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.

ArtificiaI intelligence (AI). The capability of a machine to imitate intelligent human behaviour (source).
Algorithm. A procedure for solving a mathematical problem in a finite number of steps that frequently involves repetition of an operation (source).
Automation. The automatically controlled operation of an apparatus, process, or system by mechanical or electronic devices that take the place of human labour (source).
'Driven by’. A negative event or situation in which an incident and/or issue is directly triggered by an AI, algorithmic or automation system, including its’ technology and/or governance. The event or situation may be deliberate or accidental and may be triggered by internal factors such as algorithmic opacity, misleading marketing, or poor ethics (or by the perception thereof), or by external factors such as a third-party research report, assessment, investigation, cyberattack or data breach, or the gaming/manipulation of the system.
‘Relating to’. The technology and/or its’ governance is one of several factors contributing to an incident or controversy, though the system or part thereof is likely to have played a significant role.

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.

System. A technology programme, project, or product, and its governance. A System page is mostly appropriate for a system generating multiple incidents.

Examples: Amazon Buy Box; ChatGPT chatbot; Oregon DHS Safety at Screening Tool
Incident. A sudden known or unknown event (or ‘trigger’) that becomes public and which takes the form of a disruption, loss, emergency, or crisis. Most AIAAIC Repository entries are classified as incidents.

Examples: AI system or robot malfunction; Actual or perceived inappropriate or unethical behaviour by a system operator or developer; Data privacy or info confidentiality leak exposes system vulnerability
Issue. Concerns publicly raised about the nature and/or potential impacts of a System, but without evidence of recognised harms.

Examples: A public debate/controversy about an unlaunched system, technology, or patent; Research indicating unwarranted carbon emissions or water consumption by a system

An issue also applies to a longer-term public debate or dispute relating to the poor, inappropriate, or unethical governance of an AI, algorithmic, or automation system that may arise because of, or lead to, one or more incidents, or, if properly managed, may subside or disappear over time.

These may directly or indirectly relate to topics such as: business model, competition/collusion; employment, marketing, surveillance, anthropomorphism, ethics, supply chain management, and the environment.

Examples: