Evidence (14055 claims)
Adoption
8570 claims
Productivity
7631 claims
Governance
6869 claims
Human-AI Collaboration
6491 claims
Org Design
4175 claims
Innovation
4114 claims
Labor Markets
3566 claims
Skills & Training
2966 claims
Inequality
2066 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 758 | 199 | 100 | 900 | 2007 |
| Governance & Regulation | 826 | 400 | 191 | 122 | 1563 |
| Organizational Efficiency | 777 | 193 | 124 | 84 | 1189 |
| Technology Adoption Rate | 635 | 233 | 124 | 97 | 1098 |
| Research Productivity | 422 | 128 | 57 | 336 | 954 |
| Output Quality | 476 | 179 | 59 | 47 | 761 |
| Decision Quality | 328 | 177 | 81 | 47 | 640 |
| Firm Productivity | 435 | 57 | 88 | 20 | 606 |
| AI Safety & Ethics | 218 | 277 | 65 | 33 | 599 |
| Market Structure | 180 | 170 | 123 | 24 | 502 |
| Task Allocation | 213 | 64 | 72 | 33 | 387 |
| Skill Acquisition | 170 | 61 | 61 | 17 | 309 |
| Innovation Output | 203 | 27 | 43 | 18 | 292 |
| Employment Level | 105 | 54 | 107 | 13 | 281 |
| Fiscal & Macroeconomic | 131 | 69 | 43 | 26 | 276 |
| Consumer Welfare | 117 | 63 | 42 | 11 | 233 |
| Firm Revenue | 153 | 48 | 26 | 3 | 230 |
| Task Completion Time | 173 | 31 | 8 | 12 | 225 |
| Inequality Measures | 44 | 122 | 49 | 6 | 221 |
| Worker Satisfaction | 89 | 65 | 22 | 12 | 188 |
| Error Rate | 69 | 92 | 10 | 2 | 173 |
| Regulatory Compliance | 77 | 69 | 14 | 5 | 165 |
| Automation Exposure | 56 | 56 | 26 | 13 | 154 |
| Training Effectiveness | 94 | 21 | 13 | 19 | 149 |
| Wages & Compensation | 77 | 36 | 25 | 6 | 144 |
| Team Performance | 86 | 17 | 27 | 10 | 141 |
| Developer Productivity | 95 | 17 | 14 | 6 | 133 |
| Job Displacement | 12 | 80 | 20 | 1 | 113 |
| Hiring & Recruitment | 52 | 7 | 8 | 3 | 70 |
| Creative Output | 31 | 18 | 8 | 3 | 61 |
| Skill Obsolescence | 5 | 46 | 6 | 1 | 58 |
| Social Protection | 27 | 16 | 8 | 2 | 53 |
| Labor Share of Income | 17 | 19 | 17 | — | 53 |
| Worker Turnover | 11 | 12 | — | 3 | 26 |
| Industry | — | — | — | 1 | 1 |
The study coded 500 adaptation events.
Explicit statement: 'and 500 coded adaptation events.'
The qualitative dataset included 48 executive and technical informants.
Explicit statement: 'including 48 executive and technical informants'.
The study uses a comparative multi-case dataset of 12 multinational firms (4 tri-jurisdictional, 4 Atlantic, 4 China-primary).
Explicit dataset description in the paper: 'A comparative multi-case dataset of 12 multinational firms (4 tri-jurisdictional, 4 Atlantic, 4 China-primary) was analyzed.'
We employ the Gemini API to generate reward function logic and weights across three refinement rounds rather than performing per-step inference.
Methodological description in abstract: use of Gemini API to generate reward logic and weights; three rounds of refinement.
We deploy a Soft Actor-Critic (SAC) agent in CityLearn v2 for experiments.
Methodological description in abstract: SAC agent used within CityLearn v2 environment.
We use four empirically grounded occupant profiles from the ASHRAE Global Thermal Comfort Database II (13,440 votes).
Dataset citation and sample size reported in abstract: ASHRAE Global Thermal Comfort Database II with 13,440 votes; four occupant profiles derived from it.
We ran 24 matches pairing 23 expert humans with 16 AI agents, capturing 387 delegation and 1440 adoption decisions.
Author-reported experimental setup and counts from the study (24 matches; 23 human experts; 16 AI agents; counts of delegation and adoption decisions).
The model introduces the 'Sciencepreneur' as the central human archetype in agentic R&D.
Conceptual/design claim within the HARMONY artifact presented in the paper.
Evidence also includes pattern matching with documented agentic R&D deployments.
Methodological statement in the paper claiming pattern matching with documented agentic R&D deployments (unspecified number/source).
The study includes a foresight scenario analysis projecting four plausible 2040 R&D futures to stress-test design choices.
