AI Accessibility Gains Momentum as Microsoft Strategist Calls for Balanced Approach
A Microsoft accessibility innovation strategist today urged a cautious yet optimistic approach to artificial intelligence in accessibility, highlighting both significant risks and transformative potential—especially in generating alternative text for images. The strategist, who oversees the company's AI for Accessibility grant program, told Tech Access Now that while current computer-vision models remain flawed, targeted improvements and human oversight could turn AI into a powerful assistive tool.
"AI can be used in very constructive, inclusive, and accessible ways; and it can also be used in destructive, exclusive, and harmful ones," the strategist said. "I'm very skeptical of AI myself, despite my role. But I want to provide some visibility to projects where AI can make meaningful differences for people with disabilities."
Background
Current AI systems for image analysis often examine images in isolation, without understanding context or distinguishing between content that needs description and decorative elements. This limitation, the strategist noted, stems from separate "foundation" models for text and image analysis.
"Today’s models aren’t trained to distinguish between images that are contextually relevant and those that are purely decorative," the strategist explained. The result is often poor-quality alt text that frustrates users and accessibility advocates alike.
Human-in-the-Loop: A Pragmatic Path Forward
Despite these shortcomings, the strategist sees value in AI as a starting point. "Human-in-the-loop authoring of alt text should absolutely be a thing. If AI can pop in to offer a starting point—even if that starting point might be a prompt saying 'What is this BS? That’s not right at all… Let me try to offer a starting point'—I think that’s a win," they said.
The strategist also described a more advanced approach: training a model to analyze image usage in context. Such a system could quickly identify decorative versus content-rich images, improving author efficiency and reinforcing accessibility norms.
What This Means
For people with disabilities, these developments could eventually mean faster, more accurate content accessibility—especially for complex images like graphs and charts, which remain challenging even for human describers. The strategist pointed to demonstrations like the one in the GPT-4 announcement as proof that richer, context-aware descriptions are on the horizon.
However, the message comes with a stark warning: the pressing issues with AI need to be addressed "yesterday," and the technology must be deployed with rigorous oversight. "I'm not trying to refute any of what Joe Dolson said about the risks," the strategist concluded. "I want to talk about what’s possible, in hopes that we’ll get there one day."