NOTE4STUDENTS:
The article explains AI’s impact, ethics, sustainability, and global governance efforts. UPSC often frames AI-related questions in a multidisciplinary way. In GS-3, it links AI with healthcare, economy, or sustainability. In GS-4, it focuses on ethical concerns like fairness, privacy, and decision-making. Recent trends show a shift towards AI governance and its role in public policy. Many students focus only on AI’s definition and applications but miss its real-world challenges. This article provides a global perspective on AI governance, linking international AI summits with India’s policy approach. This gives aspirants a ready framework to answer questions on AI’s ethical, economic, and governance aspects.
PYQ ANCHORING
GS 3: Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to the privacy of the individual in the use of AI in the healthcare? [2023]
GS 4: The application of Artificial Intelligence as a dependable source of input for administrative rational decision-making is a debatable issue. Critically examine the statement from the ethical point of view. [2024]
MICROTHEMES: ARTIFICIAL INTELLIGENCE, APPLIED ETHICS
France and India co-chaired the Artificial Intelligence Action Summit on 10-11 February 2025, bringing together global leaders to advance AI for public good. The summit built on key milestones from the Bletchley Park (November 2023) and Seoul (May 2024) summits. France welcomed India as the host of the next AI Summit.
Key Outcomes of the AI Action Summit (February 2025)
Outcome | Details |
Joint Statement on “Inclusive and Sustainable AI for People and the Planet” | Signed by 58 countries, including India, China, Brazil, France, Australia, and the European Commission. The U.S. and U.K. abstained. |
Public Interest AI Platform and Incubator | Aimed at bridging gaps between public and private AI initiatives and addressing digital divides. |
Founding Members | India, Kenya, Germany, Chile, Finland, Slovenia, France, Nigeria, Morocco. |
Objective | To create a trustworthy AI ecosystem by supporting technical projects in data, transparency, model development, talent, financing, and collaboration. |
Observatory on Energy, AI, and Data Centres | Led by the International Energy Agency (IEA), this will track AI’s energy consumption and sustainability applications. Report to be released in 2025. |
Coalition for Environmentally Sustainable AI | Focuses on integrating AI sustainability into global discussions, similar to AI security and ethics. Initiated by France, UNEP, and ITU. |
Green Digital Action Initiative | A new green computing initiative by ITU, featuring a Sustainable AI working group. |
Current AI | A $400 million fund launched by MacArthur Foundation with governments, tech firms, and philanthropists. Aims to raise $2.5 billion for transparent, fair, and ethical AI. |
AI for Labour | Establishes Observatories to track AI’s impact on workplaces, training, education, and productivity. |
Global Dialogue on AI Governance | A commitment to align AI governance efforts globally, preventing redundancy and ensuring collaboration through an Independent International Scientific Panel on AI. |
Inclusive and Sustainable AI for People and the Planet – Key Highlights
Aspect | Details |
Third Global AI Statement | Follows the Bletchley Declaration (UK, 2023) and Seoul Declaration (South Korea, 2024), both of which focused on AI risks and opportunities. |
Bletchley Declaration | Signed by 28 countries + EU, established a shared understanding of AI risks and safety. |
Seoul Declaration | Signed by 10 countries + EU, reinforced the need for responsible AI development. |
Key Priorities | |
Accessible AI | AI should be widely accessible, ensuring trust and safety in its deployment. |
Fostering Innovation | Encourages a competitive AI ecosystem that avoids market monopolization and supports industrial growth. |
Labour Safety | AI should positively impact jobs and labour markets, shaping the future of work responsibly. |
Human Rights-Based AI | AI must be ethical, human-centric, safe, and trustworthy, respecting human rights. |
Reducing Inequality | Calls for AI capacity-building in developing countries to bridge the global AI divide. |
Sustainable AI | AI systems—from data centres to training models—must run on sustainable energy. |
Energy Consumption Concern | In 2022, data centres consumed 1.65 billion gigajoules of electricity (about 2% of global demand, as per IEA). |
Concerns Regarding The AI Economy
Issue | Details |
AI’s Massive Energy Demand | AI is an energy-intensive sector. A single ChatGPT query consumes 2.9 watt-hours of electricity—10 times more than a Google search (0.3 watt-hours). |
Rising Carbon Footprint | Data center power demand is projected to increase by 160% by 2030, leading to a social cost of $125-140 billion in carbon emissions. |
AI’s Impact on Jobs | AI could disrupt entry-level jobs, raising concerns about economic displacement and widening social inequalities. |
Job Loss Risk | The International Labour Organisation (ILO) estimates that 75 million jobs worldwide are at high risk of being automated due to AI. |
Automation Inequality | AI benefits could be concentrated in a few developed nations, leaving labour-rich developing countries behind, worsening inequality. |
Bias in AI Models | AI systems can inherit societal biases from training data, leading to discriminatory decisions in hiring, policing, and lending. |
Diverging AI Governance Approaches | Europe: Focuses on regulation and investment. China: Expands AI access through state-backed tech giants. U.S.: Favors a deregulated, hands-off approach. |
Way Forward
- Energy-Efficient AI: AI systems should be designed to use less energy. This includes optimizing algorithms and integrating AI into smart power grids to improve electricity usage.
