Algorithms have long been the cornerstone of computing but now there’s a lot of talk about artificial intelligence (AI). What’s its role? What is the difference? As CDP focuses on accessibility for digital documents, we also ask the question: “What is the impact for Digital Accessibility?” There is growing excitement around AI’s role in reshaping the field. This raises questions about its growing influence and whether it should become as integral as traditional algorithms. Each serves unique roles across many of today’s applications—from straightforward automation to intricate decision-making. While they are interconnected, their functions and impacts on technology vary significantly. This is a follow-up to last year’s CDP article: “Limitations of AI for Accessibility“. Has much changed since then? This article will explore the relationship between AI & Algorithms with a focus of the impact for Digital Document Accessibility.
Understanding Algorithms
So, what is an algorithm? It is typically referred to as a computer “program”. It can be defined as a finite sequence of well-defined instructions to solve a problem or perform a computation. From sorting data to performing calculations, algorithms are the building blocks of all computer processes. Algorithms work predictably, following clear rules to consistently deliver expected results.
Exploring Artificial Intelligence
Artificial Intelligence, or AI, goes a step further than basic computer programs. It’s designed to imitate how humans think. AI can make its own decisions, learn from what happens around it, and adjust to new information all by itself. Unlike regular algorithms, which strictly follow a set of rules, AI uses these rules in more advanced ways to learn and make decisions over time, showing a kind of intelligence similar to humans. The results may be different than you expect.
AI & Algorithms: Enhancing Digital Accessibility
AI and algorithms both play pivotal roles but in distinctly different ways. Here’s how they relate to digital document accessibility:
- Complexity and Scope: While algorithms execute specific tasks, AI systems manage broader applications like language processing and predictive analytics, crucial for adaptive accessibility solutions.
- Learning Capability: AI’s ability to learn and improve from data through machine learning surpasses traditional algorithms, offering innovative approaches to accessibility challenges.
- Practical Application: Algorithms excel in defined, straightforward tasks. AI, however, thrives in environments that demand adaptability, such as real-time accessibility adjustments in digital content.
Concerns with AI in Document Accessibility
Despite the advancements in AI, several challenges persist, particularly in fields requiring high accuracy and reliability, such as document accessibility for sensitive information. These concerns include:
- Human Judgment and Expertise: AI still lacks the nuanced understanding and judgment that human experts bring, particularly in interpreting complex images or documents where context and detailed comprehension are crucial.
- Accuracy and Dependability: As noted in previous discussions, AI’s reliability isn’t yet sufficient for critical applications. This includes legal documents, financial statements, or health records. The risk of errors in these areas can have significant consequences.
- Privacy and Security: AI systems often require data to be shared with third-party services, raising concerns about data privacy and security. Sensitive information could potentially be exposed or misused.
- Maturity of Technology: AI is an exciting field but it is still evolving. The technology has not matured enough to handle tasks where precision is critical. Inaccuracies in AI-generated content, such as alternative text for images in complex transactional documents, could lead to misunderstandings or misrepresentations.
Ethical and Practical Challenges Highlighted by Industry Experts
As if those concerns about AI were not enough, Sheri Byrne-Haber, a leading advocate for accessibility, shared an additional critical oversight. Sheri also is also a W3C committee member and is a member of the IAAP Global Leadership Council. To quote Sheri: “and once again technology has evolved faster than the ethical use of that technology.” Her observation reflects broader concerns about AI’s rapid development and its implications for increased energy demands. This surge in electricity use is straining power grids and prompting the development of AI data centers in regions with lax environmental standards, underscoring the environmental impact of unchecked technological growth.
Conclusion
While AI and algorithms are interlinked, with AI depending on algorithms to function, they fundamentally differ. Algorithms are defined, rule-based instructions, whereas AI offers a broader, more adaptive range of technologies capable of learning and decision-making. For digital accessibility, where accuracy, privacy, and reliability are paramount, a cautious approach to AI adoption is essential. By prioritizing the development of robust algorithms and closely monitoring AI’s evolution, we can ensure responsible progress in accessible technology.
Despite the potential of AI, it is crucial to acknowledge that the technology is not yet sufficiently reliable for full dependence in the context of digital accessibility. Current AI technologies, while innovative, often fall short in accurately interpreting complex elements of digital documents, such as nuanced text and image descriptions needed for individuals with disabilities. This gap underlines the importance of continuing to lean on human expertise and carefully tested and evaluated algorithms to ensure that digital accessibility standards are met without compromise. As we further integrate AI into accessibility solutions, it is imperative to maintain rigorous testing and validation processes to safeguard against the risks of premature reliance on AI systems.
