AI Incidents
Real-world cases where AI systems caused harm, classified by risk domain and entity. Data sourced from 
AIID and classified by 
MIT AI Risk Initiative. CC BY-SA 4.0
1,751 incidents
Kronos Scheduling Algorithm Allegedly Caused Financial Issues for Starbucks Employees
Kronos’s scheduling algorithm and its use by Starbucks managers allegedly negatively impacted financial and scheduling stability for Starbucks employees, which disadvantaged wage workers.
Robot kills worker at German Volkswagen plant
A Volkswagen plant robot "crushed to death" a worker by pinning him to a metal plate.
Tech Companies Reportedly Influenced Gig Workers' Behaviors Using Algorithms to Vary Pay for Same Amount of Work
Amazon and Uber were alleged in a multiyear ethnographic study using algorithmic systems based on gig workers' data to vary pay, such as by offering them lower wages for the same amount of work.
Misreading of an Automated License Plate Reader (ALPR) Unverified by Police, Resulting in Traffic Stop in Missouri
An automated license plate reader (ALPR) camera misread a 7 as a 2 and incorrectly alerted the local police about a stolen Oldsmobile car, which was allegedly not able to be verified by an officer before a traffic stop was effected on a BMW in Kansas City suburb.
Facebook's Auto-Generated Targeting Ad Categories Contained Anti-Semitic Options
Facebook's automated advertising categories generated using users' declared interests contained anti-Semitic categories such as "Jew hater" and "How to burn Jews" which were listed as fields of study.
Nest Smoke Alarm Erroneously Stops Alarming
In testing, Google Nest engineers demonstrated that the Nest Wave feature of their Nest Protect: Smoke + CO Alarm could inadvertently silence genuine alarms.
ETS Used Allegedly Flawed Voice Recognition Evidence to Accuse and Assess Scale of Cheating, Causing Thousands to be Deported from the UK
International testing organization ETS admits voice recognition as evidence of cheating for thousands of previous TOEIC test-takers that reportedly included wrongfully accused people, causing them to be deported without an appeal process or seeing their incriminating evidence.
Excessive Automated Monitoring Alerts Ignored by Staff, Resulting in Private Data Theft of Seventy Million Target Customers
Alerts about a Target data breach were ignored by Minneapolis Target’s staff reportedly due to them being included with many other potential false alerts, and due to some of the company’s network infiltration alerting systems being off to reduce such false alerts, causing private data theft for millions of customers.
Michigan's Unemployment Benefits Algorithm MiDAS Issued False Fraud Claims to Thousands of People
Michigan’s MiDAS system falsely accused over 34,000 people of unemployment fraud from 2013 to 2015, which reportedly caused financial ruin for many. The automated system was designed to cut costs, but it adjudicated fraud cases without human oversight. That led to an 85% error rate. Victims faced wage garnishments, some lost homes, and some faced bankruptcy. Despite early warnings, Michigan’s UIA defended MiDAS until lawsuits and federal pressure forced reforms. Legislators have been seeking compensation for those wrongfully accused.
Facial Recognition Researchers Allegedly Used YouTube Videos of Transgender People Without Consent
YouTube videos of transgender people used by researchers to study facial recognition during gender transitions were allegedly used and distributed without permission.
Compromise of National Biometric ID Card System Leads to Reverification and Change of Status
When the leader of the Afghan Taliban was found possessing a valid ID card in the Pakistani national biometric identification database system, Pakistan launch a national re-verification campaign that is linked to numerous changes in recognition status and loss of services.
Coffee Meets Bagel’s Algorithm Reported by Users Disproportionately Showing Them Matches of Their Own Ethnicities Despite Selecting “No Preference”
Users selecting “no preference” were shown by Coffee Meets Bagels’s matching algorithm more potential matches with the same ethnicity, which was acknowledged and justified by its founder as a means to maximize connection rate without sufficient user information.
Sexist and Racist Google Adsense Advertisements
Advertisements chosen by Google Adsense are reported as producing sexist and racist results.
NJ Transit's Use of Modeling Software Miscalculated Storm Surge Threat Level
New Jersey Transit's use of a federal government storm modeling software underestimated the threat of storm surges to the Meadows Maintenance Complex, leaving millions of dollars worth of equipment in the rail yard before Hurricane Sandy struck.
UT Austin's GRADE Algorithm Reportedly Reduced Review of Lower-Scored PhD Applicants Amid Bias Concerns
From the 2013 through 2019 admissions cycles, UT Austin's Department of Computer Science used GRADE, a statistical machine-learning system trained on past admissions decisions, to score and organize PhD applications. Critics said the system could reproduce historical admissions inequities and reduce attention to lower-scored applicants, while UT Austin said human reviewers still evaluated each file and later discontinued the tool.