The potential of artificial intelligence (AI) is vast and multifaceted. AI has the ability to revolutionize industries such as healthcare, transportation, and finance by streamlining processes and increasing efficiency. The Scholarly Kitchen brought this interesting topic to us in their article, “Guest Post — Accessibility Powered by AI: How Artificial Intelligence Can Help Universalize Access to Digital Content.”

AI also has the potential to solve some of the world’s biggest challenges such as climate change and poverty. With great power, however, comes great responsibility. The fear around AI lies in its potential misuse or unintended consequences.

AI-powered tools are one way to improve accessibility, but the creation of accessible content and systems requires a collaborative effort that includes publishers, product, tech, design, and other teams. There are many important aspects to consider in this effort, such as web design, user experience, regular accessibility audits, and input from editors, authors, and typesetters. With this collaboration in place, integrating tools powered by AI can help us create an inclusive place for everyone to access scholarly content.

Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, and its potential biases. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, changing search to found.