ARTIFICIAL INTELLIGENCE – SOCIAL TRANSFORMATION SPECIAL REFERENCE TO INDIA

 

                                                                                                                - Dr. S. Vijay Kumar

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. It is a subset of computer science that focuses on machine-driven intelligence (i.e., non-human intelligence). John McCarthy coined the term 'artificial intelligence’ in 1956. He defined it as ‘the science and engineering of making intelligent machines”. The Study of Artificial Intelligence is one of the currently emerging fields. As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optical character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function. Artificial intelligence is an interdisciplinary science with multiple approaches like the ability of a computer or machine to mimic the capabilities of the human mind—learning from examples and experience, recognizing objects, understanding, and responding to language, making decisions, solving problems—and combining these and other capabilities to perform functions a human might perform, such as greeting a hotel guest or driving a car. In Vedas, Yoga Vāsistha describes application of Artificial Intelligence, human emotions, ego to Robots. Yoga Vāsistha is a discourse of sage Vasishta to Prince Rama. Sage Valmiki is credited as its author. In one of the part of it, application of Artificial Intelligence, human emotions etc. to Robots is described. Intelligent robots and artificial beings also appeared in the ancient Greek myths of Antiquity. While the roots are long and deep, the history of artificial intelligence as we think of it today spans less than a century. Today, the applications for artificial intelligence are endless. The technology can be applied to many different Sectors and Industries. Understanding AI and AI terminology can be difficult because many of the terms are used interchangeably; and while they are actually interchangeable in some cases, they aren’t in other cases. For example: Difference between artificial intelligence and machine learning? Between machine learning and deep learning? Between speech recognition and natural language processing? Between weak AI and strong AI? This article is an attempt to explain the importance of “Artificial Intelligence” in social transformation of our country with the following objectives and methodology.

Objectives of the Study:

1.      History of Artificial Intelligence.

2.      Meaning, Types of Artificial Intelligence, Applications.

3.      Importance of Artificial Intelligence in Social Transformation in India.

4.      Benefits/Advantages and Risks/Disadvantages of Artificial Intelligence.

5.      National Strategy for Artificial Intelligence and Future Outlook.

6.      Conclusion.

 

Methodology: This Paper is based on Secondary data and information accessed from different sources like Journals, Research Articles, Artificial Intelligence National and International Research Centers. Relevant Websites.

History of Artificial Intelligence: Myths considered to be the world’s first science fiction stories. No single civilization had a monopoly on ancient dreams of advanced technology. Whether one looks at Hindu, Greek, Chinese, Egypt, or any other ancient cultural myths about artificial intelligence (For example: myths featuring flying chariots, giant robots, machines in Mahabharata, Ramayana. Self-navigating ships appear in Egyptian texts etc.). It is not possible to draw a direct line of development from mythology to modern scientific knowledge. By 3^rd Century BC, craftspeople and engineers in India, China began making self-moving devices, flying bird models, animated machines, and automatons like those described in myths.

Key Events in the History of Artificial Intelligence:

 

380 BC - Late 1600s: Various mathematicians, theologians, philosophers, professors, and authors pondered about mechanical techniques, calculating machines, and numeral systems that all eventually led to the concept of mechanized “human” thought in non-human beings.

Early 1700s: Jonathan Swift’s novel “Gulliver’s Travels” mentioned a device called the engine, which is one of the earliest references to modern-day technology, specifically a computer.

 

1872: Author Samuel Butler’s novel “Erewhon” toyed with the idea that at an indeterminate point in the future machines would have the potential to possess consciousness.

 

1929: Japanese biologist and professor Makoto Nishimura created Gakutensoku, the first robot to be built in Japan.  Some of its features included moving its head and hands as well as changing its facial expressions.

 

1950: Claude Shannon, “the father of information theory,” published “Programming a Computer for Playing Chess,” which was the first article to discuss the development of a chess-playing computer program. Alan Turing published “Computing Machinery and Intelligence,” which proposed the idea of The Imitation Game – a question that considered if machines can think. This proposal later became The Turing Test, which measured machine (artificial) intelligence. 

 

1956: John McCarthy coins the term 'artificial intelligence' at the first-ever AI conference at Dartmouth College. (McCarthy would go on to invent the Lisp language.) Later that year, Allen Newell, J.C. Shaw, and Herbert Simon create the Logic Theorist, the first-ever running AI software program.

 

1967: Frank Rosenblatt builds the Mark 1 Perceptron, the first computer based on a neural network that 'learned' though trial and error. Just a year later, Marvin Minsky and Seymour Papert publish a book titled Perceptrons, which becomes both the landmark work on neural networks.

 

1980s: Neural networks featuring backpropagation—algorithms for training the network—become widely used in AI applications.

 

1997: IBM's Deep Blue beats then world chess champion Garry Kasparov, in a chess match (and rematch).

2011: IBM Watson beats champions Ken Jennings and Brad Rutter at Jeopardy!

 

2015: Baidu's Minwa supercomputer uses a special kind of deep neural network called a convolutional neural network to identify and categorize images with a higher rate of accuracy than the average human.

 

2016: 

·         DeepMind's AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champion Go player, in a five-game match.

