Glossary

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Datasheets for datasets(also: Dataset documentation, Data cards)

A standardized documentation framework proposed by Gebru et al. that accompanies machine learning datasets with information about their creation, composition, intended use, and limitations. For accessibility, datasheets help surface representation gaps — such as whether people…

Decision-Theoretic Planning(also: Decision-Theoretic Approach)

A computational approach to planning that uses mathematical models of decision-making under uncertainty, most commonly Markov Decision Processes (MDPs), to select optimal actions based on the current state of the system and predicted outcomes. In assistive technology,…

Deep Learning(also: DL)

Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to learn complex patterns from large amounts of data. In accessibility contexts, deep learning powers many assistive technologies including automatic image description for…

Deepfake(also: Synthetic Media, AI-Generated Media)

AI-generated or AI-manipulated media (images, video, audio, or text) designed to convincingly depict events, people, or statements that never occurred. Deepfakes pose specific risks for people with disabilities: AI-generated fake images of disabled people have been used for…

Description Logic(also: DL, Description Logics)

A family of formal knowledge representation languages used as the mathematical foundation for ontology languages like OWL. Description logics describe a domain in terms of individuals (specific entities), concepts or classes (sets of individuals with shared characteristics), and…

Differential privacy(also: DP)

A mathematical framework for sharing statistical information about a dataset while providing provable guarantees that individual records cannot be identified. In accessibility contexts, differential privacy is proposed as a way to resolve the tension between collecting…

Digital mental health(also: E-mental health, Digital therapeutics)

The use of digital technologies including AI chatbots, mood tracking apps, and online therapeutic platforms to support mental health assessment, monitoring, and intervention. Designing accessible and explainable AI for digital mental health is particularly challenging because…

Directional Stimulus Prompting(also: DSP)

A prompt engineering technique for large language models that provides specific keywords or directional stimuli to guide the model toward generating output focused on particular aspects or attributes. In accessibility applications, DSP is used to produce targeted,…

Disability-Centered Dataset(also: Disability-First Dataset, Accessibility Dataset)

A research dataset specifically designed to capture the practices, environments, and experiences of people with disabilities, rather than retrofitting general-purpose datasets for accessibility evaluation. Disability-centered datasets reflect the real variability, messiness, and…

Domain Adaptation(also: Cross-Domain Transfer, UDA, Unsupervised Domain Adaptation)

A machine learning technique that enables models trained on data from one domain (such as web interfaces) to perform well on a different but related domain (such as mobile app interfaces). Domain adaptation is valuable for accessibility because it allows models trained on…

Dynamic Bayesian Network(also: DBN, Temporal Bayesian Network)

A probabilistic graphical model that represents sequences of variables over time, extending standard Bayesian networks to handle temporal relationships. In accessibility and affective computing contexts, Dynamic Bayesian Networks are used to model how facial expressions, head…

Dynamic Content Filtering(also: Intelligent Content Filtering, AI-Based Filtering)

The automated process of selectively showing or hiding web content based on computed relevance to a user's goals, preferences, or context. Dynamic content filtering uses AI models (such as large language models) to assess which page elements are relevant to a specific task and…

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