Evidence (13827 claims)
Adoption
8454 claims
Productivity
7544 claims
Governance
6789 claims
Human-AI Collaboration
6327 claims
Org Design
4126 claims
Innovation
4058 claims
Labor Markets
3520 claims
Skills & Training
2924 claims
Inequality
2057 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 749 | 195 | 97 | 889 | 1979 |
| Governance & Regulation | 815 | 391 | 188 | 121 | 1539 |
| Organizational Efficiency | 771 | 189 | 124 | 83 | 1177 |
| Technology Adoption Rate | 624 | 233 | 123 | 96 | 1084 |
| Research Productivity | 410 | 121 | 56 | 331 | 929 |
| Output Quality | 466 | 177 | 59 | 47 | 749 |
| Decision Quality | 320 | 174 | 75 | 42 | 618 |
| Firm Productivity | 435 | 55 | 88 | 20 | 604 |
| AI Safety & Ethics | 214 | 276 | 65 | 33 | 593 |
| Market Structure | 178 | 166 | 122 | 24 | 495 |
| Task Allocation | 206 | 64 | 70 | 31 | 376 |
| Skill Acquisition | 165 | 57 | 60 | 17 | 299 |
| Innovation Output | 201 | 27 | 41 | 18 | 288 |
| Employment Level | 105 | 51 | 107 | 13 | 278 |
| Fiscal & Macroeconomic | 131 | 69 | 43 | 26 | 276 |
| Consumer Welfare | 116 | 63 | 42 | 11 | 232 |
| Firm Revenue | 149 | 46 | 26 | 3 | 224 |
| Inequality Measures | 44 | 122 | 49 | 6 | 221 |
| Task Completion Time | 169 | 29 | 8 | 12 | 219 |
| Worker Satisfaction | 89 | 61 | 20 | 12 | 182 |
| Error Rate | 69 | 91 | 10 | 2 | 172 |
| Regulatory Compliance | 76 | 68 | 14 | 5 | 163 |
| Training Effectiveness | 92 | 19 | 13 | 19 | 145 |
| Wages & Compensation | 77 | 36 | 25 | 6 | 144 |
| Automation Exposure | 51 | 54 | 22 | 12 | 142 |
| Team Performance | 86 | 17 | 27 | 9 | 140 |
| Developer Productivity | 94 | 17 | 14 | 6 | 132 |
| Job Displacement | 12 | 80 | 20 | 1 | 113 |
| Hiring & Recruitment | 51 | 7 | 8 | 3 | 69 |
| Skill Obsolescence | 5 | 45 | 6 | 1 | 57 |
| Creative Output | 31 | 16 | 7 | 2 | 57 |
| Social Protection | 27 | 16 | 8 | 2 | 53 |
| Labor Share of Income | 17 | 17 | 17 | — | 51 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
The communication topology determines the spatial scale over which heterogeneity spreads in distributed production systems.
Model-based theoretical argument in the paper linking topology to the spatial scale of heterogeneity; illustrated conceptually and via examples but not via empirical sample testing.
Principle of Maximum Heterogeneity: any distributed production system optimising for performance will converge on an increasingly heterogeneous configuration.
Statement of a derived principle from the paper's model (theoretical derivation/argument); demonstration via model reasoning and examples rather than empirical testing; no sample size reported.
A small set of underlying laws generates the complex dynamics observed across fields (biology, economics, neuroscience, computing).
Theoretical argument and synthesis across disciplines within the paper; no empirical or experimental sample size reported.
The Distributed Production System model captures how agent heterogeneity, resource constraints, communication topology, and task structure jointly determine the productivity, efficiency, and robustness of distributed systems across biology, economics, neuroscience, and computing.
Presentation of a unified theoretical model (Distributed Production System) in the paper; conceptual/mathematical development and cross-disciplinary argumentation; no empirical sample size reported.
A simple regret-based payout rule is proposed that satisfies three out of the four Shapley axioms and also lies in the core.
