{"address":{"q":"ai incident database","record":"ai-incident-database-aio-20261029"},"analysis":{"analysis":"The Overview composes the database at the grain of its own about page and keeps it apart from its neighbours. It gives the operator, the model and the derived layer, and omits the incident-and-report structure that makes the database what it is. This is the baseline for the meta-aggregator's record, which was not yet indexed: no card is machinemediation.org.","d":"THE AI INCIDENT DATABASE, BY NAME, ON GOOGLE'S AI OVERVIEW, SIGNED OUT, 2026-10-29: 'a free, open-source project managed by the Responsible AI Collaborative that indexes real-world harms, near-harms, and failures caused by artificial intelligence systems'. Four points: the aviation and cybersecurity reporting model, a scope of harms (bias, privacy, misinformation, deepfakes, vehicles, safety-critical failures), growth with deepfake and scam entries multiplying, and the MIT AI Incident Tracker as a research extension that parses the database with taxonomies and LLM pipelines. Six cards: the database, the MIT tracker, Partnership on AI, the OECD catalogue entry, a Kaggle dataset, a TIME clip.","d_full":"THE AI INCIDENT DATABASE, BY NAME, ON GOOGLE'S AI OVERVIEW, SIGNED OUT, 2026-10-29: 'a free, open-source project managed by the Responsible AI Collaborative that indexes real-world harms, near-harms, and failures caused by artificial intelligence systems'. Four points: the aviation and cybersecurity reporting model, a scope of harms (bias, privacy, misinformation, deepfakes, vehicles, safety-critical failures), growth with deepfake and scam entries multiplying, and the MIT AI Incident Tracker as a research extension that parses the database with taxonomies and LLM pipelines. Six cards: the database, the MIT tracker, Partnership on AI, the OECD catalogue entry, a Kaggle dataset, a TIME clip.","findings":["THE ENTITY HELD. Operator (the Responsible AI Collaborative), purpose ('harms, near-harms'), the aviation model and the MIT tracker as a derived layer are the record's fields: the about page's operator, the editors' guide's comparison with aviation, and the tracker's own statement that it classifies AIID reports with Arcola AI's pipeline. Checked 2026-10-29 against the MMRS meta-aggregator record of 2026-10-28 and the entity's own pages, re-read the same day.","WHAT IS NOT GIVEN. The incident as the unit, the reports attached to it, and the citation page /cite/N are absent; 'collects public and crowdsourced reports' stands in for the unit.","A HOMONYM IN THE CARDS. 'AI Incidents, Failures & Controversies Database' on Kaggle (32 incidents, 29 companies, 13 countries) is another dataset with a near name; the composition does not use it, and the card sits beside the database's own.","'OPEN-SOURCE'. The database's code is open on GitHub (its about page); the record states no data licence on the snapshots page, and the composition's 'free, open-source' does not distinguish the two."],"match":"BROAD MATCH","mt":"THE AI INCIDENT DATABASE BY ITS NAME ON THE OVERVIEW — THE OPERATOR AND THE AVIATION MODEL RIGHT; THE MIT TRACKER NAMED AS ITS EXTENSION; A KAGGLE DATASET OF 32 INCIDENTS AMONG THE CARDS","notes":{"prompts":"One query. Sent by the operator on 2026-10-29 with nineteen others, one per entity of the MMRS meta-aggregator, at his offer to run them: 'ill run captures if you want, just list the semantic addresses'."},"originator":{"basis":"Not the archive's: AI Incident Database, run by Responsible AI Collaborative. Formalized by the MMRS meta-aggregator record of 2026-10-28 (https://www.machinemediation.org/aggregators/ai-incident-database/), editor Lee Sharks; the record's fields are read from the entity's own pages with source and basis. Recorded 2026-10-29.","entity_type":"dataset","name":"Responsible AI Collaborative","relation":"external","spxi_treatment":"partial"},"reading":"The innocent reading first. The Overview identifies the database, its operator and its purpose, gives the model it is built on and the kinds of harm it holds, and names the MIT tracker that reclassifies it. Its cards are the database's own about page, the tracker, the founding sponsor's page and the OECD's catalogue entry."