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There are many definitions of Artificial Intelligence. The OECD (2019, p. 7) suggests that an
"AI system is a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy."
A similarly policy-oriented definition by the European Commission (2020) suggests that:
"AI is a collection of technologies that combine data, algorithms and computing power."
One of the most cited academic definitions is from Li and Du (2007, p. 1) and notes that AI combines:
“… a variety of intelligent behaviors and various kinds of mental labor, known as mental activities, … [to] include perception, memory, emotion, judgement, reasoning, proving, identification, understanding, communication, designing, thinking and learning.”
To understand the discussion of ethics and AI it may be more helpful to ask what people refer to when they talk about AI, rather than find the "correct" definition. In the discussion of ethics and AI one can find at least three different meanings of the term:
Machine learning, the currently most prominent of "narrow" AI, i.e. of a technology that replicates one specific aspect of natural intelligence, such as speech recognition or pattern classification. Machines can be very good at individual tasks but cannot easily apply them to other areas.
The term AI is often used to denote larger socio-technical systems that incorporate and build on AI, often machine learning, but that go beyond the immediate AI technology. Examples include autonomous vehicles, credit rating systems or commercial recommender systems.
The third category is often called general AI (or artificial general intelligence) which stands for machines that can perform human-level cognitive functions. No such systems currently exist, but they figure strongly in the general literature and public imagination. They also serve as inspiration for AI research and development.