Yojana Summary – February 2024 – Artificial Intelligence
Yojana Summary – February 2024 – Artificial Intelligence
Importance of February Edition – Artificial Intelligence:
- Yojana magazine provides in-depth analysis and insights on emerging technologies like Artificial Intelligence (AI).
- AI is a crucial topic for the UPSC exam as it intersects with multiple subjects such as Science and Technology, Governance, Economy, and Ethics.
- Yojana’s coverage of AI offers candidates a comprehensive understanding of its applications, challenges, and implications in diverse sectors like healthcare, agriculture, education, and governance.
- The magazine delves into the role of AI in India’s development narrative, including initiatives like the National AI Mission.
- UPSC aspirants can gain valuable perspectives from Yojana’s articles on AI’s ethical considerations, policy frameworks, and global trends, which are relevant for both prelims and mains exams.
- Reading Yojana enhances candidates’ analytical abilities, critical thinking, and knowledge base, which is crucial for answering UPSC questions effectively.
1. India’s Vision for Harnessing AI for Global Good
Introduction to AI:
- AI refers to computer systems capable of performing tasks traditionally done by humans, such as reasoning and problem-solving.
- Common examples include ChatGPT for generating text, Google Translate for language translation, Netflix for personalised recommendations, and Tesla for self-driving features.
2023 GPAI Ministerial Declaration:
- The 2023 GPAI Summit in New Delhi aimed to foster international cooperation on AI-related priorities.
- Prime Minister Modi emphasised India’s commitment to leveraging AI for welfare, ensuring Global South’s inclusion, and establishing a regulatory framework for safe and trusted AI.
India’s ‘Techade’ Vision:
- PM Modi envisions technology as a catalyst for making India the fastest-growing innovation economy globally.
- The digital economy is expected to contribute 20% to GDP by 2026, supported by the ‘IndiaAI’ mission focusing on AI startup ecosystem support and practical applications addressing real-world challenges.
IndiaAI and Skill Penetration:
- IndiaAI aims to develop practical applications in various sectors and create infrastructure for AI computation.
- Stanford University’s AI index report highlights India’s leadership in AI skill penetration, surpassing the United States.
India’s Datasets Programme:
- India’s rapid digitalisation has generated vast volumes of data, shaping one of the world’s most extensive and diverse dataset programmes.
- A robust policy and legal framework fortifies the datasets programme, providing a competitive edge for IndiaAI.
GPAI Summit 2023 New Delhi:
- Hosted under India’s Chairmanship, the summit solidified international recognition of AI’s impact.
- The summit focused on Inclusion, Collaborative AI, and Safe & Trusted AI, reflecting India’s commitment to inclusive technology and establishing rules for safe and trusted AI.
India’s Approach Towards AI:
- India advocates for clear platform guidelines, addressing bias and misuse during model training instead of regulating AI at specific stages.
- Existing IT rules provide a foundation for addressing challenges related to AI-powered misinformation, emphasising a comprehensive regulatory approach.
India’s Evolution and Aspirations:
- Over nine years, India has transitioned into a producer of technology and solutions, positioning itself as a trusted partner in shaping the future of technology.
- With aspirations to be among the Top 3 economies, India’s trajectory aligns with the principle of inclusion, marked by accessible DPI solutions benefiting countries worldwide.
2. AI in Indian Governance and Public Services
Introduction:
- AI has the potential to solve societal challenges in healthcare, education, and agriculture, elevate competitiveness, and contribute to economic growth.
- Recent advances in AI have enhanced its potential to transform governance, public service delivery, and citizen engagement.
India’s Strategic Position:
- India is strategically poised to employ AI to transform public service delivery, improve governance, and foster innovation.
- The National Programme on Artificial Intelligence (NPAI) comprises four key interventions to nurture the domestic AI ecosystem.
Key Interventions of NPAI:
- National Data Management Office (NDMO): Aims to enhance data quality, utilisation, and accessibility, modernising government practices to unlock the potential of data and the AI innovation ecosystem.
- National Centre on AI (NCAI): Envisaged as a sector-agnostic entity identifying AI solutions for public sector problem statements, driving large-scale socio-economic transformation.
- Skilling for AI: Seeks to revamp technical education infrastructure to equip the workforce with AI-ready skills and mitigate disruptions caused by accelerated AI adoption.
