Glossary

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Hallucination(also: AI Hallucination, Confabulation)

In the context of AI and large language models, the generation of content that is plausible-sounding but not grounded in the input data or factual reality. Hallucinations pose a particular risk in accessibility applications such as captioning, audio description, or alt text…

Head Pose Estimation(also: Head Orientation Detection, Gaze Direction Estimation)

A computer vision technique that determines the orientation or direction a person's head is facing, typically classifying whether someone is looking towards or away from the camera. In accessibility contexts, head pose estimation can help blind users determine whether a passerby…

Hidden Markov Model(also: HMM)

A statistical model used extensively in pattern recognition where the system being modeled is assumed to follow a Markov process with hidden (unobserved) states. HMMs have been foundational in both automatic speech recognition and sign language recognition, as they can model…

High-Stakes Scenarios(also: Safety-Critical Scenarios)

Situations where errors in AI-generated information could lead to significant safety, health, financial, or social consequences. In the context of visual access technology for BLV users, high-stakes scenarios include medication identification (where misreading a dosage could be…

Human Computation

A computing paradigm in which humans perform tasks that computers cannot yet do reliably, often embedded within systems that combine human and machine capabilities. The classic example is reCAPTCHA, which used human text recognition to digitise books while verifying users were…

Human-AI Alignment(also: AI Alignment, Value Alignment)

The design and training of AI systems to exhibit behaviours consistent with human values, intentions, and goals. In accessibility, human-AI alignment requires that AI systems accurately represent and respond to the diverse values and experiences of disabled and neurodivergent…

Human-AI Collaboration(also: Human-AI Teaming, AI-Assisted Authoring)

An interaction paradigm where humans and artificial intelligence systems work together, each contributing their complementary strengths to achieve outcomes neither could produce as effectively alone. In accessibility contexts, human-AI collaboration combines AI efficiency in…

Human-AI Interaction(also: HAI, Human-AI Collaboration, AI Interaction Design)

The study and design of how people interact with artificial intelligence systems, including how AI communicates its outputs, uncertainty, and limitations to users. Key principles include making AI behavior transparent, supporting user correction of errors, acknowledging…

Human-in-the-Loop(also: HITL)

An approach to AI system design and evaluation that incorporates human judgment, feedback, and oversight at critical points in automated processes. In accessibility contexts, human-in-the-loop methodologies involve people with disabilities and other affected communities in…

Human-like trust in AI(also: Anthropomorphic trust)

The phenomenon where users develop trust in AI systems based on their human-like qualities — such as natural voice, conversational style, emotional expressiveness, and social behaviors — rather than the system's actual functional reliability. In accessibility contexts, this…

Hybrid Captioning(also: AI-Augmented Captioning, Blended Captioning)

A captioning approach that combines human-generated captions with AI-powered correction or enhancement to achieve higher accuracy than either method alone. Hybrid systems leverage the reliability and contextual awareness of trained human captioners while using automatic speech…

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