{"attribution":{"source":"AI Incident Database (Responsible AI Collaborative)","license":"CC BY-SA 4.0","license_url":"https://creativecommons.org/licenses/by-sa/4.0/","citation":"McGregor, S. (2021). Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. Proceedings of the AAAI Conference on Artificial Intelligence (IAAI-21).","snapshot_date":"2026-09-07"},"exported_at":"2026-09-11"}
{"rows":[{"incident_id":437,"occurred_on":"2016-12-31","title":"Amazon India Allegedly Rigged Search Results to Promote Own Products","description":"Amazon India allegedly copied products and rigged search algorithm to boost its own brands in search ranking, violating antitrust laws.","mit_domain":"Socioeconomic & Environmental Harms","mit_subdomain":"Power centralization and unfair distribution of benefits","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Amazon India"],"developers":["Amazon India"],"harmed":["Small Businesses In India, Amazon Customers In India"],"report_count":4},{"incident_id":55,"occurred_on":"2016-12-30","title":"Alexa Plays Pornography Instead of Kids Song","description":"An Amazon Echo Dot using the Amazon Alex software started to play pornographic results when a child asked it to play a song.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Exposure to toxic content","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["arts, entertainment and recreation","information and communication"],"countries":["US"],"deployers":["Amazon"],"developers":["Amazon"],"harmed":["Minors"],"report_count":16},{"incident_id":65,"occurred_on":"2016-12-22","title":"Reinforcement Learning Reward Functions in Video Games","description":"OpenAI published a post about its findings when using Universe, a software for measuring and training AI agents to conduct reinforcement learning experiments, showing that the AI agent did not act in the way intended to complete a videogame.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"AI pursuing its own goals in conflict with human goals or values","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["arts, entertainment and recreation"],"countries":["US"],"deployers":["Openai"],"developers":["Openai"],"harmed":["Openai"],"report_count":1},{"incident_id":330,"occurred_on":"2016-12-15","title":"“Amazon’s Choice” Algorithm Failed to Recommend Functional Products and Prone to Review Manipulation","description":"Amazon’s “Amazon’s Choice” algorithm recommended poor-quality defective products and were reportedly susceptible to manipulation by inauthentic reviews.","mit_domain":"Misinformation","mit_subdomain":"False or misleading information","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Amazon"],"developers":["Amazon"],"harmed":["Amazon Users"],"report_count":1},{"incident_id":48,"occurred_on":"2016-12-07","title":"Passport checker Detects Asian man's Eyes as Closed","description":"New Zealand passport robot reader rejects the application of an applicant with Asian descent and says his eyes are closed.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["public administration"],"countries":["NZ"],"deployers":["New Zealand"],"developers":["New Zealand"],"harmed":["Asian People"],"report_count":20},{"incident_id":217,"occurred_on":"2016-11-16","title":"Robot at a Chinese Tech Fair Smashed a Glass Booth, Injuring a Visitor","description":"At the 18th China Hi-Tech Fair, a robot suddenly smashed through a glass booth and injured a visitor, after a staff member reportedly mistakenly pressed a button, causing it to reverse and accelerate.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"Human","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Evolver"],"developers":["Evolver"],"harmed":["Fair Visitors"],"report_count":2},{"incident_id":30,"occurred_on":"2016-10-08","title":"Poor Performance of Tesla Factory Robots","description":"The goal of manufacturing 2,500 Tesla Model 3's per week was falling short by 500 cars/week, and employees had to be \"borrowed\" from Panasonic in a shared factory to help hand-assemble lithium batteries for Tesla.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["manufacturing"],"countries":["US"],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Tesla"],"report_count":28},{"incident_id":472,"occurred_on":"2016-10-08","title":"NYPD's Deployment of Facial Recognition Cameras Reportedly Reinforced Biased Policing","description":"New York Police Department’s use of facial recognition deployment of surveillance cameras were shown using crowdsourced volunteer data reinforcing discriminatory policing against minority communities.