Artificial Intelligence (AI), also known as the Industrial Revolution 4.0, has been making deep strides in scientific and technological innovation across different fields. It is capable of bringing considerable transformations in the way civilian activities and military operations are conducted. However, there are also concerns regarding the AI’s implications for employment and other ethical issues.
What is Artificial Intelligence (AI)?
- It is a branch of computer science that deals with creating computers or machines as intelligent as human beings.
- It refers to the ability of the machines to perform human intelligence processes like thinking, perceiving, learning, problem-solving and decision making.
- Thus in simple terms, Artificial Intelligence is the intelligence showed by machines.
- The term Artificial Intelligence was coined by John McCarthy in 1956 at the Dartmouth conference, Massachusetts Institute of Technology (MIT).
- There are two subsets under the Umbrella term AI, they are – Machine Learning and Deep Learning.
What is the difference between Machine Learning and Deep Learning?
- A subset of artificial intelligence that deals with the creation of algorithms that can modify itself without human intervention to generate desired output- by feeding itself via structured data.
- Machine learning algorithms are built to “learn” to do things by understanding labeled data, then use it to produce further outputs with more sets of data. However, they need to be retrained through human intervention when the actual output isn’t the desired one (errors).
- A subset of machine learning where algorithms are created and function similar to those in machine learning, however, there are different layers of these algorithms- each providing a different interpretation to the data it feeds on.
- Such a network of algorithms is known as artificial neural networks, as it imitates the function of the human neural networks present in the brain.
- Deep learning networks do not need human intervention as the nested layers in the neural networks put data via hierarchies of different concepts, which eventually learn from their own errors. But even these are subject to flawed outputs if the quality of data is not good enough.
To put it simply, the key difference between deep learning and machine learning stems from the way data is presented to the system. Machine learning algorithms almost always require structured data, whereas deep learning networks rely on layers of the ANN (artificial neural networks). Thus Data is the governor here. It is the quality of data which ultimately determines the quality of the result.
What are some of the examples of Artificial Intelligent Technologies?
- Robotics and Automation: Robots can be programmed to perform high-volume, repeatable tasks normally performed by humans.
- Natural Language Processing (NLP) is the processing of human language by a computer program. For example, spam detectors look at the subject line and text of an email in order to decide whether it is junk.
- Pattern recognition is a subset of machine learning that seeks to identify patterns in data. For example, a machine learning program can differentiate cats from dogs among 1000 images of cats and dogs through pattern recognition like face, whiskers, etc.
- Machine vision is the science of giving computers a vision by capturing and analyzing visual information using a camera, analog-to-digital conversion, and digital signal processing. It is mostly compared to human eyesight, however, machine vision is not constrained by biology = it can even be programmed to see through walls.
What are the applications/advantages of Artificial Intelligence (AI)?
Self-driving Cars: AI algorithms are one of the primary components that facilitate self-driving cars to make sense of their surroundings, taking in feeds from cameras installed around the vehicle and detecting objects like roads, traffic signs, other cars, and people.
Digital assistants and smart speakers: Siri, Alexa, Cortana, and Google Assistant utilise artificial intelligence to convert spoken words to text and map the text to certain commands. AI assists digital assistants to make sense of various nuances in spoken language and synthesize human-like voices.
Translation: For several decades, translating text between various languages was a pain point for computers. But deep learning created a revolution in services such as Google Translate. But to be precise, AI still has a long way to go before it perfects human language, but so far, the advances are outstanding.
Facial recognition: Facial recognition is one of the most prominent applications of artificial intelligence. It has different uses, including unlocking your phone, paying with your face, and detecting intruders in your home.
- In the medical field also, we will find the wide application of AI. Doctors assess the patients and their health risks with the help of artificial machine intelligence. It educates them about the side effects of various medicines.
- Medical professionals are often trained with artificial surgery simulators. It finds a huge application in detecting and monitoring neurological disorders as it can simulate the brain functions.