Constructive proposal in the paper with accompanying theoretical/axiomatic analysis showing compliance with three Shapley axioms and proof of core-membership.
Convexity (in the homogeneous-agent case) implies a non-empty core that contains the Shapley value and ensures both stability and fairness of payout allocations.
Theoretical implication shown in the paper: proof that convexity leads to non-empty core and that the Shapley value belongs to the core under the stated conditions.
For identical (homogenous) agents with fixed action sets, the induced TU game is convex under mild algorithmic conditions.
Theoretical result/proof provided in the paper under assumptions of homogenous agents and fixed action sets and certain algorithmic conditions.
Participants in the treatment conditions showed greater positive belief change about the AI across the session.
Pre/post measures of participant beliefs collected during the field experiment (N=388) showing larger positive shifts among those assigned to treatment conditions versus controls.
A cognitive scaffolding intervention (partnership training that reframed AI as a thought partner) was associated with higher individual document quality at the top of the distribution.
Field experiment with 388 employees comparing cognitive scaffolding to other conditions; reported improvements concentrated at the top of the individual document-quality distribution.
LLMs coordinate extremely well on similar actions.
Empirical observation from the experiment showing high coordination performance by LLMs when alignment on similar actions is the equilibrium; qualitative description in the abstract without reported quantitative metrics.
Like humans, [LLMs] regulate [action similarity] in response to coordination incentives (strategic monoculture).
Empirical claim based on experimental results comparing how humans and LLMs change similarity when incentives for coordination/divergence are manipulated. No numerical details in excerpt.
LLMs exhibit high levels of baseline similarity (primary monoculture).
Empirical observation from the experiment comparing baseline action similarity across LLM subjects (relative level described qualitatively in paper). Specific sample sizes and quantitative metrics not provided in the excerpt.
We implement a simple experimental design that cleanly separates these forces, and deploy it on human and large language model (LLM) subjects.
Methodological claim: authors report implementing an experiment that separates baseline similarity from strategic adjustments and applying it to human participants and LLM agents. No sample sizes or procedural details provided in the excerpt.
We distinguish primary algorithmic monoculture -- baseline action similarity -- from strategic algorithmic monoculture, whereby agents adjust similarity in response to incentives.
Conceptual/theoretical distinction proposed in the paper (definition and taxonomy introduced by the authors). No empirical sample size reported for this conceptual claim in the provided text.
The framework provides practical guidance for designing measurements that support identification, comparability, and efficient estimation of latent treatment effects.
Paper claims to offer practical guidance as part of the methodological framework; this is a stated contribution grounded in the theoretical framework and design recommendations (no empirical validation sample size reported).
Estimation relies on a debiasing procedure that permits valid inference even when the bridge functions are weakly identified.
Estimation approach described in the paper including a debiasing procedure and theoretical results on inference validity under weak identification of bridge functions (methodological derivations; no empirical sample size).
A design-based approach built around nonparametric bridge functions can address the noncomparability challenges; these bridge functions can be characterized and identified.
Methodological proposal with formal characterization and identification results for nonparametric bridge functions presented in the paper (theoretical proofs/derivations; no empirical sample size).
We develop a general nonparametric framework for identifying and estimating average treatment effects on latent outcomes in randomized experiments.
The paper presents a methodological contribution: a nonparametric identification and estimation framework for average treatment effects (ATE) on latent outcomes in randomized experiments. Evidence is theoretical development and formal identification arguments in the paper (no empirical sample size reported).
Relatedness-based simulations identify, when it exists, for each country the Simplest Single Sovereignty Enhancing Technology (SSSET), i.e., the most feasible single new technological direction associated with the largest expected improvement in relative geoeconomic positioning.
Simulation/relatedness analysis described in paper: for each country, relatedness-based (proximity) simulations used to propose the single most feasible technology (SSSET) expected to yield the largest improvement in geoeconomic position.