Methodological statement in the paper describing a four-scenario foresight analysis.
Empirical evidence for the design is triangulated from four semi-structured expert interviews with senior R&D leaders across industrial, healthcare, and academic settings.
Methodological statement in the paper specifying four semi-structured expert interviews.
This discrimination was invisible to standard action-log audits: bias operated entirely through who received each action, not what actions were chosen, with action-type distributions showing no increase in negative actions across conditions.
Comparison of action-recipient patterns vs action-type distributions across the experimental conditions in the simulation; reported observation that action-type distributions did not show increased negative actions and that audits of action logs (action types) failed to reveal the bias.
Because all observations come from a single practitioner, the inferential statistics are exploratory and hypothesis-generating rather than confirmatory; portability across the full portfolio awaits multi-practitioner replication.
Explicit limitation stated in the paper about the single-practitioner design and its implications for inference.
The framework is illustrated with an accounts-payable simulation and a companion spreadsheet.
Empirical illustration: the paper includes (or accompanies) an accounts-payable simulation and a spreadsheet to demonstrate the model and estimation approach.
The note starts from a compact dashboard expression, expands it into a fuller structural model, defines all variables and parameters, and shows how each cost category can be estimated from operational data.
Methodological description in the paper: construction of dashboard, expansion to structural model, full variable/parameter definitions, and stated procedures for estimating cost categories from operational data; accompanied by worked examples.
Agentic Technical Debt is a stock of accumulated design and governance liability.
Definition provided in the paper as part of the conceptual framework that labels Agentic Technical Debt as a stock (accumulated) liability tied to design and governance.
This note develops a formal and managerially usable model that distinguishes Agentic Technical Debt from Stochastic Tax.
Author states development of a formal, managerially usable model and explicit distinction between the two constructs; supported by model construction in the paper (structural model and dashboard).
Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integration.
Conceptual/definitional statement in the paper; presented as the working characterization of 'Agentic AI systems' within the model specification.
We evaluate SIA across three contrasting domains: Chinese legal charge classification (LawBench), low-level GPU kernel optimisation, and single-cell RNA denoising.
Experimental design described in the paper (three benchmark domains used for evaluation).
We propose SIA, a self-improving loop in which a language-model agent (the Feedback-Agent) updates both the harness and the weights of a task-specific agent.
Methodological contribution described in the paper (proposal of a new combined approach; implementation details presumably in methods).
These two silos (harness-update and test-time training) operate in isolation.
Authors' characterization of the research landscape presented in the paper (conceptual claim/literature observation).
Two largely disjoint research lines attack this bottleneck: the harness-update school (a meta-agent rewrites the scaffold while model weights are fixed) and the test-time training school (hand-written RL pipelines update model weights while the harness is fixed).
Paper's literature/positioning claim classifying prior work into two categories (conceptual/literature summary).
(i, continued) The counterfactual toll has explicit non-uniqueness (i.e., non-uniqueness of the toll is demonstrated).
Mathematical argument in the paper identifying conditions or constructions that lead to multiple valid tolls (formal counterexample or theorem on non-uniqueness).
Seventeen operators completed continuous search tasks under high cognitive workload while their spatial covariance was mapped using a 2D Adaptive Riemannian Oracle.
Methodological description in the paper: 17 human operators performed continuous search tasks in a Virtual Reality drone task; spatial covariance recorded using a 2D Adaptive Riemannian Oracle.
The paper proposes a policy framework consisting of six groups of solutions for Vietnam to both promote AI development and control risks in the digital age.
Declared in abstract: the paper presents a six-group policy framework for Vietnam; the framework itself is the paper's output (proposal), not empirically tested in the paper.
This study employs document synthesis and comparative analysis of international policies.
Methodological statement in the paper abstract describing the research approach; no sample size specified beyond document sources.
The rise of artificial intelligence (AI) is shaping a new Agent Economy (AE), in which autonomous AI agents represent humans in performing a wide range of complex tasks.
Statement in paper abstract/intro (conceptual definition); no empirical data or sample reported.
Outputs are graded by a fact-anchored chain of rubrics, averaging 35.6 binary criteria per task.
Benchmark grading methodology reported by the authors, with a reported average of 35.6 binary criteria per task (presumably calculated across the benchmark tasks).
JobBench covers 130 agentic tasks across 35 occupations.
Dataset/benchmark composition reported by the authors (explicit counts provided in the paper).
The study contributes a taxonomy of AI workforce impact, a Workforce Resilience Readiness Score (WRRS), an AI Workforce Trust Index (AWTI), an Ethical Automation Boundary concept, and a pilot empirical validation design.
Declared methodological and conceptual contributions in the paper (these are presented as deliverables of the study; no validated results reported in the excerpt).
