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Future Aspects of Artificial Intelligence
Pratik2nd Year IT Branch
MITS Engineering CollegeRayagada, Odisha
Rahul Abhishek2nd Year IT Branch
MITS Engineering CollegeRayagada, Odisha
Payal Sinha2nd Year IT Branch
MITS Engineering CollegeRayagada, Odisha
ABSTRACTIn this paper, we discussed about the future aspect of Artificial Intelligence (AI). First we discuss what is AI? How it will be used in future. Since AI is one of the branches of computer science which aims at building machines that can think, feel and take decisions just like humans do. It is used in Expert systems, Robotics, Neuroscience, Gaming, and in many more fields. It can be classified into two types first one is strong artificial intelligence and other is weak artificial intelligence. As the world is going towards advance technologies AI seems to be the most emerging technology between us. Emerging technologies and programming techniques increase our ability to create intelligent software programs. With the advent of viable neural networking solutions, we have come even closer to building artificially intelligent machines. This paper outlines the future aspect of artificial intelligence (AI). Computer systems will continue to get more powerful, and will become increasingly ubiquitous in the future, making the standards of development of artificial intelligence a salient topic in modern engineering.
Development of a strong artificial intelligence would surely call into question (for some) that which we define as “alive.”
Keywords
Artificial Intelligence (AI), Expert systems, Robotics, Neuroscience, Gaming, Strong AI, Weak AI.
INTRODUCTIONDefining AI succinctly is difficult because it takes so many forms. One area of agreement is that artificial intelligence is a
field of scientific inquiry, rather than an end product. The best definition is coined by M.L. Minsky, "Artificial intelligence is the science of making machines do things that would require intelligence if done by men." Computers have made our lives very easy. They can perform tasks at the speed of one click which we humans would take hours to do. On top of that they are much more efficient than humans, and unlike humans, never feel exhausted. Artificial Intelligence (AI) is a perfect example of how sometimes science moves more slowly than we would have predicted. The computers that impressed us so much back then do not impress us now, and we are soberly settling down to understand how hard the problems of AI really are. Now an expert system is an interactive computer based decision tool that uses both facts and heuristics to solve difficult decision making problems, based on knowledge acquired from an expert. It is a
model and associated procedure that exhibits within a specific domain and it is compared with traditional computer.
(Algorithm + Data structure = Program in traditional computer)
The connection between AI and robotics is means to control the robot with a software agent that reads data from the sensors decides what to do next and then directs the effectors to act in the physical world.AI can be used to handle nano-robots which will perform all molecular repairs in human bodies making it effectively immortal.In gaming AI is used to learn a large variety of ways through which the creatures learn about its surroundings, how to do certain task, how sensitive to its desire, and which method is applied in certain situations.
WHAT IS ARTIFICIAL INTELLIGENCE (AI)? Artificial Intelligence (AI) is usually defined as the science of making computers do things that require intelligence when done by humans. AI has had some success in limited, or simplified, domains. However, the five decades since the inception of AI have brought only very slow progress, and early optimism concerning the attainment of human-level intelligence has given way to an appreciation of the profound difficulty of the problem. AI textbooks define the field as "the study and design of intelligent agents” where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. It is also define as "the science and engineering of making intelligent machines."
2.2 Types of Artificial intelligence The AI is broken down into to groups
• Weak AI • Strong AI
Weak AI: - IT refers to technology that is able to manipulate predetermined rules and apply the rules to reach a well-defined goal. The most inspirational technologies that are emerged from the development of weak AI are the robotics, genetics, and nanotechnological revolution. These three are linked together.
Weak AI is presently in use and has a very promising future, but is this technology truly intelligent?
Strong AI: - It refers to technology that has the ability to think cognitively or is able to function in a way similar to the human brain. Although strong AI is still only in the conceptive stage, it is this technology that is the fuel that drives the fear associated with artificial intelligence. Strong AI, which is in its infant stage, promises a lot due to the recent developments in nanotechnology. Nanobots, which can help us fight diseases and also make us more intelligent, are being designed. Furthermore, the development of an artificial neural network, which can function as a proper human being, is being looked at as a future application of Strong AI.
