AI in Medical Microbiology—Why the Human Mind Still Reigns Supreme: A REPLY

Dear Editor, We came across an article recently published in your esteemed journal titled Role of Artificial Intelligence in Medical Microbiology.[1] We appreciate the efforts made by authors in acknowledging both the potential and limitations of artificial intelligence (AI) in this critical area. While AI may offer speed and assistance in processing huge number of data, the article itself rightly warns us that AI in microbiology is still not ready to replace human microbiologists, as microbiologists we could not agree more. The article, however, presents an imbalanced view by emphasizing the benefits without adequately addressing the potential downsides of AI. Thus, we would like to highlight the limitations and risks inherent to the AI based on clinical evidence. AI algorithms need vast representative sets of data to function accurately. However, in clinical microbiology, the environment is anything but predictable. We frequently deal with mixed infections, polymicrobial cultures, atypical presentations of diseases, rare pathogens, and emerging resistance pattern shifts on a day-to-day basis. These variations can even challenge a trained microbiologist, let alone machines that are trained on regular datasets. The article mentions applications like culture and gram stain interpretation using AI. Though we agree that these tools certainly reduce fatigue-related errors, they still lack contextual intelligence.[2] For example, an AI tool might interpret sputum culture based on colony morphology, but a microbiologist would still integrate patient history, immune status of the patient, and clinical symptoms in his diagnosis to correctly identify colonization versus infection. In real-world practice, unique cases are the norm, not the exception. AI, however, lacks the ability to identify outliers correctly or re-evaluate the decisions in case of an evolving clinical scenario. A contaminated blood culture which is flagged positive by AI could lead to the start of unnecessary antibiotics; this is something which an experienced microbiologist would catch instantly. Here, we list some peer-reviewed studies from various medical fields that supports our perspective [Table 1].Table 1: Various peer-reviewed studiesThese concrete evidences suggest that AI can not only influence the results of tests, which form the basis of further clinical treatment, but can also lead to inappropriate diagnosis, which puts unwanted financial and mental pressure on patients. In contrast, humans bring experience, reasoning, and intuition, something that a machine cannot acquire even with hundreds of datasets. The field of medical microbiology relies on interpretation, not just pattern recognition.[2] Human expertise and judgment remain irreplaceable in clinical microbiology. Critical and intuitive thinking by humans cannot be replicated by AI, at least not now. In conclusion, AI should help and complement microbiologists, not replace them. We would urge the scientific community to embrace AI, but with caution. Data availability statement No data was taken. Author contribution Savita Bhatia: Conceptualization and design; Shahzad Mirza: data acquisition/collection; Tejashree Nare: data collection;Preethy Edavaloth: writing and editing. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.