When is AI sign language acceptable, and when is it risky?

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, testimony, and legal outcomes.

In education, incorrect sign language can harm learning and language development.

In these settings, AI-generated sign language without qualified human verification is risky.

Image description (alt text):

The image shows several real-world situations where British Sign Language is used, arranged around a central device.

At the top left, a doctor speaks with a Deaf patient who is signing. At the top right, a teacher stands in front of a classroom board while a Deaf student signs. At the bottom left, a judge sits in a courtroom while a Deaf person signs in front of them. At the bottom right, a pair of hands signs beside scales of justice and an open book.

In the centre, glowing arrows from all scenes flow into a tablet held by two hands. On the tablet screen is a human-looking sign language interpreter signing, with the label “BSL” above their head. A soft, funnel-shaped glow connects the scenes to the tablet, representing information being processed.

The background is dark with subtle light effects, giving a digital and futuristic atmosphere. The image highlights how sign language interpretation is used across medicine, education, and justice, and how it is mediated through technology.

A key issue is accountability:

• Who verifies the output?

• Who approves it?

• Who is responsible when it is wrong?

  
  

If there are no qualified sign language verifiers and no clear approval process, the system should not be used in high-risk domains.

A simple principle applies:

The higher the consequence of error, the higher the need for human verification.

AI can support access, but it cannot replace responsibility.