 

·         A humanoid robot named Sophia is created by Hanson Robotics. She is known as the first “robot citizen.” What distinguishes Sophia from previous humanoids is her likeness to an actual human being, with her ability to see (image recognition), make facial expressions, and communicate through AI.

 

·         Google released Google Home, a smart speaker that uses AI to act as a “personal assistant” to help users remember tasks, create appointments, and search for information by voice.

 

2017: The Facebook Artificial Intelligence Research lab trained two “dialog agents” (chatbots) to communicate with each other in order to learn how to negotiate.

 

2018: 

·         Alibaba (Chinese tech group) language processing AI outscored human intellect at a Stanford reading and comprehension test.

 

·         Google developed BERT, the first “bidirectional, unsupervised language representation that can be used on a variety of natural language tasks using transfer learning.”

 

·         Samsung introduced Bixby, a virtual assistant. Bixby’s functions include Voice, where the user can speak to and ask questions, recommendations, and suggestions.

 

2019:

·         Chatbots + virtual assistants: Strengthened chatbot and virtual assistant automation for heightened user experience.

·         Natural language processing (NLP): Increased NLP abilities for artificially intelligent apps, including (and especially for) chatbots and virtual assistants

·         Machine Learning and Automated Machine Learning: ML will shift toward AutoML algorithms to allow developers and programmers to solve problems without creating specific models.

·         Autonomous vehicles: Despite some bad press surrounding various faulty self-driving vehicles, it’s safe to assume there will be a stronger push to automate the process of driving product from point A to point B to 1. Save on the cost of human labor, 2. Optimize the process of purchase-shipment-arrival to consumer via self-driving vehicles that – in essence – won’t get tired behind the wheel.

 

 

2020:

·     Leveraging AI to create autonomous assets that appreciate, not depreciate, in value the more that they are used becomes a reality (thanks Elon Musk)

·     Orphaned Analytics - ML models built for one-off analytic purposes but never engineered for re-usability or continuous learning and adapting - continue to be an organizational disappointment.

·     Continued advancements in open source tools for development, operationalization and management of AI/ML models.

·     Under-appreciating the unintended consequences that result from bad estimates of the costs of False Positive and False Negative errors.

 

Key 2021 Trends:

·     While Data Monetization continues as challenge, many lack a business-centric value engineering methodology to identify and prioritize where and how AI/ML can derive new sources of customer, product, and operational value.

·     Organizations begin to appreciate the economic value of data and analytics, digital assets that never wear out and get more valuable the more that they are used.

·     Autonomous Analytics start to replace Orphaned Analytics in leading organizations.

Meaning, Types of Artificial Intelligence and its applications:

Meaning of AI: It refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. AI is its ability to rationalize and take actions that have the best chance of achieving a specific goal. A subset of artificial intelligence is machine learning, which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning, techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.

Types of Artificial Intelligence: There are 7 types of Artificial Intelligence (AI). They are:

1. Reactive Machines: These are the oldest forms of AI systems that have extremely limited capability. They emulate the human mind’s ability to respond to different kinds of stimuli. These machines do not have memory-based functionality. These machines do not have the ability to “learn”. These machines could only be used for automatically responding to a limited set or combination of inputs. Best example of a reactive AI machine is IBM’s Deep Blue, a machine that beat chess Grandmaster Garry Kasparov in 1997.

 

2. Limited Memory: These are the machines that, in addition to having the capabilities of purely reactive machines, are also capable of learning from historical data to make decisions. All present-day AI systems, such as those using deep learning, are trained by large volumes of training data that they store in their memory to form a reference model for solving future problems. For instance, an image recognition AI is trained using thousands of pictures and their labels to teach it to name objects it scans. When an image is scanned by such an AI, it uses the training images as references to understand the contents of the image presented to it and based on its “learning experience” it labels new images with increasing accuracy. Almost all present-day AI applications, from chatbots and virtual assistants to self-driving vehicles are all driven by limited memory AI.

 

3. Theory of Mind: Theory of mind AI is the next level of AI systems that researchers are currently engaged in innovating. A theory of mind level AI will be able to better understand the entities it is interacting with by discerning their needs, emotions, beliefs, and thought processes.

 

4.  Self-Aware: This is the final stage of AI development which currently exists only hypothetically. Self-aware AI, which, self explanatorily, is an AI that has evolved to be so akin to the human brain that it has developed self-awareness.

 

5. Artificial Narrow or Weak Intelligence (ANI): Artificial narrow intelligence refers to AI systems that can only perform a specific task autonomously using human-like capabilities. These machines can do nothing more than what they are programmed to do, and thus have a very limited or narrow range of competencies. According to the aforementioned system of classification, these systems correspond to all the reactive and limited memory AI. Even the most complex AI that uses machine learning and deep learning to teach itself falls under ANI.

 

6. Artificial General or Strong Intelligence (AGI): Artificial General Intelligence is the ability of an AI agent to learn, perceive, understand, and function completely like a human being. These systems will be able to independently build multiple competencies and form connections and generalizations across domains, massively cutting down on time needed for training. This will make AI systems just as capable as humans by replicating our multi-functional capabilities.

