Provenance -- report_intel_dbab7b01963396b5_v1
REPORT report_intel_dbab7b01963396b5_v1 (v1, CONDITIONALLY_READY) → INTELLIGENCE OBJECT AI_LABOR intel_dbab7b01963396b5 (v3, CONDITIONALLY_READY)
Connectivity vocabulary: CONNECTED (fully resolved), PARTIALLY_CONNECTED (some but not all legs resolved), NOT_CONNECTED (no edge exists in the data), UNRESOLVED_REFERENCE (an id is referenced but not found in any readable store). Never fabricated.
Hypothesis → Claim → Evidence → Source chain
- H?: AI adoption is measurably shifting US labor force participation (status: INSUFFICIENT_EVIDENCE) hyp_f5f71f3a181d830c NOT_CONNECTED
- no claims
- HL1: AI adoption among US firms and workers is measurably increasing (status: PARTIALLY_SUPPORTED) hyp_b365b95148a3a372 PARTIALLY_CONNECTED
- A Federal Reserve Board FEDS Note ('Monitoring AI Adoption in the U.S. Economy', Jeffrey S. Allen, April 3, 2026) synthesizing three US government/Fed surveys found: per the Census Bureau's Business Trends and Outlook Survey (BTOS), 18% of US firms had adopted AI by end of 2025; per the Real-Time Population Survey (RPS), 41% of the US workforce reported using generative AI at work as of November 2025; and per the Atlanta Fed's Survey of Business Uncertainty (SBU, Nov 2025, n=1,032 executives), 78% of the labor force works at an AI-adopting firm and 54% at a firm using large language models specifically; work-related generative AI adoption grew 31% year-over-year, with professional services (33%) and financial services (30%) leading sector adoption rates. This is firm/worker-level AI ADOPTION data, not evidence of productivity or employment effect. (type: DESCRIPTIVE, status: OPEN) claim_0da20db21fe1463a NOT_CONNECTED
- no evidence resolved
- A Federal Reserve Board FEDS Note ('Monitoring AI Adoption in the U.S. Economy', Jeffrey S. Allen, April 3, 2026) synthesizing three US government/Fed surveys found: per the Census Bureau's Business Trends and Outlook Survey (BTOS), 18% of US firms had adopted AI by end of 2025; per the Real-Time Population Survey (RPS), 41% of the US workforce reported using generative AI at work as of November 2025; and per the Atlanta Fed's Survey of Business Uncertainty (SBU, Nov 2025, n=1,032 executives), 78% of the labor force works at an AI-adopting firm and 54% at a firm using large language models specifically; work-related generative AI adoption grew 31% year-over-year, with professional services (33%) and financial services (30%) leading sector adoption rates. This is firm/worker-level AI ADOPTION data, not evidence of productivity or employment effect. (type: DESCRIPTIVE, status: OPEN) claim_0da20db21fe1463a NOT_CONNECTED
- HL2: There is direct observed employment effect from AI exposure, concentrated specifically in early-career (ages 22-25) US workers (status: CONTESTED) hyp_b3a8bfef91a47a45 PARTIALLY_CONNECTED
- A Stanford SIEPR working paper (Brynjolfsson, Chandar, Chen, 'Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence', Aug 2025), using large-scale US payroll processor data, found early-career workers (ages 22-25) in the most AI-exposed occupations experienced an estimated 13% relative decline in employment since the widespread adoption of generative AI tools, compared to stable or growing employment for more experienced workers in the same occupations and for workers in less-exposed occupations; the paper reports adjustment occurring through employment levels rather than compensation, and attributes the pattern primarily to roles where AI automates (vs. augments) tasks. (type: ATTRIBUTION, status: OPEN) claim_8fd5da8f27c9fc2b NOT_CONNECTED
- no evidence resolved
- A peer-reviewed study (Kauhanen & Rouvinen, 'Assessing Early Labour Market Effects of Generative AI: Evidence from Population Data', Applied Economics Letters, published online June 10, 2025, ETLA/Finland) using comprehensive Finnish wage-earner population data found NO statistically significant differences in wage or employment changes between more-exposed and less-exposed occupations in the two years following ChatGPT's November 2022 launch, in contrast to some online-labour-market-based studies; the authors note generative AI may simultaneously complement some tasks and substitute others in ways that have not yet produced a detectable net employment or wage effect at the national population level. (type: DESCRIPTIVE, status: OPEN) claim_8e305d0c30d23514 NOT_CONNECTED
- no evidence resolved
- A Stanford SIEPR working paper (Brynjolfsson, Chandar, Chen, 'Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence', Aug 2025), using large-scale US payroll processor data, found early-career workers (ages 22-25) in the most AI-exposed occupations experienced an estimated 13% relative decline in employment since the widespread adoption of generative AI tools, compared to stable or growing employment for more experienced workers in the same occupations and for workers in less-exposed occupations; the paper reports adjustment occurring through employment levels rather than compensation, and attributes the pattern primarily to roles where AI automates (vs. augments) tasks. (type: ATTRIBUTION, status: OPEN) claim_8fd5da8f27c9fc2b NOT_CONNECTED
- HL3: AI shows a measurable productivity effect in specific, well-studied task contexts (generative-AI-assisted customer support) (status: PARTIALLY_SUPPORTED) hyp_c4b0429622eb6dd7 PARTIALLY_CONNECTED
- A field experiment (Brynjolfsson, Li, and Raymond, NBER Working Paper 31161, 2023) studying 5,179 customer support agents given a generative-AI conversational assistant found a 14% average increase in issues resolved per hour, with a 34% improvement for novice/low-skilled workers and minimal effect for experienced/highly skilled workers; this is a productivity (output-per-hour) finding, not evidence of employment or headcount change at the firm. (type: CAUSAL, status: OPEN) claim_fe878b52922b46a4 NOT_CONNECTED
