AI is growing in popular technology with various uses can be seen in many aspects of life. AI has many positive effects and creates social benefits. AI applications can improve health and living conditions, facilitate justice, create wealth, enhance public safety, and reduce the impact of human activities on the environment and climate (Montreal Declaration 2018). AI is a tool that can help people do their jobs faster and better, creating many benefits. But, beyond that, AI can also facilitate new tasks, for example by analyzing research data on an unprecedented scale, thus creating an expectation of scientific knowledge. can be beneficial in all aspects of life. In this paper we are describing negative effects of AI.
Despite widespread unfamiliarity, AI is a technology that can transform every area of ??life. It is a giant tool that allows people to rethink how we integrate information, analyze data, and use the resulting information to improve decision-making. Our hope through this comprehensive review is to explain AI to an audience of decision-makers, thought leaders, and interested observers, and demonstrate how AI has changed and is changing. change the world and raise important questions for society, the economy, and governance
The preface to the term "AI" was the 1956 Dartmouth Summer Research Project on Artificial Intelligence, where the term was coined by McCarthy and colleagues (McCarthy et al. 2006). In their proposal for this project, McCarthy et al. suggested that machines could be built to simulate "every aspect of learning or any other characteristic of intelligence", the use of language, the formation of concepts and abstractions, the interpretation of solving problems that are currently open to people and self-improvement.
This highlights the first problem in understanding AI, which is the goal of replicating or mimicking its intelligence. Intelligence itself is a controversial concept, and it's unclear what intelligence or intelligence an AI should reproduce to deserve to be called AI.
A. Perspectives OF AI
Machine learning as a prime example of a close understanding of AI, i.e. a technique that successfully reproduces very specific cognitive processes
AI as a synonym of Convergence of social engineering systems includes but goes beyond narrow AI technologies.
II. ARTIFICAL INTELLIGENCE PLAY USEFUL ROLES IN EVERY FIELD LIKE IN MEDICAL APPLICATIONS
Doctors assess patients and their health risks with the help of artificial machine intelligence.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 also helps in the radio surgery. Radio surgery is used in operating tumours and help in the operation without damaging the surrounding tissues and machine need no breaks like the humans do they are programmed for long times and can continuously perform without getting bored or distracted machines does not get tired .their efficiency is not affected by any external factor and it does not get in the way of continuous work. And overall this performance machine always take right decision .This is the level of AI. It reaches the place where humans can’t reach. Thus, helps to solve issues in a jiffy.
In 2013, the Oxford Martin School released a report predicting that 7% of jobs in the US could be threatened by NEW technologies like AI. within two decades due to advances in AI technology. Last year, the administration raised similar concerns in a presidential report on AI. The AND report, titled “Artificial Intelligence, Automation, and Economics,” concludes that AI-driven automation demonstrates the need for active public policies and strong safety nets. than to deal with work interruptions. Of course, projections of total job losses are fundamentally uncertain. Experts disagree on the size of the impact that new technologies will have on the workforce. While some warn of staggering unemployment, others point out that technology may create new job categories that will employ displaced workers. A third group argues that the computers will have little effect on employment in the future. Any policy measures that address the future of employment must account for the uncertainty of outcomes on employment.
If automation technologies like robots and artificial intelligence make jobs less secure in the future, there needs to be a way to deliver benefits outside of employment. “Flexicurity,” or flexible security, is one idea for providing healthcare, education, and housing assistance whether or not someone is formally employed. Extending the income tax credit, providing a guaranteed basic income, and encouraging companies to share profits are ideas that should be considered in the event of prolonged unemployment.
Its cost is very high apart from installation cost, it repair and maintenance also require huge cost.
Machines cannot create. They can only do what is taught or commanded to them. While they help with design and creativity, they can't match the power of the human brain. People are sensitive and intelligent and they are also very creative. They can generate ideas, think outside the box. They see, hear, think and feel, which machine cannot. Feelings guide your thoughts, which machines absolutely lack. No matter how much the machine outgrows, it does not have the intuitive abilities of the human brain, and it cannot reproduce them.
The main problem with GDP stagnating or growing at the expected rate is unemployment. People without the necessary skills are in demand. There is a big gap between supply and demand because of this. This is the riskiest and can have serious consequences. With capital-intensive technologies, the human-intensive need has diminished in some industries. If in the future humans don't add their skills, we may soon find that they will be replaced by machines.
All that said, with the pros and cons of artificial intelligence weighed, it depends on the reader, the user, and their point of view. AI and robotics will improve the way we think, the way we explore new horizons, whether it\'s space or the ocean.
As it is said, necessity is the mother of all innovation, so is AI. People know what they need and better define their needs and quickly turn them into reality. If AI surpasses humanity in general intelligence and becomes \"super intelligent\", then it could become difficult or impossible for humans to control. . A second source of concern is that a sudden and unexpected \"intelligence explosion\" might take an unprepared human race by surprise.
 American Association for Artificial Intelligence (AAAI), Welcome to AI Topics, 2003, http://www.aaai.org/AITopics/ -- a Web-based library of introductory information about various areas of artificial intelligence; altogether, a resource with links to hundreds (thousands?) of sites, organized by an easy-to-use, interactive index.
 George Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Fourth Edition Addison-Wesley, 2002 -- a well-respected introduction to artificial intelligence, as witnessed by its being in its fourth edition.
 Peter Norvig, AI on the Web, http://aima.cs.berkeley.edu/ai.html -- a list of over 800 links on various aspects of artificial intelligence.
 Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan Kaufmann Publishers, 1998 -- another fine introductory textbook on artificial intelligence.
 Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Second Edition, Prentice-Hall, 2003 -- the leading introductory textbook in the field.
 American Association for Artificial Intelligence, Expert Systems, http://www.aaai.org/AITopics/html/expert.html -- an on-line index of materials, including tutorials on the subject. Highly recommended as a starting point for readings on the subject.
 Virginia Barker and Dennis O\'Connor \"Expert Systems for Configuration at Digital: XCON and Beyond\", Communications of the ACM, Volume 32, Number 3, March 1989, pp. 298-317.
 Daniel Bobrow et al, \"Expert Systems: Perils and Promise\", Volume 29, Number 9, September 1986, pp. 880-894.
 Joseph Giarratano and Gary Riley, Expert Systems: Principles and Programming, Third Edition Brooks/Cole Publishers, 1998.
 Frederick Hayes-Roth, \"The Knowledge-Based Expert System: A Tutorial\", IEEE Computer, Volume 18, Number 9, September 1984, pp. 11-28.
 Frederick Hayes-Roth, \"Rule-Based Systems\", Communications of the ACM, Volume 28, Number 9, September 1985, pp. 921-932.
 Peter Jackson, Introduction to Expert Systems, Third Edition, Addison-Wesley, 1998.
 Gary Riley, CLIPS: A Tool for Building Expert Systems, 2002. (a Web site that provides software and support for building expert systems; the software is based in standard C for portability)
 Scandia National Laboratories, Jess: the Rule Engine for the Java Platform, 2003. (a Java-based expert system and environment, originally based on CLIPS)
 Henry Walker, Vikram Subramaniam, and Ivan Sykes, \"An Expert System to Place Incoming Students in Math and CS Classes\", Journal of Computer Science Education, Volume 3, Number 3, 1992, pp. 223-232.