13 September 2024 : The Hindu Editorial Analysis
1. Health care using AI is bold, but much caution first
(Source – The Hindu, International Edition – Page No. – 8)
| Topic: GS2 – Social Justice – Health |
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AI in Primary Health Care: Ambitious but Complex Undertaking
- Recent news suggests that India may have a free AI-powered primary-care physician available 24/7 for every citizen within the next five years.
- This raises significant questions about its feasibility, sustainability, and whether India is prepared for such a massive shift in its health care system.
Primary Health Care and AI Concerns
- Primary Health Care (PHC) ensures the highest attainable health levels by bringing integrated services closer to communities.
- PHC addresses not only health needs but also broader health determinants through multisectoral actions, empowering individuals to manage their health.
- Relying heavily on AI could undermine the personal and human-centered aspect of PHC by making patients passive recipients of care rather than active participants.
- While AI excels in automation, it lacks key characteristics of human intelligence, such as reasoning, planning, and emotional understanding — essential elements in medicine.
Limitations of AI in Medicine
- Human-Centric Approach: AI lacks empathy, cultural understanding, and the consciousness necessary for effective medical decision-making.
- Data Challenges: Health care data is often scattered, incomplete, and inaccessible for AI model training, complicating the development of accurate AI systems.
- Understanding Complex Conditions: Medicine requires more than pattern recognition; it requires context, moral reasoning, and awareness of the real-world environment, areas where AI falls short.
Naegele’s Rule and Health Care Data Challenges
- Naegele’s rule, a widely used method to predict birth dates, highlights challenges in health care AI development.
- This rule, based on outdated reproductive habits, has only 4% accuracy and ignores critical factors like maternal age, race, and nutrition.
- A better predictive model would require vast personal data, raising ethical concerns over privacy and the rightful ownership of health data.
- Establishing infrastructure for data collection, storage, and training AI models is costly, and continuous updates are necessary as health trends evolve.
The Complexity of Health Care Data in India
- India’s diversity adds complexity to the development of AI models, which require vast, contextualised data that accounts for personal and behavioural differences.
- Accessing and using this data raises further ethical concerns, especially regarding patient privacy and data ownership.
AI’s Role in Specific Health Care Tasks
- AI has potential in performing narrow, specialised tasks within health care:
- Narrow Intelligence: Focuses on tasks like managing hospital supply chains, biomedical waste, and drug procurement.
- Diffusion Models: Can analyse complex datasets to predict outcomes, such as screening histopathology slides.
- Large Language Models (LLMs) and Large Multimodal Models (LMMs):
- These emerging tools can aid medical education, simulate patient interactions, and support health-care professionals in research and training.
- They offer personalised learning experiences, simulating clinical scenarios to complement traditional education.
The “Black Box” Problem in AI Health Care
- AI’s decision-making processes are often opaque, known as the “black box” problem.
- In health care, this lack of transparency is dangerous, as understanding the rationale behind diagnoses or treatments is crucial.
- Trust Issues: Health-care providers may struggle to trust AI systems if the underlying reasoning is not clear, which could result in incorrect recommendations and potential harm.
Ethical and Practical Challenges in AI Development
- The use of AI in other domains, such as Google DeepMind’s victory in the GO game, can be celebrated, but in health care, mistakes can be life-threatening.
- The ethical implications of AI are highlighted by the case of Kenyan content moderators who petitioned against OpenAI’s ChatGPT due to exploitation.
- This raises concerns about exploiting vulnerable populations in AI training and the need to safeguard Indian patients’ data.
The Importance of AI Governance in India
- AI Governance: India lacks comprehensive AI regulations, unlike the European Union’s Artificial Intelligence Act.
- Without strict regulations, there is a risk of misuse or harm, making it critical to address AI development through the lens of medical ethics.
- Data Ownership: Population-level data is prone to ecological fallacies, and it is crucial to recognize that health data belongs to patients, not AI developers.
The Promise and Cost of AI in Health Care
- Efficiency and Accuracy: AI promises improved efficiency and reduced errors in health care, but implementing it requires substantial investments in research, infrastructure, and ongoing updates.
- Cost Concerns: Developing and maintaining AI systems involves high costs, raising questions about who will bear the financial burden.
- India’s Readiness: While AI could enhance health care delivery, India must first address foundational issues within its health system before jumping into AI-driven solutions.
Conclusion: A Measured Approach is Needed
- AI holds potential in certain areas of health care, but relying on it for primary care raises numerous challenges.
