Evidence (16496 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.
Adoption
9875 claims
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Productivity
8807 claims
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Governance
7870 claims
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Human-AI Collaboration
7560 claims
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Org Design
4892 claims
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Innovation
4781 claims
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Labor Markets
4004 claims
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Skills & Training
3308 claims
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Inequality
2332 claims
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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 |
AI embeds algorithmic actors into the microfoundations of strategy, altering the role and behavior of individual-level actors that underlie firm-level phenomena.
Conceptual analysis of Microfoundations literature; theoretical proposition that algorithms act as actors at micro levels; no empirical sample provided.
AI creates hybrid cognitive architectures by integrating algorithmic cognition with human cognition, thereby changing how strategic decisions are made.
Theoretical argument drawing on literature in Behavioral Strategy and cognitive theory; conceptual synthesis without reported empirical tests or sample.
AI introduces a theoretical discontinuity that challenges core assumptions of strategic management (specifically those rooted in industry-structure and resource-based perspectives).
Conceptual/theoretical analysis across literatures in strategic management; the paper synthesizes prior debates and argues AI undermines prior assumptions. No empirical sample or quantitative data reported.
AIO’s decarbonization effects vary systematically across climate risk, industry competition, and AI exposure (heterogeneity analyses).
Authors state they performed heterogeneity/subgroup analyses showing systematic variation in the AIO–decarbonization relationship by climate risk, the degree of industry competition, and firms' AI exposure.
Some merged PRs introduce new lint or security findings while simultaneously removing existing issues (i.e., merges sometimes involve both addition and removal of issues).
Before-and-after static analysis (Pylint and Bandit) of merged PRs showing coexistence of introduced and removed findings in observed diffs.
We examine algorithmic co-supervision (ACoS) as a hybrid control mode in which supervisors and AC systems jointly direct, evaluate, and discipline workers.
The paper's stated empirical and conceptual focus; supported by the authors' analysis of 14 real-world ACoS settings (as reported in abstract).
Managerial authority is shifting from human supervisors alone toward varying hybrid arrangements in which humans and algorithms jointly control workers.
Claim drawn from prior literature and the authors' conceptual framing; the paper also analyzes real-world settings (14) to illustrate hybrid arrangements.
"General knowledge application" is the second most popular category among highlighted benchmarks, yet it is vaguely defined.
Categorization results from applying the paper's taxonomy to the Benchmarking-Cultures-25 dataset (counts/rankings reported by category). The paper comments on the vagueness of the label.
Benchmarks are attributed different competencies by different builders, depending on their narrative.
Qualitative and comparative analysis mapping benchmark labels and builders' claims in the Benchmarking-Cultures-25 dataset (139 model releases); the paper documents instances where the same benchmark is presented as evidence of different capabilities by different builders.
The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases and company blog posts, where model builders highlight results on selected benchmarks.
Descriptive/argumentative claim in the paper's introduction framing the research question; based on the authors' survey of contemporary practices and motivation for the dataset and analysis.
Cross-model validation reveals architecture-level trade-offs independent of specific LLMs: Dual Process excels at numeric/temporal queries (65-90% accuracy) while RAG excels at historical retrieval (60-85% accuracy).
Empirical cross-model tests across six LLMs; reported accuracy ranges for different query types and architectures.
AI functions both as a general-purpose technology and as an innovation in the method of innovation.
Conceptual/theoretical framing presented in the paper (the authors characterize AI as both a GPT and an innovation in methods of innovation).
Clarifying-question prompts produced mean rubric scores of 6.67 out of 8, higher than raw prompts but lower than checklist-improved prompts.
Reported mean rubric scores in the abstract showing clarifying-question prompts scored 6.67, compared to 5.67 for raw and 7.50 for checklist.
Classical categories (labour, capital, firm, market, productivity, trust) remain necessary but are incomplete for describing economic action when technologies prepare decisions, coordinate workflows, support tasks, verify transactions, and reshape responsibility.
Conceptual analysis supported by diagnostic indicators showing distributed decision/action capacity across humans, AI agents, robots, protocols, compute and energy systems; argumentative/theoretical evidence rather than causal inference.
Labour projections are more consistent with task reallocation than labour disappearance.
Analysis of labour-market reallocation data and labour projections (public sources) interpreted under a task-reallocation framework rather than full employment loss, using relative growth and reallocation indicators.
Readiness and performance-related variables are associated with higher predicted success, whereas higher barrier levels are associated with lower predicted success.
Model coefficients/feature effect analyses and nonlinear diagnostics from the fitted models.
The central challenge is whether commercial influence in generative systems can be made trustworthy, i.e., attributable, measurable, contestable, and aligned with user welfare.
