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Trustworthy AI is also a work programme of the International Telecommunication Union, an agency of the United Nations, initiated under its AI for Good programme. [2] Its origin lies with the ITU-WHO Focus Group on Artificial Intelligence for Health, where strong need for privacy at the same time as the need for analytics, created a demand for a standard in these technologies.
In the field of artificial intelligence (AI), a hallucination or artificial hallucination (also called bullshitting, [1] [2] confabulation [3] or delusion [4]) is a response generated by AI that contains false or misleading information presented as fact.
On June 26, 2019, the European Commission High-Level Expert Group on Artificial Intelligence (AI HLEG) published its "Policy and investment recommendations for trustworthy Artificial Intelligence". [78] This is the AI HLEG's second deliverable, after the April 2019 publication of the "Ethics Guidelines for Trustworthy AI".
"AI slop", often simply "slop", is a derogatory term for low-quality media, including writing and images, made using generative artificial intelligence technology. [ 4 ] [ 5 ] [ 1 ] Coined in the 2020s, the term has a derogatory connotation akin to " spam ".
Generative artificial intelligence (generative AI, GenAI, [165] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 166 ] [ 167 ] [ 168 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 169 ...
Concern over risk from artificial intelligence has led to some high-profile donations and investments. In 2015, Peter Thiel, Amazon Web Services, and Musk and others jointly committed $1 billion to OpenAI, consisting of a for-profit corporation and the nonprofit parent company, which says it aims to champion responsible AI development. [126]
[6] [7] At the time, the focus of the research was on improving Seq2seq techniques for machine translation, but the authors go further in the paper, foreseeing the technique's potential for other tasks like question answering and what is now known as multimodal Generative AI. [1] The paper's title is a reference to the song "All You Need Is ...
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.