Glossary
Searchable terminology from accessibility, web standards, and related fields.
27 results found in AI ethics.
- AI Auditing (Algorithmic Auditing, AI Audit)
- The systematic evaluation of an AI system's outputs, behaviour, or training data to identify harms such as bias, stereotype reproduction, or accessibility failures. Audits may be conducted by industry…
- AI Ghostwriter Effect (Ghostwriter Effect)
- A phenomenon, first named by Draxler and colleagues, in which people who use AI writing assistants do not perceive themselves as authors or owners of the resulting text yet still publicly self-declare…
- AI Over-Reliance (Automation Bias (AI), Over-Reliance on AI)
- The tendency of users to accept AI system outputs — recommendations, classifications, or content — without sufficient critical evaluation, even when those outputs are wrong or biased. Over-reliance is…
- AI for Accessibility (AI4A, Artificial Intelligence for Accessibility)
- An umbrella framing used by technology companies and researchers for applications of artificial intelligence — including computer vision, natural language processing, speech recognition, and generativ…
- Algorithmic Audit (AI Audit, Algorithmic Auditing)
- A structured evaluation of an algorithmic system that measures how its behaviour differs across users, groups, or contexts - typically to surface bias, fairness failures, or disparate impact. Accessib…
- Algorithmic Hiring (AI Hiring, Hiring AI, AI-Enabled Hiring)
- The use of algorithmic systems — including machine learning and large language models — to source, screen, rank, or select job candidates. Proponents argue algorithmic hiring reduces human bias and sc…
- Allocative Harm (Allocational Harm)
- A category of algorithmic harm in which an automated system disproportionately withholds opportunities, resources, or services from certain individuals or groups - often because those groups are under…
- Automated Employment Decision System (AEDS, AEDT, Automated Employment Decision Tool)
- A software system that screens, evaluates, categorises, recommends, or otherwise makes or facilitates hiring or employment decisions about job candidates or workers. AEDSs span résumé sorters, persona…
- Automation Transparency (AI Transparency (Automation), Transparent Automation)
- The degree to which an automated or autonomous system communicates its current state, intent, and reasoning to the humans who depend on it. In autonomous transport, transparency includes cues such as …
- Black Box Model (Opaque Model)
- A machine-learning model whose internal workings are not directly inspectable or interpretable by a human, either because the model is architecturally complex (deep neural networks, large language mod…
- Co-Authorship (Co-authoring, AI Co-Authorship)
- In AI-mediated writing and communication, the shared production of text between a human user and an AI system, where neither party fully owns the resulting output. Co-authorship raises questions about…
- Colorism (Skin Tone Bias, Shadeism)
- Colorism is a form of discrimination in which people are treated differently based on the shade of their skin tone, typically favoring lighter skin over darker skin within and across racial groups. In…
- Computer Says No (Computer-Says-No)
- A pattern in which an organisation invokes an algorithmic or automated decision as justification for an adverse outcome — a rejected application, a denied claim, an adjusted score — thereby deflecting…
- Constitutional AI (CAI)
- A training method introduced by Anthropic in 2022 in which a large language model is aligned to a written set of principles (a 'constitution') through self-critique and reinforcement learning from AI …
- Counterfactual Explanation (Counterfactual XAI)
- An explanation technique that communicates what minimal change to the input would have produced a different output from an AI model, for example 'if the applicant's income had been $5,000 higher, the …
- Data Annotation (Data labeling, AI labeling)
- The process of attaching labels, transcriptions, bounding boxes, or other structured metadata to raw data so that it can be used to train, evaluate, or benchmark machine-learning models. Annotation is…
- Data Colonialism
- A critical framework, advanced by Couldry and Mejias (2019) and others, that describes how contemporary data extraction practices replicate historical patterns of colonialism — appropriating resources…
- Disability-First Dataset (Disability-first AI dataset)
- An approach to AI dataset creation, articulated by Theodorou et al. and others, that treats serving a disability community as the primary objective rather than collecting disability data as a minority…
- EU AI Act (European Union Artificial Intelligence Act, Artificial Intelligence Act (EU))
- A European Union regulation, adopted in 2024, that establishes a risk-based framework for AI systems deployed in the EU. High-risk systems — including AI used in employment, hiring, worker management,…
- End-User Auditing (User-Led Auditing, End User Audits)
- An approach to AI auditing in which everyday users — rather than professional evaluators — identify problems, biases, or harms in AI outputs based on their lived experience. End-user auditing is parti…