Artificial Intelligence – it’s roughly a capacity of machines, computer programs, and systems to perform intellectual and creative functions of a human, find the original solution to a problem, make decisions and reach a conclusion. As of today, this topic became one of the most exciting thanks to the development of modern technologies and popularization of science in movies, TV series, and social media. We were all marveled when the robot Sophia obtained citizenship of Saudi Arabia and became the first inanimate object with citizenship ever. The world from science fiction seems so reachable like never before, and this fact makes us shiver as in fictional novels robots leave not a chance for humans. In this article, we will consider whether artificial intelligence is our friend or a living nightmare.
Artificial intelligence definition is not quick and clean. Before answering what is artificial intelligence we should give an answer to what is intelligence. The term itself is a matter of philosophy as humanity is still not able to provide a proper definition of intellect not to mention the creation of an artificial one. That’s why it is the mechanical philosophy and the works of Gottfried Leibniz, Rene Descartes and Thomas Hobbes which had a great impact on the development of this science field. These philosophers explored the possibility that all rational thought could be made as systematic as algebra or geometry, which became the basis of the physical symbol system hypothesis and shaped the early vision of AI.
The rise of interest in the possibility of creating artificial mind flourished in XVIII century thanks to the development of technology and clockwork in particular. In the middle of 1750th, an Austrian inventor Friedrich von Knaus designed machines that were able to write fairly long texts with a pen.
Achievements in mechanics of XIX century lead to new inventions which contributed to the modern understanding of artificial intelligence. In 1830 an English mathematician Charles Babbage developed the concept of the complex digital calculator, an analytic machine which according to his statement could calculate moves in chess. And later in 1914 the head of one of the Spanish techs. Leonardo Torres y Quevedo invented an electromechanical device able to play out simple chess endgames almost quite as well as a human.
In 1950 Alan Turing in his article “Computing Machinery and Intelligence” for philosophical magazine “Mind” aimed to define whether a machine could think the way people do. Turing suggested considering a machine to be intelligent if a person who communicates with it won’t be able to tell robot from a human.
One of the major attributes of intellectuality is a capacity for learning. So that in 1961 one of the leading English experts in artificial intelligence Dr. Donald Michie developed Machine Educable Noughts And Crosses Engine (MENACE). Through training, MENACE has learned to play a Tic-Tac-Toe.
At the beginning of 1970th experts in AI began implementing programs for solving particular problems which resulted in developing of groundbreaking yet simple concept. The concept was that in order to create an intellectual program developers should provide high-quality specialized information about the particular area. The outcome of this developing led to the invention of expert systems.
In 1980th machine learning finally started development. Until this decade experts had to manually transfer data to a program, which was a tedious process.
In the present, AI evolved to provide benefits almost in every sphere and began to be the essential part of our usual life. Nevertheless, it’s still not even close to Skynet thus there’s no reason to be scared. Keep reading to learn more about the impact of AI on every-day processes some of which are going to surprise you.
Is Artificial Intelligence The Same As Machine Learning?
In five words machine learning is a way of achieving AI. This area studies methods of developing algorithms capable of learning on their own which is important in cases where there is no clear solution. It would seem that the easiest way to get the best answer is to delegate work to a machine although we might end up with the answer ‘42’. For those who didn’t understand the reference, it came from the book “The Hitchhiker’s Guide to the Galaxy”, by Douglas Adams. Plot: a hyper-intelligent race created a supercomputer Deep Thought for one sole purpose to get an answer to The Ultimate Question of Life, the Universe, and Everything. It took Deep Thought seven and a half million years to come up with the answer ‘42’.
Deep Thought is an example of narrow AI – meaning it was specially designed to solve the one single question, but it couldn’t come up with an answer that makes sense. The reason is the question had slight philosophy gradient and demanded creative thinking which is intrinsic to human but unavailable to a machine. A machine with all of the characteristics of human intelligence, including creative thinking, would be an example of general artificial intelligence. While general AI is unreachable and still is a matter of science fiction, narrow AI is performed in many areas of our modern life.
Types of AI
As of today, there are four types of artificial intelligence:
Type I AI. Reactive machines
The most basic fundamental type of AI is purely reactive. It responses according to the particular situation and can’t form memories or rely on the past experience to issue a new solution. Those machines are designed for one specific use. The perfect example of this type of machines is Deep Blue, IBM’s supercomputer for playing chess, which beat international grandmaster Garry Kasparov in 1997. Deep Blue knows how each figure moves and can calculate amounts of optimal moves for itself and its opponent from all known possibilities. However, Deep Blue doesn’t have any memory of what happened before and images the situation on the board only the way it looks right at the moment.
This type of AI considered to be trustworthy as it will behave the same exact way in the same exact situation. You don’t want your autonomous car to cut off the drivers and create dangerous situations on the road, do you? No, you want it to be a reliable driver, which follows the rules.
Type II AI: Limited memory
Unlike the first type, the second type of artificial intelligence takes into account the past events and adds them to its preprogrammed representations of the world. Self-driving cars are the perfect examples of this type of AI. Since it’s nearly impossible to evaluate traffic in just one moment, a car has to identify other road users and monitor their speed and direction over time. However, the car can’t gain experience and learn from the past events, the way people, who drive over years, do.
Type III AI: The theory of mind
The next generation machines will be so evolved they will be able to understand the other creatures’ emotions and thoughts and the way they can affect behavior. In psychology, it’s called “theory of mind”. This is crucial when it comes to social interactions because if we don’t take into account motivation of another human being, it will be at best difficult to work together, at worst impossible. And in order to allow robots in our life, we should implant them an ability to empathize and to adjust their behavior accordingly.