Inclusive Artificial intelligence for development

11 Apr Inclusive Artificial intelligence for development

This article covers “Daily Current Affairs” and the Topic of Inclusive  Artificial intelligence for development

SYLLABUS MAPPING:

GS-3-Science and technology- Inclusive Artificial intelligence for development 

FOR PRELIMS

What is Artificial Intelligence (AI)? How can AI be used to make farming, healthcare, and education better?

FOR MAINS

What is the Indian government doing for AI? How can AI help India become a better country?

Why in the News? 

Artificial Intelligence (AI) is reshaping economies and societies, offering significant potential to accelerate sustainable development. However, many developing countries face challenges in harnessing its benefits due to insufficient digital infrastructure, limited data access, and a lack of necessary skills. To bridge the gap with leading economies, developing countries should swiftly implement AI policies to overcome barriers to AI diffusion consistent with their development strategies and goals while addressing possible economic and social downsides of AI. The cross-border impacts of AI further highlight the need for global collaboration to make it accessible and beneficial for all, fostering inclusive innovation to tackle global challenges. As AI development is highly concentrated in a few countries and companies, stronger international cooperation is crucial to co-create inclusive governance mechanisms and to ensure AI will drive sustainable progress rather than deepening existing inequalities.

What is AI and its Types

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and make decisions. These machines can perform tasks that typically require human cognition, such as reasoning, problem-solving, perception, language understanding, and learning from experience. AI systems work using algorithms, vast data sets, and computational power to mimic intelligent behaviour, adapt to inputs, and improve over time.

Leveraging AI in Various fields

1. Healthcare: AI aids in early and accurate diagnosis through imaging analysis, supports drug discovery, enables robotic surgeries, and provides virtual health assistants for patient care.
2. Agriculture: Helps in precision farming, real-time crop and soil monitoring, pest detection, and yield forecasting, boosting productivity and sustainability.
3. Education: Enables personalized learning experiences, AI tutors, automated grading systems, and predictive analytics to improve student outcomes.
4. Finance: Enhances fraud detection, enables algorithmic trading, automates credit scoring, and provides smart financial advisory through AI-powered chatbots.
5. Manufacturing: Improves efficiency with predictive maintenance, AI-driven quality control, smart automation, and optimization of supply chains.
6. Transportation: Powers self-driving vehicles, enhances traffic management systems, streamlines smart logistics, and supports drone-based delivery.
7. Retail: AI enhances customer experience through behaviour analysis, manages inventory, offers virtual try-on tools, and enables dynamic pricing strategies.
8. Defense and Security: Assists in surveillance, autonomous drones, threat detection systems, and analysis of large-scale security data.
9. Environment: Supports climate modelling, disaster forecasting, pollution control, and wildlife monitoring for ecological conservation.
10. Governance: AI improves public service delivery through e-governance, decision-making support, citizen grievance redressal, and increased administrative efficiency.

Govt Policies, National and International 

National (India)
1. National Strategy for AI (NITI Aayog): Known as AIForAll, it focuses on inclusive growth in key areas: healthcare, agriculture, education, smart mobility, and smart cities.
2. National Programme on AI (MeitY): Implements AI in government services and builds AI computing infrastructure and R&D.
3. IndiaAI Mission (Upcoming): Proposed comprehensive mission with a focus on AI research, compute infrastructure, datasets, startups, and skilling.
4. Responsible AI for Youth: Initiative to train students in ethical AI use.
5. AI in Digital India: Integration of AI in e-governance, digital health, education portals, and public grievance systems.
6. Data Governance Framework: Under development to manage AI datasets, privacy, and responsible data sharing.
7. Centre for AI (CAIR, IITs, IIITs): Government supports academic institutions for research and innovation in AI.
8. AI-related PLI Schemes: Encourage electronics, chip-making, and AI hardware manufacturing.

International
1. OECD Principles on AI (2019): Focus on trustworthy, transparent, and human-centred AI.
2. UNESCO Recommendation on AI Ethics (2021): First global framework on AI ethics, ensuring rights, privacy, and fairness.
3. European Union AI Act (Ongoing): A risk-based regulation classifying AI systems and regulating high-risk AI.
4. USA – National AI Initiative Act (2020): Promotes AI leadership, R&D, education, and ethical standards.
5. China – Next Gen AI Development Plan (2017): Ambitious AI leadership goals by 2030 through massive state investment.
6. Global Partnership on AI (GPAI): India is a founding member and promotes responsible and inclusive AI globally.
7. G20 & BRICS AI Cooperation: Platforms to share best practices and regulate AI across borders.

Challenges in AI

1. Data Privacy and Security: AI systems rely on vast data, raising concerns over misuse, surveillance, and breaches of personal privacy.
2. Bias and Discrimination: AI can reflect or even amplify societal biases present in training data, leading to unfair decisions.
3. Lack of Explainability (Black Box Problem): Many AI models, especially deep learning, work in opaque ways, making it hard to understand or trust their decisions.
4. Job Displacement and Unemployment: Automation through AI threatens traditional jobs, particularly in routine or repetitive sectors.
5. Ethical and Legal Issues: Moral dilemmas arise in areas like autonomous weapons, predictive policing, and AI-based surveillance.
6. High Cost and Infrastructure Needs: Developing and deploying AI systems require advanced computing power and large-scale infrastructure.
7. Skilling and Talent Gap: Shortage of trained professionals in AI research, data science, and ethical AI governance.
8. Fragmented Regulation and Governance: Lack of a unified global or national AI regulatory framework hampers responsible innovation.
9. Misinformation and Deepfakes: AI tools can be misused to create fake images, videos, or content, threatening democratic processes.
10. Cybersecurity Risks: AI systems themselves can be vulnerable to adversarial attacks or used to create smart malware.

Global cooperation for inclusive and equitable AI