Five or 10 years from now, glaucoma diagnosis will probably be a lot easier, thanks to inevitable advances in artificial intelligence. It’s easy to paint AI as a panacea for countless difficult or tedious tasks throughout society, and I’m leery of making uncritical assumptions. Glaucoma is in fact more slippery than other diseases on the radar of AI researchers. Especially in its earliest stages, its presence is much less concrete than something like diabetic retinopathy, where fundus images alone are definitive and hence AI systems can be trained on large datasets of confirmed cases. By contrast, in glaucoma the wide variability in optic nerve anatomy makes it hard to draw a sharp line between normal and abnormal, so AI metrics will be more couched in probabilities than certainties.

Still, any data-driven field that creates huge reference sets to scan is going to get an AI boost at some level. At this year’s ASCRS meeting, one glaucoma expert even speculated that since AI’s predictive algorithms are getting so good, it may one day put visual field testing out of business. Why muck around with all that subjective testing if structural imaging will get you answers that are as good or better?

In some ways, I actually hope AI’s benefits in glaucoma are still a few years away. You’ve surely heard (from me and countless others) that ODs are the only realistic solution to the delivery of glaucoma care in America. With far fewer ophthalmologists in practice and that profession’s high degree of subspecialization, there’s not nearly enough capacity in the MD ranks to serve millions of glaucoma patients in a way they need and deserve.

Optometry’s capacity in glaucoma is gaining steam—medication prescribing rights in all 50 states and SLT in 10 of them—but the profession is still held back by structural problems in insurance billing and patient access, as well as a reluctance among some to really dive into the messy work of full-scope glaucoma care. “The general tendency of ODs who manage glaucoma is to prescribe a prostaglandin analog, and if the patient needs escalation of therapy, they refer the patient to ophthalmology,” says Danica Marrelli, OD, this month in “Avoid These Common Glaucoma Mistakes” on page 64.

If optometrists tend to hit a wall in their uptake of glaucoma responsibilities—wherever that may be for each individual—I worry that handing them too many AI tools might blunt their ability to work through tricky clinical problems themselves and, in so doing, gain vital insights into the disease itself. I’m reminded of an allegory used nearly 20 years ago on ABC’s TV show Lost that has stuck with me ever since: how a moth must dig at its cocoon to break out of it and can only survive because that effort prepared it for the world. “Struggle is nature’s way of strengthening,” a mentor figure explains.

Our 29th annual glaucoma report targets dozens of areas where some ODs struggle to move beyond the fundamentals. If that’s you, we hope this issue helps you break out of that cocoon and emerge stronger than ever. You’ll have to put it into practice—no article can give you everything you need—but once you know the disease better than any AI ever could, you’ll be able to use diagnostic technology as tool instead of a crutch.