INTRODUCTION
Technology is one of the most important things in human civilization. In this modern era, the development of technology is growing rapidly. In everyday life, people are increasingly in need of technology assistance in their activities. Therefore, in technological development, artificial intelligence required as a supporting component to realize the desired technology. According to Oxford Dictionary (2010), definition of artificial intelligence is “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages” (p. 69). Artificial intelligence provides an opportunity for human development through improvement in learning and performance. Intelligence agent is very much found in the environment. One of the manifestation of intelligence agent is robot, which in nowadays robot has been widely used by humans to facilitate their activities. As stated by Ali A.Z (2011), robots are used to perform exploration and research into the ocean, poles and even into outer space, which environment is incompatible for human being. Artificial intelligence is completely useful to be applied when traditional methods are unsuccessful. There is a big opportunity that artificial intelligence will become familiar in the general public.
Many experts state that artificial intelligence may compete or even smarter than human brains, including scientific inventiveness, conventional wisdom, and social intelligence, thus, it must be considered as an essential factor to determine decisions in life and particularly in Islamic societies (Ali, 2011). The aim of this report to explain definition, history, methodology, application, advantages and disadvantages of artificial intelligence.
Definition of Artificial Intelligence
According to Pannu (2015), artificial intelligence is a machine or software’s that have the ability to reason, learn, gather knowledge, communicate, manipulate and perceive objects. artificial intelligence also has been artificial intelligence to perform narrow task and can outperformed humans in terms of finishing the task effectively. According to John McCarthy (1981), artificial intelligence as a shrewd machine that is the result of science and technology, mainly on discerning computer programs. Stuart Russell and Peter Norvig (2009) define artificial intelligence as “the designing and building of intelligent agents that receive percepts from the environment and take actions that affect that environment” (pg.1). Liu et al. (2018) define the function of artificial intelligence as extending and augmenting the efficiency of humans through the use of intelligent machines with the artificial intelligence of making humans and machines may harmoniously coexist together. Basically, artificial intelligence is a system that may perceive and act based on its environment that combines computer science, mathematics and other complex sciences.
From islamic perspective, according to Khalid Yong (2013), Quran Al-An’am 6:65, there are ‘Qaadir’ which means power or intelligence. The verse indicated power, thus Al-Quran interpret about artificial intelligence. In addition, ‘tasrif’ in the verse similar to recursive which artificial intelligence will not exist without recursive, the word ‘yafqahun’ means deep comprehension and deep education.
History of Artificial Intelligence
1) The gestation of artificial intelligence (1943–1955)
Artificial intelligence started from the first discovery by Warren McCulloch and Walter Pitts (1943) which consists of three sources, which are concept of the fundamental physiology and capacity of neurons in the cerebrum, a formal investigation of propositional philosophy due to Russell and Whitehead, and Turing’s hypothesis of computation (Russel & Norvig, 2009). In 1949, Donald Hebb introduced Hebbian learning as a new simple principle for transforming connection power between neurons (Russel & Norvig, 2009). In this era there are a number of inventions, but the most influential artificial intelligence is Turing’s vision (Russel & Norvig, 2009). Stuart Russell and Peter Norvig (2009) mentioned, “He gave lectures on the topic as early as 1947 at the London Mathematical Society and articulated a persuasive agenda in his 1950 article Computing Machinery and Intelligence. Therein, he introduced the Turing Test, machine learning, genetic algorithms, and reinforcement learning.” (pg. 17).
2) The birth of artificial intelligence (1956)
Princeton is a new place for other influential figures on the development of artificial intelligence (Russel & Norvig, 2009). In 1956, John McCarthey assembled several members to conduct a research called Darthmouth workshop, which consist of automata hypothesis, neural nets, and the investigation of intelligence (Russel & Norvig, 2009). Although the research was unsuccessful, two of the research members, Newell and Simon, have quietly found a program called Logic Theory (LT) which is capable to verify and obtain an easier way to complete Russel and Whitehead’s Principia Mathematica (Russel & Norvig, 2009).
3) Early enthusiasm, great expectations (1952–1969)
According to Stuart Russell and Peter Norvig (2009), John McCarthy invented ‘one X after another’ in a machine which is called as ‘Look, Ma, no hands!’ era. In 1976, Newell and Simon managed to create General Problem Solver or GPS (Russel & Norvig, 2009). In 1952, Arthur Samuel invented Geometry Theorem Prover which capable to verify theorems that complicated to solve (Russel & Norvig, 2009). In 1958, McCarthy succeeded to create Lips, which is high level program that became popular over the next 30 years. As stated by Stuart Russell and Peter Norvig (2009), Perceptrons published by Marvin Minsky and Seymour Papert in 1969, a feed-forward structure was consisted of two layers which is a boundary that has never been recognized.
