Aiid
Free, open database cataloging real-world AI incidents and harms for research and governance.
AIID is a vital, free resource for AI safety research and governance. Compared to commercial risk platforms like Credo AI or Holistic AI, it's free, transparent, and community-driven, but it's a manual research tool—not live monitoring. Pair it with real-time tools if you need immediate alerts. Its depth and openness are unmatched for learning from past incidents.
Verified 5d ago · liveness 60/100 · cite: rightaichoice.com/tools/aiid
- AI safety researchers studying failure patterns across domains
- Developers auditing their AI systems against known harms
- Policy analysts drafting AI regulation or guidelines
- Journalists investigating AI-related incidents and trends
- Users seeking real-time monitoring for live AI systems
- Teams needing automated incident detection or alerting
- Organizations looking for vendor-specific risk assessment reports
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
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Skip AIID if you need real-time incident alerts or automated risk analysis for live systems; it's a retrospective archive, not a monitoring tool.
No hidden costs: all features are free, but you may find that researching incidents manually takes significant time compared to commercial tools.
AIID is free for everyone, making it ideal for independent researchers, nonprofits, and students. Unlike commercial platforms with per-seat fees, AIID requires no budget. If you need ongoing monitoring or vendor-specific analytics, you'll pay elsewhere.
In short
Aiid — Free, open database cataloging real-world AI incidents and harms for research and governance. Best for AI safety researchers studying failure patterns across domains, Developers auditing their AI systems against known harms, Policy analysts drafting AI regulation or guidelines. Free to use.
What's new in Aiid
Checked 5 days agoAcross the latest 4 updates: 4 news mentions.
Strengthening AI Incident Monitoring and Reporting in Africa for Global AI Safety
AIID blog post discusses efforts to improve AI incident monitoring and reporting in Africa, contributing to global AI safety.
AI Incident Roundup - May, June, and July 2026
Quarterly roundup covering new incident entries and patterns from May through July 2026.
Matching Incidents to Use Cases: A Case Study in Applying AIID Data to Governance Workflows
Case study demonstrating how to use AIID incident data proactively in governance workflows.
Notes for the Growing AI Safety Ecosystem: Corporations and Governments
Blog post sharing notes for corporations and governments building on the AI Incident Database.
What people actually say about Aiid — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
27 mentions across 3 sources (YouTube, GitHub, Lemmy) · researched Jul 29, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Free and open-source with no registration required to use.
- +Over 1,500 real-world AI incidents cataloged with full metadata.
- +Multiple views: table, list, spatial map, entity/taxonomy filters.
- +Dataset downloadable and API accessible for large-scale analysis.
- +Quarterly roundups and guidance for corporations and governments.
- −Almost no user community on mainstream platforms like Reddit or HN.
- −249 open GitHub issues may indicate slow maintenance.
- −No formal support; reliance on GitHub issues only.
- −YouTube and Lemmy data show zero relevant user discussions.
- −Incident selection may lack global or diverse representation.
Viability Score
How well maintained and how widely used is Aiid? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Browse over 1,600+ AI incident reports with metadata
- Table, list, and spatial map views for incidents
- Filter by entity, taxonomy, and date
- Search across all incidents and reports
- Submit new incident reports via form
- Download full incident dataset
- Random incident discovery
- API access for programmatic queries
- Entity and taxonomy categorization
- Flag incidents for review
- Quarterly AI Incident Roundups
- Subscribe to new incident email notifications
- Dark mode and accessibility features
About Aiid
The AI Incident Database (AIID) is a free, open, community-driven repository that systematically collects, classifies, and shares reports of real-world incidents where AI systems caused or contributed to harm. Built for researchers, developers, product managers, policymakers, and journalists, it serves as a collective memory of AI failures, helping you identify patterns, conduct risk assessments, and inform regulation. With over 1,600 entries—from autonomous vehicle accidents to algorithmic bias and AI-generated hallucinations in legal filings—it's a go-to resource for understanding how AI goes wrong. Explore incidents through multiple views: a table view for sorting, a list view for scanning, a spatial map for geographic trends, and entity and taxonomy filters for structured analysis. A random incident feature offers serendipitous discovery, while powerful search lets you zero in on specific events. New reports are submitted by the community and undergo editorial review before being indexed, ensuring quality and relevance. The database is open-source, governed by the Responsible AI Collaborative, and funded through donations and grants. All features—including full dataset downloads, API access, and the blog with quarterly roundups—are free and require no registration. Recent entries include AI-generated fake citations in legal filings, deepfake impersonation scams, and unauthorized recording by transcription tools. The latest incidents (September 2026) highlight AI agents being used in cyberattacks, wiping production databases, and other high-impact failures. For anyone tracking AI harms, AIID is a practical alternative to commercial risk platforms: it's free, transparent, and community-driven, though it demands manual research. It's not a real-time alerting tool, but a rich, searchable archive for learning from the past.
