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The Algorithmic Justice League (AJL) is a digital advocacy non-profit organization based in Cambridge, Massachusetts.Founded in 2016 by computer scientist Joy Buolamwini, the AJL uses research, artwork, and policy advocacy to increase societal awareness regarding the use of artificial intelligence (AI) in society and the harms and biases that AI can pose to society. [1]
AI alignment involves ensuring that an AI system's objectives match those of its designers or users, or match widely shared values, objective ethical standards, or the intentions its designers would have if they were more informed and enlightened. [40] AI alignment is an open problem for modern AI systems [41] [42] and is a research field ...
Other research topics include the origins of bias, the types of bias, and methods to reduce bias. [4] In recent years tech companies have made tools and manuals on how to detect and reduce bias in machine learning. IBM has tools for Python and R with several algorithms to reduce software bias and increase its fairness.
Using machine learning to detect bias is called, "conducting an AI audit", where the "auditor" is an algorithm that goes through the AI model and the training data to identify biases. [166] Ensuring that an AI tool such as a classifier is free from bias is more difficult than just removing the sensitive information from its input signals ...
Systemic bias: This page outlines real, useful information about systemic bias on Wikipedia. We are aware that we have biases, and we do what we can to combat them. One against many: This page gives advice for dealing with situations where one editor wants to make a change but multiple editors oppose the change.
The AI Now Institute at NYU is a research institute studying the social implications of artificial intelligence. Its interdisciplinary research focuses on the themes bias and inclusion, labour and automation, rights and liberties, and safety and civil infrastructure.
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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.