 

7. Artificial Super Intelligence (ASI): The development of Artificial Superintelligence will probably mark the pinnacle of AI research, as AGI will become by far the most capable forms of intelligence on earth. ASI, in addition to replicating the multi-faceted intelligence of human beings, will be exceedingly better at everything they do because of overwhelmingly greater memory, faster data processing and analysis, and decision-making capabilities. The development of AGI and ASI will lead to a scenario most popularly referred to as the singularity. And while the potential of having such powerful machines at our disposal seems appealing, these machines may also threaten our existence or at the very least, our way of life.

AI Applications: Some of the most common examples of AI applications are: Smart assistants (like Siri and Alexa), Disease mapping and prediction tools, Manufacturing, and drone robots, Optimized, personalized healthcare treatment recommendations, Conversational bots for marketing and customer service, Robo-advisors for stock trading, Spam filters on email, Social media monitoring tools for dangerous content or false news, Song or TV show recommendations from Spotify and Netflix.

Importance of Artificial Intelligence in Social Transformation in India: In this 21^st Century, “man meets machine” is the reality of unfolding several social, economic, and juristic challenges. Prime Minister Narendra had advised the NITI Aayog to acquaint all the ministries with high-end technologies. He had also asked the Indian think tank to describe how AI would be beneficial to address the country’s socio-economic problems.

Initiatives of Government of India in AI: Since the early 90s, the IT and ITeS (Information Technology Enabled Services) Sector in India has been of tremendous importance to its economy eventually growing at 7.7% of India’s GDP is expected to increase to 10% by 2025. In Feb, 2018 Indian government think-tank, National Institution for Transforming India (NITI) Aayog, spearheaded a national programme on AI focusing on research. This development comes on the heels of the launch of a Task Force on Artificial Intelligence for India’s Economic Transformation by the Commerce and Industry Department of the Government of India in 2017. As the Indian government pushes for digitization and enacts more AI initiatives, more and more Indian startups and established tech firms are beginning to implement AI in their products and services. NITI Aayog, which has been tasked with spearheading India’s AI strategy – is engaged in the three public sector areas: Agriculture, Health Care, and Indian Language Project.

Agriculture – The government has initiated a proof of concept pilot in 15 districts (counties) in India to use artificial intelligence based real-time advisory based on satellite imagery, weather data, etc. to increase farm yields where the farm production levels are low

Healthcare – Pathologists and Radiologists are very few in number India relative to the overall population, (especially in rural areas) and these are applications which can be augmented through image recognition AI. NITI Aayog is working on early diagnosis and detection of Diabetic Retinopathy and Cardiac Risk based on the AI models. Such initiatives would in the long run help patients on proactive medication in early stages rather than reactive healthcare in advanced stages – bringing down healthcare costs and better chances of recovery. 

Indian Languages Project – NITI Aayog has initiated a long-term project to build a complete natural language processing platform for Indian languages. This would aid in the development of several applications, like conversational general and career counseling through chatbots and assistants, conversing in 22 Indian languages.”

In India, AI interest has manifested in the following three ways:

1) Industries have started working to skill their manpower to enable themselves to compete with other global players

2) Educational institutions have started working on their curricula to include courses on machine learning and other relevant areas

3) Individuals and professionals have started acquiring these skills and are comfortable investing in upgrading their own skills.

Like any other sector, artificial intelligence plays a vital role in the social sector. It is already impacting our lives in a major way. Be it getting driving instructions through our smartphone or getting daily reminders by our fitness device to increase our workouts, all these are manifestations of how artificial intelligence is changing the way of our life.

AI can contribute in some or other way to tackle the United Nation’s Sustainable Development Goals, helping large sections of the population in both developing and developed countries. It is already being applied in a number of real-life situations, from helping blind people navigate and diagnosing cancer to identifying sexual harassment victims and helping with disaster relief.

Some Important Social Domains of AI:

Agriculture: AI can help farmers analyze a variety of factors, such as temperature, weather conditions, soil conditions, and water usage, in real-time. AI can analyze where weeds are growing. AI bots can help to harvest crops at a higher volume and faster pace than human laborers.

It can be used to optimize planning and generate a more bountiful yield by determining the best crop choices and the most optimal way to utilize resources. It has been effectively deployed to detect crop damage with the help of low-attitude sensors, from drones to smartphones, to improve the crop yield of small farms.

Healthcare: Early diagnosis of diseases is another area where AI can help for the better. AI-based image processing software was able to scan images of lesions and determine whether they were cancerous more effectively than professional dermatologists. By interpreting the heart rate sensor data, wearable devices with AI-powered software can detect people prone to diabetes with up to 85 percent accuracy. AI is used in healthcare to build sophisticated machines that can detect diseases and identify cancer cells. It uses the combination of historical data and medical intelligence for the discovery of new drugs.

 

Educational Challenges: AI can be used to maximize the achievement of students and the productivity of teachers. Adaptive teaching technologies can be used to recommend content and courses to students based on their engagement and success with past courses and material.

Environmental challenges: To sustain biodiversity and combat climate change, pollution, and the degradation of natural resources. For example - Rainforest Connection, a non-profit organization located in the Bay Area, uses AI tools like TensorFlow to conserve fragile rainforest ecosystems around the globe. By analyzing the audio-sensor data in vulnerable areas, we can successfully detect and prevent illegal logging activity.