Behind the Verdict
AIID fills a critical gap: a public, searchable archive of real AI failures. Unlike vendor-specific risk assessment reports or proprietary databases, it's free and open, making it accessible to researchers, journalists, and smaller organizations. The strength is the volume and structure—over 1,600 incidents with metadata, taxonomies, and multiple viewing modes. You can filter by entity, taxonomy, and date, which is useful for spotting patterns across domains. The spatial map helps visualize geographic trends. However, it's a manual research tool. There's no real-time alerting; you check the database when you need to research past incidents. The data quality varies because it relies on community submissions and public records, so you must verify sources. API documentation is minimal, which might frustrate developers wanting to integrate data programmatically. Also, it's not predictive—it tells you what happened, not what might happen. For a developer auditing your AI system, you can search for similar past incidents to inform risk assessments. For a policy analyst, it provides empirical evidence for regulations. For a journalist, it offers context and history. But for teams needing continuous monitoring of live systems, you need a different tool. Recent 2026 incidents underscore the growing risk of AI agents acting autonomously during cyber intrusions and coding errors. AIID captures these cases, making it increasingly valuable as AI agents become more powerful. The blog's quarterly roundups and governance case studies show how the data can be applied proactively. In short, AIID is indispensable for learning from the past. Use it to build your own risk register or research failure patterns. But don't expect it to alert you to new incidents as they happen. You pair it with real-time sources if you need that.
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Real-world workflow fit
Concrete scenarios for the personas Aiid actually fits — and what changes day-one when you adopt it.
Study recent agent-related incidents to inform a new paper.
Outcome: Search for 'agent' incidents, filter by date, and download relevant reports to analyze patterns.
Draft a regulatory brief on AI harms.
Outcome: Use the spatial map and taxonomy filters to find incidents across sectors, then export a summary for the brief.
Audit a new AI product against known failure modes.
Outcome: Search for incidents that match your product's domain, review details, and incorporate findings into a risk checklist.
Use Cases
- Research historical AI failures to identify recurring patterns and risks.
- Support policy submissions with empirical evidence from documented incidents.
- Integrate incident data into AI safety checklists for model deployment.
- Use the dataset for academic research on AI harm taxonomy.
- Educate teams on the real-world consequences of AI system failures.
- Track emerging AI harm trends via quarterly roundups.
- Reference past incidents when designing corporate AI governance frameworks.
- Cite AIID in journalism to provide context for current AI controversies.
Limitations
- Incident reports are sourced from public records and submissions, which may introduce reporting bias or lag.
- The database relies on community contributions for completeness, so not all incidents may be captured.
- API access is available but documentation is minimal.
- No real-time monitoring or automated alerting.
- Report quality varies with source credibility.
- The database is focused on past incidents, not predictive risk assessment.
as of 2026-09-09
Verification history
We have re-verified Aiid 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Aiid tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Anyone needing access to AI incident data: researchers, journalists, developers, and policymakers without budget for commercial risk platforms.
What this tier adds
All features are free: full access to incident reports, all views, filters, submission, downloads, API, and email notifications.
Where the pricing makes sense
The company stage and team size where Aiid's pricing actually pencils out — and where peers do it cheaper.
AIID is free for everyone, making it ideal for independent researchers, nonprofits, and students. Unlike commercial platforms with per-seat fees, AIID requires no budget. If you need ongoing monitoring or vendor-specific analytics, you'll pay elsewhere.
Setup time & first value
How long it actually takes to get something useful out of Aiid — broken out by persona, not the marketing-page minute.
Setup is instant: no registration required. You can start browsing incidents and using filters within minutes. If you want to use the API, you may spend a few hours reading minimal docs and testing endpoints.
Switching to or from Aiid
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a paid risk platform like Credo AI: export incident data and manually map it to AIID's taxonomy; you'll keep your historical records but gain a free, broader database.
- ↗To a real-time monitoring tool like Robust Intelligence: export AIID dataset via CSV or API, then set up your own watchlists for ongoing monitoring.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Aiid”, and we withheld 6: 6 could not be judged, because “Aiid” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Aiid.
Official links
Tools that pair well with Aiid
Common stack mates teams adopt alongside Aiid, with the specific reason each pairing earns its keep.
Fiddler AI
Fiddler AI is an enterprise AI control plane for agent observability, guardrails, and governance across the agentic lifecycle.
Iris.ai
Iris.ai builds an AI knowledge foundation that turns complex regulated enterprise data into auditable, explainable intelligence.
Norm.ai
Agentic law platform that embeds legal judgment into AI agents for verifiable compliance
Featured Head-to-Head Comparisons
Aiid vs Surge Ai
If you need to study past AI failures for research or policy, AiID is the free, definitive source. If you're building frontier models and need expert human feedback or red teaming to align them, Surge AI is the premium choice. They serve completely different stages of the AI lifecycle: retrospect vs. proactive alignment.
Aiid vs Praktika
Praktika and Aiid serve completely different needs. If you're an intermediate language learner seeking conversational fluency with AI-powered feedback, Praktika's freemium model offers real-time pronunciation and grammar correction. If you're an AI safety researcher or developer needing to understand failure patterns, Aiid's free repository of 1,500+ incident reports is invaluable. Choose based on your goal: language practice vs. harm analysis.
Alternatives to Aiid
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Fiddler AI
Fiddler AI is an enterprise AI control plane for agent observability, guardrails, and governance across the agentic lifecycle.
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