**14. Negative impact of AI**

The developers of AI are striving continuously to make the computers simulate the human brain and visualise a day, computers outperform humans. There are many areas where the AI claims success. Recent advances have shown successful attempts to enter the emotional domain of human brain. The elimination of human error and fatigue factor in repetitive tasks, decision making algorithms, speed of action, and precision are some of the advantages. Yet there are concerns of the negative impact of AI.

The foremost concern is the lack of trust. The user perceptions and reliability of AI are two issues that influence the trust. The computers act on the inputs and function as a rule-based machine. The AI/ML tools are built on the database and as algorithms. With the concept of patient centred health care delivery gaining importance, the explainability, validity and reliability of the AI decision support systems are of great concern. Situations unexpected or unusual, are often met in clinical practice. Does the database reflect the real-world situation and ethnic variations. The influence of bias in sample selection, variations in the disease patterns, false negatives and false positives influencing the clinical decisions is significant on what is essentially retrospective database that is used while training the AI/ML tools. How predictable is the AI when applied to a prospective situation? Does it cover adequately the drifts and data shifts possible in newer practices, populations, and lifestyles? The clinician is likely to ignore diagnostic challenges or alternatives when an easier option like decision support systems is available. The human bias in case selection contributing to the database may lead to erroneous insights [85–89].

The scare of loss of jobs when a computer takes over the human actions is a reality. Fatigue or distraction are common in humans performing repetitive tasks. The precision the computers achieve is well known. The scare one might be replaced by

a computer that outperforms a human is a fear in many. A Gallup poll held in USA revealed that the jobs lost are more than created. The AI proponents argue creation of new jobs will compensate the losses of human jobs to machines. The new jobs need new skills. Skill sets required, shortages in healthcare personnel will keep the AI in forefront in job creations, the proponents of AI claim. The AI developers have to strive hard to gain the trust of users and other stakeholders [89, 90]. Those concerned with healthcare, instead of mistrust in AI, should exercise their stakes in this technology. The medical professional shall see the database is well represented covering all variations and contribute to the development of AI. Data at the point of care contributing to the database is the primary responsibility of the healthcare personnel on which the AI/ML tools are built.
