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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.
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]
The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. [3] This bias has only recently been addressed in legal frameworks, such as the European Union's General Data Protection Regulation (proposed 2018) and the Artificial Intelligence Act (proposed 2021, approved 2024).
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.
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 ...
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.
“No trustworthy large-scale studies have determined that conservative content is being removed for ideological reasons,” the NYU report says. “Even anecdotal evidence of supposed bias tends ...
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.