- Responsible AI: Aims to address potential biases and discrimination in AI adoption through indigenous tools, guidelines, frameworks, and suitable governance mechanisms.
Impact of AI Integration:
- Evidence-based decision-making facilitated by AI enables policymakers to access comprehensive data insights, leading to more targeted socio-economic benefits.
- AI integration in public service delivery enhances data analysis, automates tasks, and streamlines decision-making, fostering efficiency, innovation, and citizen engagement.
Government Initiatives Leveraging AI:
- UMANG (Unified Mobile Application for New-Age Governance): Provides access to 1836 government services, leveraging AI to offer a more inclusive solution through a voice-based chatbot.
- DigiYatra: A biometric-based boarding system for Indian airports, enhancing the air travel experience through seamless registration and boarding processes.
- Digital India Bhashini: Builds speech-to-speech machine translation systems for various Indian languages, leveraging AI for language identification, translation, and speech synthesis.
- AI in Urban Governance: AI and image recognition are used for near-real-time monitoring of traffic and infrastructure, facilitating timely intervention and maintenance.
- AI in Healthcare: Projects like ATMAN AI for Covid detection and AI-based models for tuberculosis and breast cancer detection showcase AI’s potential in healthcare.
- AI-Based Pest Management and Agriculture Solutions: Solutions like CottonAce for early pest warning and AI-based irrigation systems demonstrate AI’s impact on increasing crop yields and water conservation.
- AI-Based Attendance Monitoring (Shiksha Setu): Assam’s Shiksha Setu app uses AI-based facial recognition to record digital attendance, eliminating proxy attendance and reducing costs.
Way Forward:
- India adopts a multi-stakeholder approach to develop voluntary frameworks, policies, and legal mechanisms for safe and accessible AI deployment.
- Initiatives like the Digital Personal Data Protection Act aim to protect citizens’ privacy and enhance accountability.
- India’s commitment to promoting innovation while regulating AI misuse is demonstrated through its leadership in international forums like the GPAI.
3. India’s Tech Services Industry – Harnessing generative AI for scalable, secure and human-centric solutions
Generative AI Economic Value:
- According to a study by McKinsey, Generative AI is estimated to yield an annual economic value of USD 2.6 to USD 4.4 trillion worldwide.
- A significant portion of this value is expected to come from functions and industries central to India’s technology services industry.
Opportunities for Industry Growth:
- Expansion in the Addressable Market: Generative AI will drive substantial market expansion over the next five years, introducing new services and offerings aligned with evolving industry needs.
- Delivery Excellence: Service delivery processes are anticipated to become significantly more efficient by integrating Generative AI.
- Sales Excellence: Generative AI is set to streamline the entire sales lifecycle, from lead generation to sales strategy formulation.
- Productivity Gains: In internal enabling processes such as finance, legal, and HR, Generative AI holds the potential to automate time-consuming tasks.
India’s Distinct Position in the AI Landscape
- India leads in inclusive and secure digital transformation, prioritising economic growth and digital inclusion at all levels.
- Embracing the AI era, India focuses on opportunity and impact-oriented development, viewing AI as a tool for advancement while embedding safety and inclusivity in design principles.
Addressing AI Security and Ethical Concerns:
- As AI systems advance, ensuring their security and ethical use becomes paramount.
- The Indian tech industry invests in secure AI development, data protection, and ethical guidelines to safeguard against malicious attacks, ensure privacy, prevent bias, and maintain transparency and human control.
Human-Centric AI: A Core Focus:
- Thorough testing of algorithms for unintended consequences and biases before deployment is emphasised.
- Scrutinising data for implicit biases is crucial to prevent harm and distortion in outcomes.
- Regulation is considered a shared responsibility, with industry self-regulation emphasising transparency and accountability, which are as crucial as national and international regulatory frameworks.
Conclusion:
- Generative AI emerges as a transformative force in India’s tech sector, vital for GDP growth and job creation.
- Early adopters are poised to lead innovation and set global standards for ethical and practical Generative AI use.
4. Unlocking the potential and challenges of Generative AI
Overview of Generative AI and its Growth Potential:
- Generative AI, a subset of artificial intelligence, is gaining significant attention from governments, corporations, and businesses. Reports suggest that the market for Generative AI is expected to double every two years in the coming decade.
