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Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).
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 ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [1] This includes algorithmic biases, fairness, [2] automated decision-making, accountability, privacy, and regulation.
On January 7, 2019, following an Executive Order on Maintaining American Leadership in Artificial Intelligence, [160] the White House's Office of Science and Technology Policy released a draft Guidance for Regulation of Artificial Intelligence Applications, [161] which includes ten principles for United States agencies when deciding whether and ...
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. [1]
The post Watch: Artificial intelligence and the bias against dark skin appeared first on TheGrio. “It puts us in danger…,” says Damon Hewitt, head of the Lawyers’ Committee for Civil ...
Coded Bias says that there is a lack of legal structures for artificial intelligence, and that as a result, human rights are being violated. It says that some algorithms and artificial intelligence technologies discriminate by race and gender statuses in domains such as housing, career opportunities, healthcare, credit, education, and ...
Over 80% of trans workers have experienced discrimination or harassment, report finds. ... Artificial Intelligence is reshaping the job application process, simplifying some aspects — and ...