Crisis response: There are a number of crisis specific challenges, where AI can be applied such as relief response to man-made and natural disasters, especially rescue missions and disease outbreaks, on satellite data to predict wildfire progressions and optimize the control response. It can be used in conjunction with drones to look for missing persons in the wilderness. Rainier Mallol, a scientist from the Dominican Republic, was successfully able to predict dengue outbreaks three months in advance with up to 81% accuracy after feeding statistics of previous outbreaks to an AI algorithm.

Inclusiveness and equality: AI-based technology also has the potential to improve social inclusiveness and fight discriminatory tendencies by using and analyzing big data. A good case study is Affectiva, a combined effort by the media lab at MIT and the Autism Glass Project that makes use of AI to automate emotion recognition and provide helpful social cues to people at different stages. Addressing challenges related to inclusiveness, equality, and self-determination are some of the most pertinent issues in this domain. These include reducing bias based on religion, race, sexual orientation, disabilities, and citizenship.

Energy: AI is being used in energy sector in several ways. Making energy clean, affordable and reliable has been recognized essential for fighting against several problems including poverty. Google has applied AI successfully in reducing the energy usage by 40% which means several millions of dollars. Google used the technology used in DeepMind for predictions on loads at different points and controlling equipments efficiently.

Information validation: With the fake news epidemic growing direr by the day, we need systems to facilitate provision and validation of reliable, helpful, and valuable information to the masses. We need to focus on counteracting or filtering distorted and misleading content, including false information peddled on social media, internet, and messaging applications. Malicious and false content can have severe negative consequences, from the manipulation of election results to mob lynchings. AI can contribute to this domain by presenting counteractive views to the ideologically insulated pockets across social media platforms.

Infrastructure management: AI can also help with infrastructure challenges and promote the public good in the power sector, waste and water management, real estate, urban planning, and transportation. For instance, traffic light control systems can be optimized with the help of real-time footage and Internet of Things sensors to maximize the passage of vehicles through crowded areas. AI systems can be used to schedule maintenance of public transport systems, from trains to public infrastructure, and to identify malfunctioning components.

Business Strategy: The prediction capability of AI-based solutions can be used in deciding business strategy. A company uses predictions about the customers and market conditions to decide where to focus. Once more and more accurate predictions are available, the company may decide to use different strategy. For instance, the predictions about the customers can be used by a company to bring different types of products and services. One example of use of AI for predictions is that by Amazon which recommends certain products when someone shops on the platform. More extensive data on the customers can help in making the decisions on where to store the products and in what quantity.

Customer Care: AI systems have been developed for customer care in several sectors. The systems use natural language to interact with the customers. Though chatbot has been used for customer care for a long time, it has become more useful with better natural language processing and speech recognition. If the customer remains unsatisfied, it is handed over to a human executive. In order to reduce the cost, companies are using IVRS (Interactive Voice Response System).

 

E-Commerce: There are a number of product and service recommender systems such as the one used by Amazon on its shopping portal. It keeps a track of which items have been purchased by the people over a period of time and identifies certain patterns which are used to decide the products and services of interest to the user. These patterns are not fixed and hard coded in the system but are created using machine learning techniques. For example: A chatbot has been developed to order coffee from Starbucks. The customer can order coffee using spoken natural language describing the type of coffee, etc., and the order is sent to the nearest Starbucks unit. The payment is made automatically using the pre-registered credit/debit card.

 

Personalized Shopping: Artificial Intelligence technology is used to create recommendation engines through which one can engage better with their customers. These recommendations are made in accordance with their browsing history, preference, and interests. It helps in improving relationship with customers and their loyalty towards a particular brand.

 

AI-powered Assistants: Virtual shopping assistants and chatbots help improve the user experience while shopping online. Natural Language Processing is used to make the conversation sound as human and personal as possible. Moreover, these assistants can have real-time engagement with the customers.

 

Fraud Prevention: Credit card frauds and fake reviews are two of the most significant issues that E-Commerce companies deal with. By considering the usage patterns, AI can help reduce the possibility of credit card frauds taking place. Many customers prefer to buy a product or service based on customer reviews. AI can help identify and handle fake reviews. 

 

AI in Navigation: Based on research from MIT, GPS technology can provide users with accurate, timely, and detailed information to improve safety. The technology uses a combination of Convolutional Neural Network and Graph Neural Network, which makes lives easier for users by automatically detecting the number of lanes and road types behind obstructions on the roads. AI is heavily used by Uber and many logistics companies to improve operational efficiency, analyze road traffic, and optimize routes. Neural networks are computing systems with interconnected nodes that work much like neurons in the human brain. Using algorithms, they can recognize hidden patterns and correlations in raw data, cluster and classify it, and – over time – continuously learn and improve. neural networks can improve decision processes in areas such as:
Credit card and Medicare fraud detection, Optimization of logistics for transportation networks, Character and voice recognition, also known as natural language processing, Medical and disease diagnosis, Targeted marketing, Financial predictions for stock prices, currency, options, futures, bankruptcy and bond ratings, Robotic control systems, Electrical load and energy demand forecasting, Process and quality control, Chemical compound identification, Ecosystem evaluation, Computer vision to interpret raw photos and videos (for example, in medical imaging and robotics and facial recognition).