Understanding AI, Machine Learning, and Deep Learning:
- AI involves the creation of intelligent agents capable of reasoning, learning, and autonomous action to mimic human thought and behaviour.
- Machine learning, a subset of AI, trains models using available data to make accurate predictions for new or unfamiliar data.
- Deep learning, a type of machine learning, utilises artificial neural networks to process complex patterns inspired by the human brain.
Generative AI and Large Language Models (LLMs):
- Generative AI is a subset of deep learning, utilising artificial neural networks and supervised learning methods to process labelled data.
- Large Language Models (LLMs) like ChatGPT are trained on vast collections of web pages, books, and articles, enabling them to predict answers to various prompted questions.
Potential Impact Areas
- Writing: GenerativeAI is a helpful brainstorming companion and can assist in writing tasks such as press releases. Generative AI can generate detailed and insightful press releases tailored to specific events by providing event details.
- Reading: It excels in reading tasks, enabling quick identification of customer complaints in emails for companies like online shopping e-commerce platforms.
- Chatting: Special-purpose chatbots, including government chatbots, utilise Generative AI to provide information and assistance to citizens regarding schemes and policies.
Concerns about AI:
- Gender Bias: There are concerns that AI, such as LLMs, could amplify human biases as they are trained on internet text, reflecting both positive and negative human traits.
- Job Losses: Another primary concern is the potential for job displacement, as AI can perform tasks faster and cheaper than humans.
- Hallucinations and Misinformation: AI systems may sometimes produce inaccurate information confidently, inventing nonexistent references, sources, and deep fakes.
- Plagiarised Content: LLMs may output plagiarised content, raising concerns about originality and authenticity.
Responsible AI – Need Of The Time:
- Fairness: Ensuring that AI does not perpetuate or amplify gender biases in information.
- Transparency: Providing transparency in AI decision-making processes.
- Privacy: Protecting user data and ensuring confidentiality.
- Security: Safeguarding AI systems from malicious attacks.
- Ethical Use: Ensuring that AI is used only for beneficial purposes.
Initiatives for Responsible AI:
- NITI Aayog publishes discussion papers on ‘Responsible AI for All’, presenting a framework for implementing AI responsibly.
- A checklist incorporating fairness, transparency, privacy, security, and ethical use is suggested for brainstorming.
Conclusion:
- Generative AI holds the potential to provide intelligent guidance on addressing significant global challenges like climate change and pandemics. However, its responsible use contributes to longer, healthier, and more fulfilling lives worldwide.
5. Use Cases of Generative Artificial Intelligence in Governance
Overview of Generative AI
- Generative AI (GAI) is a subset of artificial intelligence capable of generating various data types, including audio, code, images, text, simulations, and videos, drawing inspiration from existing data while producing new and unexpected outputs.
- It operates on Large Language Models (LLMs), trained on extensive datasets, allowing for diverse content creation.
Generative AI Use Cases for Governments
- GAI presents numerous opportunities for governments, particularly in automating internal processes and enhancing stakeholder experiences through faster query resolutions.
- Platforms leveraging GAI could offer transparency in service request statuses, improving citizen engagement experiences.
- Analytical reporting facilitated by GAI enables decision-makers to gain real-time insights from vast document streams processed by government departments.
- GAI’s ability to generate high-quality visual outputs simplifies comprehension of complex data from multiple sources.
- Language automation through GAI enables personnel training and automates tasks like meeting notes and document abstracts, reducing time spent on documentation.
Examples From Other Parts Of The World
- Governments worldwide are integrating GAI into administrative systems to enhance efficiency and decision-making.
- Examples include the US FEMA employing AI for satellite imagery analysis to aid disaster response, Singapore’s Smart Nation initiative optimising traffic management, and Estonia piloting various AI-related initiatives such as job matching and traffic management solutions.
Challenges and Considerations in GAI Implementation
- The integrity and credibility of GAI outputs heavily rely on the quality of ingested data, and subjective prompts often yield unsatisfactory responses.
- GAI usage necessitates careful exposure of organisational data to prevent breaches of internal information assurance protocols and data privacy.
- GAI systems must address principles of FATE (Fairness, Accountability, Transparency, Ethics) to ensure responsible and ethical use.
