Evidence (1835 claims)
Adoption
7395 claims
Productivity
6507 claims
Governance
5877 claims
Human-AI Collaboration
5157 claims
Innovation
3492 claims
Org Design
3470 claims
Labor Markets
3224 claims
Skills & Training
2608 claims
Inequality
1835 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 609 | 159 | 77 | 736 | 1615 |
| Governance & Regulation | 664 | 329 | 160 | 99 | 1273 |
| Organizational Efficiency | 624 | 143 | 105 | 70 | 949 |
| Technology Adoption Rate | 502 | 176 | 98 | 78 | 861 |
| Research Productivity | 348 | 109 | 48 | 322 | 836 |
| Output Quality | 391 | 120 | 44 | 40 | 595 |
| Firm Productivity | 385 | 46 | 85 | 17 | 539 |
| Decision Quality | 275 | 143 | 62 | 34 | 521 |
| AI Safety & Ethics | 183 | 241 | 59 | 30 | 517 |
| Market Structure | 152 | 154 | 109 | 20 | 440 |
| Task Allocation | 158 | 50 | 56 | 26 | 295 |
| Innovation Output | 178 | 23 | 38 | 17 | 257 |
| Skill Acquisition | 137 | 52 | 50 | 13 | 252 |
| Fiscal & Macroeconomic | 120 | 64 | 38 | 23 | 252 |
| Employment Level | 93 | 46 | 96 | 12 | 249 |
| Firm Revenue | 130 | 43 | 26 | 3 | 202 |
| Consumer Welfare | 99 | 51 | 40 | 11 | 201 |
| Inequality Measures | 36 | 105 | 40 | 6 | 187 |
| Task Completion Time | 134 | 18 | 6 | 5 | 163 |
| Worker Satisfaction | 79 | 54 | 16 | 11 | 160 |
| Error Rate | 64 | 78 | 8 | 1 | 151 |
| Regulatory Compliance | 69 | 64 | 14 | 3 | 150 |
| Training Effectiveness | 81 | 15 | 13 | 18 | 129 |
| Wages & Compensation | 70 | 25 | 22 | 6 | 123 |
| Team Performance | 74 | 16 | 21 | 9 | 121 |
| Automation Exposure | 41 | 48 | 19 | 9 | 120 |
| Job Displacement | 11 | 71 | 16 | 1 | 99 |
| Developer Productivity | 71 | 14 | 9 | 3 | 98 |
| Hiring & Recruitment | 49 | 7 | 8 | 3 | 67 |
| Social Protection | 26 | 14 | 8 | 2 | 50 |
| Creative Output | 26 | 14 | 6 | 2 | 49 |
| Skill Obsolescence | 5 | 37 | 5 | 1 | 48 |
| Labor Share of Income | 12 | 13 | 12 | — | 37 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
Inequality
Remove filter
Aggregate productivity (output per worker or per unit of inputs) can rise while labor’s share and employment decline due to substitution toward K_T.
Macro growth-accounting exercises decomposing output growth into contributions from labor, traditional capital, and technological capital; model simulations showing productivity gains coexisting with falling labor shares under substitution elasticities.
The analysis also identifies risks linked to exclusion, symbolic compliance, and concentration of control over compliance processes.
Theoretical risk mapping produced by the integrative review and interpretive synthesis; no primary empirical evidence presented.
Uncertainty around compliance and excessive risk avoidance reduce the space for lawful business activity.
Interpretive synthesis of evidence and arguments across the reviewed literatures (sanctions compliance, institutional voids); no original empirical test.
Firms working under such conditions often experience limited access to finance and markets.
Claim derived from literature on firm constraints in weak institutional/sanctioned contexts as reviewed in the paper; no primary empirical data reported.
Post-conflict and sanctions-affected environments are strongly affected by sanctions pressure, weak rule enforcement, and high levels of corruption risk.
Synthesis of literature on sanctions, weak institutions, and corruption risk presented in the integrative review; no new empirical sample reported.