4) A dose of reality (1966–1973)
In 1957, Herbert Simon believes that in the future there will be machine that is able to think, learn and produce, in addition, it might be exist in the next 10 years. In fact, the predicted machine was recently exist in the next 40 years after the statement was issued (Russel & Norvig, 2009). Failure occurs in almost all cases of artificial intelligence when applied on complex and extensive issues. The first difficulty occurs because the created program has their unknown subject, and only uncomplicated syntactic manipulation that makes the program succeed (Russel & Norvig, 2009). The second difficulty encountered is artificial intelligence was attempting to solve numerous difficult problems (Russel & Norvig, 2009). Majority of initial artificial intelligence program found solution by attempting various combinations. The third difficulty appeared because of major limitation on the fundamental structures which used to resulted intelligent behavior (Russel & Norvig, 2009).
5) Knowledge-based systems: The key to power? (1969–1979)
In the first decade of artificial intelligence research, the concepts applied in problem solving by investigating for general-purpose, furthermore, assembled into basic idea which lead to the proper solution (Russel & Norvig, 2009). Feigenbaum and others at Stanford began the Heuristic Programming Project (HPP) to test the extent to which the new technique was be able to applied in other areas of human expertise (Russel & Norvig, 2009).
6) Artificial intelligence becomes an industry (1980–present)
As stated by Stuart Russell and Peter Norvig (2009), in 1981, the Japanese declared the Fifth Generation project which has plans for the next 10 years, the prologue is used to create intelligent computers. In response, the United States formed the Microelectronics and Computer Technology Corporation (MCC) as an investigation of consortium intended to ensure national competitiveness (Russel & Norvig, 2009). Based on both cases, artificial intelligence was component of a comprehensive effort such as chip plan and human-interface research (Russel & Norvig, 2009). Stuart Russell and Peter Norvig (2009) state, “In 1988, including hundreds of companies building expert systems, vision systems, robots, and software and hardware specialized for these purposes.” (pg. 24). Furthermore, AI Winter period which a number of companies went bankrupt because of failure in their promises accomplishment (Russel & Norvig, 2009).
7) The return of neural networks (1986–present)
There are at least 4 groups that rediscovered the back-propagation learning algorithm that Bryson and Ho invented in 1969. The algorithm had a major impact because it has been applied in computer technology and psychology (Rumelhart and McClelland, 1986). Stuart Russell and Peter Norvig (2009) mention, “These so-called connectionist models of intelligent systems were seen by some as direct competitors both to the symbolic models promoted by Newell and Simon and to the logicist approach of McCarthy and others (Smolensky, 1988).” (pg. 24).
8) Artificial intelligence adopts the scientific method (1987–present)
In the methodological aspect, artificial intelligence completely be strengthened by scientific methods, the hypothesis must be according to exhaustive empirical experiments and it is essential to perform data processing using statistics (Russel & Norvig, 2009). In recent years, some work areas have been dominated by hiddenMarkov models (HMMs) (Russel & Norvig, 2009). There are two relevant aspects of HMMs, which are based on a exhaustive mathematical theory and created by a procedure of preparing on an expansive corpus of real speech data (Russel & Norvig, 2009). Revolution occurs slowly on robotics, computer vision, and education representation. Stuart Russell and Peter Norvig (2009) state, “A better understanding of the problems and their complexity properties, combined with increased mathematical sophistication, has led to workable research agendas and robust methods” (pg. 26).
9) The emergence of intelligent agents (1995–present)
Progress in solving subproblems of artificial intelligence has made researchers begin to see the problem of ‘whole agents’ again (Russel & Norvig, 2009). Internet is an indispensable facility for smart agents. There is a risk when attempting to build a complete agent, such as an artificial intelligence that was previously isolated may require improvement when their results should be tied together (Russel & Norvig, 2009). The effort to make machines that was capable to talk, think, learn and produce, as in Simon’s statement, thus the effort called as human level artificial intelligence or HLAI. Stuart Russell and Peter Norvig (2009) mention, “A related idea is the subfield of Artificial General Intelligence or AGI (Goertzel and Pennachin, 2007), AGI looks for a universal algorithm for learning and acting in any environment, and has its roots in the work of Ray Solomonoff (1964)” (pg. 27).
10) The availability of very large data sets (2001–present)
Stuart Russell and Peter Norvig (2009) state, “As another example, Hays and Efros (2007) defined an algorithm that searches through a collection of photos to find something that will match. They found the performance of their algorithm was poor when they used a collection of only ten thousand photos, but crossed a threshold into excellent performance when they grew the collection to two million photos” (pg. 28). This case shows that the ‘knowledge bottleneck’, which means how to display problems to earn all the knowledge needed in the system, in artificial intelligence with various applications through learning methods rather than using hand-coded knowledge engineering (Russel & Norvig, 2009).
