Evidence (1311 claims)
Adoption
5227 claims
Productivity
4503 claims
Governance
4100 claims
Human-AI Collaboration
3062 claims
Labor Markets
2480 claims
Innovation
2320 claims
Org Design
2305 claims
Skills & Training
1920 claims
Inequality
1311 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 373 | 105 | 59 | 439 | 984 |
| Governance & Regulation | 366 | 172 | 115 | 55 | 718 |
| Research Productivity | 237 | 95 | 34 | 294 | 664 |
| Organizational Efficiency | 364 | 82 | 62 | 34 | 545 |
| Technology Adoption Rate | 293 | 118 | 66 | 30 | 511 |
| Firm Productivity | 274 | 33 | 68 | 10 | 390 |
| AI Safety & Ethics | 117 | 178 | 44 | 24 | 365 |
| Output Quality | 231 | 61 | 23 | 25 | 340 |
| Market Structure | 107 | 123 | 85 | 14 | 334 |
| Decision Quality | 158 | 68 | 33 | 17 | 279 |
| Fiscal & Macroeconomic | 75 | 52 | 32 | 21 | 187 |
| Employment Level | 70 | 32 | 74 | 8 | 186 |
| Skill Acquisition | 88 | 31 | 38 | 9 | 166 |
| Firm Revenue | 96 | 34 | 22 | — | 152 |
| Innovation Output | 105 | 12 | 21 | 11 | 150 |
| Consumer Welfare | 68 | 29 | 35 | 7 | 139 |
| Regulatory Compliance | 52 | 61 | 13 | 3 | 129 |
| Inequality Measures | 24 | 68 | 31 | 4 | 127 |
| Task Allocation | 71 | 10 | 29 | 6 | 116 |
| Worker Satisfaction | 46 | 38 | 12 | 9 | 105 |
| Error Rate | 42 | 47 | 6 | — | 95 |
| Training Effectiveness | 55 | 12 | 11 | 16 | 94 |
| Task Completion Time | 76 | 5 | 4 | 2 | 87 |
| Wages & Compensation | 46 | 13 | 19 | 5 | 83 |
| Team Performance | 44 | 9 | 15 | 7 | 76 |
| Hiring & Recruitment | 39 | 4 | 6 | 3 | 52 |
| Automation Exposure | 18 | 16 | 9 | 5 | 48 |
| Job Displacement | 5 | 29 | 12 | — | 46 |
| Social Protection | 19 | 8 | 6 | 1 | 34 |
| Developer Productivity | 27 | 2 | 3 | 1 | 33 |
| Worker Turnover | 10 | 12 | — | 3 | 25 |
| Creative Output | 15 | 5 | 3 | 1 | 24 |
| Skill Obsolescence | 3 | 18 | 2 | — | 23 |
| Labor Share of Income | 8 | 4 | 9 | — | 21 |
Inequality
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Hybrid norms combined with AI platforms lower coordination costs and may encourage more decentralized or platform‑based organizational structures, changing the premium on co‑location.
Theoretical integration of organizational economics and digital platform literature; supported by conceptual examples but no firm‑level causal analysis in the paper.
Differential access to informal learning and sponsorship in hybrid settings can produce long‑term human‑capital inequalities; AI-based mentoring and visibility tools may partially mitigate these gaps but risk biased recommendations if trained on skewed data.
Synthesis of literature on mentorship, social capital, and algorithmic bias; illustrative case examples rather than empirical evaluation of AI mentoring systems.
Geographic dispersion plus AI-enabled remote hiring can widen the labor supply for firms, potentially compressing wages for some roles while raising returns to digital-collaboration skills.
Economic reasoning and literature review on remote hiring and labor supply effects; the paper offers conceptual arguments rather than presenting empirical wage-impact estimates.
Automation of routine tasks may shift task content toward relational and creative work, areas where hybrid arrangements influence social capital accumulation.
Theoretical argument combining automation literature with sociological perspectives on social capital; no direct empirical measurement or longitudinal data in the paper.
