Artificial Intelligence : Challenges and Opportunities

In recent developments in artificial intelligence (AI) offers the potential for significant challenges and opportunities for industry, governments and society. Within automobile sector, the AI based systems has changed the whole transportation sector through automated driving cars which reduces the pollution emitted by conventional vehicles, increases the safety, economic and societal benefits, efficiency and convenience. It has also created a lot of new employment opportunities. 

In this article, we will discuss the opportunities and challenges, mainly focusing on policy on AI based intelligent systems.

What is artificial intelligence (AI) ?

You may have heard a lot of buzz around AI but what exactly AI is ? Artificial Intelligence can be think of as a machines or systems ability to learn and interpret external data via algorithms or software by performing a certain set of tasks currently executed by humans. Several authors have been using alternative terms for artificial intelligence such as expert systems, decision support system, knowledge based systems, machine learning, natural language processing, neural networks, pattern recognition, recommendation systems and text mining.

Opportunities and Applications

A multitude of opportunities have been presented for the application and use of AI powered systems in various fields specifically to assist where structured decision making is needed. The ability of AI to overcome some of the computationally intensive, intellectual and perhaps creative limitations of humans opens up new application fields 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 enabled system 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.
• Schmelzer suggested that AI can impact education in three ways as follows: a) Building student centric learning profile and in developing customized learning environments based on ability, preferred mode of learning and experience. b) Use of smart assistants such as amazon alexa, google assistants, apple siri, microsoft cortana etc,. and associated technologies offer significant potential to help students. c) AI powered systems can assist educators with secondary tasks such as grading activities, providing personalized responses to students, handling routine and repetitive paper work and dealing with logistic related matters.

Also Dwivedi et al. has elaborated on how AI based systems can help in achieving United Nations Sustainable Development Goals (SDGs), Specifically, AI can significantly help in health care systems operating in within rural and remote areas in developing countries where access to medical care is limited. In such scenarios, AI powered machines can also help achieve  the "Zero Poverty and Zero Hunger" (SDG 2) by assisting in resource allocation for predicting adverse environmental conditions, diagnose crop diseases and identify pests in timely manner to mitigate the risk of catastrophic agricultural events. Similarly, AI powered systems can help in achieving SDGs such as "Clean Water, Sanitation" and "Affordable clean energy".

Application of AI in India

India is an ocean of opportunities for AI start ups to grow in various sectors such as industry, governments and society. For example, health, education and agriculture sectors are important to highlight as the AI is further adopted. But India has a largest mobile phone users with internet (600 million) around the world. On top of that India provides cheapest data rates in the world which opens up huge potential for implementation of AI powered technology in India.

The Tamil Nadu e-Governance Agency (TNeGA), along with the Department of Agriculture of Tami Nadu, is developing an AI-based solution that equips farmers with a mobile app, through which they can send in photos of diseases or pests. The AI engine will detect the pest or diseases and prescribe suitable treatments/interventions in real-time. This system has gain a lot of good responses from nearly 400 farmers who are posting identification requests and getting solution every day.

In collaboration with Health department, TNeGA has developed AI powered solutions such as radiographic diagnostics like "detection of internal bleeding in brain from CT scans " which can assist doctors, lab technicians and increase their reach to serve remote areas of India.

The Tamil Nadu government employee now saving 45 minutes per day by using AI powered attendance system which operates on facial recognition and freeing up extra time for core educational activities in schools.

Challenges and limitation

There are a number of challenges and limitations in implementing and utilization of AI powered systems in both private and public sectors exists. Some of the key challenges are briefly outlined here.

Lack of explainability

Generally AI powered systems are operates as black-box based system which means it does not explain the reason behind certain decision, classification, prediction or forecast made by it. This is the major limitation of this technology as it direct impact on trust and confidence of using decision made by it.

Lack of contextual awareness and inability to learn 

Although AI powered systems perform extra ordinary at certain task with given parameters and rules. It still have a limitations in terms of making decision where a context plays a critical role. This limits the power of AI in certain areas because it cannot learn from surrounding environments.

Lack of standardization

AI powered systems function through utilizing tremendous data from various sources. The difference sources can give different decision made by AI. For example, smart assistants, modules for enterprise products, widely available cloud libraries and bespoke data science driven application. All of this can pose 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 and associated quality differences? Furthermore, organization face challenges on how to ensure AI and human work together successfully.

Job losses

The critical consequences of AI use will continue to impact all sectors and countries across the world but particularly developing economies where employment opportunities are already limited. As increase the automation in sectors where at operational and low level skill are required for repetitive task will lead to significant job losses. This shows that the need for strategic management of AI by considering a number of major challenges such as how to select task for automation, how to select the level of automation for each task, how to manage the impact of AI powered automation on human performance and how to manage AI powered automation errors. 

Lack of competency and need for re-scaling and up scaling of workers

A large number of organization still lack in house competency to successfully develop and implement AI powered systems. Using or working with AI powered systems requires workers to be equipped with a new and advanced set of skills which is a challenge for government, organization and individuals.

Lack of trust 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. This poses a major challenge on how to establish trust among workers and stakeholders in the management of resistance to change in adopting AI systems.

Public policy is facing unprecedented uncertainty and challenges in this dynamic world of AI is so high that it creates an interesting dynamics in terms of the need to predict its impact and inability to draw boundaries.


For more information read full article in Yojana, February issue 2020.