Glossary

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Task Automation(also: Web Task Automation, Browser Automation)

The use of software agents or scripts to automatically perform web-based tasks on behalf of users, such as filling forms, making purchases, or extracting information. Task automation in accessibility contexts promises to reduce the effort required for screen reader users to…

Teachable AI(also: Teachable Machine Learning, Interactive Machine Learning)

Teachable AI refers to artificial intelligence systems that allow end users to personalize the system by providing their own training examples, high-level constraints, or prompts — without requiring programming or machine learning expertise. In the accessibility context,…

Teachable Object Recognition(also: Teachable Object Recognizer, TOR, Personalized Object Recognition)

A machine learning approach that allows users to train an object recognition system to identify their own personal items by providing a small number of training examples, typically photos or videos. This technology is particularly valuable for blind and low vision users who need…

Text-to-Image(also: Text-to-Image Generation, T2I)

An AI capability that generates visual images from natural language text descriptions (prompts). Text-to-image models like DALL-E, Midjourney, and Stable Diffusion have opened new creative possibilities for blind individuals by allowing them to create visual content through…

Text-to-Image Generation(also: Text-to-Image AI, Text-to-Image Synthesis)

An artificial intelligence capability that creates visual images from natural language text descriptions, also known as prompts. Tools such as DALL-E, MidJourney, and Stable Diffusion use large-scale diffusion models trained on image-text pairs to generate novel images matching…

Text-to-Image Model(also: T2I Model, T2I, Text-to-Image Generator)

A generative AI system that produces images from natural-language prompts. Prominent examples include DALL-E, Stable Diffusion, and Midjourney. In accessibility contexts, text-to-image models have been shown to replicate and amplify disability stereotypes — for example,…

Time-Causal Model(also: Temporal Causal Model, Sequential Logic Model)

A computational model that enforces temporal coherence in predictions by ensuring that the sequence of recognized events follows a logical causal order. In recipe tracking, a time-causal model prevents the system from predicting that an earlier step is currently happening after…

Topic Segmentation(also: Text Segmentation, Topicalisation)

A natural language processing technique that automatically divides a document into coherent sections based on changes in topic or subject matter. Topic segmentation algorithms detect boundaries where the semantic content of adjacent sentences or paragraphs shifts significantly,…

Toxicity detection(also: Content toxicity scoring, Toxic speech detection)

An NLP-based content moderation technique that assigns scores to text indicating the likelihood it is rude, disrespectful, or likely to make someone leave a conversation. Research has shown that toxicity detection models encode disability bias, scoring innocuous sentences that…

Training Data(also: Training Set, Training Dataset)

The collection of labeled examples used to teach a machine learning model to perform a specific task. The quality, quantity, and diversity of training data directly determine how well a model will perform. In accessibility contexts, training data quality is especially important…

Trajectory Analysis(also: Route Analysis, Path Analysis)

The computational study of movement patterns over time and space, typically derived from GPS or other location data. Trajectory analysis involves modelling, comparing, and classifying sequences of spatial positions to identify patterns, anomalies, or behaviours. In assistive…

Transfer Learning

A machine learning technique where a model trained on a large general dataset is adapted to perform a new, more specific task using a much smaller amount of new training data. Rather than training a model from scratch, transfer learning leverages patterns already learned by an…

Transparency in AI(also: AI Transparency, Algorithmic Transparency)

The principle that AI systems should clearly communicate how they work, what data they use, where processing occurs, and what their limitations are. In accessibility contexts, blind users have expressed strong desires to understand how AI-enabled privacy techniques are designed,…

Turing Test(also: Imitation Game)

The Turing Test, proposed by Alan Turing in 1950, is a thought experiment for assessing whether a machine's conversational behaviour is indistinguishable from that of a human. A human evaluator engages in a text-based exchange with both a human and a machine and must decide…

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