Currently, systematic assessment errors cause owners of lower-valued properties to face disproportionately high tax burdens, creating regressivity in the property tax system.
Empirical analysis of property assessments and tax burdens using 26 million property sales across ~95% of U.S. counties, showing systematic errors that bias tax burdens toward lower-valued properties.
There are limits to technology‑led growth strategies in labor‑abundant contexts; such strategies do not reliably deliver inclusive employment gains.
Argument based on synthesis of theory and comparative field evidence demonstrating weak employment outcomes from technology‑led growth in labor‑abundant settings (no quantitative effect sizes reported).
Digital media play a significant role in shaping youth mobilization and political unrest in migrants' countries of origin.
Empirical observations and regional field evidence reported in the paper linking digital media use to youth mobilization and political outcomes (qualitative/comparative evidence; no numeric sample size provided).
Developing countries face macroeconomic vulnerabilities because of dependence on remittances, which are exposed by automation-driven changes in migrant labor demand.
Analytical linkage developed in the paper supported by comparative field evidence and macroeconomic reasoning; remittance dependence highlighted as a vulnerability (no quantitative estimates or sample sizes reported).
Technology adoption in core industries in advanced economies is linked with labor displacement, rising youth unemployment, and urban labor saturation in South Asia and North Africa.
Geographically grounded framework combined with comparative regional field evidence focused on South Asia and North Africa (qualitative/comparative field data referenced; no numeric sample sizes provided).
AI adoption and accelerating automation amplify employment precarity in labor‑surplus economies.
Conceptual synthesis grounded in economic geography and labor economics, supported by comparative field evidence cited for labor‑surplus contexts (no quantitative sample size reported).
Automation functions as a transnational shock that contracts demand for migrant labor in advanced economies.
Theoretical argument drawing on economic geography, labor economics, and development studies; comparative/regional field evidence referenced in the paper (no numerical sample size reported).
Unless labour law evolves to address digitally mediated control and platform-based asymmetry, the gig economy risks normalising exploitative labour conditions under the guise of innovation and flexibility.
Predictive/theoretical claim based on the paper's synthesis of platform practices, legal gaps, and normative concerns; argued through comparative analysis and conceptual reasoning rather than quantitative forecasting.
The paper uses the concept of 'digital slavery' as a normative framework to describe labour conditions shaped by coercive algorithmic management, absence of bargaining power, and structural precarity.
Conceptual and normative framing within the paper, using the 'digital slavery' metaphor to interpret observed platform labour practices and their implications; theoretical argumentation rather than empirical measurement.
While several jurisdictions (UK, US, EU, India) have attempted to regulate gig work, most regulatory responses remain incomplete and fail to fully address platform accountability.
Comparative policy/regulatory analysis of the United Kingdom, United States, European Union and India assessing statutes, litigation and policy measures; qualitative assessment rather than statistical evaluation (no quantitative sample size reported).
Platform companies rely on contractual misclassification, corporate structuring, and the legal fiction of neutrality to separate control from liability.
Legal and corporate-structure analysis across jurisdictions, examining contracts, corporate forms and legal doctrines; based on comparative statutory and case-law review (no quantitative sample size reported).
The platform economy produces a deeply unequal labour structure marked by algorithmic control, economic dependency, surveillance, and lack of social protection.
Synthesis and critical analysis combining literature, policy review and comparative jurisdictional study to argue systemic effects on labour structure; primarily qualitative evidence and theoretical framing (no quantitative sample size reported).
Gig workers, though formally classified as independent contractors, are functionally subjected to pricing control, performance monitoring, automated penalties, and deactivation mechanisms that closely resemble managerial authority.
Descriptive/qualitative evidence in the paper: examples and analysis of platform design and management practices (algorithmic pricing, monitoring, penalties, deactivation); based on platform policy documents, case examples and comparative review (no quantitative sample size reported).
Digital labour platforms exercise employer-like control while avoiding employer-like legal responsibilities.
Argument and comparative legal analysis across jurisdictions (United Kingdom, United States, European Union, India) demonstrating platform practices and legal/regulatory responses; based on documentary/legal review and critical analysis (no quantitative sample size reported).
