The healthcare sector is under pressure from chronic diseases, an increase in patient demand, and limited resources. The amount of data in all healthcare settings has increased at the same period that the use of digital health technology is gradually growing. If AI is utilized effectively in the healthcare system, medical professionals may research the reasons behind illnesses and track the effectiveness of therapies and preventative measures.

Clinical entrepreneurs, computer scientists, and data scientists observe that artificial intelligence (AI), particularly machine intelligence or computer intelligence, will be essential to achieving success in the healthcare sector. Many research studies by professional researchers suggest AI can perform well or better than humans at key healthcare duties such as drug discovery, diagnosing diseases, targeted treatment, etc. AI is capable of automating some of the elements of healthcare. AI is a good dataset in the pharmaceutical industry or healthcare industry.

But as a French proverb rightly says, 'every rose has its horn', AI too has a lot of drawbacks. It is a more complex form of machine learning; it requires proper skills, training, and machinery, or AI tools, to perform the assigned work. In AI, the involvement of manual work is less; it is more automated work. Moreover, issues like data privacy, potential cybersecurity risks, medical malpractice, interoperability issues, etc. are a threat to the safety and security of mankind.

AI and medical diagnosis: Can AI help us to diagnose disease more accurately?

Needless to say, AI has been concentrating on treating and diagnosing illness since, about 1970s, when Stanford developed MYCIN to identify blood-borne diseases. AI assists healthcare in identifying and diagnosing diseases more accurately rather than older techniques.

AI is capable of examining a vast number of patient data, including graphic data, medical history, vital signs, bio-signals, and outcomes of laboratory tests. It can assist better to medical professionals in making better-informed options regarding patient care. Healthcare professionals can gain more detailed data about a patient's health and the underlying causes of their symptoms by assembling several data sources.

More accurate data on a patient's health can lower the possibility of mistakes in diagnosing, enhance diagnosis accuracy, and may faster the treatment process of the patient. Healthcare professionals can recognize possible health issues early, with the help of AI, before they become serious or potentially life-threatening.

AI and Medical Malpractice: Who is liable when AI goes wrong?

Although several theories by medical researchers pertain to the liability of the uses of AI, errors in AI are a major problem. Currently, there is no proper solution to this problem. As AI is invented by humans for the convenience of work, it is just a replacement for the human mind and is performed by computer intelligence.

However, it is always essential for humans to recheck the data which is provided by AI, as the healthcare field deals with the life of a patient. Sometimes due to a fault of the machine, it may result in major issues. It is observed that the legal handling of AI is based on the degree of autonomy of the program or software; if AI is just used to assist decisions, the radiologist who makes the final determination is liable for any culpability.

Or if the AI program functions as a subordinate of the radiologist, the doctrine of vicarious liability could be applied in such type of cases. A defect in the product or machine may lead to an error in the health report or health data. According to Mezrich, in such a case, a radiologist would be responsible for liability if he/she had a chance to review or recheck the report and determine the errors before releasing it to the patients.

AI and patient's privacy: How can we protect patient data in the age of AI?

In the landmark case 2017, the judgment of K.S. Puttaswamy V. Union of India, the Supreme Court bench held privacy as a fundamental right under Article 12 of the Constitution of India. As privacy is a very important facet of one's life, doctors must abide by the guidelines established by the Indian Medical Council Act, 2020 (IMC Act).

The act says that 'medical ethical standards, which include those outlined in the IMC act regarding patient's confidentiality and privacy, are mandatory and must be followed by doctors and other medical professionals. The Human Immunodeficiency Virus and Acquired Immune Deficiency Syndrome Prevention and Control Act, 2017 (HIV/AIDS Prevention Act) strives to safeguard the legal and human rights of those affected by HIV/AIDS.

Without the subject's informed consent, no medical procedure, HIV test, or any medical research will be carried out on him. No one may be forced to disclose their HIV status unless they have given their informed consent or order by any court of law. Many other policies about patient privacy protection that mandate patient confidentiality must be maintained.

AI in Drug Discovery and Development

As per research, the traditional method of the drug discovery process is notoriously time-consuming and the development of drugs takes about 7-10 years and also extravagant in costs than modern methods or AI-related tools for the discovery and development of drugs. Target discovery, validation, high throughput screening, animal studies, regulatory approval, and clinical trials are often used processes of traditional methods. Artificial Intelligence (AI) tools are the way to accelerate and reduce costs.

AI tools are transforming almost every stage of the drug discovery process, with significant potential to redesign the industry's speed, efficiency, and economy. AI has accelerated the process of identifying new pharma logical targets in the field of drug development and discovery. Vast datasets may be rapidly analyzed with the help of machine learning algorithms. Medical researchers and pharmaceutical industries will eventually conserve time and capital.

Conclusion
Since AI will be utilized more and more in the healthcare sector, it must be ethically accountable. AI judgments are systematic as the algorithms are involved for which it can take the fastest decision, compared to human judgments. But sometimes due to some technical error, it presents wrong data or wrongfully performs the assigned task. From the working of AI, it is quite pertinent that AI cannot completely replace humans, rather it will support mankind in providing better and more efficient treatment to the patients.

A major challenge for future governance of AI technologies is making sure that AI is created and deployed in a transparent, consistent with the public interest. AI technologies have a great ability to address significant health issues but might be limited by the quality of the health data or health report and by the fact that AI cannot emulate some human traits like compassion, kindness, sympathy, care, love, and many more.

References:

• https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3830536
• https://hbr.org/2018/03/how-ai-is-taking-the-scut-work-out-of-health-care
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955430/
• Justice K.S. Puttaswamy (Retd.) and Anr. V. Union of India, (2017) 10 SCC.
• https://wbconsumers.gov.in/writereaddata/ACT
• https://naco.gov.in/sites/default/files/HIV%20AIDS%20Act.pdf
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6552674/
• https://blog.petrieflom.law.harvard.edu/2023/03/20/how-artificial-intelligence-is-revolutionizing-drug-discovery/