What do you call a technology which helps in creating machines which can mimic the Behaviour of human beings?

His focus is on the ethics of artificial intelligence, and on formulating policies to regulate its design and application. He has just published a book, AI Ethics, with The MIT Press.

Coeckelbergh is a member of the High-Level Expert Group on Artificial Intelligence advising the European Commission and acts both as a critic and an adviser to industry on building practical regulations into the first stages of developing new technologies.

“As an academic you often find yourself pushed into the role of defending the common good against particular private interests, because who else is going to do it, except maybe one or two NGOs?” he said in an interview for SSSHARC.

“On the other hand, we’re creating guidelines as a way of saying ‘Here is a tool that you as a company can use, that you as an engineer, a computer scientist can use to think about the ethical issues of your technology’. Without this kind of constructive approach we’re not really moving much, because people are going to develop this stuff anyway and sometimes it’s better for us to also be there and try to give ethical influence.”

Artificial intelligence is already in your pocket

Philosophy of technology emerged as an academic field after World War II demonstrated how destructive technology could be. As a “second-generation” philosopher of technology, Coeckelbergh has done specific research in robotics and recently published Introduction to Philosophy of Technology (OUP), the first textbook to update the subject with a decade of new developments.

John McCarthy, an American computer scientist, coined the term “artificial intelligence” in 1955 and organised a landmark workshop at Dartmouth College. Artificial intelligence now has ever-expanding applications, for example, from the everyday use of mobile phones and social media to robots in healthcare and industry, self-driving cars and autonomous weapons. Most worrying to Coeckelbergh is the misuse of facial recognition, especially by governments for political purposes.

“There’s no such thing as general AI, an AI which can completely mimic the cognitive capacities of human beings,” he said. “The project of AI as it was formulated in the Dartmouth workshop was to imitate human intelligence. Well, this project has not succeeded yet. What has succeeded, though, is that artificial intelligence helps us to do specific tasks and artificial intelligence in that sense is already there, is already behind the apps in your phone and is already in your pocket.”

He lists the general ethical principles that can be adapted to specific uses: privacy and data protection, safety, moral and legal responsibility, transparency and explainability to makers and users, and avoidance of built-in bias.

Coeckelbergh is a member of a robotics council established by the Austrian Ministry for Transport, Innovation and Technology. In his Sydney Ideas talk he used the example of self-driving cars to examine the complex problem of responsibility. In 2018 a pedestrian died after being hit by a self-driving car in the US State of Arizona. The car cannot be held responsible, he said, because it does not operate with free will or awareness. So humans are responsible, but who exactly?

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Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment. Although there are no AIs that can perform the wide variety of tasks an ordinary human can do, some AIs can match humans in specific tasks.

No, artificial intelligence and machine learning are not the same, but they are closely related. Machine learning is the method to train a computer to learn from its inputs but without explicit programming for every circumstance. Machine learning helps a computer to achieve artificial intelligence.

Artificial intelligence’s impact on society is widely debated. Many argue that AI improves the quality of everyday life by doing routine and even complicated tasks better than humans can, making life simpler, safer, and more efficient. Others argue that AI poses dangerous privacy risks, exacerbates racism by standardizing people, and costs workers their jobs, leading to greater unemployment. For more on the debate over artificial intelligence, visit ProCon.org.

artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks—as, for example, discovering proofs for mathematical theorems or playing chess—with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced. Intelligence—conspicuously absent in the case of Sphex—must include the ability to adapt to new circumstances.

Psychologists generally do not characterize human intelligence by just one trait but by the combination of many diverse abilities. Research in AI has focused chiefly on the following components of intelligence: learning, reasoning, problem solving, perception, and using language.

There are a number of different forms of learning as applied to artificial intelligence. The simplest is learning by trial and error. For example, a simple computer program for solving mate-in-one chess problems might try moves at random until mate is found. The program might then store the solution with the position so that the next time the computer encountered the same position it would recall the solution. This simple memorizing of individual items and procedures—known as rote learning—is relatively easy to implement on a computer. More challenging is the problem of implementing what is called generalization. Generalization involves applying past experience to analogous new situations. For example, a program that learns the past tense of regular English verbs by rote will not be able to produce the past tense of a word such as jump unless it previously had been presented with jumped, whereas a program that is able to generalize can learn the “add ed” rule and so form the past tense of jump based on experience with similar verbs.