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2. Artificial Intelligence: Challenges and Opportunities for India

  • Categories
    Yojana/Kurukshetra
  • Published
    26th Mar, 2020
  • AI can be described as a system’s ability to learn and interpret external data via software/algorithms or machines/devices for problem solving by performing specific roles and tasks currently executed by humans.
  • The term AI has been used interchangeably with other closely related terms such as expert systems, decision support systems, knowledge based systems, machine learning, natural language processing, neural networks, pattern recognition, recommender systems and text mining.
  • Due to recent development in technology signified mainly by development of supercomputers, improved storage capability and super-fast speed of data storage machines and robotics has enabled AI to gain significant momentum in terms of development, application and use within public and private sector organization.

Dimension of AI and its application in various fields


  • The AI has the ability to overcome some of the computationally intensive, intellectual and perhaps creative limitations of humans. Therefore, it opens up new application domains within manufacturing, law, medicine, healthcare, education, government, agriculture, marketing, sales, finance, operations and supply chain management, public service delivery and cyber security.
  • Within the education sector, AI can be deployed to improve teacher effectiveness and student engagement by offering capabilities such as intelligent game-based learning environments, tutoring systems and intelligent narrative technologies.
  • AI can impact education in three ways: AI enabled hyper-personalization helps in developing student-specific learning profile and in developing customized learning environments based on ability, preferred mode of learning and experience.
  • The use of smart assistants (Amazon Alexa, Google Home etc.) and associated technologies offer significant potential to help students.
  • AI systems can assist educators with secondary tasks such as grading activities, providing personalized response to students etc.

AI and Sustainable Development Goals (SDGs)

  • It can be used within several other sectors for enhancing both efficiency and effectiveness. It can be used to achieve multi-dimensional Sustainable Development Goals by its utilization in an effective manner.
  • It can be used in achieving good health and wellbeing (SDG 3) in rural and remote areas in developing countries where access to medical care is limited.
  • In this case, AI can be utilized for conducting remote diagnosis supporting doctors to help improve health service delivery.
  • AI-based systems can also ahelp achieve the “Zero Poverty and Zero Hunger” (SDG 2) by assisting in resource allocation for adverse environmental conditions, diagnose crop disease and identify pests in timely manner to mitigate the risk of catastrophic agricultural events.
  • Similarly, AI-Based system can be used to predict energy utility and demand to help achieving sustainable development goals such as “Clean Water and Sanitation”(SDG 6) and “Affordable Clean Energy” (SDG 7).

 Application of AI in various sectors of India

Health

  • India has 8 per thousand doctor-to-patient ratio (UK – 2.8, Australia – 5, China – Approx. 4). In India, doctors spend just 2 minutes per patient, whereas in the US it is close to 20 minutes.
  • AI could be a valuable assistive tool for doctors in helping reduce their workload and assisting in diagnosis.

Agriculture

  • The per hectare cereal productivity in India is almost half that of China and UK (3000 kg/ha vs. over 6000 kg/ha). There is significant loss of productivity due to pests and diseases.
  • AI-based agricultural pest and disease identification system are helping farmers in identifying the disease and advising the remedial measures.

Education

  • India has about 50% less teachers per thousand students when compared with developed countries (India 2.4/thousand UK 6.3/thousand). In this scenario, AI can help in providing education in remote areas.

 

India’s Potential to implement Artificial Intelligence in Various fields:

  • India has 18 billion mobile phone users with 600 million internet users and 374 million smartphone users.
  • It has one of the cheapest data rates in the world ($0.24/GB) and an average data speed of 6 MBPS. These factors open up huge potential for adoption of AI technology in India.

Successful implementation of AI in India till date

  • The Tamil Nadu Govt. is implementing an innovative use of AI through face recognition for recording attendance. The system is saving more than 45 minutes per day and is freeing up extra time for core educational activities in schools.
  • The Tamil Nadu e-Governance Agency has partnered with Anna University to launch a Tamil smart assistant called “Anil”. The NLP-based smart assistant provides a step-by-step guide to people in helping them pply online for scores of critical government services.
  • The agency has recently launched an AI-based agricultural pest and disease identification system and made it available to over half a million farmer families through a mobile app.
  • The Tamil Nadu Govt. is implementing an innovative use of AI through face recognition for recording attendance. The system is saving more than 45 minutes per day and is freeing up extra time for core educational activities in schools.
  • AI solutions such as radiographic diagnostics like “detection of internal bleeding in brain from CT scans” are being tried to assist doctors and increase their reach to serve remote areas of India.

