Glossary
Searchable terminology from accessibility, web standards, and related fields.
192 results found in artificial intelligence.
- AI Accountability (Algorithmic Accountability, AI Governance)
- The principle that developers, deployers, and operators of AI systems should be held responsible for the outcomes those systems produce, including negative effects on marginalized populations such as …
- AI Chatbot Accessibility (Accessible AI, LLM Accessibility)
- The design and evaluation of AI-powered chatbots and large language model applications to ensure they are usable by and beneficial to people with disabilities. This encompasses both the technical acce…
- AI Code Generation (Code Generation Model, AI Coding Assistant, LLM Code Generation)
- The use of large language models and machine learning to automatically generate, suggest, or complete source code based on natural language prompts or existing code context. Tools like GitHub Copilot,…
- AI Coding Assistant (AI Pair Programmer, Code Copilot)
- An artificial intelligence tool integrated into code editors that assists developers by generating code suggestions, completing code snippets, and answering programming questions using large language …
- AI Confidence (Model Confidence, Prediction Confidence)
- A measure of how certain an AI model is about a particular output or prediction. In the context of image descriptions for BLV users, AI confidence can be communicated through various means: internal p…
- AI Dubbing (AI Voice Generation, Neural TTS Dubbing)
- The use of artificial intelligence text-to-speech systems to generate spoken narration and character dialogue for media production. In accessible webtoon and comic production, AI dubbing offers a cost…
- AI Fairness (Algorithmic Fairness, Fair AI)
- The principle that AI systems should not create or reinforce unfair bias against particular groups. Standard AI fairness frameworks primarily address race and gender but are increasingly recognized as…
- AI Hallucination (Model Hallucination, Confabulation)
- The phenomenon where an AI model generates confident, plausible-sounding responses that are factually incorrect, fabricated, or not grounded in the actual input data. In accessibility contexts, AI hal…
- AI Homogenization (AI-Driven Homogenization, Generative AI Homogenization Effect)
- The tendency for generative AI systems to produce outputs that converge toward similar patterns, reducing the diversity and uniqueness of results across different users and contexts. In accessibility …
- AI Incident Database (AIID, AI Incident Tracker)
- A publicly accessible repository that documents reported incidents where AI-driven systems have caused harm or produced negative outcomes for individuals, communities, or society. Major databases incl…
- AI Mental Model (Mental Model of AI, User Mental Model of AI)
- A user's conceptual representation of how an artificial intelligence system works, including beliefs about its information sources, processing methods, capabilities, and limitations. Mental models of …
- AI Overreliance (Automation Bias, Over-Trust in AI)
- The tendency for users to trust AI systems more than is warranted by their actual accuracy, accepting AI-generated outputs without sufficient critical evaluation. In accessibility contexts, AI overrel…
- AI Recourse (Algorithmic Recourse, AI Appeal Mechanism)
- The ability of individuals negatively affected by AI-driven decisions to challenge, appeal, or seek correction of those decisions. For people with disabilities, AI recourse is particularly critical be…
- AI Trust Calibration (Trust Calibration, Appropriate Trust)
- The process of aligning a user's level of trust in an AI system with the system's actual reliability and capabilities. In accessibility contexts, trust calibration is critical because blind and low vi…
- AI Verification (Accessible AI Verification, AI Output Verification)
- The process of checking and confirming the accuracy of AI-generated output, particularly by end users who may not have visual access to the original content. For blind users, AI verification is challe…
- AI disability representation (AI disability simulation, Disability representation in AI)
- The portrayal or simulation of disabled experiences, communication styles, or perspectives by artificial intelligence systems. AI disability representation raises significant ethical concerns: while A…
- AI ethics (Artificial intelligence ethics, Machine learning ethics)
- The field concerned with ensuring that artificial intelligence systems are developed and deployed in ways that are fair, transparent, accountable, and respectful of human rights. In accessibility cont…
- AI hallucination (Model hallucination, Confabulation)
- The generation of plausible-sounding but factually incorrect or fabricated information by AI systems, particularly large language and multimodal models. In accessibility applications, AI hallucination…
- AI literacy (Artificial intelligence literacy, Algorithm literacy)
- The knowledge, skills, and critical awareness needed to understand, evaluate, and effectively engage with artificial intelligence systems. For people with disabilities, AI literacy is particularly imp…
- AI sycophancy (Sycophantic AI, AI agreeableness bias)
- The tendency of AI systems, particularly large language models, to provide overly affirmative, agreeable, or encouraging responses that cater to the user rather than providing accurate information. In…