 

AI in Robotics: Robotics is another field where artificial intelligence applications are commonly used. Robots powered by AI use real-time updates to sense obstacles in its path and pre-plan its journey instantly. It can be used for: Carrying goods in hospitals, factories, and warehouses, Cleaning offices and large equipment, Inventory management.

 

AI in Human Resource: Artificial Intelligence helps with blind hiring (It reduces biases during the talent acquisition process by removing information like name, gender, religion, or socioeconomic background. It also removes things like academic qualifications or experience, meaning candidates are judged based on skills––not where they came from). Using machine learning software, one can examine applications based on specific parameters. AI drive systems can scan job candidates' profiles and resumes to provide recruiters an understanding of the talent pool they must choose from.  

 

AI in Gaming: AI can be used to create smart, human-like NPCs (Non-Player Character is any character in a game which is not controlled by a player, but controlled by the game master or referee rather than another player. In video games, this usually means a character controlled by the computer (instead of the player) that has a predetermined set of behaviors that potentially will impact game play) to interact with the players. It can also be used to predict human behavior using which game design and testing can be improved.

 

AI in Automobiles: Artificial Intelligence is used to build self-driving vehicles. AI can be used along with the vehicle’s camera, radar, cloud services, GPS, and control signals to operate the vehicle. AI can improve the in-vehicle experience and provide additional systems like emergency braking, blind-spot monitoring, and driver-assist steering.

 

AI in Social Media:

Instagram: On Instagram, AI considers you likes and the accounts you follow to determine what posts you are shown on your explore tab.

 

Facebook: Artificial Intelligence is also used along with a tool called Deep Text. With this tool, Facebook can understand conversations better. It can be used to translate posts from different languages automatically.

 

Twitter: AI is used by Twitter for fraud detection, removing propaganda, and hateful content. Twitter also uses AI to recommend tweets that users might enjoy, based on what type of tweets they engage with.

 

AI in Marketing:

·         Using AI, marketers can deliver highly targeted and personalized ads with the help of behavioral analysis, pattern recognition, etc. It also helps with retargeting audiences at the right time to ensure better results and reduced feelings of distrust and annoyance.

·         AI can help with content marketing in a way that matches the brand's style and voice. It can be used to handle routine tasks like performance, campaign reports, and much more.  

·         Chatbots powered by AI, Natural Language Processing, Natural Language Generation, and Natural Language Understanding can analyze the user's language and respond in the ways humans do. 

·         AI can provide users with real-time personalizations based on their behavior and can be used to edit and optimize marketing campaigns to fit a local market's needs. 

 

Benefits/Advantages and Risks/Disadvantages of Artificial Intelligence (AI):

 

Benefits/Advantages of AI:

 

1. Reduction in Human Error: AI can significantly reduce errors and increase accuracy and precision. When programmed properly, these errors can be reduced to null. 

 

2. Zero Risks: Big advantage of AI is that humans can overcome many risks by letting AI robots to do the difficult jobs for us. Examples: defusing a bomb, going to space, exploring the deepest parts of oceans. Machines with metal bodies are resistant in nature and can survive unfriendly atmospheres. Moreover, they can provide accurate work with greater responsibility and not wear out easily.

 

3. 24x7 Availability: There are many Studies that show humans are productive only about 3 to 4 hours in a day. Humans also need breaks and time offs to balance their work life and personal life. But AI can work endlessly without breaks. They think much faster than humans and perform multiple tasks at a time with accurate results. They can even handle tedious repetitive jobs easily with the help of AI algorithms. 

 

4. Digital Assistance: Almost all the big organizations these days use digital assistants to interact with their customers which significantly minimizes the need for human resources. You can chat with a chatbot and ask them exactly what you need. Some chatbots have become so intelligent these days that you wouldn’t be able to ascertain whether you are chatting with a chatbot or a human being.

 

5. New Inventions: AI has helped in new inventions in almost every domain to solve complex problems. A recent invention has helped doctors to predict early stages of breast cancer in women using advanced AI-based technologies.

 

6. Unbiased Decisions: Human beings are driven by emotions, whether we like it or not. AI on the other hand, is devoid of emotions and highly practical and rational in its approach. An advantage of AI is that it doesn't have any biased views, which ensures more accurate decision-making.

 

7. Repetitive jobs: The same old task, which doesn’t add value is of no use. Also, repetitive jobs are monotonous in nature and can be carried out with the help of machine intelligence. Machines think faster than humans and can perform various functions at the same time.

 

8. Medical Applications: The applications help to educate the machine about the side effects of various medicines. Nowadays, medical professionals are trained with artificial surgery simulators. It uses application which helps in detecting and monitoring neurological disorders and stimulate the brain functions. This also helps in the radiosurgery. Radiosurgery is used in operating tumors and help in the operation without damaging the surrounding tissues. The integration of AI tools in the healthcare sector has improved the efficiency of treatments by minimizing the risk of false diagnosis.

