**10. The promise and challenges of AI in healthcare**

The AI in healthcare promises a bright future. The functions of AI can be summarised as relieving, splitting, replacing, and augmenting the role of healthcare personnel [56]. The AI helps streamlining of the work, front office management, the EHRs, human error prevention, administrative work, and provides the expert systems, decision making algorithms, and new insights. The contribution of AI in the diagnostic work especially the interpreting the images in radiology, retinopathy, pathology, and oncology is striking. Help in analysis and mining of large cohorts is a great boon to the epidemiologist. The speed and accuracy of the data processing and predictions are more efficient than humans. Stroke prediction and cardiovascular risk assessment are some of the newer algorithms available. Robotics processes automation are used in healthcare, for repetitive tasks like prior authorisation, updating patient records and billing [57–59].

The challenge of acceptance by the patients remains. The value of the databases used and updating is always problematic. The ownership of the data, portability and sharing across all data sets need clarity. The ethical and legal issues of responsibility and accountability for adverse outcomes of use or rejection of expert advice of AI need clearer understanding. Informed consent is another area when AI based expert systems are used or not used. How informed is informed consent? It is necessary to inform the patient if the clinician is basing his decision as per the recommendations of AI [60].

There are some problems in AI [61]. Unlike much of the research publications and recommendations, the AI data and inferences are not peer reviewed and blinded on evaluation. Who is responsible and accountable for the insights it provides—the developer, the tech company, the regulator, or the clinician? Can the emotional component of the doctor patient relationship be simulated? Who among the developer, the tech company, regulator, the doctor, or other stakeholders are accountable for any mishaps that happen when AI system recommendations are followed? The AI in healthcare has on one side systematised the various tasks and made available the information at the click of a button, does it with confidence dispense away the human supervision, assure safety and security? Not all human qualities are easy to digitise, and machines may not succeed in copying the sensitive and realistic relationship between the patient and the doctor. The quality AI depends on the quality data. One is aware of the old colloquial saying "garbage in and the garbage out".