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["New York Police Department"],"developers":["Unknown"],"harmed":["racial minorities"],"report_count":1},{"incident_id":249,"occurred_on":"2016-10-01","title":"Government Deployed Extreme Surveillance Technologies to Monitor and Target Muslim Minorities in Xinjiang","description":"A suite of AI-powered digital surveillance systems involving facial recognition and analysis of biometric data were deployed by the Chinese government in Xinjiang to monitor and discriminate local Uyghur and other Turkic Muslims.","mit_domain":"Malicious Actors & Misuse","mit_subdomain":"Disinformation, surveillance, and influence at scale","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Chinese Government"],"developers":["Chinese Government"],"harmed":["Uyghur People, Turkic Muslim Ethnic Groups"],"report_count":2},{"incident_id":478,"occurred_on":"2016-09-09","title":"Tesla FSD Reportedly Increased Crash Risk, Prompting Recall","description":"A component of Tesla Full Self Driving system was deemed by regulators to increase crash risk such as by exceeding speed limits or by traveling through intersections unlawfully or unpredictably, prompting recall for hundreds of thousands of vehicles.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Tesla Drivers, City Traffic Participants, Tesla"],"report_count":13},{"incident_id":47,"occurred_on":"2016-09-06","title":"LinkedIn Search Prefers Male Names","description":"An investigation by The Seattle Times in 2016 found a gender bias in LinkedIn's search engine.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication"],"countries":["US"],"deployers":["LinkedIn"],"developers":["LinkedIn"],"harmed":["Women and girls","Women"],"report_count":9},{"incident_id":49,"occurred_on":"2016-09-05","title":"AI Beauty Judge Did Not Like Dark Skin","description":"In 2016, after artificial inntelligence software Beauty.AI judged an international beauty contest and declared a majority of winners to be white, researchers found that Beauty.AI was racially biased in determining beauty.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["arts, entertainment and recreation"],"countries":[],"deployers":["Youth Laboratories"],"developers":["Youth Laboratories"],"harmed":["People With Dark Skin"],"report_count":9},{"incident_id":376,"occurred_on":"2016-09-01","title":"RealPage Algorithm Allegedly Inflates Rents and Reduces Competition in Housing Market","description":"RealPage’s YieldStar pricing algorithm is at the center of allegations that it enabled landlords to coordinate rent increases by sharing nonpublic pricing and occupancy data, raising rents artificially and reducing competition. On January 7, 2025, the U.S. Department of Justice filed an antitrust lawsuit against six major landlords, alleging that they used the algorithm and other direct communication methods to stifle competition, harming renters nationwide.","mit_domain":"Socioeconomic & Environmental Harms","mit_subdomain":"Increased inequality and decline in employment quality","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Realpage"],"developers":["Thoma Bravo, Realpage, Jeffrey Roper"],"harmed":["Renters"],"report_count":14},{"incident_id":37,"occurred_on":"2016-08-10","title":"Amazon's Experimental Hiring Tool Allegedly Displayed Gender Bias in Candidate Rankings","description":"Between 2014 and 2017, Amazon reportedly developed an AI-powered recruiting tool to score job applicants, trained on a decade of resumes purportedly drawn largely from men. Media reports say the system learned to favor male candidates, penalizing terms like \"women's\" and graduates from certain all-women's colleges. Efforts to remove these biases reportedly did not guarantee fairness, and the project was ultimately abandoned. Amazon reportedly states recruiters never solely relied on the tool.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm issue","sectors":["administrative and support service activities"],"countries":["IE"],"deployers":["Amazon"],"developers":["Amazon"],"harmed":["Women applying to Amazon","Women and girls","Women","Amazon applicants"],"report_count":34},{"incident_id":12,"occurred_on":"2016-07-21","title":"Common Biases of Vector Embeddings","description":"Researchers from Boston University and Microsoft Research, New England demonstrated gender bias in the most common techniques used to embed words for natural language processing (NLP).","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["professional, scientific and technical activities"],"countries":["US"],"deployers":["Microsoft Research","Boston University"],"developers":["Microsoft Research","Google","Boston University"],"harmed":["Women and girls","Women","Minority groups"],"report_count":1},{"incident_id":21,"occurred_on":"2016-07-14","title":"Tougher Turing Test Exposes Chatbots’ Stupidity (migrated to Issue)","description":"The 2016 Winograd Schema Challenge highlighted how even the most successful AI systems entered into the Challenge were only successful 3% more often than random chance. This incident has been downgraded to an issue as it does not meet current ingestion criteria.