10 Feb “Governing AI: A Crucial Imperative for the Future”
This article covers “Daily Current Affairs,” and the topic details related to “Governing AI: A Crucial Imperative for the Future”
Syllabus mapping:
GS-2: International Relations: global concerns, affecting India’s interest.
For Prelims:
What is AI, types of AI? What are the international laws regulating AI? What is Global Partnership on Artificial Intelligence (GPAI)?
For mains:
Applications of AI in various fields and the need to regulate AI at the global level.
Why in the news?
The Paris AI Action Summit 2025 will be a pivotal event in shaping global AI policies, governance, and innovation. Led by India and France, the summit will gather world leaders, tech giants, and policymakers to discuss key issues like privacy, ethics, AI governance, and economic impact. The focus areas include AI regulation, data security, economic growth, and global collaboration, aiming to establish responsible AI frameworks, safeguard user data, and drive AI-driven innovation across industries.
Definition of AI:
Artificial Intelligence (AI) refers to the ability of machines or computer systems to simulate human intelligence by performing tasks such as learning, reasoning, problem-solving, and decision-making. It enables machines to analyze data, recognize patterns, and make predictions with minimal human intervention.
Global AI Laws, Agreements, and Cooperation Treaties
| Name | Enacted By / Organization | Mandate |
|---|---|---|
| EU AI Act (2024) | European Union (EU) | Regulates AI systems based on risk levels, with strict rules for high-risk applications. |
| U.S. Executive Order on AI (2023) | U.S. Government | Ensures AI safety, security, transparency, and promotes AI-driven innovation. |
| China’s AI Regulations | Chinese Government | Imposes restrictions on generative AI, deepfakes, and ethical AI development. |
| India’s AI Framework | Government of India | Focuses on responsible AI use, data protection, and AI-driven economic growth. |
| G7 Hiroshima AI Process (2023) | G7 Nations | Establishes voluntary AI governance standards among G7 member countries. |
| Global Partnership on AI (GPAI) | OECD & Partner Countries | Promotes human-centric AI policies, research, and ethical AI deployment. |
| OECD AI Principles | Organization for Economic Cooperation and Development (OECD) | Provides guidelines for trustworthy and ethical AI. |
| UNESCO AI Ethics Framework | United Nations (UNESCO) | Sets global ethical standards for AI to ensure fairness, inclusivity, and human rights protection. |
| EU-U.S. AI Collaboration | European Union & United States | Aligns AI governance frameworks, enhances AI safety, and promotes innovation. |
| India-France AI Cooperation | Governments of India & France | Strengthens AI research, innovation, and regulatory policy alignment. |
| China-EU AI Dialogue | European Union & China | Focuses on AI safety, trade regulations, and cross-border AI policies. |
| AI in BRICS Nations | Brazil, Russia, India, China, South Africa (BRICS) | Develops common AI standards and promotes AI cooperation among BRICS members. |
Applications of AI in Various Fields
| Field | Application | Example (Global & India) | Data/Impact |
|---|---|---|---|
| Healthcare | Improved Diagnostics – AI analyzes medical images (X-rays, MRIs) with higher accuracy. | Global: PathAI aids in cancer diagnosis. India: Niramai uses AI for early breast cancer detection. | A study in JAMA found AI detecting diabetic retinopathy with accuracy similar to ophthalmologists. |
| Drug Discovery – AI accelerates drug discovery by analyzing large datasets. | Global: Atomwise predicts drug effectiveness. India: Bengaluru-based Innoplexus uses AI for faster drug research. | AI can reduce drug development time and cost significantly. | |
| Transportation | Autonomous Vehicles – AI-powered self-driving cars enhance road safety. | Global: Waymo tests self-driving cars. India: Tata Elxsi works on AI for autonomous driving. | NHTSA reports 94% of accidents are due to human error, AI can reduce this. |
| Traffic Optimization – AI analyzes real-time traffic data to optimize flow. | Global: Google Maps provides real-time updates. India: Bengaluru Traffic Police uses AI-powered Adaptive Traffic Signals. | AI can cut travel time by up to 25%. | |
| Retail | Personalized Recommendations – AI suggests products based on customer behavior. | Global: Amazon uses AI for personalized recommendations. India: Flipkart’s AI models enhance product recommendations. | McKinsey reports AI-driven personalization can increase sales by 20%. |
| Inventory Management – AI predicts demand to optimize stock levels. | Global: Walmart optimizes inventory with AI. India: Reliance Retail uses AI for supply chain efficiency. | AI can reduce waste and stockouts, improving customer satisfaction. | |
| Finance | Fraud Detection – AI identifies suspicious financial transactions. | Global: Banks use AI to flag fraudulent activities. India: ICICI Bank deploys AI for real-time fraud detection. | AI-powered fraud detection can reduce losses by 70%. |
| Risk Management – AI assesses risks by analyzing financial data. | Global: Insurance firms use AI for risk profiling. India: SBI Life uses AI for customer risk assessment. | AI improves loan approval accuracy and reduces financial risks. | |
| Manufacturing | Predictive Maintenance – AI detects potential failures in machinery. | Global: General Electric uses AI for jet engine maintenance. India: Tata Steel employs AI for equipment health monitoring. | Predictive maintenance can reduce downtime by 50% and extend equipment lifespan by 40%. |
| Quality Control – AI-powered vision systems detect product defects. | Global: AI inspects manufactured goods for quality. India: Maruti Suzuki uses AI for vehicle quality checks. | AI enhances product reliability and reduces manufacturing waste. | |
