Artificial Intelligence powered grievance management application

Context:

Raksha Mantri Shri Rajnath Singh launched an Artificial Intelligence (AI)-powered grievance management application in New Delhi

Key Highlights Artificial Intelligence powered grievance management application:

• It developed by Ministry of Defence with the help of IIT-Kanpur. Minister of State (Independent Charge) for Personnel, Public Grievances & Pensions
• This is the first AI based system developed to improve grievance redressal in the Government.
• The AI tool developed as part of the initiative has capability to understand the content of the complaint based on the contents therein. As a result, it can identify repeat complaints or spam automatically.
• Based on the meaning of the complaint, it can categorise complaints of different categories even when key words normally used for such search are not present in the complaint.
• It enables geographical analysis of complaints in a category including analysis of whether the complaint was adequately addressed or not by the concerned office.
• Easy user-friendly search enables user to formulate his own queries/categories depending on management requirements and seek performance results based on the query.
• Given that lakhs of complaints are received on CPGRAMS portal of DARPG, this application will have great use in understanding the nature of complaints, geographies from where they emanate and policy changes which can be introduced to create systemic improvements to address these grievances. 
• AI-powered application will automatically handle and analyse the complaints of the people and would reduce human intervention, save time and bring more transparency in their disposal. 
• This project is first of its kind initiative of the Government for using AI, data science and Machine Learning techniques in grievance redressal.

What is Artificial Intelligence:

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. 

How AI works:

AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields:

• Machine learning automates analytical model building. It uses methods from neural networks, statistics, operations research and physics to find hidden insights in data without explicitly being programmed for where to look or what to conclude.
• A neural network is a type of machine learning that is made up of interconnected units (like neurons) that processes information by responding to external inputs, relaying information between each unit. The process requires multiple passes at the data to find connections and derive meaning from undefined data.
• Deep learning uses huge neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data. Common applications include image and speech recognition.
• Cognitive computing is a subfield of AI that strives for a natural, human-like interaction with machines. Using AI and cognitive computing, the ultimate goal is for a machine to simulate human processes through the ability to interpret images and speech – and then speak coherently in response.  
• Computer vision relies on pattern recognition and deep learning to recognize what’s in a picture or video. When machines can process, analyze and understand images, they can capture images or videos in real time and interpret their surroundings.
• Natural language processing (NLP) is the ability of computers to analyze, understand and generate human language, including speech. The next stage of NLP is natural language interaction, which allows humans to communicate with computers using normal, everyday language to perform tasks.

AI in everyday life

Below are some AI applications that you may not realise are AI-powered:

Online shopping and advertising

Artificial intelligence is widely used to provide personalised recommendations to people, based for example on their previous searches and purchases or other online behaviour. AI is hugely important in commerce: optimising products, planning inventory, logistics etc.

Web search

Search engines learn from the vast input of data, provided by their users to provide relevant search results.

Digital personal assistants

Smartphones use AI to provide services that are as relevant and personalised as possible. Virtual assistants answering questions, providing recommendations and helping organise daily routines have become ubiquitous.

Machine translations

Language translation software, either based on written or spoken text, relies on artificial intelligence to provide and improve translations. This also applies to functions such as automated subtitling.

Smart homes, cities and infrastructure

Smart thermostats learn from our behaviour to save energy, while developers of smart cities hope to regulate traffic to improve connectivity and reduce traffic jams.

Cars

While self-driving vehicles are not yet standard, cars already use AI-powered safety functions. The EU has for example helped to fund VI-DAS, automated sensors that detect possible dangerous situations and accidents.

Cyber security

AI systems can help recognize and fight cyber attacks and other cyber threats based on the continuous input of data, recognizing patterns and backtracking the attacks.

Artificial intelligence against Covid-19

In the case of Covid-19, AI has been used in thermal imaging in airports and elsewhere. In medicine it can help recognise infection from computerised tomography lung scans. It has also been used to provide data to track the spread of the disease.

Fighting disinformation

Certain AI applications can detect fake news and disinformation by mining social media information, looking for words that are sensational or alarming and identifying which online sources are deemed authoritative.

Health

Researchers are studying how to use AI to analyse large quantities of health data and discover patterns that could lead to new discoveries in medicine and ways to improve individual diagnostics.

For example, researchers developed an AI program for answering emergency calls that promises to recognise a cardiac arrest during the call faster and more frequently than medical dispatchers. In another example, EU co-funded KConnect is developing multi-lingual text and search services that help people find the most relevant medical information available.

Manufacturing

AI can help European manufacturers become more efficient and bring factories back to Europe by using robots in manufacturing, optimizing sales paths, or by on-time predicting of maintenance and breakdowns in smart factories.

Satisfactory, an EU co-funded research project, uses collaborative and augmented-reality systems to increase work satisfaction in smart factories.

Food and farming

AI can be used in creating a sustainable EU food system: it can ensure healthier food by minimising the use of fertilisers, pesticides and irrigation; help productivity and reduce the environmental impact. Robots could remove weeds, lowering the use of herbicides, for example.

Public administration and services

Using a wide range of data and pattern recognition, AI could provide early warnings of natural disasters and allow for efficient preparation and mitigation of consequences.

Source: PIB

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