MMRS
MMRS meta-aggregator / database

MIT AI Risk Repository

databaseharmactive
The MIT AI Risk Repository is a database of more than 1,700 AI risks extracted from 74 published risk frameworks (version 4, December 2025; the Initiative's home page gives 65+), run by the MIT AI Risk Initiative (MIT FutureTech) under CC BY 4.0. The Initiative's AI Incident Tracker, a workstream beside it, classifies AI Incident Database incidents against the same taxonomy.
Visit MIT AI Risk Repository ↗The /non rowCaptureFollow

Entity

Canonical nameMIT AI Risk Repository
Addresshttps://airisk.mit.edu/risks
OperatorMIT AI Risk Initiative (MIT FutureTech) op
Kinddatabase
Rolesharm
Lifecycleactive (version 4, December 2025)
Observation2026-10-28: read
Unitrisk, extracted from published risk frameworks op
Countmore than 1,700 risks from 74 frameworks (version 4, December 2025); the Initiative's home page gives 65+ (as of 2026-10-29) op
LicenceCC BY 4.0 ('unless a specific page states otherwise') op
Noteitself an aggregator of frameworks; real-world incidents are kept separately in its AI Incident Tracker

op operator statement · 3p third-party report · obs our observation · rd our reading

What it is

Its unit is the risk as a framework states it. Each source framework is summarized, and the source documents and key excerpts are published with it. The risks are sorted into a domain taxonomy with subdomains; the April 2025 update added a subdomain for multi-agent risks.

What it gathers

It aggregates aggregators: its sources are frameworks, which are themselves syntheses. What enters is what a framework named. A risk no framework has written down has no row.

Place in the field

Its incident layer is a second-order reading of the AI Incident Database, done by machine. The repository sits over the harm basin as a taxonomy for it.

Relations

Neighbours in the basin

Captures: the composition layer's account

The /non row

Provenanceevery source read, with its date3

Cite this record

Lee Sharks, ed. "MIT AI Risk Repository." MMRS meta-aggregator, Machine-Mediated Reception Studies, compiled 2026-10-29. https://www.machinemediation.org/aggregators/mit-ai-risk-repository/

Record https://www.machinemediation.org/aggregators/mit-ai-risk-repository/ · entity https://www.machinemediation.org/aggregators/mit-ai-risk-repository/#entity

Editor: Lee Sharks (ORCID 0009-0000-1599-0703). This page is the MMRS record of the entity above: its reading, fields and relations are MMRS's, and each field carries its source and basis. Record https://www.machinemediation.org/aggregators/mit-ai-risk-repository/ · entity https://www.machinemediation.org/aggregators/mit-ai-risk-repository/#entity · compiled 2026-10-29