Key takeaway: Artificial Intelligence (AI) can support accessibility workflows, but it cannot fully replace human expertise. Accurate accessibility remediation requires contextual understanding, quality control, and expert judgment that current AI technologies cannot reliably provide on their own.
AI has limitations when it comes to accessibility for digital content. We all love to find a way to get a task done quicker, easier, and cheaper. As a result, AI has become a hot topic recently. Of course, those of us who work with accessibility technology immediately imagine that this could be the “holy grail” to quick, easy, economical remediation of digital content.
But really?
Have you ever used it?
Would you depend on the results of AI for something that really matters?
There is a myth out there that you can rely on AI for all your accessibility needs. AI is great in certain, very specific situations. Some even claim that you can add one line of code and then your website will be accessible. Unfortunately, there is no silver bullet or magic solution. Digital accessibility remediation is detailed and skilled work and requires human involvement.
According to the World Health Organization, more than 1.3 billion people globally live with some form of disability, highlighting the importance of accurate accessibility solutions for digital content.
“Accessibility requires thoughtful design, testing, and human expertise.”
— World Wide Web Consortium (W3C)
Ensuring equal access to information for people with print disabilities is a crucial consideration. Assistive technologies and solutions have emerged to address this need, and among them, AI holds great promise. AI-powered remediation tools have the potential to automate the process of making digital documents accessible, but it is important to acknowledge the current limitations and risks associated with relying solely on AI for this task. This article aims to explore the challenges and concerns surrounding the use of AI in remediating digital documents for individuals with print disabilities.
The potential of AI in remediation
AI technologies, such as machine learning and natural language processing, offer tremendous potential in automating various aspects of document accessibility remediation. These tools can analyze document structures, recognize text, and apply appropriate accessibility enhancements like alternative text for images, semantic structure for headings, and proper tagging for screen readers. The speed and efficiency of AI-driven remediation tools have the potential to revolutionize the accessibility landscape. Unfortunately, AI is also known to produce erroneous results with speed and efficiency.
Security risks and confidentiality
Another significant concern when utilizing AI for digital document remediation is the potential security risks and confidentiality breaches. AI tools often require access to sensitive and confidential documents that may contain personal or proprietary information. Sharing such documents with third-party AI platforms raises legitimate concerns about data privacy and security. The risk of unauthorized access or data breaches during the remediation process can have severe consequences for individuals and organizations.
Lack of contextual understanding
One of the critical limitations of current AI technologies is the lack of contextual understanding. While AI algorithms can recognize patterns and structures, they struggle to comprehend the full context of the document’s content. This limitation can result in misinterpretation and inappropriate application of accessibility features. For example, an AI tool may misidentify the purpose of an image or fail to recognize the appropriate hierarchical structure of a complex document, leading to suboptimal or even misleading accessibility remediation.
Lack of quality control and human judgment
AI is not yet capable of completely replacing the expertise and judgment of human accessibility professionals. The remediation process requires meticulous attention to detail, understanding of accessibility guidelines, and subjective judgments regarding appropriate accessibility enhancements. While AI can automate certain tasks, it cannot fully replace the human element in ensuring the accuracy, quality, and appropriateness of the remediation process.
AI is known for routinely including inaccurate information which it passes off as fact. To quote this Washington Post article about the inaccuracies of AI: “they still have a major fatal flaw: they make stuff up all the time.”
Conclusion
AI holds great promise in revolutionizing the remediation of digital documents for individuals with print disabilities. However, it's essential to acknowledge the current limitations and risks associated with relying solely on AI for this critical task. Inaccuracies in recognition, security risks, lack of contextual understanding, limited customizability, and the need for human judgment and quality control are significant challenges. If you would not base your important life decisions on the results of AI, it is not a viable approach to make accessible content for people with print disabilities either.
Quadient offers an automated solution for high-volume digital document remediation called Inspire Adapt. This approach is not based on AI, rather it is designed, tested, and supported by our skilled team of digital document developers. Contact us for more details.
Frequently asked questions
Can AI automatically make digital documents accessible?
AI can assist with tasks such as text recognition, tagging suggestions, and structural analysis. However, it cannot reliably ensure full accessibility without human validation and expert oversight.
What are the main limitations of AI for accessibility?
Key limitations include lack of contextual understanding, potential inaccuracies, security risks related to document data, and the inability to apply human judgment to accessibility decisions.
Why is human expertise important in accessibility remediation?
Accessibility professionals understand standards such as WCAG and PDF/UA and can interpret document meaning, context, and usability in ways that current AI systems cannot.
Are AI tools useful for accessibility workflows?
Yes. AI can support accessibility efforts by speeding up certain processes, but it should be used as part of a broader strategy that includes manual testing and quality assurance.
What is the risk of relying only on AI for accessibility?
Relying solely on AI can result in incorrect tagging, misleading alternative text, structural errors, and documents that technically pass automated checks but are still unusable for assistive technology users.