- Robotics is often used in helping mental health patients to come out of depression and remain active.
- A popular application of artificial intelligence is radiosurgery. Radiosurgery is used in operating tumours and this can actually help in the operation without damaging the surrounding tissues.
Agriculture Sector: AI can be utilised to predict advisories for sowing, pest control, input control = enable increased income and giving stability for the agricultural community. Image classification tools in addition to remote and locally sensed data can bring a revolutionary change in – utilisation and efficiency of farm machinery, weed removal, early disease identification, harvesting, and grading.
- In order to take care of highly repetitive tasks – robotic automation is applied which perform faster, effortlessly and tirelessly than humans.
- Moreover, Machine learning algorithms are being integrated into analytics and CRM (Customer Relationship Management) platforms to provide better customer service. Chatbots being used in the websites to provide instant service to customers.
- Automation of job positions has also become a discussion point among academics and IT consultancies like Gartner and Forrester.
- Artificial Intelligence can make certain educational processes automated like grading, rewarding marks, etc. thus giving educators more time.
- Furthermore, it can analyse students and adapt to their requirements so as to help them work at their own pace.
- AI can change where and how students learn, perhaps even replacing a few teachers.
- AI is applied to personal finance applications and could compile personal data and give financial advice. In fact, nowadays software trades more than humans in Wall Street.
- Detection of financial fraud uses artificial intelligence in a smart card-based system.
Legal Sector: Automation can result in a faster resolution of pending cases by minimising the time taken while analyzing cases = better use of time and more efficient legal & judicial processes.
Manufacturing sector: Robots are being utilised for manufacturing since a long time now but more advanced exponential technologies have emerged like additive manufacturing (3D Printing) which with the support of AI can revolutionize the whole manufacturing supply chain ecosystem.
Intelligent Robots: Robots can do the tasks given by a human with the help of sensors to detect physical data from the real world like light, heat, temperature, movement, sound, bump, and pressure. Furthermore, they have effective processors, multiple sensors and enormous memory, to showcase intelligence. Also, they can learn from their errors and hence can adapt to the new environment.
Gaming: AI has a significant role in strategic games like chess, poker, tic-tac-toe, etc., where the machine can think of a huge number of possible positions according to heuristic rule (A set of rules intended to increase the probability of solving some problem).
Smart Cities and Infrastructure: AI is used to monitor patronage and accordingly control associated systems such as pavement lighting, park maintenance, and other operational conditions = lead to cost savings + improving safety and accessibility.
Space sector: Intelligent robots are fed with information and are sent to explore space. Since they are machines with metal bodies, they are more resistant and have a higher ability to endure the space and hostile atmosphere. Because they are created in such a way that they cannot be modified or get disfigured or breakdown in a hostile environment.
Mining sector: Artificial intelligence and the science of robotics can be put to use in mining and other fuel exploration processes. Not only that, these complex machines can be used for exploring the ocean floor and hence overcome the human limitations.
Defence Sector: Artificial Intelligence (AI) based tools would aid the defence forces constructively in areas such as decision support, sensor data analysis, predictive maintenance, situational awareness, accurate data extraction, security, etc. These tools will assist defence personnel in better operations, maintenance, and logistics support.
What are the concerns with the AI?
- Replacement of humans with machines can lead to large-scale unemployment. Unemployment is a socially undesirable phenomenon. People with nothing to do can lead to the destructive use of their creative minds.
- Humans can unnecessarily be highly dependent on the machines if the use of artificial intelligence becomes rampant. They will lose their creative power and will become lazy.
- Also, if humans start thinking in a destructive way, they can create havoc with these machines.
- If you have an issue with your current human boss, be thankful that he isn’t a cold, emotionless machine because AI is already being used to monitor employee productivity.
- In what seems like the scary nightmares of a dystopian future, IBM’s Watson has been using AI and Watson Analytics to decide if employees are worthy of a pay rise, a bonus or a promotion by looking at the experience and past projects of employees to judge the qualities and skills that individuals might have to serve the company in the future.
