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Artificial Intelligence

Mains Test Series

Context:

The NITI-Aayog has put forward a discussion paper on artificial intelligence in India

What is Artificial intelligence (AI)?

  • Artificial Intelligence is a way of making a computer, a computer-controlled robot, or software perform human-like tasks.
  • It refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making.
  • There are two subsets under the umbrella term AI: Machine learning and Deep learning
  • Machine Learning involves the use of algorithms to parse data and learn from it. This enables making a determination or prediction.
  • Deep learning is technique for implementing machine learning.
  • The term was coined in 1956 by John McCarthy

Evolution of AI

Categorization of AI:

Advantages of AI

  • No leisure time required
  • Lower error rate compared to humans. Better precision and accuracy. Eg: Robotic radio surgery
  • Better speed
  • Not affected by surrounding environment
  • Replace humans in repetitive, tedious tasks
  • Better user experience through predictive technology e.g. Help in predicting what a user will type, ask, search, and do. Can easily act as assistants and recommend actions.
  • Interact with humans for entertainment or a task. E.g. Sophia robot
  • Logical – devoid of emotions. Can make rational decisions with less or no mistakes.

Disadvantages:

  • Initial cost too high
  • Cannot take decisions if they encounter a situation unfamiliar to them.
  • Repair costs are high
  • May lead to destruction, if put in the wrong hands. E.g. terrorists
  • May have Impact on employment
  • Ethical concerns:

Application of AI:

  1. Agriculture:

Application of AI in agriculture can help in increasing crop yield by providing real-time advisory, early detection of pest attacks, prediction of crop prices, precision farming etc.

Examples:

  1. PEAT – Machine Vision for Diagnosing Pests / Soil Defects

Berlin-based agricultural tech start-up PEAT has developed a deep learning application called Plantix that reportedly identifies potential defects and nutrient deficiencies in soil.

  1. CROPTIX- diagnose crop diseases in the field and alert rural farmers in Kenya

It is a new mobile app that uses artificial intelligence to accurately diagnose crop diseases in the field

  1. Microsoft -ICRISAT AI Sowing App: The app sends sowing advisories to participating farmers on the optimal date to sow
  2. Healthcare:

Can be used in diagnosis, treatment design, imaging diagnosis, early detections of disease outbreaks, robot assisted surgeries, virtual nurse assistants etc.

Examples:

  1. Sensely’s “Molly”– an AI-powered nurse used by UCSF and the UK’s NHS to interact with patients
  2. Recently, researchers at an Oxford hospital developed AI that can diagnose scans for heart disease and lung cancer
  3. Education:
  • Can be used for developing tools for customised learning, interactive and intelligent tutoring systems, and predicting tools- for example predicting dropouts
  • Can also be used in developing automated teacher posting and transfer systems, using analytics based on demand – supply gaps across schools

Example:

Pearsons’ WriteToLearn software:

It uses natural language processing technology to give students personalised feedback, hints, and tips to improve their writing skills

  1. Urban planning:

Can be used for optimizing infrastructure in cities, service delivery, crowd management, cyber security, public safety and water and waste management

Examples:

Bandicoot

In Kerala, engineers have developed sewer-cleaning robots to put an end to manual scavenging

  1. Transportation:
  • Can be used in developing AI-based traffic management system including sensors, CCTV cameras, automatic number plate recognition cameras, speed detection cameras, signalised pedestrian crossings
  • Can help in predictions in public transport journeys
  • Can help in optimising parking

Example:

Intelligent traffic signals at Pittsburgh

Smart parking garages in USA

  1. Retail

Can be used in customer demand anticipation, improved inventory management,  efficient delivery management, interaction with customers etc

Example:

Japan’s Pepper:

It is a humanoid robot that can interact with customers and “perceive human emotions”.

  1. Manufacturing:

Can be used in supply chain management, predictive maintenance, logistics, and quality assurance

Example:

General Electric’s Brilliant Manufacturing:

Designed to make the entire manufacturing process more efficient and thus reduce costs.

  1. Energy

Can be used in energy system modelling, predictive analysis, demand and infrastructure management, renewable management, building energy efficient buildings, etc

Example:

EWeLiNE, Germany:

It can work as an early-warning system for grid-operators to assist them in calculating renewable-energy output over the next 48 hours using AI

  1. Defence:

Areas of application of AI in defence include:

  • Intelligent and Autonomous Unmanned Weapon Systems
  • Tactical artificial intelligence: Tactical AI analyzes the battlefield and acts on information by creating a Course of Action that exploit the weaknesses in enemy’s position
  • AI-Enabled Data Fusion, Information Processing, and Intelligence Analysis
  • Cyber defence and cyber warfare

Examples:

AI powered planning tool, USA

Global Developments:

Various initiatives taken by countries to promote and develop artificial intelligence

Artificial Intelligence in India

Why does India need AI?