},"measures":{"archive_controlled_cites":0,"cite_list":[{"n":1,"note":null,"rel":"third_party","site":"AI Incident Database","snip":"About the Database The AI Incident Database is dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment ...","title":"AI Incident Database","url":null},{"n":2,"note":null,"rel":"third_party","site":"MIT AI Risk Initiative","snip":"Overview: MIT AI Incident Tracker classifies 1,752 real-world AI incident reports from the AI Incident Database using Arcola AI's LLM pipeline, MIT Risk Reposit...","title":"MIT AI Incident Tracker","url":null},{"n":3,"note":null,"rel":"third_party","site":"Partnership on AI","snip":"As AI technology is integrated into an increasing number of safety-critical systems — entering domains such as transportation, healthcare, and energy — the pote...","title":"AI Incident Database - Partnership on AI","url":null},{"n":4,"note":null,"rel":"third_party","site":"OECD AI Policy Observatory","snip":"AI Incident Database Website Github Technical Educational Uploaded on Apr 25, 2024 The AI Incident Database is free and open-source project dedicated to indexin...","title":"AI Incident Database","url":null},{"n":5,"note":null,"rel":"third_party","site":"Kaggle","snip":"32 verified incidents · 29 companies · 13 countries · 24 columns — Every major AI failure, documented 📌 Why This Dataset? AI incidents surged 56.4% in 2024 alo...","title":"AI Incidents, Failures & Controversies Database - Kaggle","url":null},{"n":6,"note":"video, 1:35","rel":"third_party","site":"LinkedIn·TIME","snip":null,"title":"AI Incident Database | TIME posted on the topic","url":null}],"cites":6,"per":0.5,"per_note":"The Responsible AI Collaborative and Partnership on AI named; no person named (the record names Sean McGregor); no identifier or citation page given; the database's own pages cited.","per_v":{"author":false,"id":false,"inst":true,"src":true}},"observation":{"auth":"signed out, incognito","date":"2026-10-29","ev":"paste","q":"ai incident database","q_kind":"the name of an entity of the MMRS meta-aggregator (AI Incident Database; record https://www.machinemediation.org/aggregators/ai-incident-database/, compiled 2026-10-28), run at the operator's offer on 2026-10-29 to supply the composition layer's account of the entity for its record and its /non row; one of the record's reception battery queries. A baseline: the record landed on machinemediation.org the same night (commit 8997e28) and no card cites it. NEW address.","s":"Machine Reception","surface":"Google AI Overview","transcript":"[Google AI Overview at the query, signed out and incognito (operator defaults of 2026-10-01 and 2026-10-14), 2026-10-29. The paste is the Overview expanded (the 'AI Mode Conversation' view, with the source cards that follow the answer); the 'You said' line carries the query twice, run together, and is given once here. Inline links are Google redirect URLs, kept as pasted. The closing disclaimer cut.]\n\n[QUERENT] ai incident database\n\n[SYSTEM] The [AI Incident Database](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw) is a free, open-source project managed by the [Responsible AI Collaborative](https://www.google.com/goto?url=CAESbwHrOzAVQJB-mdnnQ6r52BIfaBkZdpvIYmeG5iTBUzeQEwySxYcKr4WzFleLjuPKMrQKQTK3W2B9l2jGnS5pLy19F1B1fTurJ-XoVDm2xfief4Gqb_ptw2t6ueReQR1dw3n-38GlP31Dx2C5MCLIXg) that indexes real-world harms, near-harms, and failures caused by artificial intelligence