The United States and Israel consistently occupy a marked 'high-diversity/low-ubiquity' position and lead the GCI ranking, followed by China, France, Japan, and Germany.
Empirical ranking produced by the GCI measure applied to the 17-country sample (paper reports ordering and characterization of US and Israel positions).
Cloud Computing, Cybersecurity Tools, and Medtech exhibit the highest ETGCI values, reflecting concentration of specialization in a small set of leading countries.
Empirical result computed from ETGCI values derived from the RVA specialization matrix; paper reports these domains as having the highest ETGCI (implying concentration among high-GCI countries).
From this matrix we derive two eigenvector-based measures: a Geoeconomic Complexity Index (GCI) that ranks countries by the composition of their venture specializations, and an Emerging Technology Geoeconomic Complexity Index (ETGCI) that ranks domains by the extent to which specialization is concentrated among high-GCI countries.
Methodological claim: eigenvector centrality/complexity approach applied to the RVA-based specialization matrix to derive two indices (GCI for countries, ETGCI for domains).
We construct an RVA-based country-technology specialization matrix for the 17 countries with the highest aggregate VC funding.
Methodological statement in paper: Revealed Venture Advantage (RVA) metric computed and used to build country-by-technology specialization matrix restricted to top 17 countries by aggregate VC funding.
We map venture-backed startups to 18 emerging technology domains via a probabilistic multi-label large-language-model classifier using Crunchbase firm- and deal-level data.
Methodological description in paper: Crunchbase firm- and deal-level data used; classification into 18 domains performed with a probabilistic multi-label LLM classifier (paper states this pipeline).
In a test of eight behavioural persuasion strategies, all outperformed the most effective attitudinal persuasion strategy, but differences among the eight were small.
Experimental comparison within the preregistered studies of eight behavioural persuasion strategies versus the best attitudinal persuasion strategy; results reported in paper showing each behavioural strategy exceeded the attitudinal strategy and that variation among the eight behavioural strategies was small.
We replicated prior findings that information provision drove effects on attitudes.
Experimentally manipulating information provision within the preregistered studies and observing effects on attitudinal outcomes, consistent with prior literature (sample reported in paper).
We found sizable AI persuasion effects on these behavioural outcomes (e.g. +19.7 percentage points on petition signing).
Experimental results from the two preregistered studies reported in the paper; example effect explicitly reported as +19.7 percentage points increase in petition signing. Overall sample reported as N=17,950 responses.
Organizations that strategically invest in blended, context-rich, and partnership-based development programs position themselves for sustainable competitive advantage in an increasingly automated marketplace.
Normative recommendation supported by the paper's synthesis of theory and practice (organizational development, adult learning, workforce development); no empirical effect sizes or sample-size-based evaluation provided.
Forward-thinking organizations are redesigning learning architectures to cultivate irreplaceable human capabilities that complement rather than compete with AI systems.
Synthesis of literature from organizational psychology, adult learning theory, and workforce development practice cited in the paper; presented as descriptive statement about current organizational practice rather than based on a reported empirical study with sample size.
Corporate and academic learning ecosystems will converge (necessary convergence of corporate and academic learning ecosystems).
Conceptual synthesis and argumentation in the paper referencing workforce development practice and organizational development research; no quantitative measures or sample size reported.
Human skills (critical thinking, adaptive decision-making, interpersonal acumen) will be elevated to core competency status as AI automates technical tasks once considered core competencies.
Argument and synthesis presented in the paper drawing on organizational psychology, adult learning theory, and workforce development practice; no empirical sample size or statistical tests reported (conceptual/literature-based claim).
Overall, BDA functions as a performance amplifier, yielding higher returns for ventures well-positioned to leverage its potential.
Synthesis conclusion from empirical findings across multiple outcomes (survival, costs, sales, employee growth, financing) in the sample of German start-ups.
For high-performing BDA adopters, employee growth is even more pronounced.
