Today's Editorial

Today's Editorial - 10 March 2024

The art and craft of deploying AI responsibly

Relevance: GS Paper III

Why in News?

The Ministry of Electronics and Information Technology (MeitY) recently issued an advisory to the Artificial Intelligence industry. 

Broader picture:

  • The recent advisory came amid controversial responses from Google’s Gemini chatbot about the Indian Prime Minister. More concerning was the platform's well-moderated responses to similar queries about other global leaders.
    • The advisory points to a growing concern over the unchecked proliferation of AI technologies.
  • The advisory caused a lot of concern in technology circles.
    • However, the minister later clarified that the advisory is aimed at significant platforms, and permission seeking from Meity is only for large platforms and will not apply to startups.
  • The incident points to the broader, global challenge of ensuring that AI operates within ethical and legal constraints while continuing to innovate and that the government’s approach must be strategic rather than reactionary.

Understanding AI models:

  • AI models today digest vast amounts of information, combining it into what experts call “latent spaces.”
    • Latent spaces are the engine rooms of AI, thriving on impreciseness and flexibility.
  • Understanding that AI models are not designed to function like traditional look-up databases is essential.
  • Expecting them to deliver precise answers or politically correct opinions without specific guidelines is a misunderstanding of their capabilities.
  • To address these challenges, many AI companies have instituted guardrails.
    • These mechanisms work outside the core AI system, ensuring that the output is generally safe for work by not providing certain opinions or accepting specific queries.

Case study -

European Union:

  • The European Union has responded to similar challenges by introducing the AI Act, the first comprehensive AI law globally.
  • It focuses on high-risk AI applications, particularly in sectors like education, healthcare, and policing, and mandates new standards for these applications.
    • For example, specific uses of AI, like creating facial recognition databases or using emotion recognition technology in workplaces or schools, are banned.
  • This act calls for greater transparency in AI model development and holds organisations accountable for any harm resulting from high-risk AI systems.


  • The Copyright Act of Japan allows the use of copyrighted works for information analysis without permission from creators, provided the service is limited to the minimum necessary and does not unreasonably harm creators’ interests.
  • Yet, unresolved issues remain regarding the scope of these exceptions and the definition of “unreasonable harm,” especially in AI.
    • Japan is navigating its course in this domain.


  • AI transparency has become a focal point in the United States, with states like Pennsylvania introducing legislation to ensure transparency in using AI algorithms in insurance claim processing.
  • Furthermore, the US is witnessing significant legal activities, such as class action lawsuits against major insurers, over the use of AI algorithms.
  • The administration has also taken steps through an Executive Order to outline actions ensuring AI’s safe, secure, and trustworthy development across various sectors.

Way forward:

  • Flexibility in regulation and innovation:
    • For policymakers in India and beyond, the task is to create an environment where AI can thrive without compromising ethical standards or societal values.
    • A strategic, responsible approach to AI is needed. This includes developing mechanisms for accountability, flexible regulations, public awareness initiatives, addressing legal and ethical concerns, and maintaining a balance between innovation and regulation.
  • Government regulation and frameworks:
    • The Government of India is working to create a comprehensive global regulatory framework for AI with a pro-growth, pro-jobs, and pro-safety stance.
    • This framework is expected to be released in the June-July timeframe.
  • Long-term impact assessment:
    • Companies at the forefront of AI deployment must address the immediate concerns and anticipate the long-term impact of their AI platforms on society.
    • They must implement robust guardrails to ensure the output is safe for work, culturally sensitive, and politically neutral.
  • Corporate Responsibility:
    • Responsible deployment of AI is as much an art as a business necessity.
    • Businesses should push the envelope of innovation while also taking the lead in ethical considerations, especially now that the full impact of AI has yet to be adequately grasped.
  • Public awareness and education:
    • It is also critical for users to have at least a high-level understanding of AI’s capabilities and, more importantly, its limitations.


The recent incident highlights a critical junction in AI governance. India’s stance on AI development will have profound implications as a nation fuelling digital innovation with its talent pool.

Beyond Editorial:

Strategic positioning of India in AI:

  • India has formulated a distinctive approach to digital transformation through the 'Digital India' programme, prioritising inclusivity and accessibility through projects like Aadhaar, UPI, and Digilocker.
    • A recent industry report suggests that Generative Al (GenAl) could contribute up to 1.5 trillion dollars to India's GDP by 2030.
    • The Stanford AI Index 2023 ranks India as the foremost country in AI skill penetration.
  • India's burgeoning AI landscape is exemplified by a robust startup ecosystem, ranking 5th in newly funded AI companies by geographic area and attracting significant investments exceeding $475 million in GenAl startups in the past two years.

