![]() What Are the Expectations and Limitations of AI?ĪI might be able to revolutionize our interactions with the electronic health record and improve our analysis of complex datasets. Through these effects, AI may indirectly increase the amount of innovation in ophthalmology, optometry, and vision science by increasing the amount of time clinicians can dedicate to research, improving data analysis (e.g., in big datasets associated with basic and as well as with clinical research) and, via increased efficiency of clinical trial design and execution, increasing the working capital available to support more extensive efforts in research and product development. Regarding trial design, greater analytical capacity may improve hypothesis generation and patient selection, as well as support more sensitive clinical outcome monitoring, thus enabling one to design clinical trials of shorter duration with fewer patients enrolled. 25 If routine screening could be done outside of doctors’ offices, then clinicians could spend more time treating rather than screening patients. 15 – 24 AI may even predict diabetic retinopathy progression. AI can identify common vision threatening diseases with sensitivity and specificity that is comparable to that of experienced clinicians. How Will AI Influence Ophthalmology and Optometry?ĪI is likely to have an important direct impact on access to the care, monitoring, and treatment of chronic conditions, and clinical trial design. The computational capacity of computers has increased exponentially with the development of integrated circuits and microchips. This link is important and helps to explain why AI has become so pervasive at this point in human history. 1 Intelligence is linked to computational capacity. Intelligence is associated with (1) an ability to acquire and apply knowledge and skills (learning), (2) using rules to reach conclusions (reasoning), and (3) self-correction. So, computation is not intelligence, and computation is not learning, which is a recursive rearrangement of computational architecture. We can even identify the nature of emotional interactions between subjects portrayed in the work (e.g., love between mother and child in Picasso's Mother and Child ). We can identify readily the authors of paintings (e.g., Picasso) by their distinctive style. Would anyone argue that a calculator is more intelligent than a human? In contrast, the human brain performs remarkably well at computations involving the highly complex task of image analysis. ![]() For most of us, that calculation is difficult. It is trivial for a calculator to compute 314,159 × 271,828. Computational capacity, therefore, is not the same as intelligence. 1 Computation is deterministic, that is, the same input always gives the same output. Computation involves the transformation of one memory state into another.
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