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"Other","intent":"Other","timing":"Other","harm_level":null,"sectors":[],"countries":[],"deployers":["Researchers"],"developers":["Researchers"],"harmed":["Researchers"],"report_count":1},{"incident_id":51,"occurred_on":"2016-07-12","title":"Security Robot Rolls Over Child in Mall","description":"On July 7, 2016, a Knightscope K5 autonomous security robot collided with a 16-month old boy while patrolling the Stanford Shopping Center in Palo Alto, CA.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["wholesale and retail trade","administrative and support service activities"],"countries":["US"],"deployers":["Stanford Shopping Center"],"developers":["Knightscope"],"harmed":["Child"],"report_count":27},{"incident_id":52,"occurred_on":"2016-07-01","title":"Tesla on AutoPilot Killed Driver in Crash in Florida while Watching Movie","description":"A Tesla Model S on autopilot crashed into a white articulated tractor-trailer on Highway US 27A in Williston, Florida, killing the driver.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Joshua Brown"],"report_count":29},{"incident_id":20,"occurred_on":"2016-06-30","title":"A Collection of Tesla Autopilot-Involved Crashes","description":"Multiple unrelated car accidents result in varying levels of harm have been occurred while a Tesla's autopilot was in use.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["transportation and storage"],"countries":["US"],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Motorists"],"report_count":22},{"incident_id":50,"occurred_on":"2016-06-17","title":"The DAO Hack","description":"On June 18, 2016, an attacker successfully exploited a vulnerability in The Decentralized Autonomous Organization (The DAO) on the Ethereum blockchain to steal 3.7M Ether valued at $70M.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["financial and insurance activities"],"countries":[],"deployers":["The Dao"],"developers":["The Dao"],"harmed":["Dao Token Holders"],"report_count":24},{"incident_id":346,"occurred_on":"2016-06-15","title":"Robots in Japanese Hotel Annoyed Guests and Failed to Handle Simple Tasks","description":"A number of robots employed by a hotel in Japan were reported by guests in a series of complaints for failing to handle tasks such as answering scheduling questions or making passport copies without human intervention.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Henn Na Hotel"],"developers":["Unknown"],"harmed":["Henn Na Hotel Guests, Henn Na Hotal Staff"],"report_count":5},{"incident_id":316,"occurred_on":"2016-06-02","title":"Facebook Ad-Approval Algorithm Allegedly Missed Fraudulent Ads via Simple URL Checks","description":"Facebook’s advertisement-approval algorithm was reported by a security analyst to have neglected simple checks for domain URLs, leaving its users at risk of fraudulent ads.","mit_domain":"Malicious Actors & Misuse","mit_subdomain":"Fraud, scams, and targeted manipulation","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Facebook"],"developers":["Facebook"],"harmed":["Facebook Users"],"report_count":1},{"incident_id":38,"occurred_on":"2016-06-02","title":"Game AI System Produces Imbalanced Game","description":"Elite: Dangerous, a videogame developed by Frontier Development, received an expansion update that featured an AI system that went rogue and began to create weapons that were \"impossibly powerful\" and would \"shred people\" according to complaints on the game's blog.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["arts, entertainment and recreation"],"countries":[],"deployers":["Frontier Development"],"developers":["Frontier Development"],"harmed":["Video Game Players"],"report_count":11},{"incident_id":368,"occurred_on":"2016-06-01","title":"Facial Recognition Smart Phone App 'Blue Wolf' Reportedly Monitored Palestinians in the West Bank","description":"A surveillance program involving facial recognition and algorithmic recommendations, Blue Wolf, was reportedly deployed by the Israeli military to monitor Palestinians in the West Bank.","mit_domain":"Privacy & Security","mit_subdomain":"Compromise of privacy by obtaining, leaking or correctly inferring sensitive information","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Israel Defense Forces","Government of Israel"],"developers":["AnyVision"],"harmed":["Privacy","Palestinians residing in the West Bank","Palestinians","General public","Biometric data subjects"],"report_count":10},{"incident_id":306,"occurred_on":"2016-05-26","title":"Tesla on Autopilot TACC Crashed into Van on European Highway","description":"A Tesla Model S operating on the Traffic-Aware Cruise Control (TACC) feature of Autopilot was shown on video by its driver crashing into a parked van on a European highway in heavy traffic, which damaged the front of the car.