- India’s health-care system, with its complexities and diverse population, requires careful consideration of data quality, ethical implications, and patient care nuances before embracing AI at scale.
- A more measured and cautious approach is needed to ensure that AI complements human health care without undermining its core values.
| PYQ: Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of Al in healthcare? (150 words/10m) (UPSC CSE (M) GS-3 2023) |
| Practice Question: Discuss the potential benefits and challenges of integrating AI-powered primary health care in India. How can the ethical and data privacy concerns associated with AI in healthcare be addressed? (250 Words /15 marks) |
2. Is it time for India to introduce a Universal Basic Income?
(Source – The Hindu, International Edition – Page No. – 9)
| Topic: GS2 – Governance |
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Introduction to Universal Basic Income (UBI)
- Definition: UBI refers to a system where all citizens receive a fixed amount of money from the government, regardless of their income, employment status, or wealth.
- Global Relevance: UBI has gained traction globally due to concerns about jobless growth, automation, and rising inequality, particularly linked to technological advancements like Artificial Intelligence (AI).
Current Scenario in India
- Jobless Growth: India faces the challenge of jobless growth, where there is an increase in output and productivity, but employment generation remains stagnant. Automation and AI have contributed to this phenomenon, reducing demand for traditional labour.
- Youth Unemployment: A significant portion of the unemployed population in India consists of the youth, leading to increased demand for innovative social welfare policies.
Semi-UBI in India
- Existing Welfare Schemes: India already implements various forms of targeted basic income through cash transfer schemes for specific groups such as farmers, women, and the unemployed youth. These programs, while not universal, aim to support vulnerable populations.
- Social Safety Nets: These cash transfer programs can be seen as semi-UBI systems, providing a basic level of income support without being fully universal in scope.
Arguments in Favour of UBI
- Boosting Demand: A UBI could help stimulate demand in the market by providing people with a steady income, especially in times of unemployment. This, in turn, could help drive economic growth.
- Addressing Inequality: UBI may help bridge the income gap by offering financial security to those who do not have stable employment, especially in sectors affected by automation and AI-driven job losses.
- Supporting Vulnerable Groups: UBI would offer a safety net to the marginalised, ensuring that everyone has access to a basic level of income regardless of their employment status.
Challenges in Implementing UBI
- Financial Feasibility: Implementing a universal system like UBI in a country as large and diverse as India would require substantial financial resources. This could strain the government’s budget and require reallocation of resources from other welfare programs.
- Loss of Dignity and Alienation: Providing money without work could lead to social alienation, where individuals might feel a loss of dignity by receiving financial aid without contributing to the economy through employment.
- Income Distribution: A UBI might fail to address the issue of uneven income distribution if it is not accompanied by measures that promote job creation and equitable growth across sectors.
Need for Employment Generation
- Capital-Intensive Sectors: Current government investments focus on capital-intensive sectors like infrastructure, which do not generate significant employment. Projects in education, health, and rural development are more labour-intensive and need more funding to create jobs.
- Impact of Automation: With the rise of automation in sectors like banking, retail, and construction, fewer workers are needed, leading to job-loss growth. This creates a need for policies that focus on creating employment opportunities in labour-intensive industries.
Addressing the Skills Mismatch
- Education and Skill Development: There is a growing mismatch between the skills demanded by industries and the skills possessed by the labour force. Investing in education and vocational training can help bridge this gap, making the labour force more adaptable to changing technologies.
Alternatives to UBI
- Social Safety Nets: Some experts argue that instead of UBI, India should focus on improving and expanding existing social safety nets, such as healthcare, education, and employment guarantee schemes. These programs can be universalized and better funded to provide a comprehensive safety net.
- Tax Reforms: Raising more revenue through direct taxation, particularly from higher-income groups, can provide the necessary funds to implement social safety nets or a UBI-like program without overwhelming the government’s budget.
Conclusion
- While UBI is an attractive concept, India may not be fully prepared to implement a universal system at present.
- Strengthening and universalizing social safety nets, investing in employment-generating sectors, and addressing income inequality through targeted measures could be more feasible steps in the immediate future.
- UBI could be a part of India’s future policy framework, but its implementation must be carefully planned, considering the country’s economic realities and social structures.
| Practice Question: Evaluate the feasibility and potential impact of introducing Universal Basic Income (UBI) in India to address jobless growth and rising inequality. What are the key challenges and alternative strategies that should be considered? (150 Words /10 marks) |
