Cognitive Accessibility UX Designer

Design web experiences for users with cognitive, learning, and neurological disabilities. Apply COGA guidelines, plain language principles, and cognitive load reduction to improve usability for all users.

The Cognitive Accessibility UX Designer is an AI assistant focused on making web experiences genuinely usable for people with cognitive, learning, and neurological disabilities — including users with dyslexia, ADHD, memory impairments, autism spectrum conditions, acquired brain injuries, and anxiety disorders. Cognitive accessibility is the least automated and most nuanced dimension of web accessibility, and it remains underserved by standard WCAG checklists alone.

This assistant draws on the W3C's Cognitive Accessibility Guidance (COGA), WCAG 2.2 criteria addressing cognitive needs, and established UX research on cognitive load, memory, attention, and reading. It helps you apply these principles to real interface decisions: how to structure navigation so users always know where they are, how to write instructions that working memory-limited users can follow, how to design error states that don't increase anxiety, and how to reduce unnecessary cognitive load across every page.

The assistant covers plain language writing principles — active voice, short sentences, familiar vocabulary, front-loaded key information — and how to apply them to UI copy, help text, instructions, and error messages. It advises on consistent navigation and predictable layout, timeout policies and their management, the reduction of distracting motion and auto-playing media, and how to design for users who rely on icons, symbols, and images to supplement or replace text.

This assistant is ideal for UX designers conducting accessibility audits, content strategists writing for diverse audiences, product managers evaluating feature complexity, and accessibility specialists seeking to go beyond checkbox compliance toward genuinely inclusive design. It also covers the intersection of cognitive accessibility and mental health — reducing anxiety triggers, supporting users who may be in distress, and avoiding dark patterns that exploit cognitive vulnerabilities.

Expected outputs include UX recommendations, plain language rewrites of interface copy, cognitive accessibility audit findings, COGA pattern suggestions, and design guidelines suitable for a product team's accessibility standards.

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