Artificial intelligence is based around the idea that human intelligence can be defined in such exact terms that a machine can mimic it. The goals of artificial intelligence include learning, reasoning and perception.Machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology and more.

As technology advances, previous benchmarks that defined artificial intelligence became outdated. For example, machines that calculate basic functions or recognize text through methods such as optimal character recognition are no longer said to have artificial intelligence; since this function is now taken for granted as an inherent computer function.

Machine learning is also a core part of AI. Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Classification determines the category an object belongs to and regression deals with obtaining a set of numerical input or output examples, thereby discovering functions enabling the generation of suitable outputs from respective inputs. Mathematical analysis of machine learning algorithms and their performance is a well-defined branch of theoretical computer science often referred to as computational learning theory.

Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world. This means that a computer can analyze and sense things similar to how a human can, but with extra details we don’t have the capability to sense. Robots will be able to learn to get used to certain aspects of the world much like a human does as they grow up.

Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning and mapping.

Some examples of machines with artificial intelligence include computers that play chess, which have been around for years, and self-driving cars, which are a relatively new development. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, this end result is winning the game. For self-driving cars, the computer system must take into account all external data and compute it to act in a way that prevents collision.

Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up, and they will take off on their own, redesigning themselves at an exponential rate. Another is that machines can hack into people’s privacy and even be weaponized. Other arguments debate the ethics of artificial intelligence, and whether or not intelligent systems such as robots should be treated with the same rights as humans.

Self-driving cars have been the subject of controversy, as their machines tend to be designed for the lowest possible risk and the least casualties. While they remove the incidence of human error, this means that if they were put in a situation in which they had to decide between a collision with one person and a collision with another, they would calculate which option would cause the least amount of damage, but would still have to choose one. This is disconcerting to many people who believe that lives should not be put at the mercy of a machine.