- no evidence resolved
- A field experiment (Brynjolfsson, Li, and Raymond, NBER Working Paper 31161, 2023) studying 5,179 customer support agents given a generative-AI conversational assistant found a 14% average increase in issues resolved per hour, with a 34% improvement for novice/low-skilled workers and minimal effect for experienced/highly skilled workers; this is a productivity (output-per-hour) finding, not evidence of employment or headcount change at the firm. (type: CAUSAL, status: OPEN) claim_fe878b52922b46a4 NOT_CONNECTED
- HL4: AI is driving large-scale, economy-wide job displacement at the national level (beyond the narrow early-career cohort) (status: WEAKENED) hyp_8691a1cb2d7c0d45 PARTIALLY_CONNECTED
- Korea Development Institute (KDI) report '인공지능(AI)의 거시경제 영향 분석' (Analysis of AI's Macroeconomic Impact, released July 22, 2026) FORECASTS that over a 10-year horizon AI diffusion could raise Korea's total factor productivity by up to 3.5% (annual gains of roughly 0.15-0.35 percentage points), while projecting approximately 256,000 jobs per year could be displaced (about 2.1% of Korea's 2024 employed workforce), concentrated in mid-to-high-skill professional, administrative, and sales roles; separately, the report estimates 72% of occupations have some AI-automatable tasks today but only 1.4% of jobs (1.8% by revenue) are currently economically viable to automate immediately. (type: PREDICTIVE, status: OPEN) claim_30fdf98bc1a9c818 NOT_CONNECTED
- no evidence resolved
- US BLS JOLTS report for August 2026 (released September 29, 2026) recorded job openings at 7.1 million (4.3% rate), hires at 5.2 million (3.3% rate), and total separations at 5.1 million (3.2% rate), each described by BLS as little changed/unchanged from the prior month. (type: DESCRIPTIVE, status: OPEN) claim_4731da53eae6b843 NOT_CONNECTED
- no evidence resolved
- A peer-reviewed study (Kauhanen & Rouvinen, 'Assessing Early Labour Market Effects of Generative AI: Evidence from Population Data', Applied Economics Letters, published online June 10, 2025, ETLA/Finland) using comprehensive Finnish wage-earner population data found NO statistically significant differences in wage or employment changes between more-exposed and less-exposed occupations in the two years following ChatGPT's November 2022 launch, in contrast to some online-labour-market-based studies; the authors note generative AI may simultaneously complement some tasks and substitute others in ways that have not yet produced a detectable net employment or wage effect at the national population level. (type: DESCRIPTIVE, status: OPEN) claim_8e305d0c30d23514 NOT_CONNECTED
- no evidence resolved
- Vanguard research (reported by Axios, Dec 17, 2025) analyzing nearly all US occupations using Labor Department occupational data from Q2 2023 to Q2 2025 found that occupations with the highest AI exposure experienced FASTER real wage growth (3.8% vs. 0.7% in less-exposed occupations) and FASTER employment growth (1.7% vs. 0.8%) over that period, counter to a mass-displacement narrative; Vanguard characterized this as "a snapshot of where we are now -- not a forecast of where we are headed," and separate reporting (CNN/ABC17, Dec 18, 2025) on related Vanguard analysis of ~140 AI-vulnerable occupations found high-AI-exposure jobs grew 1.7% post-Covid (mid-2023 to mid-2025) vs. 1% pre-Covid (2015-2019), with no systematic evidence of lower employment in AI-exposed roles, alongside isolated anecdotal Fed Beige Book reports of individual firms cutting staff or pausing entry-level hiring citing AI. (type: DESCRIPTIVE, status: OPEN) claim_1a69cf2e8f4f0f92 NOT_CONNECTED
- no evidence resolved
- Korea Employment Information Service (한국고용정보원) "2025-2035 Qualitative Job Outlook Report" (released May 18, 2026) qualitatively projects employment trends for 182 major domestic occupations through 2035 based on demographic (aging population), technological (AI/digital transformation), and cultural (K-content global expansion) factors; it forecasts approximately 93.4% of the 182 occupations will maintain current levels or increase (114 stable, 47 increasing slightly, 9 increasing), with no occupations forecast to decline -- this is a FORECAST/전망 of qualitative employment direction, not a measurement of AI-specific job losses or an observed outcome, and is Korea's official labor-market agency's outlook, separate from and less pessimistic in direction than KDI's AI-specific macroeconomic displacement forecast (claim_30fdf98bc1a9c818). (type: PREDICTIVE, status: OPEN) claim_cfb369e965025922 NOT_CONNECTED
- no evidence resolved
- Korea Development Institute (KDI) report '인공지능(AI)의 거시경제 영향 분석' (Analysis of AI's Macroeconomic Impact, released July 22, 2026) FORECASTS that over a 10-year horizon AI diffusion could raise Korea's total factor productivity by up to 3.5% (annual gains of roughly 0.15-0.35 percentage points), while projecting approximately 256,000 jobs per year could be displaced (about 2.1% of Korea's 2024 employed workforce), concentrated in mid-to-high-skill professional, administrative, and sales roles; separately, the report estimates 72% of occupations have some AI-automatable tasks today but only 1.4% of jobs (1.8% by revenue) are currently economically viable to automate immediately. (type: PREDICTIVE, status: OPEN) claim_30fdf98bc1a9c818 NOT_CONNECTED
Claim → Statistical Series → Source
| Statistical Series | Source | Connectivity |
|---|---|---|
| series_c302bf9e2576ad47 | src_worldbank_api | CONNECTED |