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Explainable AI ( XAI ), often overlapping with interpretable AI, or explainable machine learning ( XML ), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1] [2] The main focus is usually on the reasoning behind the decisions ...
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.
AI alignment involves ensuring that an AI system's objectives match those of its designers, users, or widely shared values, objective ethical standards, or the intentions its designers would have if they were more informed and enlightened. AI alignment is an open problem for modern AI systems and is a research field within AI.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.
An introduction to FAIR data and persistent identifiers. FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability (FAIR). [1] [2] The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations. [1]
OpenAI is an American artificial intelligence (AI) research organization founded in December 2015 and headquartered in San Francisco. Its mission is to develop "safe and beneficial" artificial general intelligence, which it defines as "highly autonomous systems that outperform humans at most economically valuable work".
Knowledge representation and reasoning. Knowledge representation and reasoning ( KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language.
Qualitative Reasoning (QR) is an area of research within Artificial Intelligence (AI) that automates reasoning about continuous aspects of the physical world, such as space, time, and quantity, for the purpose of problem solving and planning using qualitative rather than quantitative information. [1] Precise numerical values or quantities are ...
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