Method to Create Artificial Intelligence
In computer science, artificial intelligence research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals (Poole, Mackworth & Goebel, 1998). Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving” (Russell, Stuart J. Norvig, Peter, 2009).
General intelligence is among the field’s long-term goals (Kurzweil, 2005). Approaches include statistical methods, computational intelligence, and traditional symbolic artificial intelligence. Many tools are used in artificial intelligence, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The artificial intelligence field draws upon computer science, mathematics, psychology, linguistics, philosophy and many others. Artificial intelligence techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and artificial intelligence techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science.
Artificial intelligence often revolves around the use of algorithms. An algorithm is a set of unambiguous instructions that a mechanical computer can execute. A complex algorithm is often built on top of other, simpler, algorithms. A simple example of an algorithm is the following recipe for optimal play at tic-tac-toe:
- If someone has a “threat” (that is, two in a row), take the remaining square. Otherwise,
- If a move “forks” to create two threats at once, play that move. Otherwise,
- Take the center square if it is free. Otherwise,
- If your opponent has played in a corner, take the opposite corner. Otherwise,
- Take an empty corner if one exists. Otherwise,
- Take any empty square.
The traditional problems (or goals) of AI research include planning, learning, natural language processing, machine perception and the ability to move and manipulate objects (Russell, Stuart J.; Norvig, Peter, 2009).
1. Planning
Intelligent agents must be able to set goals and achieve them. They need a way to visualize e the future—a representation of the state of the world and be able to make predictions about how their actions will change it—and be able to make choices that maximize the utility (or “value”) of available choices (Dreyfus & Dreyfus, 1986)
In classical planning problems, the agent can assume that it is the only system acting in the world, allowing the agent to be certain of the consequences of its actions (Russell, Stuart J., Norvig, Peter, 2009).
2. Learning
Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories.
3. Natural Processing
Natural language processing gives machines the ability to read and understand human language. A sufficiently powerful natural language processing system would enable natural language user interfaces and the acquisition of knowledge directly from human-written sources, such as newswire texts. (Luger & Stubbelefield, 2004)
4. Machine Perception
Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. (Malcolm, Tatum, 2012) The basic method that the computers take in and respond to their environment is through the attached hardware.
Application of Artificial Intelligence
As Mankind forced by nature to adapt and use our creativity to create things for ourselves. Creativity is not specific for an individual, everyone can come up with their own things. It is connected with ideas, analogical thinking and also perception. A product is creative when it is novel and appropriate. A novel product is original not predictable. The bigger the concept, and the more the product stimulates further work and ideas, the more the product is creative (Sternberg & Lubart, 1995). Human have been invented a lot of things from the stone age until now. The most advanced and latest of human invention is artificial intelligence.
Speech Recognition
Speech recognition is the power of a machine or program to detect the human language, then translate it to another format that can be recognize by the machine or program. The command that given, tell the machine or program has narrow knowledge and only respond to narrow request. The most useful speech recognition now is Siri. Siri was founded on 2005 by Dag Kittlaus, Adam Cheyer, and Tom Gruber. It was introduced to public on 2011 by implemented it on an iPhone 4s, it has 3 differences voice accent which are American, British, and Australian. In the future, Siri is implemented in all apple’s product such as iPad, Mac, Apple Watch, Apple Tv, and Homepod. Apple created simple command to activate siri on all their devices, easily by saying “Hey, Siri” and follow by the command for the task. Siri need an internet connection to process the command, after siri record the voice of the command then send it to Apple Data Center. In Apple Data Center the voice recorded will be process, such as pronunciation and language. Data center will determine the request that will be perform. The command for the device will be send back, the task will be performed immediately.
Machine Learning Platform
Time by time, computer is learning and trying to keep up with human life likewise computer is getting better and smarter every day. With the implementation of algorithms, applications, development, and many more, machine learning is getting smarter and better. Machine learning main purpose is to develop computer program without human intervention, it could access the data and process the data so the machine could learn from the data given. In the future, the computer will learn automatically. The most automated and easiest to use machine learning nowadays is created by Amazon. Amazon used algorithm that was founded by Amazon’s internal data scientist community for more over than 20 years. The platform uses the algorithm to predict and find the patterns of the data, in the end it will predict the future result. Amazon’s machine learning provides tools and guide the users during process of building machine learning models, without having good skills in machine learning algorithm. After finish the model the users desired, it will predict using simple API (Application Programming Interface).
