learn from their experience and improve their performance. Such systems may be developed in computer software, physical hardware, or other contexts not yet contemplated. They may solve tasks requiring human-like perception, cognition, planning, learning, communication, or physical action. In general, the more human-like the system within the context of its tasks, the more it can be said to use artificial intelligence. (B) Systems that think like humans, such as cognitive architectures and neural networks. (C) Systems that act like humans, such as systems that can pass the Turing test or other comparable test via natural language processing, knowledge representation, automated reasoning, and learning. (D) A set of techniques, including machine learning, that seek to approximate some cognitive task. (E) Systems that act rationally, such as intelligent software agents and embodied robots that achieve goals via perception, planning, reasoning, learning, communicating, decision making, and acting. (2) The term artificial general intelligence means a notional future artificial intelligence system that exhibits apparently intelligent behavior at least as advanced as a person across the range of cognitive, emotional, and social behaviors. (3) The term narrow artificial intelligence means an artificial intelligence system that addresses specific application areas such as playing strategic games, language translation, self-driving vehicles, and facial or other image recognition. . (B) How to create a climate for public and private sector investment and innovation in artificial intelligence. (C) The possible benefits and effects that the development of artificial intelligence may have on the economy, workforce, and competitiveness of the United States. (D) Whether and how networked, automated, artificial intelligence applications and robotic devices will displace or create jobs and how any job-related gains relating to artificial intelligence can be maximized. (E) How bias can be identified and eliminated in the