Opinion

Simon Jones: Preventing artificial tears

Opinion

After weaponising sustainability ahead of the 2024 election by making Britain’s future Net Zero targets a wedge issue among voters, Prime Minister Rishi Sunak has quickly moved to pour doom and gloom on artificial intelligence (AI), warning that there may only be a year before it can no longer be controlled. On AI, at least, he may well have a point.

While Sunak uses the reference points of bio-terrorism and national security to encourage more dialogue among countries, there are other ways in which AI is outpacing the current regulations and processes needed to regulate it.

Copyright infringement is a key battleground and cases raised by it could begin to provide the legal precedents needed to start stuffing the genie back in the bottle. For example, the lawsuit raised by information services company Thomson Reuters against Ross Intelligence for unlawfully copying content from its legal-research platform Westlaw to train a competing artificial intelligence-based platform.

In a sector full of patents, trademarked designs and research, optometry has an awful lot to lose if more regulation on AI isn’t promptly introduced.

Equally, there’s an awful lot to gain if AI is harnessed properly. Potential use in screening for diabetic retinopathy has been well documented, and systems capable of identifying genetic causes of inherited retinal diseases have been developed in recent years.

Emerging research from the Singapore National Eye Centre has even sought to deploy AI in the battle against myopia in children. Its AI algorithms have been used to predict the five-year development of high myopia in multi-ethnic children aged between six and 12 years old with predictive performance of 94% using just a fundus image.

Researchers say the algorithms have the potential to be implemented into school or community where at-risk children can be identified and treated earlier than before.

The challenge is now to make sure the AI and its sub-sets like machine learning and deep learning, can exist in harmony with open-ended generative AI platforms like ChatGPT and Stable Diffusion.