Tim Scannell, Accessibility Consultant:

Enhancing Access for the Deaf and Hard of Hearing by Focusing on Sign Language, Digital Accessibility, and Information Access for Everyone.

Deaf people spent centuries building language, education, careers, and equal communication. AI companies should not be allowed to reduce that to a one-way system and call it progress. This is the question I keep returning to: who gave AI sign language approval? That question matters because AI sign language is not just a technical experiment. It touches language, identity, culture, education, employment, and human dignity. It affects Deaf children and adults whose lives have

Artificial intelligence is developing fast, but live interpreting shows exactly where its limits still are. For prepared speeches, AI-generated sign language can look impressive. It performs best when the language is structured, the content is predictable, and the system operates on clean input. But conferences are rarely that simple. Live panels are unpredictable. Speakers interrupt each other. They react in the moment. They change direction. They overlap. They leave thought

Six days ago, my post reached 28,000 expressions — thank you. I am now sharing it on my Wix blog. The post said: Spotted at Crufts. A useful reminder that software only outputs what it is given.The printing company probably printed exactly what was in the file. In the same way, AI and other software tools can reproduce errors perfectly unless a human stops and checks. One missing letter. Completely different meaning. Proofreading still matters. Alt text: A photo of a large ex

Between 1999 and 2003 , when I was at university, one of my subjects was Human–Computer Interaction (HCI) . At that time, many people were still avoiding the Internet. Today, smartphones and smart devices give almost everyone access to apps and platforms across the Internet — the shift has been significant. We are now experiencing a similar moment with AI and sign language . There is increasing experimentation with signing via Meta platforms, AI-assisted accessibility tools,

On Sunday , 16 February , I published a blog post on “blurring the handshape.” The central point was simple: When the handshape is blurred, the meaning is blurred. This is not a minor technical issue. It is: a language integrity issue, an accessibility issue, and a Deaf rights issue. AI-generated signing is increasingly being presented as “accessibility.” However, sign language access is not merely visual output on a screen. Sign language access is a conversation. It dep

AI-generated sign-language interpretation is now appearing in public events. Accessibility is crucial, but so are clarity, linguistic accuracy, and accountability. YouTube: https://www.youtube.com/watch?v=30TgqnxeRlk Observations on AI Signing From what I observed in the PIP window, the signing still looks stiff and choppy. The transitions feel unnatural. The clarity and linguistic accuracy need significant refinement. Without proper validation by Deaf communities and qualifi

Not all uses of AI-generated sign language carry the same level of risk. In low-risk public information contexts — such as airports, train stations, or general announcements — AI sign language may be acceptable if it is clearly presented as assistive and not a replacement for human interpretation. However, the situation changes in high-stakes contexts . In medicine , errors can affect consent, diagnosis, and patient safety. In justice , misinterpretation can affect rights,

Generative AI is now being used to convert written text or spoken language into sign language avatars for websites, videos and public communication. Innovation in accessibility is positive. However, when working with British Sign Language (BSL), accuracy is essential. BSL is a complete language. It has its own grammar, structure and visual rules. If these rules are not clear, meaning can change. HOLMN: The Foundation of BSL Every sign in BSL depends on five key elements. Thes

Spatiality and phonology are core parts of sign language. Many current AI systems still struggle to represent them accurately. When errors appear in AI-generated sign language, responsibility is often implicitly placed on the human sign language translator involved. This is unfair and incorrect. In most systems, translators are not delivering sign language directly to the AI. They are contributing to datasets, often in the form of sign language gloss. Gloss is a simplified re