Classifications and definitions

The AIAAIC Repository (sheet and website) is managed in line with the classifications and definitions below.

Please note that the current taxonomy is non-hierarchical, non-exhaustive, and contains overlaps. It will shortly be updated

The AIAAIC Repository details incidents and controversies driven by and relating to artificial intelligence, algorithms, and automation


AIAAIC does not (currently) collect data for the following issues or technologies: 


Additions to the AIAAIC Repository (sheet and website) are classified and managed in line with the definitions below. 

The definitions below may be revised.


Each entry is classified as a System, Incident, Issue, or Data.

Examples: People in Photo Albums (PIPA) dataset; Stanford University Brainwash cafe facial recognition dataset; Google 

GoEmotions dataset mis-labelling


The year (and, on the website, month) a system or dataset/database is soft and/or formally launched.


The year (and, on the website, month) an incident or issue occurs, or first occurs.


The geographic origin and/or primary extent of the system/incident/issue/data. 


The industry (including government and non-profit) sector primarily targeted by the system or adversarial attack.

Aerospace; Agriculture; Automotive; Banking/financial services; Beauty/cosmetics; Business/professional services; Chemicals; Construction; Consumer goods; Education; Food/food services; Gambling; Govt - home/interior, welfare, police, justice, security, defence, foreign, etc; Health; Media/entertainment/sports/arts; NGO/non-profit/social enterprise; Manufacturing/engineering; Politics; Private – individual, family; Real estate sales/management; Retail; Technology; Telecoms; Tourism/leisure; Transport/logistics


The name of the individual(s), group(s), or organisation(s) deploying/managing the system or dataset/database involved in an incident or issue on a day-to-day basis, or the platforms on which the system is hosted or being carried.


The name of the individual(s) or organisation(s) involved in designing, or developing/providing the system or dataset/database, and/or that commissions  a system to be developed with a view to placing it on the market or putting it into service under its own name or trademark whether for payment or free of charge or that adapts general purpose systems for a specific intended purpose. There may be multiple providers along the system lifecycle.

System name(s)

The name of the system, set of systems, or dataset/database involved in an incident or issue.


The type(s) of technology deployed in the system. These include the following technology types and their application(s): 

Advertising management system; Advertising authorisation system; Age detection; Anomaly detection; Augmented reality (AR); Automatic identification system (AIS); Automated license plate/number recognition (ALPR, ANPR); Behavioural analysis; Biodiversity assessment algorithm; Blockchain; Border control system; Bot/intelligent agent; Chatbot; Collaborative filtering; Colourisation; Computer vision; Content labelling system; Content ranking system; Content recommendation system; Credit score algorithm; Data matching algorithm; Decision support; Deepfake - video, audio, image, text; Deep learning; Diversity Recognition; Driver assistance system; Drone; Emotion detection; Emotion recognition; Environmental sensing; Expert system; Facial analysis; Facial detection; Facial identification; Facial recognition; Fingerprint biometrics; Gait recognition; Generative adversarial network (GAN); Gender detection; Gesture recognition; Gun/weapons detection; Gunshot detection; Heart rate variability algorithm; Image classification; Image segmentation; Image recognition; Learning management system; Link blocking; Location tracking; Location recognition; Machine learning; Mask recognition; Neural network; NLP/text analysis; Object detection; Object recognition; Order matching algorithm; Palm print scanning; Pattern recognition; Pay algorithm; Performance scoring algorithm; Personality analysis; Prediction algorithm; Pricing algorithm; Probabilistic genotyping; Rating system; Recommendation algorithm; Reinforcement learning; Resource assessment algorithm; Risk assessment algorithm; Robotic Process Automation (RPA); Robotics; Routing algorithm; Safety management system; Saliency algorithm; Scheduling algorithm; Search engine algorithm; Self-driving system; Signal processing; Social media monitoring; Sleep sensing; Smile recognition; Speech-to-text; Speech recognition; Suicide prevention algorithm; Text-to-image; Triage algorithm; Virtual currency; Virtual reality (VR); Vital signs detection; Voice recognition; Voice synthesis; Web accessibility overlay; Workforce management system


The aim(s) of the system or dataset/database. The aim(s) may be stated, likely, or alleged, and may include: 

Rank content/search results; Recommend users/groups; Recommend content; Moderate content; Minimise mis/disinformation; Identify/verify identity; Increase productivity; Increase speed to market; Improve quality; Engage users/increase revenue; Improve customer service; Increase visibility; Increase revenue/sales; Increase engagement; Moderate content; Improve insights; Cut costs; Defraud; Scare/confuse/destabilise; Damage reputation

Media trigger(s)

The internal or external trigger for a public issue or incident. These may take the form of one or more of the following:

Academic research paper/study/report; Artwork/prank; Audit report publication; Commercial investigation/experiment/hack; Commercial research study/report; Developer research study/report; Data breach/leak; FOI(A)/public records request; Investor presentation; Media investigation/coverage; Media report; Non-profit research study/report/investigation; Parliamentary enquiry/report; Patent application/approval; Police investigation/arrest; Product demonstration/release/launch; Professional body paper/study/report; Public comments/complaints; Regulatory investigation/action; Regulator paper/study/report; Researcher investigation/paper/study/report; Lab/product test; Lawsuit filing/litigation; Legal communication; Legal complaint/threat; Legislative proposal; SEC/regulatory filing; Statutory body paper/study/report; User comments/complaints; Whistleblower; White-hat hack


The issues of concern posed by a system, its governance and/or technology, or by third-parties. 

Risks include: Deliberate development of dangerous/lethal weapons; Accidental development of dangerous/lethal weapons; Inappropriate/unethical data sharing; Inappropriate/unethical code sharing; Inappropriate/unethical model sharing

Risks include: Carbon dioxide emissions; Water consumption; Water pollution; Waste disposal; Hazardous materials disposal; Ecology/biodiversity; Rare earth consumption; Local community rights and freedoms

Risks include: Appropriateness/need; Business model; Capabilities/skills; Capacity/resources; Competition/collusion; Complaints/appeals; Conflicts of interest; Dual/multi-use; Effectiveness/value; Hypocrisy; Incentivisation; Inclusiveness/diversity; Leadership understanding/support; Oversight/review; Ownership/accountability; Purpose; Risk management; Scope creep/normalisation; Supply chain management; Values/culture/ethics

Risks include: Freedom of expression (censorship, assembly, association, petition, press, religion, speech); Freedom of information (including right to know); Right to collective action; Right to work; Right to due process; Protection of minors, elderly, and disabled people

Risks include: Training data; Algorithm design; Software guardrails; User policies/terms; Usage monitoring; Usage enforcement; Complaints/appeals process

Risks include: Addiction; Anxiety/depression; Self-harm/suicide; Radicalisation; Hate speech/violence; Harassment/abuse; Intimidation; Shaming; Stalking

Risks include: 


Harms are the actual negative impacts caused by an incident, system, or dataset/database. The harms may be caused directly (sometimes known as ‘first-level’ harms) or indirectly (‘second-level’) harms. 

Harm data is only accessible to Premium Members.


Harms include: Damage to physical property; Damage to physical health and safety; Psychological damage; Personal agency/autonomy loss; Chilling effects; Discrimination; IP and identity loss; Personal data loss; Limitation or loss of rights and freedoms; Financial loss; Reputational damage


Harms include: Legal complaint/filing; Litigation; Regulatory inquiry/investigation; Legislative inquiry; Legislative questions/complaints. 

Last updated: June 10, 2024