Robotic Processes Automation
As the push to go progressively advanced and accomplish more with accessible assets, the requirement for companies to engage their workers through innovation increments. In going up against unsurprising and repeatable assignments, programming “robots” can possibly immeasurably lessen cost, enhance process quality and consistency, and empower prominent adaptability. Robotic process automation instruments have developed unobtrusively finished the most recent decade, and now they are finding a place in numerous associations. Japan is the most ambitious nowadays in term of robots. One of their company, Honda created the most advanced humanoid robot that have the purpose to help people called Asimo. Asimo was built to not only to walk like human, in addition Asimo’s ability is to understand human gestures and command, identify the face and voices, and dangerous things human to do. Sensors and algorithm used to build asimo, to perform small things such as helping the human at home. Asimo can process a lot of things at the same time, it because all the sensors and algorithm that Honda put inside asimo. Elder could ask asimo to help tye daily routine.
Advantages and Disadvantages of Artificial Intelligence
Artificial intelligence has brought various advantages towards the efficiency of performing tasks in many field.
Advantages
The advantages of artificial intelligence is as follow:
1. Accuracy and precision.
Accuracy and precision is something that is hard to achieve by mankind when performing their tasks. However, it can be improved by the implementation if artificial intelligence. This is because, artificial intelligence has the ability to learn and reason in order to solve a problems or perform any tasks (Pannu, 2018). Precision treatment is the best example for this as by using artificial intelligence, doctors could predict more accurately the treatment and prevention strategies for particular disease that might work for artificial intelligence people.
2. Repetitive Tasks
Performing a repetitive task might be tiring for mankind and may cause error during the process. However, by implementing artificial intelligence during the process is the best solution. As an example, smart manufacturing has the potential to benefit every industry as it can support human safety (Bowser et al, 2017). This is because, repetitive tasks might cause boredom and fatigue to human which can interfere their performance. Artificial intelligence systems have a function that can recognize pattern and is highly artificial intelligence lorded to particular tasks (Stanford University, 2016).
3. Difficult exploration
Artificial intelligence can be used to perform difficult tasks or exploration such as space travel, fuel exploration or mining that might be difficult for human to perform. Examples of artificial intelligence solving difficult tasks is the In-Core Fuel Management Optimization (Meneses, Lima & Schirru, 2010) in which artificial intelligence helps to determine the loading pattern for producing full power of a nuclear reactor. Artificial intelligence is used for this task due to its complexity of the problems.
There are radiant opportunities for artificial intelligent machines will have the capacity to complete critical duty. Intelligence machines may have the capacity to utilize them for perilous missions, along these lines limiting the hazard to human life. Human is not perfect, everything that human create have bad effect. Intelligent machine is included.
Disadvantages
Cost
As good as it sounds, artificial intelligent demand attention and time to build, rebuild and repair. Years after now, mankind will spend more than billions to develop a perfect artificial intelligence. After mankind succeed and artificial intelligence become primary needs, the cost to build and repair the artificial intelligence will be higher.
Misuse
Autonomous weapons are computerized reasoning framework modified to slaughter. In the hands of the wrong individual, these weapons could without much of a stretch reason mass loss. Additionally, an artificial intelligence weapon contest could coincidentally prompt an artificial intelligence war that likewise brings about mass casualties. To abstain from being frustrated by the enemy, these weapons would be intended to be to a great degree hard to just “kill,” so mankind could conceivably lose control of such a circumstance. This hazard is one that is available even with narrow artificial intelligence, yet develops as levels of artificial intelligence knowledge and independent increment.
Lack of Human Soul
One of the real impediments of intelligence machines is that they could not be human-enough. Mankind might have the capacity to influence intelligent machine to think, but couldn’t create the capacity to influence intelligence machines to feel. Artificial intelligence have the capacity that human have not, which is work for extended periods. Replacing individuals with robots in each field may not be a correct choice to make. There are numerous occupations that require the human touch. Intelligent machines will definitely not have the capacity to substitute for minding conduct of healing center medical caretakers or the promising voice of a specialist.
CONCLUSION
It all started from the middle 19th century, the idea was simple. Mankind created a machine learning that have the capacity to reformed learning and to utilize algorithm as the base of the system. The capacity of artificial intelligence had evolved and became more advanced. Presents days, artificial intelligence could detect thousands of human faces from thousands of photos. Numerous apparatuses are utilized as part of artificial intelligence, including rendition of examination and numerical advancement, neural networks and strategies in view of insights, probability and likewise financial matters. The traditional purpose of artificial intelligence research includes planning, learning, natural language processing, machine perception and the capacity to act and shape objects.
Mankind born with one of the important skill which is have the ability to adapt with the environment, from adaptation with the environment human could innovate things already innovated. The most advanced and latest of human invention is artificial intelligence. Mankind compete with other mankind to innovate a better artificial intelligence that would be useful for the entire mankind, from something that not exist like intelligence machine platforms until an innovation that human could interact with it likewise robot. Human is far away from the word perfect, all human creation has flaws. At some point human creation could benefit the world, in the meantime makes other human questioned what they have done and the impact of human creation.