As with any legislation, the proposed bill defines key terms. In this, we have a look at how the federal government might one day classify artificial intelligence. Here are the five definitions given:

A) Any artificial systems that perform tasks under varying and unpredictable circumstances, without significant human oversight, or that can 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.

The proposed committee wouldn’t just be focused on jobs lost to AI either. Its scope is poised to include guidance on ethics training and development for developers, open research, international competitiveness and cooperation on AI, accountability of AI systems, how AI can help rural areas, and how AI can help the government.

Large technology companies have been independently building organizations to create ethics standards and explore the impact of products built on artificial intelligence, but the Trump administration has taken little notice of the technology. In March, Treasury secretary Steve Mnuchin said automation wasn’t even on the administration’s radar screen.

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