  1. To reap economic benefit
  • According to a research by Accenture, AI can boost India’s annual growth rate by 1.3 percentage points by 2035.
  1. Business opportunities: Can host enterprises and institutions globally to develop AI technology which can be easily implemented in the rest of the developing and emerging economies
  2. Social development and inclusive growth

AI developments in India:

Business

  • There has been an increase in AI focused start-ups
  • According to a PwC research, 36 percent large financial establishments in India have invested in AI technologies
  • Artificial Intelligence Industry in India is currently estimated to be $180 Million annually in revenues

Defence:

  • Center for Artificial Intelligence and Robotics (CAIR) in DRDO conducts research in artificial intelligence
  • Indian Army already has Wheeled Robot with Passive Suspension, Snake Robot, Legged Robot, Wall-Climbing Robot, and Robot Sentry,
  • CAIR has been working on a project to develop a Multi Agent Robotics Framework (MARF)- will have array of robots functioning as human soldiers

Health Sector:

  • NITI Aayog is working with Microsoft and Forus Health to introduce a technology for early detection of diabetic retinopathy as a pilot project
  • 3nethra developed by Forus Health for detecting common eye problems

Agriculture:

  • NITI Aayog and IBM have partnered to develop a crop yield prediction model using AI to provide real time advisory to farmers.

Education:

  • Andhra Pradesh government has collaborated with Microsoft to predict drop-outs and address the issue

Urban infrastructure and Transport:

  • Pune Street Light Project- energy efficient street lights: can be remote controlled through a Supervisory Control and Data Acquisition (SCADA) systems.
  • Surat has collaborated with Microsoft to develop solutions for water management and urban planning.
  • Traffic Management System based on radar-based monitoring with the help of AI to be used in Delhi
  1. Kamakoti Committee:

AI Task Force headed by V.Kamakoti was set up to to explore possibilities to leverage AI for development across various fields.

Key recommendations:

  1. Set up digital data banks, marketplaces and exchanges to ensure availability of cross-industry information
  2. Data ombudsman: to address data-related issues and grievances.
  3. Ensure availability of funds for R&D
  4. Setting up National Artificial Intelligence Mission (N-AIM)

10 domains need attention:

  • Manufacturing
  • Fintech
  • Healthcare
  • Agriculture
  • Education
  • Retail/Customer engagement
  • Public utility services
  • Aid for differently-abled persons/Accessibility technology
  • Environment
  • National security
  1. Education and awareness

National strategy on artificial intelligence

  • NITI Aayog in its recent discussion paper addresses the national strategy on artificial intelligence.
  • It identifies 5 cores areas for application of artificial intelligence:
  1. Healthcare: increased access and affordability of quality healthcare
  2. Agriculture: enhanced farmers’ income, increased farm productivity and reduction of wastage
  3. Education: improved access and quality of education
  4. Smart Cities and Infrastructure: efficient and connectivity for the burgeoning urban population
  5. Smart Mobility and Transportation: smarter and safer modes of transportation and better traffic and congestion problems

Challenges to Adoption in India

  1. Unavailability of proper data ecosystem
  2. Insufficient funding and research in AI.
  3. Inadequate availability of AI expertise, manpower and skilling opportunities
  4. High resource cost
  5. Low awareness for adopting AI in business processes
  6. Lack of proper privacy, security and ethical regulations
  7. Unattractive Intellectual Property regime. This hinders research and adoption of AI
  8. Unemployment issues

Way Forward

  1. Research:
  • Two-tiered structure for AI research:
  1. Centre of Research Excellence (CORE) focused on developing a better understanding of existing core research and pushing technology frontiers through creation of new knowledge
  2. International Centres of Transformational AI (ICTAI) for developing and deploying application-based research. Private sector collaboration is considered to be a key aspect of ICTAIs.

  • Increased public sector spending.
  • Private investment
  • Achieve excellence in AI research

Best Practice:

  • EU’s Robotics Public Private Partnership, 2013:
  • One of the biggest civilian research programme- has helped Europe in emerging among top robot manufacturers.
  1. Skilling and Re-skilling of workforce, help in adoption of AI
  2. Facilitating creation of large foundational annotated data sets
  3. Partnership of Industries and Academia
  4. Supporting start-ups
  5. Spreading awareness on advantages of AI
  6. Taxing of Robots: Bill Gates had suggested that governments should tax companies using robots. This tax could be used for funding human services.
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