- Although AI can virtually remove human error from processes, it can still exist in the code, along with bias and prejudice.
- Being largely algorithm-based, technology can be coded to have a negative impact on certain demographics and discriminate against people.
- For example, Microsoft’s ill-fated chatbot, Tay Tweets, had to be taken down after only 16 hours after it started to tweet racist and inflammatory content – ideas it repeated from other Twitter users.
- Worryingly, if security is not 100%, hackers can take advantage of AI’s thirst for knowledge.
- Creation of artificial intelligence requires huge costs as they are very complex machines. Their repair and maintenance require huge costs.
- They have software programs which need frequent up-gradation to cater to the needs of the changing environment and the need for the machines to be smarter by the day.
- In the case of severe breakdowns, the procedure to recover lost codes and reinstating the system might require huge time and cost.
Not ethical to replicate Humans:
- Intelligence is believed to be a gift of nature. Therefore an ethical argument continues, whether human intelligence is to be replicated or not.
Cannot replicate Humans:
- Machines do not have any emotions and moral values. They perform what is programmed and cannot make the judgment of right or wrong. They cannot take decisions if they encounter a situation unfamiliar to them. They either perform incorrectly or breakdown in such situations.
- Unlike humans, artificial intelligence cannot be improved with experience. With time, it can lead to wear and tear. It stores a lot of data but the way it can be accessed and used is very different from human intelligence.
- Machines are unable to alter their responses to changing environments.
- In the world of artificial intelligence, there is nothing like working with a whole heart or passionately. Care or concerns are not present in the machine intelligence dictionary. There is no sense of belonging or togetherness or a human touch. They fail to distinguish between a hardworking individual and an inefficient individual.
No Original Creativity:
- While the AI can help you design and create, they are no match to the power of thinking that the human brain has or even the originality of a creative mind.
- Human beings are highly sensitive and emotional intellectuals. They see, hear, think and feel. Their thoughts are guided by the feelings which completely lacks in machines. The inherent intuitive abilities of the human brain cannot be replicated.
Privacy & Security:
The increasing accessibility of facial-recognition technology has also increased concerns with respect to privacy, security, and civil liberties.
What is the global status of AI adoption?
- China and the U.K. estimate that by 2030, about 26% and 10% of their GDPs respectively will be sourced from AI related activities and businesses.
- There have been numerous activities regarding AI policy positions and the development of an AI ecosystem in various countries in recent years.
- Infrastructural supply-side initiatives have been planned by several countries for building a larger ecosystem of AI development.
- Even local/city governments have become increasingly aware of the significance and potential of AI and have committed public investments.
- For creating the future workforce for AI, countries are also significantly increasing the allocation of resources for Science, Technology, Engineering and Maths (STEM) talent development via investment in universities, mandating new courses (e.g., AI and law), and launching schemes to retrain people.
- AI technology development and applications are rapidly evolving with major implications for economies and societies. A study by EY and NASSCOM found that by 2022, about 46 percent of the workforce will be engaged in entirely new jobs.
What are the possible areas for AI applications in Indian conditions?
- India has the potential to position itself among leaders on the global AI map – with a unique brand of #AIforAll.
- It can complement Digital India Mission by helping in the big data analysis which is not possible without using AI.
- Targeted delivery of services, schemes, and subsidy can be further fine-tuned.
- Smart border surveillance and monitoring to enhance security
- Weather forecasting models may become proactive and therefore preplanning for any future mishaps such as floods, droughts and therefore addressing the farming crisis, farmer’s suicide, crop losses, etc.
- By analyzing big data of road safety data and NCRB (National Crime Record Bureau) data for crimes, new policies can be formulated.
- Disaster management can be faster and more accessible with the help of robots and intelligent machines.
- In the counterinsurgency and patrolling operations, we often hear the loss of CRPF jawans which can be minimized by using the robotic army and lesser human personnel.