The International Labour Organization's 2025 update highlights the need to assess the exposure of generative AI at the task level using task data, expert input, and AI model predictions.
Reference to ILO 2025 update recommendation described in the paper (policy/technical guidance rather than primary empirical data in the excerpt).
A path analysis was used to trace structural relationships between HR quality, effectiveness perceptions, and AI readiness.
Paper reports a path analysis linking composite HR quality indices, perceived HR effectiveness, and AI readiness measures; uses same survey sample.
A binary logistic regression modelling active AI adoption was estimated with McFadden R² = 0.032.
Reported logistic regression model fit (McFadden R² = 0.032) for AI adoption outcome using the survey data.
An OLS regression was estimated explaining perceived HR effectiveness with R² = 0.446.
Reported OLS model fit statistics in the paper (R-squared = 0.446); model explains perceived HR effectiveness using survey data.
Constructed and validated a composite index of external HR quality factors with Cronbach's α = 0.959.
Measurement validation reported in the paper; Cronbach's alpha reported for external HR factors.
Constructed and validated a composite index of internal HR quality factors with Cronbach's α = 0.924.
Measurement validation reported in the paper; Cronbach's alpha reported for internal HR factors.
A large-scale empirical survey of 12,562 public servants was conducted in June 2025 in Kazakhstan.
Statement in paper specifying survey sample and date; sample of public servants N = 12,562, June 2025.
A strict May 2026 trajectory subset captured 627 model-completed events and 73.95 million recorded tokens, of which 82.9% were cache reads.
Subset analysis of telemetry for a May 2026 trajectory reported by authors; counts of model-completed events and token logs, with cache-read classification.
Memory-derived records identified 482 output-proxy events and 889 failure, verification, correction, or protocol-proxy events.
Analysis/parsing of memory-derived records from the persistent environment yielding categorized event counts.
Active system time was 579.7 hours (30-minute capped-gap estimate).
Computed runtime activity metric from system telemetry/logs over the study period; authors report a 30-minute capped-gap estimate to compute active system time.
The workspace included 502 memory-related files, 17 configured agent directories, and 57 skill files.
Inventory of the implemented persistent agent workspace reported by authors as part of the case study (counts extracted from workspace metadata/filesystem).
Recoverable main-agent telemetry contained 75,671 de-duplicated records across 96 active days, with 8,059 user-role and 23,710 assistant-role messages.
Structured self-observed implementation case study (unit: a single persistent human-agent environment) conducted Jan 31–May 25, 2026; authors report recoverable telemetry logs totaling these counts.
We compare and benchmark strategy profiles adopted by open and proprietary state-of-the-art language models deployed in AgentSociety against best response.
Empirical benchmarking experiments comparing multiple language models' strategy profiles to best-response strategies (experimental evaluation / benchmarking).
Historically, the most visible high-end bugonomics was offense-priced because production-grade zero-days and exploit chains were expensive specialist outputs for governments, brokers, and offensive vendors.
Historical observation corroborated by reference to public exploit-market price anchors (market price data referenced; no specific figures included in the abstract).
Identification limits prevent a strict causal claim; the paper outlines an agenda for cleaner tests.
Authors' explicit caveat in the abstract noting limits to identification and stating they outline future cleaner tests.
The analysis exploits the staggered rollout of Claude Code across GitHub between May 2025 and January 2026, using a panel of 5,838 developers observed monthly over 28 months, with treatment defined by a developer's first Claude-co-authored commit and not-yet-treated developers as controls, and estimates obtained via the doubly robust Callaway and Sant'Anna (2021) estimator.
Methods and data description as stated in the abstract: staggered rollout timing, sample size (5,838), observation window (28 months), treatment definition (first Claude-co-authored commit), estimator (Callaway & Sant'Anna 2021).
Results are robust to two stricter activity filters.
Robustness checks reported in the paper applying two stricter activity filters to the sample; claim refers to consistency of estimated effects under these alternate sample definitions.
The actual water footprint of a specific load varies dynamically with generation dispatch and network conditions.
Conceptual claim presented in the paper motivating the need for dynamic attribution (discussion/analysis rather than a reported empirical sample).
Water withdrawals associated with electricity consumption occur at generation sites and are virtually allocated to demand based on network power flows.
Conceptual statement about how water withdrawals are attributed to loads via network power flow accounting (methodological description in paper).
The analysis is structured across past, present, and future phases using an integrative socio-technical political economy framework and validated secondary sources (OECD, ILO, UNDP, WTO, WEF) alongside official Indian statistics and sector evidence.
Methodological claim stated in abstract describing the approach and data sources used in the paper (OECD, ILO, UNDP, WTO, WEF, MoSPI/NSO, PLFS, HCES, Reuters, Nasscom).