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AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment , which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.
Discussions on regulation of artificial intelligence in the United States have included topics such as the timeliness of regulating AI, the nature of the federal regulatory framework to govern and promote AI, including what agency should lead, the regulatory and governing powers of that agency, and how to update regulations in the face of rapidly changing technology, as well as the roles of ...
v. t. e. Regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). It is part of the broader regulation of algorithms. [1] [2] The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international ...
California lawmakers are considering legislation that would require artificial intelligence companies to test their systems and add safety measures so they can't be potentially manipulated to wipe ...
The term "robot ethics" (sometimes "roboethics") refers to the morality of how humans design, construct, use and treat robots. [14] Robot ethics intersect with the ethics of AI. Robots are physical machines whereas AI can be only software. [15] Not all robots function through AI systems and not all AI systems are robots.
The Artificial Intelligence Act ( AI Act) [a] is a European Union regulation concerning artificial intelligence (AI). It establishes a common regulatory and legal framework for AI within the European Union (EU). [1] Proposed by the European Commission on 21 April 2021, [2] it passed the European Parliament on 13 March 2024, [3] and was ...
AI alignment is a subfield of AI safety, the study of how to build safe AI systems. Other subfields of AI safety include robustness, monitoring, and capability control . [22] Research challenges in alignment include instilling complex values in AI, developing honest AI, scalable oversight, auditing and interpreting AI models, and preventing ...
Many AI platforms use Wikipedia data, [298] mainly for training machine learning applications. There is research and development of various artificial intelligence applications for Wikipedia such as for identifying outdated sentences, [299] detecting covert vandalism [300] or recommending articles and tasks to new editors.
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related to: ai that can explain code of standards and conduct in public safety