Artificial Intelligence (AI)

In News

The experts suggest that the Artificial Intelligence based technology could be used for health care as well as many other present and future challenges in various sectors.

Artificial Intelligence

• It is the science and engineering of making intelligent machines, especially intelligent computer programs. 
• It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.
• AI would not replace people but create new opportunities in various fields. 
• It works on data, and if we could train our machines, it could do wonders for us in milliseconds by automating processes. 
• AI is creating new opportunities which could not be achieved by traditional technology.

Artificial Intelligence Applications

• Speech Recognition: It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting. 
• Customer Service: Online chatbots are replacing human agents along the customer journey. They answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. 
  • Examples include messaging bots on e-commerce sites with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually done by virtual assistants and voice assistants.
• Computer Vision: This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. 
  • This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry.  
• Recommendation Engines: Using past consumption behavior data, AI algorithms can help to discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.
• Automated stock trading: Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.
• 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.
• 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.
• Automobiles: 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. Navigation is largely AI-powered.
• Cybersecurity: AI systems can help recognise and fight cyberattacks and other cyber threats based on the continuous input of data, recognising patterns and backtracking the attacks.
• 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.
• Transport: AI could improve the safety, speed and efficiency of rail traffic by minimising wheel friction, maximising speed and enabling autonomous driving. Tesla Cars use AI.
• Agriculture: AI applications in agriculture have developed applications and tools which help farmers inaccurate and controlled farming by providing them proper guidance to farmers about water management, crop rotation, timely harvesting, type of crop to be grown, optimum planting, pest control etc. use of drone to analyze the captured images and provide a detailed report containing the current health of the farm. It helps the farmer to identify pests and bacteria helping farmers to timely use pest control and other methods to take required action.
• Health: It can be used for diagnostic purposes for various diseases, including COVID-19, and could prove very effective in remote areas where adequate health facilities are not available.
  • 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. 
• Key to success in using AI for various problems is to reach out to maximum people

Challenges

• Massive Data Centres Needed: AI requires massive computational capacity, which means more power-hungry data centres and a big carbon footprint.
• More Energy Consumption: According to studies, around 40 % of the total energy that data centres consume goes to cooling IT equipment. Now, to reduce energy consumption, companies are moving their data centres into cooler climates such as Siberia.
  • Environmental Impact of Coolants used in Data Centres: The environmental impact caused by data centres doesn’t stop at electrical consumption. Coolants are often made of hazardous chemicals, and battery backups at data centres – needed for when there are power shortages – cause an environmental impact both due to mining for battery components and the disposal of the toxic batteries afterward.
• Jurisdictional Issues of Data Pooling: Countries are passing stricter legislations on data security that require citizen data to be stored on servers located domestically, picking colder climates beyond their borders is becoming a difficult option.
  • Privacy Issues: AI uses digital footprints and feeds them in their algorithm to exploit commercially without our consent.
• Displacement and loss of jobs of lower strata: Robotics and AI companies are building intelligent machines that perform tasks typically carried out by low-income workers: self-service kiosks to replace cashiers, fruit-picking robots to replace field workers, etc.
  • Creating New Inequalities: Without clear policies on reskilling workers, the promise of new opportunities will in fact create serious new inequalities.
• Widening gap: Widens Gap between the developing and the developed countries

Way Forward

• A “whole of society” approach to AI governance will enable us to develop broad-based ethical principles, cultures and codes of conduct, to ensure the needed harm-mitigating measures, reviews and audits during design, development and deployment phases, and to inculcate the transparency, accountability, inclusion and societal trust for AI to flourish and bring about the extraordinary breakthroughs it promises.
• The UN Secretary-General’s Roadmap on Digital Cooperation: It could become a good starting point as it lays out the need for multi-stakeholder efforts on global cooperation so AI is used in a manner that is “trustworthy, human rights-based, safe and sustainable, and promotes peace.
  • UNESCO has also developed a global, comprehensive standard-setting draft Recommendation on the Ethics of Artificial Intelligence to Member States for deliberation and adoption.
• NITI Aayog’s Report recognises that our digital future cannot be optimised for good without multi-stakeholder governance structures that ensure the dividends are fair, inclusive, and just. 
  • NITI Aayog has decided to focus on five sectors that are envisioned to benefit the most from AI in solving societal needs: 
    • Healthcare
    • Agriculture
    • Education
    • Smart cities and infrastructure
    • Smart mobility and transportation. 

Source: PIB