Hybrid work complicates traditional productivity metrics, making AI-driven analytics and monitoring tools more attractive but creating trade-offs between measurement accuracy, privacy, and employee trust.
Conceptual argument synthesizing literature on measurement, monitoring, and AI tools; no empirical evaluation of specific tools or datasets in the paper.
Sustaining productivity and organizational culture under hybrid arrangements depends crucially on leadership practices—trust, communication, and fairness—and on inclusive policies that explicitly manage equity, well‑being, and flexibility.
Comparative case illustrations and management literature integration; recommendations derived from secondary sources and theoretical argumentation rather than controlled empirical testing.
Dispersed work alters identity construction, belonging, and social cohesion; digital interactions reshape workplace rituals and norms.
Sociological literature synthesis and qualitative case illustrations emphasizing identity and ritual processes; no longitudinal or quantitative measures provided in the paper.
The paper proposes an 'algorithmic workplace' framework emphasising hybrid agency (agents composed of humans plus GenAI), decentralised decision processes, and erosion of rigid managerial boundaries.
Conceptual synthesis derived from thematic mapping, co‑word analysis and interpretive discussion of the mapped literature; framework presented as the article's conceptual contribution.
AI diffusion and China’s delayed retirement policy jointly shape pre-retirement workers’ willingness to stay employed.
Cross-sectional survey (n=889) of pre-retirement respondents in Beijing, Guangzhou, and Lanzhou; multivariate regression analysis examining associations between employment willingness and regional AI exposure plus policy context (delayed retirement).
Vulnerability is path-dependent and contingent on states’ adaptive capacity—governance quality, industrial policy, and bargaining leverage determine whether a country captures upgrading opportunities or becomes a strategic casualty.
Comparative case analysis using indicators of governance, industrial policy presence, and bargaining outcomes; process tracing of critical junctures showing divergent trajectories. (Data sources: governance indicators, case comparisons; sample sizes not specified.)
Trade diversion caused by tariff escalation and restrictions re-routes production and trade flows, but benefits are asymmetric: countries with stronger institutions, infrastructure, and policy capacity capture more investment and value-added.
Analysis of bilateral trade and FDI flow changes after tariffs; supply-chain mapping of relocation events; firm announcements of relocation; comparative cases emphasizing institutional/infrastructure differences. (Data sources: trade and investment flow data, supply-chain maps, firm-level announcements; sample sizes not specified.)
The benefits of AI come with governance, ethical, and sustainability challenges (standards, control, accountability) that require balancing against innovation incentives.
Synthesis of policy, ethics, and governance literature documenting concerns about standards, accountability, and incentive trade-offs; argument is qualitative and prescriptive rather than empirically tested within this paper.
AI has enhanced delivery in education, health, transportation, and government, improving some service outcomes while persistent issues like bias, privacy, transparency, and accountability remain.
Synthesis of applied-AI case studies and sectoral evaluations drawn from interdisciplinary literature; evidence described qualitatively without new empirical aggregation or meta-analysis in this paper.
AI reshapes demand for skills, redefines occupations, and accelerates the need for reskilling, with distributional effects that can increase inequality.
Narrative review of labor-economics and workforce studies documenting task reallocation and shifting skill requirements; based on observational studies and sectoral analyses summarized in the review (no unified sample size or new empirical test in this paper).
Ethics is distinct from and prior to law: legal codification cannot fully capture the primordial ethical demand.
Philosophical engagement with Derrida and Levinas; normative argumentation and conceptual examples. No empirical validation of precedence.
Legal norms and technical reforms are necessary but incomplete: they must remain responsive to a primordial, non-codifiable ethical obligation that structures how responsibility is perceived and allocated in practice.
Conceptual analysis drawing on Derrida and Levinas; argument supported by illustrative cases across three domains (care robotics, AVs, algorithmic governance). No empirical measurement of legal efficacy.
AI feedback may either augment teacher productivity (complementarity) or substitute for routine teacher feedback tasks (substitution), with unclear net labor impacts.
Workshop deliberations among 50 scholars highlighting competing theoretical scenarios; no causal labor-market evidence provided.
