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Accessibility and AI in Practice

Designing for Access

Accessibility is not a checklist; it is a design mindset.

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I design learning experiences where accessibility shapes structure, content, and interaction from the very beginning. My goal is to create digital environments that are clear, usable, and inclusive for as many learners as possible.

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Artificial intelligence supports this process as a design partner, helping improve efficiency and expand accessibility practices while maintaining human-centered decision-making.

How I Approach Accessibility

My work is grounded in:

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Across my projects, I document not only what I designed, but the decisions, trade-offs, and reflections behind each experience.

Accessibility Practices I Use 

1

Universal Design for Learning (UDL)

I design for multiple ways of engaging with content:

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  • Combining text, visuals, and guided walkthroughs

  • Providing captions and transcripts

  • Offering downloadable resources and templates

  • Structuring content into short, scannable sections

2

Clear Structure and Navigation

Accessible design begins with clarity.

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  • Clear heading hierarchy

  • Consistent navigation patterns

  • Plain language and concise instructions

  • Readable typography and high-contrast visuals

  • Content structured to reduce cognitive load

3

Accessible Multimedia

I design content to be usable across devices and technologies:

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  • Captions and transcripts for video

  • Alt text for images and instructional visuals

  • Accessible document structure (headings, formatting)

  • Mobile-responsive layouts

4

Psychological and Cultural Accessibility

Accessibility also includes emotional and social dimensions:

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  • Inclusive, respectful language

  • Culturally aware examples and scenarios

  • Psychological safety in learning environments

  • Opportunities for reflection and practice

AI as a Design Partner

Artificial intelligence supports accessibility workflows when used intentionally and ethically.

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I use AI to assist with:

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  • Drafting and refining alt text

  • Generating transcript drafts

  • Assisting withd different mediums to deeper understanding

  • Improving clarity and readability

  • Identifying ambiguous instructions

  • Supporting iterative revisions

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All outputs are reviewed and refined to ensure accuracy, inclusivity, and alignment with human-centered design values.

Accessibility and AI Workflow

Accessibility and AI are integrated throughout my design process, not just applied at the end.

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My workflow includes:

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  • Identify learner needs and potential barriers

    • I consider accessibility needs, cognitive load, and varying levels of technology familiarity.​

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  • Structure content for clarity first

    • I establish a clear hierarchy, navigation, and organization before visual design begins.

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  • Apply accessibility frameworks

    • I integrate UDL principles, WCAG-informed practices, and accessible multimedia from the start.​

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  • Use AI to support accessibility workflows

    • I use AI to assist with alt text drafting, transcript generation, and refining instructional clarity.​

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  • Conduct accessibility reviews

    • I evaluate contrast, readability, navigation, and compatibility with assistive technologies.​

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  • Refine and iterate

    • I review all outputs to ensure they align with human-centered, inclusive design practices.

Where AI Needed Human Judgment

  • AI-generated content but did occasionally lack cultural nuance or emotional tone, requiring revision for clarity and inclusivity, and keeping the emphasis on learner-centered design

  • AI-generated scripts but required refinement to align with learner context, needs, and tone

  • Accessibility outputs (i.e., alt text, captions, etc.) required manual review for accuracy and usability

​Design decisions relied on human judgment to ensure clarity, inclusivity, and accuracy

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