOT accept new patients +- Rural communities face workforce shortages at nearly twice the rate of urban areas + +**Burnout:** +- 2023 survey of 750 behavioral health professionals: 93% experienced burnout, 62% experienced SEVERE burnout +- Burnout is both cause and effect of the shortage — high caseloads + inadequate reimbursement → burnout → exit → higher caseloads + +**What's not helping:** +- MHPAEA enforcement (targets coverage parity, not workforce supply) +- Technology (teletherapy reduces geographic barriers but doesn't create new therapists) +- Loan repayment programs (H.R.6672 Mental Health Professionals Workforce Shortage Loan Repayment Act of 2025 is in the 119th Congress — not yet law) + +## Agent Notes + +**Why this matters:** The HRSA data makes the supply constraint concrete and quantitative. 48-day wait times, 6/10 psychologists not accepting new patients — these are the ACCESS numbers that enforcement cannot change. You can mandate perfect benefit design parity and still have a 48-day wait time if there are no providers to see. + +**What surprised me:** The psychiatrist supply is projected to DECREASE — not just fail to keep up with demand, but actually shrink — 20% by 2030. This means the shortage is not stable; it's accelerating in the wrong direction. The window for intervention is closing. + +**What I expected but didn't find:** Any evidence that teletherapy platforms (BetterHelp, Talkspace) are meaningfully closing the access gap in shortage areas. The existing KB claim says "technology primarily serves the already-served rather than expanding access" — the HRSA data supports this. + +**KB connections:** +- Directly supports: "the mental health supply gap is widening not closing because demand outpaces workforce growth and technology primarily serves the already-served rather than expanding access" +- Confirms: enforcement (federal or state) addresses benefit design, not workforce supply — enforcement cannot solve the problem the HRSA data quantifies +- Connects to the RTI 27.1% reimbursement differential: lower reimbursement → burnout → exit → shrinking supply + +**Extraction hints:** +- CLAIM: "Mental health workforce shortage is accelerating as psychiatrist supply falls 20% by 2030 while demand rises 3%, creating a structural access gap that insurance parity enforcement cannot address" +- This is an update/enrichment of existing KB claim "the mental health supply gap is widening not closing" +- The 20% supply decline vs. 3% demand increase is the specific quantitative update +- The mechanism is: reimbursement differential → burnout → workforce exit → shrinking supply + +**Context:** HRSA is the authoritative federal source for health workforce data. Their projections are the basis for federal shortage area designations that determine federal funding allocations. + +## Curator Notes (structured handoff for extractor) +PRIMARY CONNECTION: "The mental health supply gap is widening not closing" — this enriches it with 2025 projections +WHY ARCHIVED: The 20% decline in psychiatrist supply by 2030 is a significant quantitative update. Combined with the 48-day average wait time and 6/10 psychologists not accepting patients, this makes the shortage concrete and measurable, not just directional. +EXTRACTION HINT: Enrich the existing claim rather than writing a new one. Add: "Psychiatrist supply projected to fall 20% by 2030 while demand rises 3%" and "6/10 psychologists not accepting new patients, 48-day average wait." These specifics make the existing claim stronger.