Severe penalties in underfunded Eastern systems, mediated by financial distress, drive families toward resource exhaustion.
Cross-country comparisons in SHARE-derived analyses showing larger financial penalties in underfunded Eastern European systems, with mediation analysis implicating financial distress and resultant resource exhaustion.
Financial distress acts as a profound multiplier of the burdens associated with palliative care.
Interaction/moderation analyses in SHARE-derived synthetic data showing that pre-existing financial distress amplifies financial and caregiving burdens under PC.
Socio-demographics heavily modulate exposure: lacking a spousal net inflates the burden.
Subgroup/moderation analyses in SHARE-derived data comparing households with and without spousal support, showing higher burdens when no spouse is present.
Non-cancer trajectories drive massive structural penalties that escalate at the distribution's tail, mechanically compounded by physical dependency.
Stratified analyses by disease trajectory (non-cancer vs cancer) using SHARE data (2016-2021) and quantile models showing larger penalties for non-cancer cases, especially in tail quantiles; physical dependency identified as a compounding factor.
Quantile treatment models expose a 'broken shield' for vulnerable households and severe tail events (PC protection fails or reverses at distributional tails).
Application of quantile treatment effect models to synthesized SHARE-derived digital twins (2016-2021), explicitly examining distributional/tail effects.
Increased levels of AI assistance may degrade productivity, leading to potentially significant shortfalls under the model's identified conditions.
Model-based comparative-statics and steady-state analysis showing scenarios where marginal increases in AI assistance reduce expected task output; examples/parameter illustrations provided in the paper (theoretical, no empirical sample).
Introducing AI unreliability (errors/noise in AI outputs) in the model can also generate a productivity paradox: greater AI assistance may lower productivity.
Analytical/theoretical model incorporating AI unreliability; model derivations and examples demonstrating conditions under which unreliability leads to reduced productivity (no empirical data).
Incorporating endogeneity in skill development into the model can induce a productivity paradox where increased AI assistance reduces productivity.
Analytical/theoretical model of human-AI interaction with utility-maximizing human agents and endogenous skill development; steady-state and comparative-static analysis reported in the paper (no empirical sample).
Direct demographic targeting excludes users whose demographics the platform cannot infer ('unknown users') if advertising platforms do not provide a way to target unknown users directly, as is the case on Google Ads.
Platform capability statement about Google Ads (authors' description of Google Ads targeting options); no sample size provided.
Skewed ad delivery of public-service ads can prevent certain groups of individuals from accessing information about resources on the basis of their demographic identity.
Argument/implication drawn from observed demographic skew in ad delivery and its relevance to public-service outreach; no specific empirical sample size reported in the excerpt.
Ad delivery can be skewed by demographic attributes, such that ads are systematically under-delivered to certain groups despite advertiser intent to reach groups proportionally.
Cites prior audits of ad delivery (literature/audit studies referenced by the paper); descriptive claim based on prior empirical work (no sample size stated in the provided excerpt).
Credential erosion is evident in the aggregate pattern (credentials losing signaling value relative to AI-augmented skill demonstrations).
Synthesis statement from included studies noting credential erosion alongside skill signaling changes; not quantified in the excerpt.
Developing economies reliant on cognitive services outsourcing face disproportionate disruption through both direct exposure and indirect demand-erosion channels.
Preliminary empirical evidence across included studies indicating larger negative impacts for economies dependent on cognitive-services exports; described as preliminary but material.
Observable labor market data already document patterns consistent with AI-driven displacement rather than mere transformation—concentrated among routine cognitive tasks and junior roles.
Synthesis of observed labor market indicators from retained empirical studies since 2020 showing concentration of declines in routine cognitive tasks and junior roles.
Evidence from online labor markets shows a 2%–21% reduction in posting volumes for automatable creative tasks following ChatGPT's release.
Empirical analyses of online labor market posting volumes reported in multiple studies included in the review; range reported across studies.