Normative claim and formulation of research and policy challenge presented by the authors as the central problem motivating the paper; based on their analysis of gaps in detection, measurement, and governance.
This reframes generative AI advertising as a problem of trustworthy intervention rather than content placement.
Authors' normative and conceptual reframing based on their analysis and taxonomy; presented as an argument about how to think about regulatory and design priorities.
High-AIC participants realized outsized gains from GenAI access; low-AIC participants saw limited or even negative marginal returns.
Subgroup analysis of the randomized experiment comparing treatment effects by AIC level; authors report large positive treatment effects for high-AIC subgroup and small or negative effects for low-AIC subgroup.
The distribution of gains from GenAI access was highly uneven across users.
Experimental results showing heterogeneous effects across participants (variance/heterogeneity analyses reported in the paper).
Joint estimation confirms simultaneous adjustments across financing and innovation margins.
Joint estimation (likely a system or simultaneous-equations approach) showing concurrent changes in financing costs and innovation-related variables following the shock (method stated; no sample size or exact estimates in abstract).
The same observable behavioral signal can carry opposite meaning for different agent configurations.
Synthesis of the cross-configuration empirical findings (directional disagreements such as the error-rate example and other features).
Five other continuous features and three of seven binary patterns from prior SE literature show similar directional disagreement across configurations.
Aggregate empirical finding across the set of features and binary patterns analyzed in the 126-configuration dataset.
Error rate is the cleanest case: 47 configurations resolve more issues when their error rate is lower, while 48 resolve more when it is higher.
Empirical counts from the paper's analysis of configurations (reported 47 vs 48 configurations showing opposite sign relations between error rate and issue resolution).
On most signals, configurations disagree not merely in magnitude but in direction (i.e., the same signal correlates positively with resolution in some configurations and negatively in others).
Across-configuration comparison of behavior–outcome correlations for many signals in the dataset of 126 configurations / 64,380 runs.
Swapping the framework while the LLM is held fixed produces large behavioral differences in every action feature.
Comparative analysis across configurations holding LLM fixed; reported observation across action features.
The system is generically bistable, with a stable partial adoption equilibrium coexisting alongside full genuine adoption.
Analytical results from the evolutionary game-theoretic model demonstrating multiple stable equilibria (bistability). No empirical sample (theoretical proof / model analysis).
Doctors choose among three strategies: genuine adoption, partial adoption, and rejection, where genuine adoption is required for systemic benefits to materialise above a population threshold.
Model specification in an evolutionary game-theoretic framework; analytical description of strategy set and threshold condition. No empirical sample (theoretical model).
Outcome-only evaluation can certify economically unsafe agents: a policy can hit a business KPI while violating deployable behavioral discipline.
Illustrated by a hotel-pricing experiment (hidden competitor state) in which a learner achieves plausible revenue per available room while failing to preserve the rate discipline of a rule-based revenue-management competitor; based on experimental results in the paper's two-hotel benchmark.
The future of work will be shaped by decisions made at every level of society.
Normative/concluding statement in the chapter; presented as an implication of the prior analysis rather than an empirically tested claim.
AI affects the labour market through four channels: evolution of existing roles, creation of entirely new ones, redistribution across geographies and demographics, and selective displacement concentrated among older and lower-mobility workers.
Chapter synthesises labour market data, historical analogy, and emerging workplace evidence to propose these four channels; selective displacement claim references demographic concentration (older and lower-mobility workers).
Adaptation determines who benefits from technological (AI) change.
One of five lessons; argued using historical analogy and labour market patterns (qualitative claim in chapter).
Rising density from rack- and pod-scale AI systems shapes these outcomes (deployable capacity, capex, performance) — we quantify how density changes these outcomes.
Modeling/simulation results reported in the paper quantifying the impact of rising rack/pod-scale density on deployable capacity, capex, and performance; specific numeric quantification not included in the abstract.
Başta ABD, Avrupa Birliği ve Çin olmak üzere büyük ekonomilerin yapay zekâ alanında benimsediği sanayi ve ticaret politikaları karşılaştırmalı olarak incelenmektedir; bu ekonomilerin teknolojik hegemonya arayışının ekonomik olduğu kadar jeopolitik bir boyut kazandığı değerlendirilmektedir.
Karşılaştırmalı politika incelemesi (kavramsal ve betimleyici); çalışmada belirli politika örnekleri tartışılıyor ancak sistematik nicel karşılaştırma ya da örneklem büyüklüğü belirtilmiyor.
Yapay zekâ teknolojilerindeki hızlı ilerleme, küresel üretim ve ticaret organizasyonunu köklü biçimde dönüştürme potansiyeline sahiptir.
Kavramsal değerlendirme ve literatüre dayalı tartışma; çalışmada ampirik örnek veya nicel örneklem sunulmamaktadır.
