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
682 incidents
Cross-Jurisdictional Facial Recognition Misidentification by NYPD Leads to Wrongful Arrest and Four-Year Jail Time in New Jersey
In 2019, facial recognition technology misidentified Francisco Arteaga as a suspect in an armed robbery in New Jersey. The incident led to nearly four years of pretrial incarceration. Despite having an alibi, Arteaga was charged based on the flawed identification. The legal battle that followed resulted in a court ruling requiring police to reveal details about the algorithms used in facial recognition. The process exposed significant gaps in transparency and accountability.
Facebook Feed Algorithms Exposed Low Digitally Skilled Users to More Disturbing Content
Facebook feed algorithms were known by internal research to have harmed people having low digital literacy by exposing them to disturbing content they did not know how to avoid or monitor.
Apple Card's Credit Assessment Algorithm Allegedly Discriminated against Women
Apple Card's credit assessment algorithm was reported by Goldman-Sachs customers to have shown gender bias, in which men received significantly higher credit limits than women with equal credit qualifications.
Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' Needs
Researchers analyzing an Optum algorithm used by a large academic hospital reportedly found evidence that it tended to under-predict the health care needs of Black patients, which in turn appeared to result in lower prioritization for extra care programs compared with white patients exhibiting similar health profiles.
Hive Box Facial-Recognition Locks Hacked by Fourth Graders Using Intended Recipient’s Facial Photo
Facial-recognition locks by Hive Box, an express delivery locker company in China, were easily opened by a group of fourth-graders in a science-club demo using only a printed photo of the intended recipient’s face, leaving contents vulnerable to theft.
Knightscope's Park Patrol Robot Ignored Bystander Pressing Emergency Button to Alert Police about Fight
A Knightscope K5 autonomous "police" robot patrolling Huntington Park, California failed to respond to an onlooker who attempted to activate its emergency alert button when a nearby fight broke out.
Thai Wallet App's Facial Recognition Errors Created Registration Issues for Government Programs
A Thai wallet app failed to recognize people’s faces, resulting in citizens and disproportionately elders unable to sign up for Thai government’s cash handout and co-pay programs or having to wait in long queues at local ATMs for authentication.
Waze Allegedly Frequently Routed Drivers through the Town of Los Gatos, Blocking Its Single Wildfire Escape Route
Waze app was blamed by Los Gatos town residents for contributing to high wildfire hazard risk via allegedly routing weekend beach-going drivers through their neighborhoods, effectively choking off their single escape route in the event of a medical emergency or wildfire.
Tesla Model 3 on Autopilot Crashed into a Ford Explorer Pickup, Killing a Fifteen-Year-Old in California
A Tesla Model 3 on Autopilot mode crashed into a pickup on a California freeway, where data and video from the company showed neither Autopilot nor the driver slowing the vehicle until seconds before the crash.
Detroit Police Wrongfully Arrested Black Man Due To Faulty Facial Recognition
A Black man was wrongfully detained by the Detroit Police Department as a result of a false facial recognition (FRT) result.
Facebook Political Ad Delivery Algorithms Inferred Users' Political Alignment, Inhibiting Political Campaigns' Reach
Facebook's political ad delivery system reportedly differentiated the price of user reach based on their inferred political alignment, inhibiting political campaigns' ability to reach voters with diverse political views, which allegedly reinforces political polarization and creates informational filter bubbles.
Amazon’s "Time Off Task" System Made False Assumptions about Workers' Time Management
Amazon’s warehouse worker “time off task" (TOT) tracking system was used to discipline and dismiss workers, falsely assuming workers to have wasted time and failing to account for breaks or equipment issues.
TikTok’s “For You” Algorithm Exposed Young Users to Pro-Eating Disorder Content
TikTok’s young users were allegedly exposed to community-guideline-violating pro-eating disorder content on their algorithmically curated “For You” page that serves videos from any user on its platform.
Sound Intelligence's Aggression Detector Misidentified Innocuous Sounds
Sound Intelligence's "aggression detection" algorithm deployed by schools reportedly contained high rates of false positive, misclassifying laughing, coughing, cheering, and loud discussions.
Facebook Allegedly Failed to Police Hate Speech Content That Contributed to Ethnic Violence in Ethiopia
Facebook allegedly did not adequately remove hate speech, some of which was extremely violent and dehumanizing, on its platform including through automated means, contributing to the violence faced by ethnic communities in Ethiopia.