systems. [[1](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw), [2](https://www.google.com/goto?url=CAESbwHrOzAVQJB-mdnnQ6r52BIfaBkZdpvIYmeG5iTBUzeQEwySxYcKr4WzFleLjuPKMrQKQTK3W2B9l2jGnS5pLy19F1B1fTurJ-XoVDm2xfief4Gqb_ptw2t6ueReQR1dw3n-38GlP31Dx2C5MCLIXg)]\nCore Purpose & Model\n\n* Aviation Safety Model: Modeled after safety incident reporting systems used in aviation and cybersecurity, it collects public and crowdsourced reports to help the industry learn from past failures. [[1](https://www.google.com/goto?url=CAESdQHrOzAVEAwZDxstOqfa0VkpGaNmKMMUp0iksIt5wKMhQJlSZH2s4ag2eyxAImW5bXA_shrWdHkDg9o2go4aRguIXp0j_UcNeCVAdipEGHaZZwzksRC_l2QRbFfdaIIX3dmL48i7pJ14tjxs2OqAzRY1Ee9MoA), [2](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw)]\n* Scope of Harms: Documents issues spanning algorithmic bias, discrimination, privacy leaks, misinformation, deepfakes, autonomous vehicle accidents, and safety-critical system failures. [[1](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4), [2](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg), [3](https://www.google.com/goto?url=CAESdQHrOzAVEAwZDxstOqfa0VkpGaNmKMMUp0iksIt5wKMhQJlSZH2s4ag2eyxAImW5bXA_shrWdHkDg9o2go4aRguIXp0j_UcNeCVAdipEGHaZZwzksRC_l2QRbFfdaIIX3dmL48i7pJ14tjxs2OqAzRY1Ee9MoA)]\n* Growth & Trends: Incidents tracked by the database have surged significantly, with deepfake and scam-related entries multiplying rapidly alongside broader media scrutiny. [[1](https://www.google.com/goto?url=CAESlAEB6zswFezfQHSC18B8ow9a-lbU8UGAl4OiqVmTAZSeCLapW8W9uc6WXeNiVXCqD_UUw1B4MiI-larfUCzACrrh6ZGlH5RBcmTNdQ5BYqRcB8U4jUmHLuJQmWGrAdY0ON7fU91djIE99PBqC6HRjfTuFmeaFrTqMKv08fi0xr-3mTMIMTGLCEh0p2Y3-Xyg-mjdbuGG), [2](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg)]\n* Research Extensions: Projects like the [MIT AI Incident Tracker](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4) parse the database using taxanomies and LLM pipelines to categorize risks into structured analytical views. [[1](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4)]\n\nWould you like to search for specific types of AI incidents (such as deepfakes, autonomous vehicles, or healthcare errors) or learn how to submit an incident report?\nAI Incident Database\nAI Incident Database\nAbout the Database The AI Incident Database is dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment ...\nMIT AI Risk Initiative\nMIT AI Incident Tracker\nOverview: MIT AI Incident Tracker classifies 1,752 real-world AI incident reports from the AI Incident Database using Arcola AI's LLM pipeline, MIT Risk Reposit...\nPartnership on AI\nAI Incident Database - Partnership on AI\nAs AI technology is integrated into an increasing number of safety-critical systems — entering domains such as transportation, healthcare, and energy — the pote...\nOECD AI Policy Observatory\nAI Incident Database\nAI Incident Database Website Github Technical Educational Uploaded on Apr 25, 2024 The AI Incident Database is free and open-source project dedicated to indexin...\nKaggle\nAI Incidents, Failures & Controversies Database - Kaggle\n32 verified incidents · 29 companies · 13 countries · 24 columns — Every major AI failure, documented 📌 Why This Dataset? AI incidents surged 56.4% in 2024 alo...\nLinkedIn·TIME\n[1:35](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg)\nAI Incident Database | TIME posted on the topic","transcript_class":"CAPTURE-TIME VERBATIM RECORD — paste of the expanded Overview with its source cards","transcript_complete":"complete as supplied","transcript_raw":"The [AI Incident Database](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw) is a free, open-source project managed by the [Responsible AI Collaborative](https://www.google.com/goto?url=CAESbwHrOzAVQJB-mdnnQ6r52BIfaBkZdpvIYmeG5iTBUzeQEwySxYcKr4WzFleLjuPKMrQKQTK3W2B9l2jGnS5pLy19F1B1fTurJ-XoVDm2xfief4Gqb_ptw2t6ueReQR1dw3n-38GlP31Dx2C5MCLIXg) that indexes real-world harms, near-harms, and failures caused by artificial intelligence