9. AI in Cyber Security: The conventional cyber security systems are slow due to the need of human interaction in several steps. AI reduces the human intervention by the automation of the processes. The rapid increase in the size and complexity of the virtual world has led to a continuing war between cyber attackers and security service providers. Each side is trying to develop more sophisticated techniques and tools. Cyber space is a dynamic environment where situation keeps on changing rapidly and can’t be predicated with certainty. As AI systems have the flexibility to respond to the changing environment, its use in increasing in all the stages in the cyber defense chain viz. early warning, prevention, detection, and response (Wirkuttis & Hadas, 2017).

10. AI in Finance: Chatbot is being used by banks for performing simple tasks such as activation of accounts or balance checking, etc. It helps the customers who are not fully familiar with IT systems and would like to interact in natural language. Chatbot asks the customers questions in natural language and performs the needed tasks. State Bank of India, HDFC Bank, ICICI Bank and Axis Bank have started using AI-based applications for providing customer services in India.

11. AI in Corporate Sector: AI systems have been developed for contract analysis, especially in corporate sector. Contract analysis involves going through a large number of contract and related documents used over a period of time to find the significant clauses. Often the time required for this is too long and it may not be practically possible to complete the task in many situations. In such a situation, it is possible to use AI-based systems to go through the documents and highlight the most relevant clauses.

12. AI in Law: Several AI-based applications have been developed and services are being offered in the domain of law. AI-based systems have been developed for legal research which involves finding the similar precedent cases for deciding the present case or making arguments in the present case.

13. AI in Transport: Self-driving car is a high-potential application of AI. Several companies including Google, Uber, and Tesla are testing their models on the roads. In Singapore, driver-less bus is being run under trial. So far very few accidents have been reported and the analysis shows that probability of accident with driverless cars is less than human driven cars. It is expected that the number of accidents by self-driving cars will be much smaller than the human-driven cars.

AI has been hailed as revolutionary in  changing the world, but it is not without risks and disadvantages. The following are the risks and disadvantages:

 

Risks/Disadvantages of AI:

 

1. Destructive Superintelligence: Artificial general intelligence that is created by humans may escape our control to wreak havoc. It is also something that might or might not come to fruition (theories vary), though at this point it is less risk than hypothetical threat, in future it may happen. As AI grows more sophisticated and ubiquitous, the voices warning against its current and future pitfalls grow louder. Ofcourse, we’re still in the very early stages.

 

2. Privacy, Security and “Deepfakes”: AI will adversely affect privacy and security. A prime example, China’s use of facial recognition technology in offices, schools, and other venues. But this is now, just one country – later, “A whole ecosphere” of companies specialize in similar tech and sell it around the world. Malicious use of AI could threaten digital security - Example: Through criminals training machines to hack or socially engineer victims at human or superhuman levels of performance. Physical security – Example: Non-state actors weaponizing consumer drones, and Political security – Example: Through privacy-eliminating surveillance, profiling, and repression, or through automated and targeted disinformation campaigns. AI will also give rise to hyper-real-seeming social media “personalities” that are very difficult to differentiate from real ones, deployed cheaply and at scale on Twitter, Facebook or Instagram, they could conceivably influence an election. The same goes for so-called audio and video “deepfakes” created by manipulating voices and likenesses. Using “machine learning”, a subset of AI that’s involved in natural language processing, an audio clip of any given politician could be manipulated to make it seem as if that person spouted racist or sexist views when in fact they uttered nothing of the sort. If the clip’s quality is high enough so as to fool the general public and avoid detection, it could “completely derail a political campaign.” 

 

3. AI Bias: AI is developed by humans and humans are inherently biased. Pope Francis speaking at a Vatican meeting titled, “The Common Good in the Digital Age,” warned that AI has the ability to “circulate tendentious opinions and false data that could poison public debates and even manipulate the opinions of millions of people, to the point of endangering the very institutions that guarantee peaceful civil coexistence.”

 

4. Autonomous Weapons and Potential Arms Race: The key question for humanity today is whether to start a global AI arms race or to prevent it from starting, if any major military power pushes ahead with AI weapon development, a global arms race is virtually inevitable, and the endpoint of this technological trajectory is obvious: autonomous weapons will become the catastrophe for tomorrow. Unlike nuclear weapons, they require no costly or hard-to-obtain raw materials, so they will become ubiquitous and cheap for all significant military powers to mass-produce. It will only be a matter of time until they appear on the black market and in the hands of terrorists, dictators wishing to better control their populace, warlords wishing to perpetrate ethnic cleansing, etc. Autonomous weapons are ideal for tasks such as assassinations, destabilizing nations, subduing populations, and selectively killing a particular ethnic group. Therefore, a military AI arms race would not be beneficial for humanity. Latest example is Israel attacked Hamas (war commenced on 10/05/2021- Operation Guardian of the walls) with AI Technology. There are many ways in which AI can make battlefields safer for humans, especially civilians, without creating new tools for killing people. Hence, all the Governments of the world should think in this right direction for the safety of the whole word.

 

5. High Costs: The ability to create a machine that can simulate human intelligence requires plenty of time and resources and can cost huge money. It also needs to operate on the latest hardware and software to stay updated and meet the latest requirements.

