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As early as 2016, the Obama administration had begun to focus on the risks and regulations for artificial intelligence. In a report titled Preparing For the Future of Artificial Intelligence, [154] the National Science and Technology Council set a precedent to allow researchers to continue to develop new AI technologies with few restrictions ...
Regulation of algorithms, or algorithmic regulation, is the creation of laws, rules and public sector policies for promotion and regulation of algorithms, particularly in artificial intelligence and machine learning. [1] [2] [3] For the subset of AI algorithms, the term regulation of artificial intelligence is used.
The Artificial Intelligence Act is a European Union regulation that establishes a common framework for AI across sectors and risk levels. It covers AI applications from unacceptable to minimal risk, with different obligations and conformity assessments, and creates a European Artificial Intelligence Board.
Efforts in California to establish first-in-the-nation safety measures for the largest artificial intelligence systems cleared an important vote Wednesday that could pave the way for U.S ...
Government by algorithm [1] (also known as algorithmic regulation, [2] regulation by algorithms, algorithmic governance, [3] algocratic governance, algorithmic legal order or algocracy [4]) is an alternative form of government or social ordering where the usage of computer algorithms is applied to regulations, law enforcement, and generally any aspect of everyday life such as transportation or ...
Learn about the 2023 executive order that defines the U.S. administration's policy goals and actions regarding artificial intelligence (AI). The order aims to promote competition, protect rights, and ensure global leadership in AI, while creating chief AI officer positions in federal agencies.
Explainable artificial intelligence (XAI) is the ability to understand and explain the reasoning behind AI decisions or predictions. XAI aims to improve trust, transparency, and accountability of AI systems, and to overcome the "black box" problem of machine learning.
Learn about the ethical challenges and principles of AI, such as machine ethics, robot ethics, algorithmic biases, and existential risks. Explore the topics, applications, and examples of AI ethics from various perspectives and sources.
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