systems. [[1](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw), [2](https://www.google.com/goto?url=CAESbwHrOzAVQJB-mdnnQ6r52BIfaBkZdpvIYmeG5iTBUzeQEwySxYcKr4WzFleLjuPKMrQKQTK3W2B9l2jGnS5pLy19F1B1fTurJ-XoVDm2xfief4Gqb_ptw2t6ueReQR1dw3n-38GlP31Dx2C5MCLIXg)]\nCore Purpose & Model\n\n* Aviation Safety Model: Modeled after safety incident reporting systems used in aviation and cybersecurity, it collects public and crowdsourced reports to help the industry learn from past failures. [[1](https://www.google.com/goto?url=CAESdQHrOzAVEAwZDxstOqfa0VkpGaNmKMMUp0iksIt5wKMhQJlSZH2s4ag2eyxAImW5bXA_shrWdHkDg9o2go4aRguIXp0j_UcNeCVAdipEGHaZZwzksRC_l2QRbFfdaIIX3dmL48i7pJ14tjxs2OqAzRY1Ee9MoA), [2](https://www.google.com/goto?url=CAESVAHrOzAVhCp3r30WDl_s74Tm7Hc1aBx4m9gUEfwR4rqNmGz-8J-kaBBPEf7oCzpPsVYpI0IjKz6xRnV6Cp3Gh2ovoUhN7Tqyc-CNOsFltlelT6uSJw)]\n* Scope of Harms: Documents issues spanning algorithmic bias, discrimination, privacy leaks, misinformation, deepfakes, autonomous vehicle accidents, and safety-critical system failures. [[1](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4), [2](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg), [3](https://www.google.com/goto?url=CAESdQHrOzAVEAwZDxstOqfa0VkpGaNmKMMUp0iksIt5wKMhQJlSZH2s4ag2eyxAImW5bXA_shrWdHkDg9o2go4aRguIXp0j_UcNeCVAdipEGHaZZwzksRC_l2QRbFfdaIIX3dmL48i7pJ14tjxs2OqAzRY1Ee9MoA)]\n* Growth & Trends: Incidents tracked by the database have surged significantly, with deepfake and scam-related entries multiplying rapidly alongside broader media scrutiny. [[1](https://www.google.com/goto?url=CAESlAEB6zswFezfQHSC18B8ow9a-lbU8UGAl4OiqVmTAZSeCLapW8W9uc6WXeNiVXCqD_UUw1B4MiI-larfUCzACrrh6ZGlH5RBcmTNdQ5BYqRcB8U4jUmHLuJQmWGrAdY0ON7fU91djIE99PBqC6HRjfTuFmeaFrTqMKv08fi0xr-3mTMIMTGLCEh0p2Y3-Xyg-mjdbuGG), [2](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg)]\n* Research Extensions: Projects like the [MIT AI Incident Tracker](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4) parse the database using taxanomies and LLM pipelines to categorize risks into structured analytical views. [[1](https://www.google.com/goto?url=CAESYgHrOzAVvIBT1SKzmKvcCJFQEqSproxHVX3xIh9jZYYXWwPIsQ3w0bzQGE_9PRcto_82rxLm6vn-XOV6-ZgPDyQQvgN_w8tq4m9OtczrSVTPuJm_nDHPTpekibPLTiAAlAX4)]\n\nWould you like to search for specific types of AI incidents (such as deepfakes, autonomous vehicles, or healthcare errors) or learn how to submit an incident report?\nAI Incident Database\nAI Incident Database\nAbout the Database The AI Incident Database is dedicated to indexing the collective history of harms or near harms realized in the real world by the deployment ...\nMIT AI Risk Initiative\nMIT AI Incident Tracker\nOverview: MIT AI Incident Tracker classifies 1,752 real-world AI incident reports from the AI Incident Database using Arcola AI's LLM pipeline, MIT Risk Reposit...\nPartnership on AI\nAI Incident Database - Partnership on AI\nAs AI technology is integrated into an increasing number of safety-critical systems — entering domains such as transportation, healthcare, and energy — the pote...\nOECD AI Policy Observatory\nAI Incident Database\nAI Incident Database Website Github Technical Educational Uploaded on Apr 25, 2024 The AI Incident Database is free and open-source project dedicated to indexin...\nKaggle\nAI Incidents, Failures & Controversies Database - Kaggle\n32 verified incidents · 29 companies · 13 countries · 24 columns — Every major AI failure, documented 📌 Why This Dataset? AI incidents surged 56.4% in 2024 alo...\nLinkedIn·TIME\n[1:35](https://www.google.com/goto?url=CAESrQEB6zswFf3b9zemNZnPW9mi6gKhjIIMkppPLKLJDgTSLWN_bOLATV_YpfwmlhY9pR0EQzHNmeWDa55SW1UeTahm44Gn2NjTY3Yl6ss6UgoFi0pCyXrJbjX3v0Ls1XkWPGFuQUz_LYyPsGY6BZITeTiufCv-Bd0PbzJXRY-l2qsTUEzPzfKlnBCVADgaFejOSDSiRuP0Sx9TMYDQWWxJ6eGUuzJI6Ibc0tchfdeSRg)\nAI Incident Database | TIME posted on the topic","transcript_read":"READ IN FULL 2026-10-29","turns":1},"slug":"ai-incident-database-aio-20261029"}