Challenges and Shortcomings posed by AI in implementation

  • Lack of explainability – Generally AI operates effectively as a black-box-based system that does not transparently provide the reasoning behind a particular decision, classification or forecast made by the systems. It causes lack of trust, transparency and confidence of using decisions made.
  • Lack of contextual awareness and inability to learn – AI based systems are good in performing with given parameters and rules but have major limitations in terms of making decisions where context plays a critical role. Unlike human, AI system cannot learn from their environment.
  • Lack of Standardization – AI based systems are increasingly being embedded in variety of products and services. This poses a critical question: how can the inferences delivered by different AI components be integrated coherently when they may be based on different data and subject to different ecosystem conventions? Organisations face challenges on how to ensure AI and human work together successfully.
  • Job Losses – Increasing automation will lead to significant job losses particularly at operational and lower skill levels for repetitive tasks. This emphasizes the need for strategic management of AI transition requiring organisations to carefully consider a number of challenges: how to select tasks for automation; how to select the level of automation for each task; how to manage the impact of AI-enabled automation on human performance and how to manage AI-enabled automation errors.
  • Lack of competency and need for re-skilling and up-skilling workers : Lack of trusts and resistance to change – Due to above mentioned issues and negative media coverage on the consequences of AI, people are generally apprehensive about its implementation.
  • Lack of trust and resistance to change: Due to above challenges and issues posed by artificial intelligence, people are generally apprehensive about its implementation. This poses major challenges on how to establish trust among workers and stakeholders in the management of resistance to change in adopting AI systems.

Ethics

  • Ethics for machines has been an area of immense interest for the researchers. However defining has proven to be problematic and difficult to make it computable.
  • To tackle this we need to deal with ethics purely from AI perspective. There are two dimensions of Ethics in AI: I) Privacy and Data protection and II)Human and environmental values

 

I. Privacy and Data protection

  • Privacy is possibly the topmost concern while using AI systems. User’s sensitive and highly granular data is likely to be stored and shared across the AI network (For example a person's location for the day based on face recognition and CCTV feeds food habits shopping preferences movies music etc.)

 

II. Human and Environmental Values

  • Any AI system has to confirm to human value system and policymakers need to ask: Has the AI system been sensitized to human values such as respect, dignity, kindness, compassion, equity or not? Does the system know that it has preferential duty towards children, elderly, pregnant women, sick and the vulnerable? An important aspect which needs to be built in a AI system is the overall cost of decisions on the society.

Transparency and Audit

  • In the future, many of the AI based system could be interacting with human in fields such as Finance, education Healthcare, transportation and elderly Care. The technology providers must explain the decision making process to the user so that AI system doesn't remain the black box.
  • These AI systems must provide an audit trail of decisions made not only to meet the legal needs but also for us to learn and make improvements over the past decisions.

Digital divide and Data deficit

  • Since the entire AI revolution has a data at is foundation. There is a real danger of societies being left behind.
  • Countries and governments have good quantity of granular data are likely to derive maximum benefit out of their disruption.
  • Countries where the data is of poor quality or poor of granularity would be left behind in harnessing the power of AI to improve lives of citizens adversely affecting low-resource communities.

Fairness and Equity

  • AI can disrupt social order and hierarchy creating a new social paradigms which could damage the social fabric exposing people lower in bargaining by hierarchy with a real of exploitation and unfair treatment.
  • This could lead to commoditization of human labour and chip away human dignity.
  • An AI system designed with equity as a priority would ensure that no one gets left with behind in this world.
  • Another key need to autonomous system is fairness. They must not exhibit any gender or racial bias and they must be designed so to stay away from social profiling.

Accountability and legal issues

  • Without AI, any system designed by human is only a machine under the control of the operator. Therefore accountability has no not been an issue. Almost all civil and criminal liability laws of the world fairly unanimously attribute accountability to the operator, owner and manufacturer of the machine in varying degree, depending upon the facts of the case.
  • However ones machines are equipped with AI and take anonymous decision, the question of accountability becomes very hard to answer more so when the algorithms are known to the designer.

Misuse protection

  • Internet has been proliferated across the globe benefiting billions, but also carried along with it a beam of cybercrime ,viruses, malware and violent game online games which result in loss of innocent lives of teens around the world.
  • Autonomous AI system must be designed for misuse protection.

Conclusion:

AI as a technology holds tremendous potential for a country like India, which is data rich and has the requisite technological capability to create are solutions for many of the problems. States like Tamil Nadu have already started deploying AI systems at large scale for addressing some of the key challenges in health, education and agriculture sectors. Public rollout of AI system need to address issues of ethics, transparency, audit, fairness, equity and accountability and misuse prevention and effective public policy framework for AI.

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