- Governments must develop initiatives and guidelines to guide GAI application, considering aspects like data privacy and surveillance to counter illegal content and misinformation.
Implications for Practice and Policy
- Governments should train employees to use data and leverage GAI platforms for their work effectively.
- Capacity enhancement programs in areas like Data Science can help employees better adapt to evolving technologies.
- Collaboration with universities can facilitate skill development and ensure the effective utilisation of advanced AI tools.
Conclusion
- Generative AI and other AI tools hold significant potential in the digital transformation of governments and public sector undertakings.
- By leveraging GAI, governments can enhance decision-making processes, improve stakeholder engagement, and effectively address societal challenges.
- However, careful planning and adherence to ethical guidelines are essential to mitigate potential disruptions and ensure positive outcomes from GAI implementation.
6. Artificial Intelligence and Future of Media
AI in Modern Media
- Modern media, driven by AI algorithms, prioritises interactivity and visual appeal, offering personalised content delivery based on individual preferences and browsing history.
- While enhancing accessibility, this trend challenges traditional curation processes, raising concerns about information quality control.
Media’s Role in an AI-Driven Society
- In an era dominated by algorithms and AI technologies, traditional media faces challenges in remaining relevant amidst the information overflow.
- However, AI has empowered media houses with ML-based systems for fact-checking, cross-verification, and digital storytelling, surpassing human capabilities.
The Future of Journalism: AI-Powered News Production
- AI journalism utilises automation to swiftly generate news stories by analysing vast data volumes through pattern recognition and specific algorithms.
- Data, algorithms, and automated journalism will be pivotal in future news production, offering media houses efficient and rapid content dissemination.
- AI-enabled data labelling enhances news post reliability and retrievability, while automated storytelling and publishing revolutionise media content creation.
Concerns and Considerations
- AI tools, while facilitating content verification and fact-checking for media houses, are also used to spread misinformation.
- Despite advancements, AI models can still produce content that is out of context or inaccurate, posing challenges in maintaining journalistic integrity.
- Statistical Language Processing (SLP) faces limitations due to the dynamic nature of human expressions, leading to potential misinterpretations.
- Security and privacy concerns arise from the widespread use of pattern and facial recognition tools, with the emergence of deepfakes raising further challenges.
Conclusion
- The rise of synthetic media propelled by AI technologies like augmented reality signifies a new content creation and consumption era.
- While offering opportunities for producers and consumers alike, the proliferation of AI in media necessitates vigilance against potential risks and challenges.
7. Transformative Role of AI in Media
Impact of AI on Media
- In June 2023, Germany’s largest tabloid, Bild, announced layoffs of a third of its staff, with their functions set to be replaced by machines, signalling a significant shift in the media landscape.
- Mathias Doepfner, CEO of Axel Springer and the owner of Bild, suggested that AI could enhance independent journalism or replace it entirely.
Positive Transformation Enabled by AI
- AI-powered algorithms can process data at unmatched speeds, giving rise to Big Data Journalism, where journalists efficiently analyse large datasets to uncover compelling stories.
- Journalists now rely on AI for tasks like audience analysis, content discovery, and improving SEO rankings, highlighting its crucial role in modern media organisations.
- Advanced large language models have become integral to content creation, automating tasks such as document analysis, translations, social media content creation, and automated writing across various topics.
Human Uniqueness in Media Amid AI Advancements
- Despite AI’s increasing presence, media organisations remain cautious about complete machine dominance, recognising the uniqueness of human qualities essential for journalism.
- Human-centric qualities like emotions, adaptability, branding, ethics, and ground-level reporting distinguish human journalists from AI algorithms.
- AI’s limitations in decision-making are based on context, potential ethical concerns like bias propagation, and environmental consequences of energy-intensive algorithms, which further emphasise the importance of human involvement in media.
Conclusion
- The human factor remains indispensable in media, given the faith democracies place in the fourth pillar of democracy.
- While AI streamlines back-office tasks in media organisations, human qualities like emotions, adaptability, branding, ethics, and ground-level reporting set human journalists apart and ensure journalism’s integrity.
8. Role and Scope of AI for Citizen Services
Introduction
- AI integration with Aadhaar-enabled services enhances efficiency and security while protecting individuals’ identity privacy.
- DigiLocker benefits from AI integration, fostering a digital, paperless ecosystem by improving document management.
