By Vritika Chanjotra, and Amisha Singla, IIrd year B..A. LLB. (Hons.) students at RGNUL, Patiala.

Artificial Intelligence: A boon to healthcare

The healthcare sector has been driven by different societal factors, and in this never-ending cycle of innovation and expectations, there have been constant issues of managing the more complex patients in an inexpensive and systematic manner ensuring long-term care. Thus, it is observed that mechanization of the health facilities has the necessary aptitude to deal with the modern complicated healthcare problems and meet the need for quality healthcare. A report drawn by EIT health and McKinsey & Company, in order to analyze the impact of automation & AI, stated that, “the technological advancements are playing a markable role in the improvement of the healthcare sector of the economies in the areas of Chronic care, clinical decisions, diagnostics, etc.” The technological breakthroughs hold the capacity to assist the medical practitioners by keeping pace with the latest changes and fulfilling their need for assimilation & processing of heavy data which allows them to concentrate on the direct patient care and reduce the burnouts. AI is widely in use for the clinical trials saving a good amount of time and resources and also fulfilling the shortage of the medical personnel. In a nation like India where the country is facing a shortage of experienced medical practitioners and surgeons, AI has great scope for the transformation of the nation.

Several domains of healthcare such as radiation oncology, organ allocation, robotic surgery etc. have been revolutionized by AI, for example, the Food and Drug Administration (FDA) has approved a software for detecting diabetic retinopathy from diagnostic imagery. Thus, it can be said that the use of AI in healthcare has the potential to support the healthcare providers in many aspects of the patient care and administrative activities. Analyzing the improvements in the AI’s performance, an esteemed cardiologists and researcher Dr. Eric Topol once said that, “The smart integration of AI could help make healthcare more human, not less.”

The rapid expansion of AI has opened the doors for establishing an aggregated healthcare structure which is capable of generating predictive models for the automated diagnosis. AI is revolutionizing and strengthening the healthcare sector through the application of machine learning (ML) algorithms as well as other cognitive technologies. The ML assists the medical practitioners in making decisions and providing an accurate treatment plan for a specific patient based upon the patient’s data collected and processed by these intelligent devices. Therefore, AI has the ability to make healthcare more proactive by analyzing big data in a more effective and dynamic manner with an aim to pre-design a more preventive strategy for the patients’ wellbeing.

Furthermore, AI technology has been a boon for the pharmaceutical industries as the speedy discovery of process and identification of the components along with the ability to effortlessly store the big data information reduces the need for repeated work. IBM Watson is an ML-based system designed to identify the immuno-oncology treatments, whereas, Microsoft’s Hanover Project is another programme organised at Oregon in order to encourage the medical research to design patient-specific cancer treatment plan, and Google’s DeepMind is used for perceiving the health risks and medical data through the mobile application by the UK’s National Health Services. These are just a few examples from the long list of AI based programs and devices for better drug development in a quicker, economic and more operative manner.

Privacy concerns for AI

Despite numerous benefits, AI is prone to errors related to various impediments in its control and supervision by human medical practitioners. One of the main reasons for this problem is the wholly or partially opaque algorithms used by AI, which are incomprehensible by human observers, also known as the ‘black box’ problem. Besides, the patients’ data is not only stored by healthcare providers, but is also used for other health concerns, such as designing a treatment plan for similar symptoms and diseases. Over time, the patient data can be used in numerous ways by the AI, thus, the computers and servers storing and accessing the health data must be located to ensure that the data remains within the jurisdiction under which it is obtained and used within the limits to which the patient has consented. There have been numerous instances of abuse of patient health data by companies due to which trust issues have generated among the general public. This can escalate the scrutiny over use of public data as well as regulations and policies concerning data used by companies.

Additionally, a great portion of this technology is concentrated in the hands of large tech companies such as Google, IBM, Apple, Microsoft, etc. which can create a ‘power imbalance’. This can also be detrimental to the privacy protection of patient’s data, for example, Google owned DeepMind machine learning for managing kidney injuries was stigmatized for gathering the patient information on ‘inappropriate legal basis’ without informing the use and privacy impact of the data to the patients. Later on, Google took direct control over DeepMind and thus, the data jurisdiction shifted from the United Kingdom to the United States. Therefore, in implementing commercial healthcare, jurisdiction of ‘annexed’ mass data is also an important factor for consideration.

Legislative aspect of Privacy and data protection

It is the legal and ethical duty of medical practitioners to protect and maintain confidentiality of patient’s data, several regulations have been formulated both internationally and domestically for this purpose. At the global level, General Data Protection Regulation (GDPR) is regarded as the bible for the rules with respect to data processing and protection. Medical Data used by AI devices is classified as “special category data” under the GDPR, and considered as ‘sensitive personal data’ under the Data Protection Act, 1998. The GDPR grants the right to transparency to the subject, which ensures that the patient has the right to know the use of the data collected from them. Article 5 of the GDPR states that, “personal data shall be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes.” It also promotes the concept of “consenting” and provides The Right of Erasure or Right to be forgotten under Article 17 of GDPR. However, with respect to the AI-built devices, the transparency and scrutiny is an immense problem, as the AI devices are designed to work on their own with least human interference. Partial or complete automation of the devices in the healthcare system reduces the reliability and raises the concerns for accountability.

Currently, India does not have any legislation specifically governing data protection and the Information Technology (IT) Act and the Indian Contract Act, 1872 are used to deal with this issue, however, neither these provisions sufficiently meet with the continuously changing technological environment nor they solve the issues pertaining to processing of the sensitive personal data of the patients. These issues demand for a codified law on data protection, as, The Personal Data Protection Bill (PDP), 2019 seeks for the establishment of Data Protection Authority (DPA) for personal data protection. The bill is based upon the principles of transparency, Accuracy, reliability and accountability as laid down by the hon’ble SC in the K.S. Puttaswamy judgement. Despite all this, there are many gaps in the policies and regulations which need to be filled and the practical application of these principles must be ensured effectively. The political side of any matter is to be dealt with strictly in order to ensure timely enforcement of the legislations, as the heavy political interference and debate upon the governmental exemptions is seen as the main reason for pendency of PDP bill. 

In a nutshell, every sector is supposed to undergo changes and updates with the dynamic atmosphere, similarly, the healthcare sector also needs to ensure transformation in harmony with the present day requirements. However, in the absence of specialized legislation, the necessary measures should be taken to safeguard the privacy and health of the patients which includes, earliest enactment of the PDP bill in accordance to the latest needs and requirements. Furthermore, AI has already gained immense significance in various sectors of the economy, thus, there is an urgent need for AI specific laws to mitigate the possible dangers and privacy concerns attached to these technologies.  It is important that the legislations should be structured in a flexible manner to allow its coherence with the latest advancements. With respect to the healthcare sector, the principles conveyed in UDHR and GDPR should be regarded a base value for the development of Indian based laws, keeping in view it’s rationality in the Indian society and social structure. Also, the well-structured legislations might help the citizens to develop confidence in the AI technology and aided devices which will surely bring a boon to the economy and prove to be beneficial for the citizens.

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