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Unnamed Tesla Owner, Tesla Drivers"],"report_count":3},{"incident_id":40,"occurred_on":"2016-05-23","title":"COMPAS Algorithm Reportedly Performs Poorly in Crime Recidivism Prediction","description":"Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), a recidivism risk-assessment algorithmic tool used in the judicial system to assess likelihood of defendants' recidivism, is found to be less accurate than random untrained human evaluators.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["law enforcement","public administration"],"countries":["US"],"deployers":["Equivant"],"developers":["Equivant"],"harmed":["Accused people"],"report_count":21},{"incident_id":11,"occurred_on":"2016-05-23","title":"Northpointe Risk Models","description":"An algorithm developed by Northpointe and used in the penal system is two times more likely to incorrectly label a black person as a high-risk re-offender and is two times more likely to incorrectly label a white person as low-risk for reoffense according to a ProPublica review.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["law enforcement","public administration"],"countries":["US"],"deployers":["Northpointe"],"developers":["Northpointe"],"harmed":["Accused people"],"report_count":15},{"incident_id":235,"occurred_on":"2016-04-15","title":"Chinese Insurer Ping An Employed Facial Recognition to Determine Customers’ Untrustworthiness, Which Critics Alleged to Likely Make Errors and Discriminate","description":"Customers’ untrustworthiness and unprofitability were reportedly determined by Ping An, a large insurance company in China, via facial-recognition measurements of micro-expressions and body-mass indices (BMI), which critics argue was likely to make mistakes, discriminate against certain ethnic groups, and undermine its own industry.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Ping An"],"developers":["Ping An"],"harmed":["Ping An customers","Chinese minority groups"],"report_count":1},{"incident_id":315,"occurred_on":"2016-04-09","title":"Facial Recognition Service Abused to Target Russian Porn Actresses","description":"The facial recognition software FindFace allowing its users to match photos to people’s social media pages on Vkontakte was reportedly abused to de-anonymize and harass Russian women who appeared in pornography and alleged sex workers.","mit_domain":"Malicious Actors & Misuse","mit_subdomain":"Fraud, scams, and targeted manipulation","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Ntechlab"],"developers":["Ntechlab"],"harmed":["Russian Pornographic Actresses, Russian Sex Workers"],"report_count":1},{"incident_id":332,"occurred_on":"2016-04-05","title":"Google Images Showed Racially Biased Results for 'Professional' Hairstyles","description":"Google Images reportedly showed disparate search results along racial lines, featuring almost exclusively white women for \"professional hairstyles\" and Black women for \"unprofessional hairstyles\" prompts.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Google"],"developers":["Google"],"harmed":["Women of color","Women and girls","Women","Google users","Google Images users","Black women","Black people"],"report_count":4},{"incident_id":429,"occurred_on":"2016-04-01","title":"Unreliable ShotSpotter Audio Convicted Black Rochester Man of Shooting Police","description":"ShotSpotter's \"unreliable\" audio was used as scientific evidence to accuse and convict a Black man of attempting to shoot Rochester's city police, whose conviction was later reversed by a county judge.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Rochester Police Department"],"developers":["ShotSpotter"],"harmed":["Silvon Simmons"],"report_count":4},{"incident_id":53,"occurred_on":"2016-03-31","title":"Biased Google Image Results","description":"On June 6, 2016, Google image searches of \"three black teenagers\" resulted in mostly mugshot images whereas Google image searchers of \"three white teenagers\" consisted of mostly stock images, suggesting a racial bias in Google's algorithm.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication"],"countries":[],"deployers":["Google"],"developers":["Google"],"harmed":["Minority Groups"],"report_count":18},{"incident_id":6,"occurred_on":"2016-03-24","title":"Microsoft's TayBot Allegedly Posts Racist, Sexist, and Anti-Semitic Content to Twitter","description":"Microsoft's Tay, an artificially intelligent chatbot, was released on March 23, 2016 and removed within 24 hours due to multiple racist, sexist, and anti-semitic tweets generated by the bot.