- AI can be used to automate government processes, therefore, minimizing human interactions and maximizing transparency and accountability.
- It can be applied to study ancient literature upon medicines and therefore help in modernizing the health care with the juxtaposition of modern machines and ancient techniques.
- In the remotest areas where the last leg of governance is almost broken, AI can do the job. For Example: in the tribal areas and the hilly areas of the northeast.
What are the measures taken by the government to promote AI?
- A Task Force on Artificial Intelligence (AI) for India’s Economic Transformation was constituted on 24th August 2017. The Task Force gave its report on 19th January 2018. It has recommended an Inter-Ministerial National Artificial Intelligence Mission to act as a nodal agency for coordinating AI related activities in India.
- NITI Aayog unveiled its discussion paper on national strategy on AI which seeks to guide research and development in new and emerging technologies. NITI has identified 5 sectors – healthcare, agriculture, education, smart cities and infrastructure, and transportation – to focus its efforts on the implementation of AI. The paper focusses on how India can leverage transformative technologies to ensure social and inclusive growth.
- In order to create a policy framework and to develop the ecosystem for Artificial Intelligence, Ministry of Electronics & Information Technology, has constituted four committees covering all the aspects of AI. These Committees are:
- Committee on platforms and data for AI,
- Committee on leveraging AI for identifying National Missions in key sectors,
- Committee on mapping technological capabilities, key policy enablers, skilling, re-skilling and R&D
- Committee on cybersecurity, safety, legal and ethical issues.
- Task Force created by Ministry of Defence has studied research and innovation in Artificial Intelligence (AI) and outlined its adoption in defence sector including a future roadmap on how to integrate and embed AI strategy with a core defence strategy.
- In addition, the Defence Public Sector Undertakings and Ordnance Factories have been assigned a roadmap for developing AI-enabled products.
- Centre for artificial intelligence and robotics (CAIR), is the main laboratory of DRDO for research and development in various areas of defense, Information and Communication Technology (ICT) and is located in Bangalore. It is involved in the Research & Development of high-quality Secure Communication, Command, and Control, and Intelligent Systems.
- Projects: NETRA- software to intercept online communication, SECOS- Secure operating system.
What are the challenges to India’s Artificial Intelligence Development?
- Lack of enabling ecosystems for data collection and usage.
- The low intensity of AI research.
- Insufficient availability of AI expertise, manpower and skilling opportunities.
- High resource cost and low awareness for adopting AI in business processes.
- Unclear privacy, security and ethical regulations.
- Unattractive Intellectual Property regime to incentivise research and adoption of AI.
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What needs to be done?
- Incentivising creation of jobs in AI fields that could constitute the new service industry.
- Recognition and standardisation of informal training institutions.
- Creation of open platforms for learning and financial incentives for reskilling of employees.
- Lack of qualified faculty that poses a serious problem in the present scenario can be addressed through innovative measures such as MOOCs (Massive Open Online Courses).
- Acceptability and adoption of these decentralised teaching mechanisms can be ensured through prescribed certification in collaboration with the private sector and educational institutions.
- Additional investment and collaboration with the private sector and educational institutions in order to meet the market demand.
- To encourage the development of sustainable AI solutions at an appropriate price point for sectors such as health, education, and agriculture, it is necessary that a level playing field is ensured and an enabling environment be created for all players in the value chain.
- AI is a highly collaborative domain, and any framework aimed at promoting AI needs to be aligned accordingly. A multipronged approach, involving various stakeholders and promoting a collaborative approach is required for promoting the development of AI tools as well as the adoption of AI in various fields of activity.
Despite the threats and challenges, it would be foolish to argue that Artificial Intelligence (AI) is not the future and it’s only a matter of time that machines will replace most of the jobs. It is because AI is not the end of the road for humanity as we have a history of technological revolutions resulting in positive social and political changes in society such as steam engines, industrial revolutions and most recently the computers and internet. Nonetheless, there will be several opportunities in the fields not yet known and there will be more jobs to serve human needs.
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