Reducing payrolls raises short-term firm profitability but reduces aggregate household income and consumption.
Macroeconomic accounting and labor-demand theory combined with historical examples of payroll reductions; argument is theoretical/conceptual rather than estimated with new aggregate time-series regression evidence.
Reviving model-based central planning tools (ISB+NDMS) risks political-economy problems and requires evaluation of efficiency and flexibility compared to market coordination.
Analytic discussion and normative argument in the paper; no empirical comparative study provided.
Russia's digitalization and adoption of AI/Big Data are reshaping the country's socio-economic infrastructure in multifaceted and systemic ways.
Qualitative analysis of national strategies and policy documents plus the author's expert assessments; no sample size or statistical testing reported.
Generative AI is not purely a job-destroying technology but a task-transforming force that reshapes skill requirements and occupational structures.
Synthesis of empirical studies and systematic reviews reported in the paper showing task reallocation, skill shifts, and occupational restructuring (study details not specified in excerpt).
Factors identified as relevant to AI emergence/adoption include Technology Adoption Rate (AI1), Government Policies and Regulations (AI2), Labor Market Dynamics (AI3), Technological Advancements (AI4), Corporate Strategies (AI5), and Socio-cultural Factors (AI6).
Author-provided list of factors in the paper; no empirical quantification, weighting, or methodology for selecting these factors is given in the excerpt.
Evidence on apprenticeship reforms indicates a shift toward higher-level qualifications and younger participants, while overall apprenticeship participation has declined.
Synthesis of reform evaluations and comparative studies on apprenticeship systems presented in the paper (summary does not identify which reforms/countries or provide participation statistics).
Participation in adult education and training has increased overall but remains uneven across age groups and skill levels.
Secondary data and comparative evidence cited in the paper showing rising adult learning participation with heterogeneity by age and skill level (no numerical breakdown provided in the summary).
Artificial intelligence (AI) is poised to transform the distribution and sources of income.
Analytical assertion in the paper (theoretical/policy analysis); no empirical data or specific study citations provided in the excerpt.
AI adoption generates different effects across different occupations.
Summary statement based on analysis of publicly available labor market data (occupational-level heterogeneity asserted but specific datasets, sample sizes, and methods not described).
AI is not an unprecedented disruption; its effects can be situated within established economic frameworks related to automation and task substitution.
Conceptual analysis comparing recent AI developments to historical automation and task-substitution frameworks; empirical grounding claimed via publicly available labor market and productivity data (details not provided).
AI has emerged as a transformative force that influences economic systems, institutional functions, and daily human behaviors.
Stated as an overarching observation in the paper (theoretical/interpretive claim); no empirical methods or sample sizes are reported in the abstract.
The rapid global proliferation of Artificial Intelligence (AI) has created a profound paradox: while promising unprecedented productivity gains, its current trajectory exacerbates labor market polarization, deepens inequality, and threatens to fracture the 20th-century social contract.
Asserted in abstract; no empirical methods, datasets, or sample sizes described in the abstract (presumably supported in paper by literature review/argumentation).
AI alters job structures, workflow patterns, and human roles in decision-making processes.
Thematic content analysis of recent accredited journal literature as part of the qualitative library research (sources not enumerated).
AI is fundamentally transforming the workplace by creating new opportunities, intensifying challenges, and redefining professional skills.
Qualitative library research: systematic documentation and thematic content analysis of recent accredited journal sources (number of sources not specified).
The actions of large employers in an occupation or industry affect local and national wages, employment and output.
Theoretical/empirical claim in the paper; excerpt does not supply empirical methods, identification, or sample sizes demonstrating these effects.
Gender shapes the impact of social protection: program effects are mediated by gender norms and intra-household dynamics, and gender differences in opportunities, constraints, and preferences determine who can participate in and benefit from social protection.
Theoretical and literature-based assertion in the introduction; authors indicate program impacts are mediated by gender norms and household dynamics and will review evidence in the chapter (no specific empirical details in excerpt).
As AI becomes increasingly integrated into higher education, instructors and institutions face urgent questions about its implications for teaching, learning, scholarly practice, and for power, agency, and access.