Across synthesized studies, there was a 14–41% reduction in postings for entry- and mid-level software development and content-creation roles in high-income economies between 2022 and 2024 (range across individual studies: −14% to −41%; median: −23%).
Synthesis of empirical studies retained in the systematic review (numerical range and median reported across non-overlapping study designs and geographies); no pooled meta-analytic estimate provided.
Without parallel investment in digital literacy, organizational culture, and inter-firm networks, AI will reproduce rather than reduce employment inequalities.
Authors' conclusion drawn from thematic analysis of interviews and conceptual framing; predictive statement based on qualitative findings.
AI adoption in peripheral economies is not a purely technological or financial challenge but a social and human capital challenge, embedded in a biocultural environment shaped by brain drain, institutional thinness, and weak civic intermediation.
Synthesis of interview findings using Bitsani's Biocultural City framework; qualitative evidence from 12 interviews supports this argument.
Knowledge deficits and financial constraints emerge as primary barriers [to AI adoption].
Thematic analysis of the twelve semi-structured interviews reporting these themes as primary barriers.
Taken together, AI’s effects on labor and capital may strain democracy unless a set of policies we outline here are gradually implemented.
Paper's normative/predictive claim linking labor- and capital-market effects of AI to political strain on democratic institutions and proposing policy remedies (presented as contingent and prescriptive; no empirical test of democratic outcomes provided in the excerpt).
AI’s training and computing needs are intensifying the technological sector’s interest in regulatory capture.
Paper's causal/inferential claim that increased capital concentration and fixed investments raise incentives for regulatory capture in the tech sector (asserted reasoning; no political-economy empirical test reported in the excerpt).
AI’s current training and computing needs have magnified capital concentration and business investment in fixed assets.
Paper's economic claim linking AI compute/training requirements to increased capital concentration and fixed-asset investment (no quantitative investment or market-concentration data provided in the excerpt).
Many fear AI may displace them from their jobs.
Paper reports survey-style finding about public fear of job displacement (no specific surveys, question wording, dates, or sample sizes given in the excerpt).
Although AI may affect nonroutine jobs in particular.
Statement in paper; asserted as a general finding about which types of jobs AI impacts (no specific dataset, sample size, or empirical method reported in the excerpt).
LLM hallucinations are infiltrating knowledge production at scale, threatening both the reliability and equity of future scientific discovery as human and AI systems draw on the existing literature.
Synthesis/conclusion drawn from the observed prevalence, growth, distribution across fields and authorship patterns, and limited correction by moderation/publication processes described above.
Preprint moderation and journal publication processes capture only a fraction of these errors.
Comparison of hallucinated-reference prevalence in preprints versus versions that underwent moderation or journal publication, showing many errors remain uncaught.
A policy irreversibility result: there exists a critical time before the singularity after which redistribution becomes politically impossible because wealth concentration makes feasible tax rates vanishingly small.
Proof/argument in the paper showing that as time approaches the singularity the set of tax rates that satisfy political-feasibility constraints (workers' budget / feasibility) shrinks to zero, implying a latest feasible intervention time.
Financialization amplifies the exponent of the super-exponential divergence by a factor γ_F/η.
Mathematical derivation in the paper showing that the exponent in the asymptotic growth rate near the singularity is multiplied by γ_F/η when including the financialization term γ_F K_f^2 and its coupling parameter η.
Near the singularity, the wealth ratio between capital owners and workers diverges super-exponentially.
Asymptotic analysis near the finite-time singularity showing that the ratio of capital-owner wealth to worker wealth grows faster than exponential (super-exponentially) as time approaches the blow-up time.
Municipal 311 call centers and complaint intake systems face a structural mismatch between incoming volume and classification capacity that produces a bottleneck and differential service quality that follows income and racial lines.
Stated in the paper's introduction; cites prior work (Liu 2024 SLA) as support for the differential service-quality / demographic claim. No sample size or quantitative result reported in the excerpt.
The Price of Fairness can be large even when group distributions are nearly identical.
Theoretical result/constructive example in the paper showing instances where PoF is large despite near-identical group distributions.