Artificial Intelligence is reshaping the fabric of modern healthcare. Yet, as its influence grows, ethical concerns come to the forefront, raising questions about fairness, privacy, accountability, and inclusivity. These challenges are particularly pronounced when addressing the diverse needs of countries and regions like India, the United States of America and Europe.
AI is revolutionising healthcare in extraordinary ways. In India, AI tools combat tuberculosis — a major public health issue — through initiatives like the Revised National TB Control Programme, which uses AI-powered chest X-ray analysis to assist doctors in rural areas lacking access to radiologists. In the US, systems like the Epic Sepsis Model predict and prevent life-threatening infections by analysing real-time patient data and alerting physicians hours before complications arise. Meanwhile, Europe’s Horizon Europe initiative funds AI-driven disease diagnosis and telemedicine research.
Personalised medicine represents another transformative frontier. AI platforms like IBM Watson Health and India’s Strand Life Sciences tailor treatments to individual patients based on genetic data, reducing healthcare costs and improving outcomes. In Europe, AI systems aid in diagnosing rare diseases, offering hope to patients who previously endured years-long diagnostic odysseys. Companies like Tempus in the US use AI to analyse clinical and molecular data for personalised cancer treatments.
AI is also solving challenges once deemed insurmountable. DeepMind’s AlphaFold, for instance, has unlocked the ability to predict protein structures, paving the way for groundbreaking drug discoveries and therapies. AI is also transforming microbiome research. European researchers are mapping gut-brain interactions to identify microbial imbalances linked to neuropsychiatric disorders.
But AI systems are only as unbiased as the data they learn from. In 2019, a US healthcare AI tool prioritised White patients over Black patients due to skewed training data. Similar risks arise in India; AI systems trained predominantly on Western genetic data may inaccurately predict drug responses for Indian populations.
Healthcare AI thrives on data, but ownership and control remain contentious. In India, digital literacy gaps leave patients unaware of data usage. Initiatives like the National Digital Health Mission aim to digitise health records but concerns about data breaches persist.
AI’s opacity poses significant ethical challenges. Black box systems, whose decision-making processes are inscrutable even to developers, undermine trust, especially in healthcare.
AI’s automation capabilities could displace jobs, particularly in developing nations like India. While roles like lab technicians may diminish, new opportunities would emerge in AI system maintenance and data annotation. India’s Skill India initiative aims to upskill workers for emerging industries; public-private partnerships can also help balance automation with job creation.
AI’s potential to revolutionise healthcare and biology is unparalleled, but ethical stewardship is crucial. Addressing bias, privacy, transparency, and economic displacement demands collaborative efforts across governments, industries, and academia. By prioritising inclusivity and sharing best practices, India, the US, and Europe can lead a global movement to harness AI’s power responsibly.
Aranyak Goswami is a Tenure Track Assistant Professor in Computational Biology at University of Arkansas. Biju Dharmapalan is the Dean-Academic Affairs at Garden City University and an adjunct faculty at the National Institute of Advanced Studies, Bengaluru