Framing claim in the paper's introduction supported by literature context and reinforced by the study's analysis of practitioner (faculty) discussions on Reddit indicating concern/uncertainty. (The excerpt does not report survey or quantitative prevalence data on how widespread these concerns are.)
Through thematic content analysis, the study explores faculty perceptions, pedagogical tensions, and imaginative possibilities surrounding AI’s academic role.
Method stated by author: thematic content analysis of subreddit discussions to identify themes relating to faculty perceptions, pedagogical tensions, and imagined futures for AI in academia. (Exact number of themes, coding procedure, and sample size not provided in excerpt.)
AI reshapes traditional power structures, challenges regulatory frameworks, and redefines global governance mechanisms.
Broad analytic claim supported by comparative policy analysis and qualitative document review; the paper frames this as an overarching conclusion without reporting quantitative indicators or case counts.
The geopolitics of AI constitutes not only a competition for technological supremacy but also a contest over the moral and institutional foundations of global governance.
Theoretical synthesis drawing on international relations theories (realism, liberal institutionalism, constructivism) and comparative policy analysis; presented as an interpretive conclusion rather than empirically quantified.
AI represents a new dimension of geopolitical power that influences how states project authority, regulate innovation, and negotiate global norms.
Argument based on comparative policy analysis and qualitative document review of state and multilateral policy documents (specific documents and number not enumerated in text).
Artificial intelligence (AI) has emerged as one of the most transformative forces shaping the 21st-century international order.
Conceptual claim supported by literature review and theoretical framing in the paper (no empirical sample or quantitative data reported).
Knowledge democratization through AI may reduce educational inequality but may also exacerbate digital divides and erode universities' social mobility function.
Theoretical and socio-political analysis considering opposing effects; framed as a conditional/mixed outcome without empirical measurement reported in the paper.
AI displacement potential varies substantially across university functions.
Summary finding from the paper's comparative analysis of university functions; the paper provides ranked/percent estimates but does not report empirical sampling or statistical testing.
The Photo Big 5 provides predictive power comparable to race, attractiveness, and educational background.
Comparative predictive-performance analyses reported in the paper that evaluate Photo Big 5 against observables such as race, measured attractiveness, and education background within the same sample.
Generative artificial intelligence (GenAI) adoption is diffusing rapidly but its adoption is strikingly unequal.
Nationally representative UK survey data collected in 2023–2024 reporting adoption rates by subgroup; descriptive analysis of diffusion and disparities by demographic groups.
AI is transforming jobs that are technical in nature.
Asserted in the paper's conceptual discussion of dual impacts; presented without empirical measurement or reported sample data in this paper.
Data maturity, ethical governance of algorithms, and industry type shape business performance in AI-augmented workflows.
Moderator/subgroup analyses and qualitative synthesis across the reviewed studies indicating these contextual factors influence outcomes; based on the 85-publication review.
Most moderators tested in the analyses have a considerable influence on the relationship between AI use and business performance.
Moderator analyses reported in the meta-analysis (unspecified number of moderators) across the sample of reviewed studies (n=85).
Digital transformation reshapes labor markets.
Paper asserts effects on labor markets (skills demand, employment patterns); the abstract lacks details on labor market data, sample sizes, or econometric analyses used to substantiate this claim.
AI, blockchain, and big data analytics affect productivity, investment strategies, labor markets, and regulatory frameworks.
Stated in the paper as impacts analyzed; the abstract does not specify the data, methods, or scope used to measure these impacts.
Digital transformation through artificial intelligence (AI), blockchain technology (BT), and big data (BD) analytics reconfigures economic mechanisms at both micro- and macroeconomic levels.
Paper-level analytic claim referencing impacts of AI, blockchain, and big data; detailed empirical methodology and sample information not described in the abstract.
In digital tourism, there is both substitution potential (virtual experiences, demand management) and rebound risks that may offset emissions reductions.
Sectoral case synthesized from peer-reviewed studies and reports on digital tourism and travel demand (review-level evidence; no single empirical sample size).