| Education | Personalized Learning – AI adapts content to students’ learning pace. | Global: Khan Academy uses AI for math tutoring. India: Byju’s AI-based platform tailors lessons for students. | AI-driven education tools improve student engagement and performance. |
| Automated Grading – AI evaluates assignments, saving teachers time. | Global: AI grades online tests automatically. India: CBSE is exploring AI for exam evaluation. | AI can reduce grading workload by over 40%. | |
| Customer Service | Chatbots – AI-powered virtual assistants provide instant support. | Global: Many companies use AI chatbots. India: HDFC Bank’s EVA chatbot answers customer queries. | AI chatbots cut customer service costs by 30%. |
| Personalized Recommendations – AI suggests relevant content/products. | Global: Netflix recommends shows using AI. India: Hotstar uses AI to recommend content. | AI-driven recommendations enhance user experience and engagement. | |
| Agriculture | Precision Farming – AI optimizes crop yields using sensors and drones. | Global: AI drones monitor farmland. India: Agri-tech startup CropIn helps farmers with AI-based solutions. | AI increases crop yields while reducing water and pesticide use. |
| Autonomous Tractors – AI automates farming tasks for efficiency. | Global: John Deere develops self-driving tractors. India: Mahindra & Mahindra is working on AI-powered agricultural machinery. | AI lowers labor costs and boosts productivity. |
Key Issues Concerning AI Regulation and Use
Defining AI: There is no universally agreed-upon definition, making regulation inconsistent. An OECD 2023 survey found that policymakers struggle to define AI, affecting global policy alignment.
Balancing Innovation and Regulation: Overregulation can slow AI advancements in critical sectors like healthcare. EU AI Act could delay life-saving AI medical tools.
Bias and Discrimination: AI models can reinforce societal biases, leading to unfair outcomes. Amazon’s AI hiring tool discriminated against women due to biased training data.
Transparency and Explainability: Many AI decisions lack clear explanations, making accountability difficult. AI-driven loan rejections without justification raise fairness concerns.
Accountability and Liability: Unclear legal responsibility when AI systems fail or cause harm. Who is liable when a self-driving car causes an accident—the manufacturer, software developer, or owner?
Safety and Security Risks: AI vulnerabilities can lead to failures or cyberattacks. Example: Tesla’s Autopilot failed to detect an obstacle, causing a crash.
Data Privacy Concerns: AI systems collect and process vast amounts of personal data, raising privacy risks. AI-powered surveillance tools often lack proper safeguards for biometric data.
Global Cooperation Challenges: Differing AI regulations create fragmentation, making compliance complex. For example, the EU enforces a risk-based AI approach, while the US prefers sector-specific regulations.
Public Perception and Misinformation: Fear, distrust, and AI-generated misinformation can erode public confidence. Example: Deepfakes spread misinformation, impacting elections and public discourse.
Course of Action for Regulating AI and Ensuring Sustainable AI Development
Establish Strong Ethical AI Principles: AI must prioritise human rights, fairness, and transparency to ensure ethical use. For example, the EU’s GDPR enforces strict AI data privacy laws, protecting individuals from misuse.
Implement Robust Safety and Security Standards: AI systems should be safe, reliable, and resistant to cyber threats. Microsoft’s AI-driven cybersecurity tools detect and prevent cyberattacks in real-time.
Create Clear and Adaptive AI Regulations: Governments must develop flexible laws that evolve with AI advancements. Example: India’s NITI Aayog AI framework promotes responsible AI use in healthcare and agriculture.
Ensure AI Transparency and Explainability: AI models should be interpretable and accountable for their decisions. Example: Google’s Explainable AI tools help industries understand AI-driven decisions.
Encourage International Cooperation and AI Governance: Global partnerships can harmonise AI regulations and prevent misuse. For example, the Global Partnership on AI (GPAI) unites nations to ensure ethical AI development.
Invest in AI Education and Workforce Training: AI literacy programs must prepare individuals for AI-driven economies. Example: Google’s AI for Everyone initiative trains professionals on ethical AI practices.
Promote AI for Sustainable Development: AI should address global challenges like climate change, agriculture, and healthcare. AI-driven precision farming in India optimises water use and boosts crop yields.
Establish Independent AI Oversight and Accountability Mechanisms: Regulatory bodies must monitor AI use, enforce laws, and address violations. For example, the EU AI Act proposes an independent authority to oversee AI safety and ethics.
Conclusion:
The Paris AI Action Summit 2025 is a pivotal step toward global AI governance. Led by India and France, it highlights the need for collaboration on ethics, regulation, and innovation. Constructive global action is crucial for establishing transparent policies and fostering sustainable advancements to ensure AI’s responsible and inclusive growth.
Prelims Question:
Q. With reference to the Global Partnership on Artificial Intelligence (GPAI), Consider the following statement:
1. Global Partnership on Artificial Intelligence is an Intergovernmental cooperation set up by the G20 group.
2. India is the founding member of the Global Partnership on Artificial Intelligence (GPAI)
3. GPAI is hosted by the Organization of the Petroleum Exporting Countries (OPEC).
How many of the above-given statements are correct?
A. Only one
B. Only two
C. All three
D. None
ANSWER: A
Mains question:
The regulation of Artificial Intelligence is not just the need of the hour but a raison d’être (fundamental necessity). Comment.
(Answer in 150 words)
No Comments