- Government mobile apps incorporating AI create intelligent, citizen-centric platforms, enhancing processes, service delivery, and communication.
AI in Public Safety and Security
- AI is utilised in public safety initiatives such as predictive monitoring, optimising emergency responses, managing disasters, video surveillance, and detecting threats.
- Facial recognition and video analytics, among other AI technologies, enhance public safety and security measures.
AI in Healthcare Services
- AI plays a significant role in citizens’ healthcare services, from diagnostic tools to personalised health recommendations.
- Remote monitoring and telehealth services supported by AI improve healthcare accessibility.
- AI analyses medical imaging data like X-rays, MRIs, and CT scans, aiding diagnosis and treatment planning.
- It contributes to drug discovery by analysing vast datasets to identify potential candidates.
- Virtual health assistants and chatbots offer instant support and medical information.
- Remote patient monitoring facilitated by AI enhances healthcare accessibility, especially in rural areas.
- Robotic-assisted surgery benefits from AI algorithms, ensuring precision in procedures.
AI in Financial Inclusion
- AI is employed in the financial sector to promote inclusion and accessibility through mobile banking, digital payments, and AI-driven credit scoring.
- Machine learning algorithms analyse alternative data sources to assess creditworthiness, enhancing security in financial transactions.
AI in Smart Agriculture
- AI innovations enhance crop yield, sustainability, and efficiency in farming practices.
- Agricultural data analysis provides real-time insights on weather patterns, crop health, and best practices.
- Technologies like sensors, drones, and satellite imagery enable precision farming.
- AI predicts crop yields, pest outbreaks, and optimal planting times, improving farming outcomes.
AI in Education and Skill Development
- AI transforms learning and skill development by providing personalised experiences and enhancing engagement through gamification.
- Smart classrooms with AI-powered tools like interactive whiteboards, VR, and AR enrich the learning environment.
AI in Smart City Development
- AI contributes to urban planning for sustainable development, optimising waste management, energy consumption, and infrastructure usage.
- The Smart Cities Mission integrates AI and IoT technologies to enhance urban living standards.
AI in Tourism
- AI algorithms assist users in trip planning by suggesting optimal itineraries and adjusting plans based on real-time factors like weather.
- Integrating AI into the tourism industry enhances operational efficiency and provides personalised experiences for travellers.
AI in Power Management
- AI improves efficiency, reliability, and sustainability in the energy sector by accurately predicting future energy demand and optimising consumption.
- Utilities leverage AI to create responsive and sustainable energy systems.
AI in Logistic Management
- AI optimises delivery routes, reduces transit times and costs, and enhances decision-making in the supply chain through data analysis.
- It supports air traffic management, automated train operations, and smart toll collection systems.
AI in Automation of Routine Tasks
- AI automates repetitive tasks in citizen services, leading to faster response times and increased efficiency.
AI in Customer Service and Interaction
- AI-based chatbots and virtual assistants improve citizen interaction by providing prompt responses and operating 24/7.
AI in Personalized Services
- AI enhances user experience by delivering personalised recommendations and notifications to citizens.
Conclusion
- While AI offers numerous benefits in various sectors, addressing privacy, bias, and ethics concerns is essential to ensure responsible implementation in citizen services.
9. Artificial Intelligence and ease of life for visually challenged
Introduction:
- Approximately 250 million individuals worldwide grapple with visual impairment, facing challenges in attaining a satisfactory quality of life or achieving independence.
Detection of Impairment:
- AI assistive technology facilitates early detection of visual impairment, enabling timely intervention and rehabilitation.
- Through regular examinations, AI can locate blindness in infants, allowing for prompt management from an early stage.
Education:
- AI-driven learning platforms offer interactive and customisable experiences, addressing individual learning needs and promoting inclusivity.
- The Beijing Consensus provides policymakers with guidelines for leveraging AI in education.
- Virtual assistants like Siri, Alexa, and chatbots contribute to transforming the learning ecosystem by providing accessible learning tools.
AI and Social Life:
- Envision, a socially committed developer, has designed AI-enabled spectacles for blind or low-vision individuals, recognising familiar faces and providing descriptions of strangers.
- Digital magnifiers assist those with low vision in reading printed materials, enhancing their social competence.