 

6. No Creativity: A biggest disadvantage of AI is that it cannot learn to think outside the box. AI is capable of learning over time with pre-fed data and past experiences but cannot be creative in its approach. 

 

7. Job Automation/Increase in Unemployment: The reduction in the need for human interference has resulted in the death of many job opportunities. A simple example is the chatbot which is a big advantage to organizations, but a nightmare for employees. In India, where unemployment is already more due to huge population, AI growth may result further increase in unemployment.

 

8. Make Humans Lazy: AI Applications automate the majority of tedious and repetitive tasks. Since we do not have to memorize things or solve puzzles to get the job done, we tend to use our brains less and less. This addiction to AI can cause problems to future generations.

 

9. No Ethics: Ethics and morality are important human features that can be difficult to incorporate into an AI. The rapid progress of AI has raised a number of concerns that one day, AI will grow uncontrollably, and eventually wipe out humanity. This moment is referred to as the AI singularity.

India’s National Strategy of AI: In June 2018, NITI Aayog created a national approach for Artificial Intelligence in India. The report provided an introduction to the roadmap and the government’s plan to build the sector in the nation. Through sufficient implementation of the technique, Artificial Intelligence is anticipated to assist the nation to develop economically while contributing to public growth to a great extent. The government think tank have identified five sectors to focus its efforts towards implementation of AI to serve societal needs. The five sectors are:

• Healthcare: Increased access and affordability of quality healthcare.
• Agriculture: Enhanced farmers ‘income, increased farm productivity and reduction of wastage.
• Education: Improved access and quality of education.
• Smart Cities and Infrastructure: Efficient and connectivity for the burgeoning urban population.
• Smart Mobility and Transportation: Smarter and safer modes of transportation and better traffic and congestion problem.

In India, AI startups started emerging in the year 2016. A recent report estimated that around $87.85M was alone raised in the AI space in India’s startup capital, Bangalore. Top AI startups are located at cities – Bangalore, Hyderabad, Pune, Chennai, Mumbai, Delhi, Gurgaon, and Coimbatore. Top AI startup Companies in India are Manthan, SigTuple, Mad Street Den, Haptik, Flutura, Uncanny Vision, Arya.ai, Bash.ai and Niki.at. AI was among the domains that witnessed the fastest adoption among different industry sectors. Presently there are more than 400 startups working on AI and machine learning domains. About $150 million is invested in India’s AI industry by private players and the number has been increasing since 2016. These are working in the domains of healthcare, e-commerce, finance, etc. Clear Tax is developing a solution for e-filling using documents directly. AIndra is developing devices with computer vision ability for the applications like facial recognition, detection of cervical cancer, etc. Although there is progress in the field of AI in India, it is far behind countries like the US and China. With a large of growing youngsters, India will probably be banking on AI because of its economic development and enhancement in the quality of living of its people.

Indian Startups in Artificial Intelligence:

Startup		Task
Edge Networks		Matches the job seekers with jobs available
Fluid AI		Provides customer information on the products in an interactive way
Flutura		Monitors health of machines to advise on maintenance
Heckyl		Analyzes stock related information to advises on stock trading
Mad Street Den		Helps customers locate products using captured photos
ShopR360		Video analytics solution which can distinguish staff and customers
SigTuple		Affordable diagnosis solution using a microscope, cell phone and cloud
Social Cops		Interpretation of data
VPhrase		Converts structured data such as graphs, etc into words
Freenome		Analyzes genetic material to find disease signature at an early stage

 

Some Main prospects of AI in India:

• Digital assistants to be used by several highly advanced organizations to communicate with customers, saving the need for human resources.

• Together with other innovations, organizations can use AI to make machines take decisions faster than an individual and perform actions faster.

• In almost every area, AI powers several inventions that will help humans overcome the majority of complex issues.

• Trade and Development agreement to operate together to leverage the power of cutting-edge technology to improve and expand trade, such as AI and blockchain.

 

Additionally, companies like Google, Microsoft, Amazon are trying to achieve the government’s needs of cloud computing and machine learning. Private companies will rush to win big contracts, add to the stream of funds to create innovative technology, and establish new AI and data scientific startups as the Indian government pushes for digital transformation and introduces more AI initiatives.

 

Major Challenges of AI in India:

·         India has a comparatively small number of researchers in the field of machine learning and research production.

·         India has very little local awareness of the latest knowledge that is being generated by others each day.

·         Given the existing and potential possibilities, Indian businesses have been reluctant to accept AI.

·         Despite the number of available standard packages, India does not have sufficient qualified personnel to apply machine learning to its own challenges and data.

·         In its capacity to handle challenges, current AI strategies are minimal, and they will have to develop to deal with the complexity of life in India.

 

In general, India’s digital footprint has seen tremendous growth. The government is also moving different programs toward the objective of technical infrastructure. Different agencies and artificial intelligence institutes including sectors are developing policy structures and programs that instill such skills. With a little more drive towards resources and frameworks that boost its development, the Indian artificial intelligence market, which is still regarded as emerging, can certainly take a leap.