2.3 History of Artificial intelligence Charles Babbage (1792-1871), an English mathematician, is generally acknowledged to be the father of modern computing. Around 1823 he invented a working model of the world's first practical mechanical calculator. Then, he began work on his "analytical engine," which had the basic elements of a modern-day computer. Unfortunately, he was unable to raise the funds needed to build his machine. Nevertheless, his ideas lived on.
Herman Hollerith (1860-1929), an American inventor, actually created the first working calculating machine, which was used to tabulate the results of the 1890 U.S. census. There ensued a series of rapid improvements to machines which allegedly "thought." The first true electronic computer, the Electronic Numerical Integrator and Computer (ENIAC), was developed in 1946. The so-called "giant brain" replaced mechanical switches with glass vacuum tubes. ENIAC used 17,468 vacuum tubes and occupied 1,800 square feet—the size of an average house. It weighed 30 tons. Scientists began at once to build smaller computers.
In 1959, scientists at Bell Laboratories invented the transistor, which marked the beginning of the second generation of computers. Ten years later, International Business Machines Corp. (IBM) created third-generation computers when they replaced transistors with integrated circuits. A single integrated circuit could replace a large number of transistors in a silicon chip less than one-eighth of an inch square! New software that made use of increased speed and memory complemented these third-generation computers—which themselves proved to be short lived.
Only two years after the appearance of integrated circuits, Intel Corp. introduced microprocessor chips. One chip contained a computer's central processing unit. Prior to that time, computers contained specialized chips for functions such as logic and programming. Intel's invention placed all of the computers' functions on one chip. Scientists continued to improve on computers.
Miniaturization of chips led to large-scale integrated circuitry (LSI) and very-large-scale integrated circuitry (VLSI). They also contributed to the invention of microcomputers, which
revolutionized the role of computers in business. More importantly, LSI and VLSI heightened scientists' interest in the development of Al.
fig. (1) The evolution of Artificial Intelligence
FUTURE ASPECTS OF AIArtificial Intelligence is often misunderstood. People’s eyes often glaze over when we discuss AI. However, there is a common misconception that to understand AI requires an IQ of 200 and a PHD in rocket science. Artificial intelligence in the future will churn out machines and computers, which are much more sophisticated than the ones that we have today. For example, the speech recognition systems that we see today will become more sophisticated and it is expected that they will reach the human performance levels in the future. It is also believed that they will be able to communicate with human beings, using both text and voice, in unstructured English in the coming few years. However, will artificial intelligence be able to create machines that are self-aware and even more intelligent than human beings - is a question that nobody has an answer to. Also, even if this is possible, how much time it is going to take, cannot be predicted at present.
fig. (2) Artificial intelligence robots
It is expected that in the future, such machines will be developed, which have basic common sense, similar to human beings, although pertaining to specific areas only. It is also expected that the human mind functions, such as learning by experience, learning by rehearsal, cognition and perception will also be performed by future intelligent machines. In fact, research and experiments are being conducted to recreate the human brain. CCortex, a project by Artificial Development Inc.,
California, and Swiss government's IBM sponsored Blue Brain Project, are two main ventures, whose goal is to simulate the human brain. Whether this brain will have human consciousness incorporated in it - there is still no answer for that.
fig: (3) Artificial intelligent robots learning from human
It is expected that the robots in future, will take on everybody's work. Whether it is office work or the work at home, robots will accomplish it even faster and efficiently than human beings. So if somebody's falling ill, they can obtain a robot nurse who will give periodic medicines to them. How much care, concern and empathy the robot nurse will have towards the patient is anybody's guess! In spite of its great advances and strong promise, AI, in name, has suffered from low esteem in both academic and corporate settings. To some, the name is inexorably—and unfavorably—associated with impractical chess-playing computers and recluse professors trying to build a "thinking machine." As a result, many developers of Al theories and applications consciously shun the moniker, preferring instead to use the newer jargon of fuzzy applications, flexible software, and data-mining tools. In avoiding the label Al, they have found more receptive audiences among corporate decision-makers and private investors for their Al-inspired technologies.