Heterogeneity analysis in the paper indicating stronger employee growth among high-performing BDA adopters in the German start-up sample.
For high-performing BDA adopters, increases in sales are even more pronounced.
Paper reports heterogeneity analysis showing stronger sales effects among high-performing adopters in the German start-up sample.
Conditional on survival, BDA adopters are more likely to attract venture capital financing.
Empirical finding in the paper that surviving BDA adopters have a greater likelihood of obtaining venture capital, based on the sample of German start-ups.
Conditional on survival, BDA adopters show stronger employee growth.
Paper reports greater employee growth for surviving BDA adopters compared with non-adopters based on empirical data from German start-ups.
Conditional on survival, BDA adopters have higher sales.
Conditional (survivor) analysis reported for adopters versus non-adopters in a large sample of German start-ups.
The policy’s impact on inclusive green growth is most pronounced in cities with areas between 5,000 and 10,000 square kilometers.
Subgroup analysis by city area within the DID framework showing the largest estimated policy effect for cities whose area is between 5,000 and 10,000 km^2 (sample size not reported).
The policy exhibits spatial spillover effects on neighboring regions that diminish progressively with distance (spatial decay).
Spatial analysis of policy effects across neighboring regions showing declining effect sizes as geographic distance increases (details and sample size not reported).
Mechanism tests indicate the policy primarily enhances inclusive green growth by strengthening public environmental participation.
Mechanism/mediation tests reported in the study (presumably within the DID framework) showing an increase in measures of public environmental participation associated with the policy and linked to inclusive green growth (sample size not reported).
Mechanism tests indicate the policy primarily enhances inclusive green growth by strengthening government environmental participation.
Mechanism/mediation tests reported in the study (presumably within the DID framework) showing an increase in measures of government environmental participation associated with the policy and linked to inclusive green growth (sample size not reported).
The policy's positive impact on inclusive green growth is particularly pronounced in non-traditional industrial cities.
Heterogeneity/subsample analysis within the DID framework comparing treated non-traditional industrial cities to others (sample size not reported).
The policy's positive impact on inclusive green growth is particularly pronounced in digital economy clusters.
Heterogeneity/subsample analysis within the DID framework comparing treated cities located in digital economy clusters to others (sample size not reported).
The policy's positive impact on inclusive green growth is particularly pronounced in high-quality development pilot zones.
Heterogeneity/subsample analysis within the DID framework comparing treated cities in high-quality development pilot zones to others (sample size not reported).
The 2015 Green Data Center Pilot Policy effectively promotes inclusive green growth in cities, increasing the average annual growth rate of inclusive green growth by 0.9 percentage points.
Quasi-natural experiment using the 2015 Green Data Center Pilot Policy as treatment, analyzed with a difference-in-differences (DID) econometric approach on city-level data (sample size not reported in the provided text).
AI has reshaped business operations and decision-making processes across commerce sub-sectors.
Stated in the paper as part of the literature- and trend-based review of AI adoption impacts (qualitative synthesis).
Proactive policy measures and organizational strategies are essential to ensure inclusive and sustainable employment growth in the AI-driven commercial environment.
Paper conclusion and policy recommendation based on the literature review and sector trend analysis (normative recommendation, not an empirical test).
The study emphasizes the growing importance of reskilling, upskilling, and human–AI collaboration for workforce adaptability.
Conclusion drawn from the literature and sectoral trend analysis highlighting policy and organizational implications (literature review/recommendation).
AI has generated new employment opportunities that require advanced technical, analytical, and managerial skills.
Reported from analysis of existing studies and sector trends indicating creation of new roles and skill demands (literature review).
The integration of AI technologies such as machine learning, automation, chatbots, and predictive analytics has significantly improved efficiency and productivity in areas like retail, marketing, finance, and supply chain management.
Systematic analysis of existing literature and sectoral trends reported in the paper (literature review; no original primary sample or experiment reported).