Future Outlook of AI in India: India has a unique opportunity in the field of AI, using the talent available within the country, it can repeat the success story of IT industry. But, at the same time, if necessary steps are not taken in time, it will lose the opportunity. AI can help in the major programmes of the Government viz. Digital India, Make in India, and Skill India. In order to accelerate development of AI technology and its applications, it is necessary to take steps for Applications & Infrastructure Development, Policy & Regulations, Research & Development and Human Resource Development. As in other countries, India can gain significantly by the adoption of AI technology. Most of the applications developed elsewhere in the world can be developed in India as well. However, the applications have to be customized for the local needs. Few example: A virtual nurse can be developed to share the workloads of the human nurses. Due to lack of human resource in the public healthcare facilities in India, a nurse is often overloaded. A large number of people suffer from the complications after the treatment as they are not informed properly on the precautions which have to be taken. This type of information can be provided to the patients using an AI-based system. Similarly, a chatbot can be developed to advise the patients on several health-related matters in natural language. In India, mental illness is often not treated due to lack of awareness. Fortunately, the country has a high level of mobile penetration. Such applications can be easily made available on mobile devices. Applications like Do Not Pay can be used to help people by providing relevant legal information. Such applications are quite relevant for Indian society where a large percentage of the population is ignorant about the laws and procedures. Similarly, some of the areas where such applications can be developed include dowry matters, domestic violence, consumer rights protection, violence against children, taxation, etc. To start with, systems with natural language interface in English can be developed. Later on, it can be extended to other languages, and finally to speech-based systems.

AI-based education systems or intelligent tutoring systems will be useful in improving the quality of education by the existing teachers, especially in professional education. Shortage of meritorious teachers is a common problem in all types and levels of education in the country due to several reasons. Use of natural language processing makes it possible for the student to interact with the application in natural language. AI-based system is not expected to replace human teacher but can be used to provide supplementary information. The government must create infrastructure to support development of AI applications. One critical infrastructure is cloud which is needed for the development of applications. AI applications for public goods can be developed only if we have adequate infrastructure for making it available to the developers. Often public data is not made available for privacy reasons. However, such data can be anonymized before making it available. High speed network is another requirement necessary for development of AI applications. This is essential to collect and share large amount of data. Though connectivity has become available in urban areas, it remains a problem for rural and remote areas.

While our universities and premier technology institutes are carrying out research in AI, tech startups and enterprises are taking the analysis further and creating jobs to think of innovative ways and goods based upon AI. Today, India is a house to more than 7,700 tech startups. This demonstrates how Indian tech startups are centered on AI product development. In the near future, we are going to see smart cities adopting AI to handle traffic, identify traffic violations, deal with the cleanliness or may be health of roads, track blacklisted folks and do behavioral biometry. AI require solid basics in Mathematics and core Programming. Students also require access to high-performance computers to have the ability to instruct, check and deploy their AI models. In the last decade, the mobile phone has come to determine the digital experience for new customers. That could be changing. Many voice artificial intelligence (AI) startups want to create these sorts of “post-mobile” happenings a reality for their clients worldwide and in India. The future scope of AI keeps on increasing due to new job roles and advancements in the AI sector. They are: AI analysts and developers, AI engineers and scientists, AI researchers, AI algorithm specialist, Robotics expert, Military and aviation experts, Maintenance and mechanical engineers, Surgical AI technicians, Robot Personality Designer, Robot Obedience Trainer, Autonomous Vehicle Infrastructure Designer, Algorithm Trainers / Click Workers and AI Cybersecurity Expert .

Conclusion: In view of the recent advances in the area of AI, it has become necessary for our country to prepare an action plan to take the benefits of the opportunity and at the same time to deal with the challenges like job loss issue. It needs to be identified the priority areas for investment in technology development to build AI-based solutions. Government has a major role to play in AI in infrastructure development applications in public sector, policy & regulations, research & development, and human resource development, and at the same time, all the stakeholders need to come together to discuss on the issues involved to promote AI in our country.

References:

1. A Complete History of AI https://www.g2.com/articles/history-of-artificial-intelligence
2. Types of AI https://www.forbes.com/sites/cognitiveworld/2019/06/19/7-types-of-artificial-
3. Importance of Artificial Intelligence in Social Transformation in India https://idronline.org/artificial-intelligence-for-social-change/
4. AI – A Way Forward https://www.researchgate.net/publication/331972425_Artificial_Intelligence_Way_Forward_for_India
5. Advantages and Disadvantages of Artificial Intelligence (AI)

https://towardsdatascience.com/advantages-and-disadvantages-of-artificial-intelligence-182a5ef6588c

https://www.analytixlabs.co.in/blog/advantages-disadvantages-of-artificial-intelligence/

6.      AI in Cyber Security Wirkuttis & Hadas, 2017 https://www.inss.org.il/wp-content/uploads/2017/03/Artificial-Intelligence-in-Cybersecurity.pdf

7. India’s National Strategy of AI http://niti.gov.in/national-strategy-artificial-intelligence
8. Major Challenges of AI in India https://www.iastoppers.com/articles/opportunities-and-challenges-for-artificial-intelligence-in-india-mains-article
9. Future Out Look of AI in India https://www.analyticsinsight.net/artificial-intelligence-growth-and-development-in-india/
10. Future Scope of AI in India https://www.jigsawacademy.com/blogs/ai-ml/artificial-intelligence-scope-in-india/