Robots that defeat people while playing chess or computers with which we can talk – science has tried for many years to artificially recreate the complex human mind. How far did you get with it?
How intelligent is artificial intelligence?
The research area “Artificial Intelligence” (AI) tries to simulate human perception and human action through machines. What began as the science of computer programming has evolved into an exploration of human thought.
Because after decades of research one has recognized the impossibility of creating a “thinking” machine without first exploring and understanding human thinking itself. This is why there are in some cases large overlaps between AI research and neurology or psychology.
To this day it has not even come close to being able to reproduce human intellectual performance as a whole with machines. Language processing is a major obstacle. Even the execution of the simplest commands is a highly complex process for a machine.
Research is therefore increasingly concentrating on individual sub-areas, among other things with the aim of making work easier there. This requires a constant exchange between scientists from a wide variety of disciplines (cognitive science, psychology, neurology, philosophy, and linguistics).
Many scientists differentiate between strong and weak AI. Weak AI only covers sub-areas of intelligence. It is mostly based on methods from mathematics and computer science and is used, for example, in navigation systems and speech recognition.
Strong AI includes logical thinking, planning, communication, making independent, complex decisions. Many researchers doubt that this will ever exist.
And even if it were to succeed, many ethical questions would arise: Which decisions can be left to artificial intelligence that has no morality and no awareness of right, wrong, and, above all, nuances?
When does a computer pass the Turing test?
The question of when a machine is considered intelligent has been driving AI research for decades. One measurement tool that is widely accepted is what is known as the Turing test.
It was developed in 1950 by the British mathematician Alan Turing: A person communicates for a long time in parallel with another person and a machine without visual or hearing contact – for example via a chat program.
Humans and machines try to convince the tester that they are thinking people. If, after the conversation, the tester cannot say with certainty which of the conversation partners is a person and which is a machine, the machine has passed the test and can be considered intelligent.
The US sociologist Hugh G. Loebner offered a price of 100,000 dollars in 1991 for the computer program that passed the Turing test and duped a jury of experts.
In 2014 there were reports that the Russian software “Eugene Goostman” had passed the test. However, doubts about the method and the experimental setup arose afterward.
Nobody will have received the award by 2020, and the majority of AI researchers assume that won’t happen any time soon.
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Tamagotchis, robots & Co
The areas of application of artificial intelligence are extremely diverse. Often times we are not even aware of them. Their use is most successful in small sub-areas such as medicine: robots carry out certain sections of the operation – for example in the thousandths of a millimeter range – much more precisely than a surgeon.
In production lines, especially in the automotive industry, robots replace a myriad of human hand movements. Robotic arms, such as those used at General Motors in the 1960s, have become indispensable, especially for tasks that are hazardous to health and prone to accidents, such as painting or welding.
Classic areas of application for artificial intelligence are games, especially board games such as checkers and chess. Programmable and adaptive toys, mini robots, and computer programs have long since conquered children’s rooms.
The legendary Tamagotchi is already old-fashioned, but other artificial companions such as robot dogs, talking dinosaurs, or dolls are pushing onto the market, with which one can communicate with simple gestures or language and which carry out certain tasks.
Expert systems and machine learning
Expert systems specialize in very specific and narrowly limited areas of application. One example of this program with which computed tomographic recordings are converted into three-dimensional images on the computer screen. Doctors can literally get a “picture” of each part of the body and its condition.
Self-learning systems are an important component of artificial intelligence. These are used, for example, for automated spam filters in the e-mail inbox. You feed a computer with sample data, which it evaluates and analyzes.
The system recognizes patterns and similarities and can sort out spam mails even if the sender or content is unknown to it. The person only intervenes in a controlling manner and corrects, for example, if an email was incorrectly marked as spam. The computer, in turn, remembers this. The longer the system performs these tasks, the better it gets – a classic example of machine learning.
Speech recognition systems are also capable of learning. The more you use them, the more they adapt to the linguistic peculiarities of the user. In this way, you can understand his voice better over time and make fewer mistakes in processing.
Automatically into space
In 1997 machines in the service of humans traveled to the planet Mars. The aim of the “Pathfinder mission” was to bring a scientific measuring device to the surface of Mars. Suitable techniques for the flight phase, atmospheric entry, descent, and landing should be developed and tested.
Everything had to work as automatically as possible since human intervention from Earth is hardly possible due to the distance. A radio signal to earth, even if it were traveling at the speed of light, would take 14 minutes.
But the “Pathfinder mission” was successful and laid the foundation for further missions to Mars. In August 2012, the “Curiosity” vehicle landed on Mars: it weighs 900 kilograms and is equipped with a variety of instruments to explore to what extent the planet is or was suitable as a biosphere.
Even the landing was spectacular: after entering the atmosphere, the probe automatically braked 20 meters above the surface and lowered “Curiosity” on ropes.
On Mars, “Curiosity” moves with a plutonium drive, smashes and analyzes stones with a laser, and grabs rock samples in a microwave to melt them. “Curiosity” has been on the road for more than eight years. He has already covered more than twenty kilometers and transmits his findings to Earth.