1.1 Expert systems in AI Inference engine + Knowledge = Expert systemExpert systems are computer programs that are derived from a branch of computer science research called Artificial Intelligence (AI). AI's scientific goal is to understand intelligence by building computer programs that exhibit intelligent behavior.AI programs that achieve expert-level competence in solving problems in task areas by bringing to bear a body of knowledge about specific tasks are called knowledge-based or expert systems. . The area of human intellectual endeavor to be captured in an expert system is called the task domain. Task refers to some goal-oriented, problem-solving activity. Domain refers to the area within which the task is being performed. These are illustrated below in fig. 4
fig: (4) Component of expert systems
APPLICATION OF AI Artificial intelligence has different application in different sectors some are robotics, games, nanotechnologies, neuroscience, medicine, etc.
1.2 RoboticsRobots are manufactured as hardware. The connection between those two is that the control of the robot is a software agent that reads data from the sensors, decides what to do next and then directs the effectors to act in the physical world. Robots have become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. Japan is the leader in using and producing robots in the world. In 1999, 1,700,000 robots were in use worldwide.
fig: (6) Interaction by robot with the environment with the help of AI.
1.3 GamingAI is used in gaming technology to enhance the gaming experience by using it the creature used in games can learn automatically how to get over the challenges, learn how to interact with the environment and many other things. In present there are many games such as Black & White, F.E.A.R, Halo, Sim city etc. in which AI is used. The 1990s saw some of the first attempts to mass-produce domestically aimed types of basic Artificial Intelligence for education, or leisure. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy. AI has also been applied to video games.
fig: (7) Game with Robots
1.4 Neuroscience & MedicneA medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and provide medical information.
fig: (8) AI robots used in surgery
1.5 Online and telephone customer serviceArtificial intelligence is implemented in automated online assistants that can be seen as avatars on web pages. It can avail for enterprises to reduce their operating and training cost. A major underlying technology to such systems is natural language processing. Similar techniques may be used in answering machines of call centres, such as speech recognition software to allow computers to handle first level of customer support, text mining and natural language processing to allow better customer handling, agent training by automatic mining of best practices from past interactions, support automation and many other technologies to improve agent productivity and customer satisfaction.
RISK OF AIGlobal Catastrophic Risks, "Cognitive biases potentially affecting judgment of global risks".
The catastrophic scenario which stems from underestimating the power of intelligence is that someone builds a button, and doesn't care enough what the button does, because they don't think the button is powerful enough to hurt them. Or, since underestimating the power of intelligence implies a proportional underestimate of the potential impact of Artificial Intelligence, the (presently tiny) group of concerned researchers and grant makers and individual philanthropists who handle existential risks on behalf of the human species, will not pay enough attention to Artificial Intelligence.
5.1 Artificial minds can be easily copied. Since artificial intelligences are software, they can easily and quickly be copied, so long as there is hardware available to store them. Artificial minds could therefore quickly come to exist in great numbers, although it is possible that efficiency would favor concentrating computational resources in a single super-intellect.
5.2 Emergence of super intelligence may be sudden. It appears much harder to get from where we are now to human-level artificial intelligence than to get from there to super intelligence. While it may thus take quite a while before we get super intelligence, the final stage may happen swiftly.
5.3 Artificial intellects need not have human like motives. Human are rarely willing slaves, but there is nothing implausible
about the idea of a super intelligence having as its super goal to serve humanity or some particular human, with no desire whatsoever to revolt or to “liberate” itself. It also seems perfectly possible to have a super intelligence whose sole goal is something completely arbitrary, such as to manufacture as many paperclips as possible, and who would resist with all its might any attempt to alter this goal. For better or worse, artificial intellects need not share our human motivational tendencies.
5.4 Artificial intellects may not have human like psyches. The cognitive architecture of an artificial intellect may also be quite unlike that of humans. Artificial intellects may find it easy to guard against some kinds of human error and bias, while at the same time being at increased risk of other kinds of mistake that not even the most hapless human would make.
CONCLUSIONThe field of AI has a reputation for making huge promises and then failing to deliver on them. Most observers conclude that AI is hard; as indeed it is. But the embarrassment does not stem from the difficulty. It is difficult to build a star from hydrogen, but the field of stellar astronomy does not have a terrible reputation for promising to build stars and then failing. The critical inference is not that AI is hard, but that, for some reason, it is very easy for people to think they know far more about Artificial Intelligence than they actually do.
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5. “Expert Systems: Introduction to First and Second Generation and Hybrid Knowledge Based Systems”, by Chris Nikolopoulos, (1997), Mercell Dekker INC.
