Evidence (8807 claims)

Search and filter individual claims pulled from the papers. Looking for a specific finding ("what's the effect on wages?"), you're in the right place. Want to compare whole outcome categories against each other instead? Use the Evidence Explorer.

The board below groups claims two ways: by broad theme (nine paper-level topics) and by outcome category (the 34 claim-level outcomes that the Explorer and Syntheses also use).

Browse by theme

Nine broad, paper-level topics. Click one to filter the claims below.

Human-AI Collaboration

Claims by outcome category

Counts by direction of finding. These are the same 34 outcome categories the Explorer compares and the Syntheses are written for. A linked row has a published synthesis.

Outcome	Positive	Negative	Mixed	Null	Total
Other	870	233	116	1066	2363
Governance & Regulation	976	451	218	133	1809
Organizational Efficiency	949	224	144	88	1416
Technology Adoption Rate	764	287	141	122	1325
Research Productivity	501	152	74	362	1101
Output Quality	542	216	69	69	896
Decision Quality	387	198	94	54	740
Firm Productivity	513	67	101	27	714
AI Safety & Ethics	249	303	73	36	667
Market Structure	190	192	134	27	548
Task Allocation	243	77	91	36	452
Innovation Output	291	33	55	20	401
Skill Acquisition	206	72	65	21	364
Employment Level	133	63	115	22	335
Fiscal & Macroeconomic	153	79	52	32	323
Task Completion Time	206	37	12	15	272
Firm Revenue	179	52	29	5	266
Consumer Welfare	130	76	47	13	266
Inequality Measures	48	137	51	6	242
Worker Satisfaction	101	81	25	13	220
Error Rate	84	110	11	5	210
Wages & Compensation	98	47	30	10	185
Regulatory Compliance	88	73	17	7	185
Automation Exposure	66	64	33	16	182
Team Performance	105	29	30	11	176
Training Effectiveness	109	22	14	21	168
Developer Productivity	114	21	14	8	158
Job Displacement	12	90	24	1	127
Hiring & Recruitment	57	9	9	5	80
Skill Obsolescence	6	56	9	1	72
Social Protection	43	17	8	2	70
Creative Output	35	21	9	4	70
Labor Share of Income	18	21	17	1	57
Worker Turnover	15	16	—	4	35
Industry	—	—	—	1	1

Productivity Remove filter

Policy and managerial implication suggested: investing in short, targeted onboarding/training for GenAI tools (rather than only providing access) may deliver measurable performance gains and increase voluntary adoption.

Authors derive this implication from the randomized trial results showing increased adoption and improved scores with brief training (n = 164); this is an extrapolation from the trial findings.

speculative positive Training for Technology: Adoption and Productive Use of Gene... Organizational adoption and productivity (extrapolated from student trial outcom...

Policy implication (inference from results): prioritizing digital infrastructure investment to pass critical thresholds will unlock stronger productivity and environmental gains than focusing solely on advanced digital services.

Inference drawn from panel threshold findings (infrastructure threshold) and observed complementarities; this is a policy recommendation rather than a direct empirical test.

speculative positive Digital rural development and agricultural green total facto... AGTFP (policy-oriented inference)

The positive AGTFP gains from digital rural development are geographically heterogeneous and are concentrated in eastern provinces.

Regional heterogeneity analysis / sub-sample regressions across provinces showing larger estimated digitalization effects in eastern provinces compared with other regions.

medium-high positive Digital rural development and agricultural green total facto... AGTFP (regional subsample effects)

Digital infrastructure exhibits a threshold effect: its positive impact on AGTFP becomes stronger once digital infrastructure passes a critical level.

Panel threshold model applied to the provincial panel (2012–2022) that identifies a statistically significant threshold in the infrastructure sub-index where marginal effects increase above that value.

medium-high positive Digital rural development and agricultural green total facto... AGTFP (effect conditional on digital infrastructure level)

Authors recommend promoting a shift from single-link outsourcing (PAPM) toward whole-process integrated service provision (WAPM) as a policy implication of the findings.

Discussion/policy-implication section of the paper drawing on empirical results (TWFE and robustness checks) from the CLDS 2014–2018 analysis.

speculative positive Whole-Process Agricultural Production Chain Management and L... policy recommendation (expected productivity gains)

Unchecked shifts toward K_T-dominated production can amplify political risks (rising inequality, fiscal strain) that may fuel populism, protectionism, and demands for renegotiated social contracts.

Theoretical political‑economy discussion supported by historical analogies and model scenarios linking fiscal stress and distributional change to political-instability risks; qualitative case evidence.

speculative positive The Macroeconomic Transition of Technological Capital in the... political risk indicators (populist support, policy volatility) — discussed qual...

To make AI a driver of structural change, policy interventions must link AI investment to comprehensive energy subsidy reform and accelerated development of the new and renewable energy sector.

Policy recommendation based on integrated analysis showing that subsidy burdens and import dependence limit AI's macro impact; proposed linkage is derived from the study's scenario/logic assessment.

speculative positive (conditional) AI-Based Technological Transformation as a Driver for Develo... potential for AI to drive structural change conditional on subsidy reform and re...

« Prev 1 2 3 … … 176 177