Eyes on the Future: Striking the Right Balance between AI and the Human Touch in Ophthalmology

Dear Editor, There has been a plethora of conversational artificial intelligence (AI) models off late, providing real-time information for both education and patient care, thus influencing the way we detect, diagnosis and treat diseases.[1,2] Both ChatGPT and Google Gemini are tools that have been studied extensively and are advancing forward to bridge the information and interpretation gap that was not possible previously.[3] However, the responses and results provided are still purely factual. Human qualities like empathy, multi-faceted thinking and judgment remain lacking in these models. Lack of standardization between countries and the ambiguity of AI generated answers attributable to the black box theory emphasize on the necessity of a physician’s opinion.[4] Many authors have argued that AI will not replace humans in healthcare.[5] Hence, we conceptualize the term human-machine interface (HMI), a system where the AI realizes that human intervention is required and redirects the data for such need. Though the efforts to build an efficient AI model continues, the race to build a robust HMI has just started and the first system to build such a model will be able to bridge the gap between the human mind and artificial technology fortuitously. This particular task is sufficiently easy in ophthalmology owing to its preexisting heavy reliance on machine tools for longitudinal imaging and diagnosis. IDx-DR2 and EyeArt AI are two such autonomous AI systems that are revolutionizing the screening and referral process for diabetic retinopathy in the current world.[6] Ophthalmology lies in the sweet spot between needing AI for screening and diagnosis but requiring the human touch for specialized examination and complex microsurgery.[7] Artificial intelligence will not be able to replace ophthalmologists in the future, but the ones who use AI are bound to replace those who don’t. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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Publication Details

Journal
TNOA Journal of Ophthalmic Science and Research
Published
2024-10-01
DOI
https://doi.org/10.4103/tjosr.tjosr_123_24
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
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article

Eyes on the Future: Striking the Right Balance between AI and the Human Touch in Ophthalmology

Aishwarya Naik, Tamanna Ghosh, Anujeet Paul
TNOA Journal of Ophthalmic Science and Research
Retinal Imaging and Analysis
article

Eyes on the Future: Striking the Right Balance between AI and the Human Touch in Ophthalmology

Aishwarya Naik, Tamanna Ghosh, Anujeet Paul
article en

Abstract

Dear Editor, There has been a plethora of conversational artificial intelligence (AI) models off late, providing real-time information for both education and patient care, thus influencing the way we detect, diagnosis and treat diseases.[1,2] Both ChatGPT and Google Gemini are tools that have been studied extensively and are advancing forward to bridge the information and interpretation gap that was not possible previously.[3] However, the responses and results provided are still purely factual. Human qualities like empathy, multi-faceted thinking and judgment remain lacking in these models. Lack of standardization between countries and the ambiguity of AI generated answers attributable to the black box theory emphasize on the necessity of a physician’s opinion.[4] Many authors have argued that AI will not replace humans in healthcare.[5] Hence, we conceptualize the term human-machine interface (HMI), a system where the AI realizes that human intervention is required and redirects the data for such need. Though the efforts to build an efficient AI model continues, the race to build a robust HMI has just started and the first system to build such a model will be able to bridge the gap between the human mind and artificial technology fortuitously. This particular task is sufficiently easy in ophthalmology owing to its preexisting heavy reliance on machine tools for longitudinal imaging and diagnosis. IDx-DR2 and EyeArt AI are two such autonomous AI systems that are revolutionizing the screening and referral process for diabetic retinopathy in the current world.[6] Ophthalmology lies in the sweet spot between needing AI for screening and diagnosis but requiring the human touch for specialized examination and complex microsurgery.[7] Artificial intelligence will not be able to replace ophthalmologists in the future, but the ones who use AI are bound to replace those who don’t. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

TNOA Journal of Ophthalmic Science and ResearchVol. 62(4)
College of Medicine & Sagore Dutta Hospital (IN), Mandya Institute of Medical Sciences (IN)
Openalex Percentile: Top 59%
Retinal Imaging and Analysis
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