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Day 44 – Q 1. How can artificial intelligence and machine learning techniques help in improving e-governance? Illustrate with the help of suitable examples.

  • IASbaba
  • July 30, 2020
  • 0
Governance, GS 2, TLP-UPSC Mains Answer Writing
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1. How can artificial intelligence and machine learning techniques help in improving e-governance? Illustrate with the help of suitable examples. 
ई-गवर्नेंस को बेहतर बनाने में आर्टिफिशियल इंटेलिजेंस और मशीन लर्निंग तकनीक कैसे मदद कर सकती हैं? उपयुक्त उदाहरणों की सहायता से चित्रण करें।

Demand of the question:

It expects students to explain with relevant examples about how the application of artificial intelligence and machine learning techniques help in improving e-governance.

Introduction:

Artificial Intelligence (AI) and Machine Learning (ML) are the two emerging technologies. AI and ML have great  potential to do things that humans will never be able to do themselves. Hence, AI and ML together can bring a positive impact on business, society, culture and especially in e-governance.

Body:

Artificial Intelligence and Machine learning are a rapidly evolving technologies that harnesses the ability of machines to learn and perform cognitive functions, similar to that of the human brain. It incorporates, among other things, learning, problem-solving, speech recognition, and planning.

Use of Artificial intelligence and Machine learning to improve e-governance:

  • Many local municipalities or government departments can invest in and use AI in call centres or customer service. The vast majority of calls coming in are fairly basic, repeat questions or routine reports. 
  • It will reduce the burden of work on government officials and will also help to use that human capital for more productive work.
  • By making use of intelligent chat bots, this process can be automated. This automation will improve service and user experience, as it will be faster and more accurate. The chat bots can answer questions, provide information, receive, and report information, and guide citizens with applications.
  • For example, the United States Army uses an interactive virtual assistant to check qualifications, answer questions, and refer potential recruits to human recruiters. It does the work of 55 recruiters, and at a 94% accuracy rate that is improving as the machine learns
  • In the power department and meteorological department, self-learning weather forecasting technology uses machine learning, sensor information, cloud-motion physics derived from sky cameras, and satellite observations to improve rain forecasting accuracy by 30%.
  • It will in turn help to predict the amount of rainfall the region is going to receive and also helpful to declare guidelines regarding the crop sowing cycles, fertilizers etc.
  • Law enforcement, public safety, and criminal justice can all benefit from the power of AI. Facial and image recognition software can quickly and more accurately analyze thousands of hours of video footage in crime or terrorist-related issues, narrowing the search down and showing where people should focus their attention.
  • Education: In the education sector, AI and ML have a variety of use cases and applications. By analysing a student’s past data, AI and ML can help the student in making decisions when choosing courses and electives at universities. AI chat bots can be used to interact with students for admission queries.
  • Intelligence, Surveillance, and Advanced Robotics: AI can be used to monitor and control unmanned autonomous vehicles for gathering intelligence and advanced surveillance purposes. Machine learning algorithms can help in evaluating border infiltration patterns and predict the possibility of infiltrations happening at certain times.
  • Traffic Control: Traffic lights in most countries are set to a pre-set value to control the traffic. This value doesn’t vary with the changing traffic conditions. AI can help in synchronizing traffic data and control the traffic based on the situation in real-time. It ensures a smooth flow of traffic without causing any inconvenience to commuters. e.g. A 3-D Smart Traffic Signal system is developed by engineering students in Chandigarh.

The potential benefits of AI and ML are patently clear in the public sector, but still there are some impediments which needs to be addressed:

  • Learned Prejudice: the mathematical structures that AI-enabled systems depend upon can absorb and reproduce human prejudices. If machine learning systems are trained to regard different categories of people differently, they may become another engine of social inequality. e.g. Rich poor gap, Cast discrimination.
  • Cultural Sensitivity: According to World Economic Forum research, the way workers and civilians respond to the inclusion of AI systems in their lives can depend on cultural context. The populations of China and England, for instance, are much more open to AI-enabled surveillance technologies than the populations of some underdeveloped countries.
  • AI Myths & Expectation: There’s a quite discrepancy between the actual potential of the AI system and the expectations of this generation.  Artificial Intelligence, with its cognitive capabilities, has potential to replace human’s jobs.

Most government departments around the world are understaffed, under skilled, and face massive backlogs in many areas of their administration. Resources are scarce. As a result, in many cases, service delivery is slow and poor.

Conclusion:

Artificial intelligence and machine learning can take care of the time consuming, labour intensive administration, speed up internal processes, develop massive cost savings, increase productivity, improve the speed and accuracy of decision-making, identify potential problems before they become major issues, and allow for much better allocation of resources. Hence, It can make government more responsive, more efficient, and improve the lives of their citizens.

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