AI enhances forecasting accuracy only when integrated within institutional decision cycles.
Empirical finding from comparative analysis combining Flexibility Index (including AI integration) with measures of institutional decision cycles; conditional effect reported in results.
LLMs often generate responses with the structural clarity associated with early-career engineers, yet they display persistent weaknesses in factual grounding and contextual interpretation.
Qualitative and comparative analysis of LLM responses against the expert rubric during the audit (six commercial LLMs); observed patterns in response form and substantive content.
The negative quadratic term confirms a concave (inverted-U) relationship between AI and economic growth (diminishing marginal returns of AI).
Panel data for 19 G20 countries (2005–2023) estimated with a quadratic specification in GMM; reported negative and statistically significant coefficient on the AI-squared term.
Anhand von Fallstudien aus den G7-Ländern werden verschiedene Einsatzmöglichkeiten veranschaulicht und die wichtigsten Erfolgsfaktoren benannt – Netzanbindung, KI-Inputs, Kompetenzen und Finanzierung.
Evidence comes from G7 country case studies reported in the paper; method = qualitative case studies identifying key success factors (no number of case studies or sample size provided in excerpt).
This lack of focus creates uncertainty about whether regulatory technology helps legitimate economic recovery or instead strengthens exclusion and informality.
Interpretive observation from gaps identified in the reviewed literature; no empirical resolution provided.
There is a governance–task decoupling: under structural stress, text-only governance degrades on both governance and task dimensions simultaneously, whereas mechanical enforcement preserves governance quality even as task performance drops.
Experimental stress tests or structural-stress scenarios applied to both governance architectures in the paper's synthetic experiments; observed differential behavior across governance and task metrics. Abstract does not provide numeric details.
The improvement from mechanical enforcement is driven by architectural separation: LLM-generated rationales under mechanical enforcement show comparable CDL to text-only governance — the gain comes from removing clear-cut decisions from the model's control.
Analysis comparing LLM-generated rationales and a metric called CDL across governance architectures in the synthetic banking experiments; authors attribute improvement to removing certain decisions from the model's control. Specific statistics and CDL definition not provided in abstract.
The results vary across the 10 selected countries: the magnitude and significance of AI’s effects differ due to varying technological readiness and differing industrial structures.
Paper statement that results vary across the 10 selected countries and that nuances differ across countries due to varying industrial structures and technological readiness. Implied heterogeneity analysis across countries using the firm-level dataset and regression approaches; no country-level sample counts provided in the excerpt.
Digital transformation reconfigures development patterns across regions and countries, altering established trajectories of regional development.
Theoretical integration of a technology–labor–space framework together with comparative regional field evidence illustrating changing development patterns (no quantified effect sizes or sample sizes reported).
Differences in human intervention effectiveness across escalation types are partly explained by variation in workers' post-escalation intervention effort.
Observed correlations (and subgroup comparisons) in the randomized experiment showing that measures of post-escalation effort (e.g., message counts, share of chat rounds, proactivity) vary across escalation types and relate to outcome differences.
Artificial intelligence (AI) is rapidly reshaping knowledge-intensive work by automating, augmenting, and reconfiguring core professional activities.
Paper asserts this as a motivating observation based on prior literature and descriptive claims; no original empirical sample or quantified data reported.
Metis can be subdivided into 'constitutive metis' (knowledge destroyed by the act of formalization) and 'operational metis' (system-specific familiarity that automation can progressively absorb).
Conceptual taxonomy proposed by the authors; definitions and distinctions are theoretical and illustrated via argumentation and prior literature rather than quantified empirical measurement.
There is a fundamental reward-coverage tradeoff: concentrating probability mass on high-reward actions reduces variance but risks missing signal on actions the target policy may take.
Explicit characterization in abstract; claimed theoretical analysis/derivation of the tradeoff between variance reduction and coverage when designing logging policies.
Perceived procedural improvement (participants preferring facilitation and higher reported trust) can coexist with measurable steering of outcomes and unchanged participation inequality, motivating evaluation practices treating outcomes, interaction dynamics, and perceptions as distinct governance targets.
Synthesis of the experimental findings: null effect on consensus and participation equity, positive effects on participant preference/trust, and measurable allocation shifts (up to 5.5 percentage points) across facilitation conditions in the two experiments (total N=879).
Facilitators shifted select charity-level allocations by up to 5.5 percentage points, directly affecting the final charitable payout.
Analysis of final group allocation outcomes across experimental conditions showing shifts in allocation to specific charities; reported maximum observed shift of 5.5 percentage points attributable to facilitator condition(s). (Study-level sample covering the two experiments; participants organized in groups of three.)