- AI-Friendly Job Market: Strong institutions should help workers shift to better-skilled jobs where AI supports their work rather than replacing them.
- AI Education & Training: AI should be part of school and college curriculums, and workers should have access to upskilling programs to stay relevant in an AI-driven world.
- Fair & Inclusive AI Models: AI systems should be open-source, inclusive, and free from biases, including language barriers, so that everyone benefits from them.
- Democratizing AI Infrastructure: The control of AI hardware, like Nvidia’s advanced AI chips, should not be limited to a few countries. A fairer distribution of AI resources is necessary for all economies to benefit.
#BACK2BASICS: SUSTAINABLE AI
Sustainable Artificial Intelligence (AI) refers to the development and deployment of AI systems that are environmentally friendly, ethically sound, and socially responsible. It encompasses practices that ensure AI technologies contribute positively to society while minimizing negative impacts.
Five Key Components of Sustainable AI:
- Energy Efficiency: Designing AI models and data centers to consume less energy, thereby reducing their carbon footprint. This involves optimizing algorithms and utilizing energy-efficient hardware. For instance, AI can be leveraged to monitor and predict climate and weather-change trends, aiding in environmental conservation efforts.
- Ethical Frameworks: Establishing guidelines that ensure AI systems operate transparently, fairly, and without bias. This includes implementing measures to prevent discriminatory outcomes and protect user privacy. Practicing sustainable AI involves integrating environmental, economic, and social considerations throughout the AI lifecycle.
- AI Governance: Developing policies and regulations that oversee AI development and deployment, ensuring accountability and alignment with societal values. This encompasses creating standards for AI applications and monitoring their adherence. India has launched several initiatives, including the India AI mission, to foster the development and adoption of AI, reflecting a commitment to balanced and ethical AI advancement.
- Social Responsibility: Ensuring AI technologies are accessible and beneficial to all societal segments, addressing issues like job displacement through reskilling programs and promoting inclusivity. The AI for India 2030 initiative aims to integrate AI across the nation’s socio-economic fabric, promoting inclusive growth and equitable access to AI benefits.
- Sustainable AI Corporate Responsibility: Encouraging organizations to adopt sustainable practices in AI development, such as reducing electronic waste and ensuring the ethical sourcing of materials. This also involves companies being transparent about their AI systems’ environmental and social impacts. Achieving sustainable AI involves enhancing energy efficiency, reducing carbon footprints, and promoting ethical practices.
India’s Preparedness for Sustainable AI:
India has demonstrated a proactive approach toward embracing sustainable AI through various initiatives:
- Policy Initiatives: The Indian government has introduced the AI for India 2030 initiative, aiming to integrate AI into various sectors for inclusive growth. This strategy emphasizes democratizing AI access, ensuring that its benefits reach all societal levels.
- Ethical Considerations: Recognizing the importance of responsible AI, India has been involved in global discussions to promote ethical AI development. Collaborations with international organizations like UNESCO reflect India’s commitment to adopting balanced AI approaches that align with societal values.
- Corporate Engagement: Indian businesses are increasingly investing in AI-driven sustainability initiatives. A significant percentage of Indian business leaders plan to enhance IT investments to achieve sustainability goals, leveraging AI as a powerful tool in this endeavor.
While these steps indicate substantial progress, continuous efforts are necessary to address challenges such as energy consumption, ethical governance, and equitable AI access. Ongoing collaboration between the government, industry stakeholders, and international partners will be crucial in advancing sustainable AI in India.