India's Approach:

  • The Government of India promotes responsible domestic adoption of Al technology to build public trust and promote 'Al for All'.
  • The National Programme on Artificial Intelligence (NPAI) aims to nurture the building blocks of the domestic Al ecosystem through four key interventions:
    • National Data Management Office (NDMO): 
It aims to enhance data quality, utilisation, and accessibility, modernising government practices to fully unlock the potential of data and the Al innovation ecosystem.
    • National Centre on AI (NCAI): NCAl is envisaged as a sector-agnostic entity that identifies Al solutions for public sector problem statements and facilitates their nationwide deployment.
    • Skilling for Al: This pillar aims to revamp technical education infrastructure, particularly ITIs and polytechnics, by building data labs to help equip the workforce with Al-ready skills.
    • Responsible Al: Emphasises the need to address potential biases and discrimination in Al adoption by developing indigenous tools, guidelines, frameworks, etc., and suitable governance mechanisms.

Key Government Initiatives Leveraging Al:

UMANG (Unified Mobile Application for New-Age Governance):

  • Launched in 2017, it is a unified platform providing Indian citizens access to 1836 vital government services spanning from central to local government bodies, including education, COVID-19 vaccinations, public transport, employment guidance, passport applications, and cybercrime reporting.
  • It allows users to inquire about various government services in Hindi and English using voice or text inputs, eliminating technology and language barriers


  • Led by the Ministry of Civil Aviation, is a biometric-based boarding system for Indian airports.
  • The system uses facial recognition technology, where users upload selfies to enhance security and expedite boarding. It maps each passenger to their Passenger Name Record (PNR), ensuring only legitimate passengers gain entry at every checkpoint.
  • It has minimised queuing times and maximised resource utilisation.

Digital India Bhashini (National Language Translation Mission):

  • It is the Ministry of Electronics and Information Technology's initiative aiming to create a voice-based internet accessible in vernacular Indian languages and build multilingualism by developing conversational government apps and websites.

Applications of Al in Urban Governance:

  • The Al model uses advanced image recognition and sensor data analysis to detect and report issues such as potholes, damaged manhole covers, nonfunctional traffic lights, and streetlights.
  • It is also trained to detect traffic infractions like overspeeding, rash driving, and broken taillights.
  • Wigerein Cab and Food-delivery aggregator drivers are incentivised to provide video and image footage to the Al model when they are driving around cities.
  • This model results in cost savings and safer and more efficiently managed urban environments.

Applications of Al in Health Care:

  • The Centre for Artificial Intelligence and Robotics (CAIR) at DRDO has developed ATMAN Al, an Al-based COVID detection software using Chest X-rays.
  • The Ministry of Health and Family Welfare has also implemented Al-based models to analyse X-ray and mammography images for tuberculosis and breast cancer detection.
  • 3 ways effective AI deployment is eradicating India's avoidable blindness:
    • AI-based cataract screening app
    • AI screening tool for diabetic retinopathy detection
    • AI being used in eyecare screening for children

Al Applications in Agriculture:

  • The Telangana government has implemented an Artificial Intelligence (AI) solution to improve crop yield.
    • The AI solution accurately delineates field boundaries for 60,000 agriculture fields, providing 85% accuracy on acreage, forested areas, and irrigation structures.
    • It provides information on crop types, sow and harvest schedules, and water bodies.
  • Another Al-based solution deploys sensors in crop fields to estimate soil moisture content, allowing for predictions of irrigation needs.
    • This solution is estimated to save up to 42% of water for paddy.
  • CottonAce is an AI-driven early warning system that helps farmers protect their crops by providing timely advice on pesticide application.
    • Developed by Wadhwani Al, it has been piloted in Gujarat, Maharashtra, and Telangana, benefiting over 18,000 farmers.
  • After integration, the system has seen a 25% increase in cotton crop yields. Farmers upload pest photos to the CottonAce app, which uses the Al algorithm to identify and count pests, determine infestation levels, and provide actionable advice.

Al-Based Attendance Monitoring (Shiksha Setu):

  • The Assam government has developed a mobile application called 'Shiksha Setu' to record students' and teachers' digital attendance.
  • The system uses an Al-based facial recognition system to geotag and geo-fence 44,000 schools in the state. It records attendance in real-time, eliminating proxy attendance and ensuring punctuality for teachers.
  • It has also identified and removed 4 lakh ghost students, leading to significant cost savings for the government in PM Poshan, school uniforms, and textbook supplies.
  • The most significant advantage is the daily update of absenteeism and dropout rates, which allows authorities to contact parents and inquire about the reasons for their absence. This has helped reduce dropout rates.