AI and Governance:
- Unique Disability Identity cards in India, supported by AI, can reshape governance by facilitating automated verification for accessing public utility platforms.
- AI can enhance accessibility in public spaces by providing tailored assistance through AI cameras, as seen in initiatives like Indian metro rail services offering clear audio communications for the visually impaired.
AI and Accessibility:
- States are responsible for providing accessible environments for individuals with mobility challenges, including visually impaired individuals, in public buildings, transportation, and educational centres.
- AI can improve security measures in these areas, with AI cameras offering tailored assistance for the visually impaired.
Conclusion:
- AI holds immense potential to positively impact the lives of marginalised individuals, including those with disabilities, from pregnancy to rehabilitation.
- Breakthroughs like AI detecting diabetic retinopathy show promise in enhancing healthcare monitoring.
- Enhanced healthcare monitoring, governance, and affordable AI devices improve the well-being of visually impaired individuals.
- AI-enabled gadgets promote inclusivity in digital governance by offering mode selection options with intelligent audio cues.
10. Cyber Security Challenges in the Era of AI
India’s Evolving Digital Landscape
- India’s internet user base exceeds 800 million, with the government actively promoting digital initiatives like Aadhaar and Digital India.
- However, this growth attracts malicious actors, with over 1 billion cyberattacks witnessed in 2023.
AI-Powered Threats
- AI can automate threat detection, analyse data for anomalies, and predict future attacks.
- Yet, attackers can manipulate AI tools for sophisticated cyberattacks and deepfake creation.
Unique Challenges for India
- Large Digital Divide: Significant portions lack digital literacy, making them vulnerable.
- Fragmented Cybersecurity Infrastructure: Responsibility is distributed, leading to coordination issues.
- Data Privacy Concerns: These concerns are primarily concerned with digital payments.
- Skill Shortage: India needs more qualified cybersecurity professionals.
Addressing the Challenges
- Building a Robust Cybersecurity Ecosystem: Strengthening agencies like CERT-In and promoting public-private partnerships.
- Investing in AI-Powered Solutions: Crucial for proactive threat management.
- Promoting Digital Literacy: Essential for creating a resilient digital society.
- Developing a Strong Legal Framework: Deter cybercrimes and ensure data privacy.
- Investing in Cybersecurity Training: Addressing skill shortages through training programs.
A Call to Action
- Collaboration between government, private sector, academia, and civil society is crucial.
- Ethical considerations like transparency and human oversight are necessary to prevent misuse.
- International cooperation is essential for combating cyber threats through information sharing.
- India can create a secure digital future by addressing vulnerabilities and leveraging AI opportunities.
Additional Considerations
- Ethical Implications: Transparency, accountability, and human oversight are crucial.
- International Cooperation: Sharing information and expertise strengthens global cybersecurity.
- Continuous Research and Development: Necessary to stay ahead of evolving cyber threats.
Conclusion
- Cybersecurity in the era of AI presents complex challenges, but proactive measures can ensure a secure digital future for India and contribute to global cybersecurity efforts.
11. PM-JANMAN: Empowering Tribals
Pradhan Mantri Janjati Adivasi Nyaya Maha Abhiyan (PM-JANMAN)
- PM-JANMAN aims to achieve Antyodaya’s vision by empowering the most marginalised individuals in society.
Objectives
- The initiative focuses on the socio-economic welfare of Particularly Vulnerable Tribal Groups (PVTGs).
- Its primary goal is to enhance the socio-economic conditions of PVTGs by providing essential facilities such as safe housing, clean water, education, healthcare, electricity, and livelihood opportunities.
Key Interventions
- PM-JANMAN encompasses 11 key interventions spread across 9 Ministries.
- These interventions are designed to improve the well-being of PVTG households and settlements.
Scope and Coverage
- There are 75 PVTGs located across 18 States & Union Territories.
- These groups reside in 22,544 villages spread across 220 districts.
- The total population of PVTGs is estimated to be around 28 lakhs.
Impact
- PM-JANMAN has the potential to significantly uplift the living standards of PVTGs by addressing their basic needs and providing opportunities for socio-economic development.
Conclusion
- Through PM-JANMAN, the government aims to ensure that the most vulnerable tribal communities receive the necessary support and resources to improve their quality of life and achieve socio-economic empowerment.