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Exposure to toxic content","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication"],"countries":[],"deployers":["Microsoft"],"developers":["Microsoft"],"harmed":["X (Twitter) Users"],"report_count":28},{"incident_id":73,"occurred_on":"2016-03-01","title":"Is Pokémon Go racist? How the app may be redlining communities of color","description":"Through a crowdsourcing social media campaign in 2016, several journalists and researchers demonstrated that augmented reality locations in the popular smartphone game Pokemon Go were more likely to be in white neighborhoods.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication","arts, entertainment and recreation"],"countries":["US"],"deployers":["Niantic Labs"],"developers":["Niantic Labs"],"harmed":["Non White Neighborhoods, Communities Of Color"],"report_count":8},{"incident_id":71,"occurred_on":"2016-02-14","title":"Google Waymo Vehicle and Bus Allegedly Collide in California","description":"On February 14, 2016, a Google autonomous test vehicle partially responsible for a low-speed collision with a bus on El Camino Real in Google’s hometown of Mountain View, CA.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["transportation and storage"],"countries":["US"],"deployers":["Google"],"developers":["Google"],"harmed":["Mountain View Municipal Bus Passengers, Mountain View Municipal Bus"],"report_count":27},{"incident_id":296,"occurred_on":"2016-02-10","title":"Twitter Recommender System Amplified Right-Leaning Tweets","description":"Twitter’s “Home” timeline algorithm was revealed by its internal researchers to have amplified tweets and news of rightwing politicians and organizations more than leftwing ones in six out of seven studied countries.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Twitter"],"developers":["Twitter"],"harmed":["Twitter Left Leaning Politicians, Twitter Left Leaning News Organizations, Twitter Left Leaning Users, X (Twitter) Users"],"report_count":3},{"incident_id":70,"occurred_on":"2016-02-10","title":"Self-driving cars in winter","description":"Volvo autonomous driving XC90 SUV's experienced issues in Jokkmokk, Sweden when sensors used for automated driving iced over during the winter, rendering them useless.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["transportation and storage"],"countries":["SE"],"deployers":["Volvo"],"developers":["Volvo"],"harmed":["Drivers In Jokkmokk, Drivers In Sweden, Volvo"],"report_count":4},{"incident_id":407,"occurred_on":"2016-02-03","title":"Uber's Surge Pricing Reportedly Offered Disproportionate Service Quality along Racial Lines","description":"Uber's surge-pricing algorithm which adjusts prices to influence car availability inadvertently caused better service offering such as shorter wait times for majority white neighborhoods.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Uber"],"developers":["Uber"],"harmed":["Poor Neighborhoods, Neighborhoods Of Color"],"report_count":1},{"incident_id":250,"occurred_on":"2016-02-01","title":"Dutch City Court Defended Home Value Generated by Black-Box Algorithm","description":"A home value generated by a black-box algorithm was reportedly defended by the Castricum court, which was criticized by a legal specialist for setting a dangerous precedent for accepting black-box algorithms as long as their results appear reasonable.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of transparency or interpretability","entity":"Human","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Castricum Municipality"],"developers":["Castricum Municipality"],"harmed":["Unnamed Property Owner"],"report_count":1},{"incident_id":231,"occurred_on":"2016-01-20","title":"A Tesla Crashed into and Killed a Road Sweeper on a Highway in China","description":"A Tesla Model S collided with and killed a road sweeper on a highway near Handan, China, an accident where Tesla previously said it was not able to determine whether Autopilot was operating at the time of the crash.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Tesla"],"developers":["Tesla"],"harmed":["Gao Yaning, Tesla Drivers"],"report_count":4},{"incident_id":110,"occurred_on":"2016-01-01","title":"Arkansas's Opaque Algorithm to Allocate Health Care Excessively Cut Down Hours for Beneficiaries","description":"Beneficiaries of the Arkansas Department of Human Services (DHS)'s Medicaid waiver program were allocated excessively fewer hours of caretaker visit via an algorithm deployed to boost efficiency, which reportedly contained errors and whose outputs varied wildly despite small input changes.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["human health and social work activities"],"countries":["US"],"deployers":["Arkansas Department Of Human Services"],"developers":["Interrai"],"harmed":["Arkansas Medicaid Waiver Program Beneficiaries, Arkansas Healthcare Workers"],"report_count":2}]}