Algorithmic bias refers to the systematic and repeatable errors in computer systems that result in unfair outcomes, such as favoring one category over another. This bias can arise from various factors, including algorithm design, data coding, and unintended use. It has been observed in search engines and social media platforms, impacting privacy and reinforcing social biases. Algorithmic bias has gained attention in legal frameworks, and its consequences range from election outcomes to wrongful arrests. However, understanding and addressing algorithmic bias is challenging due to proprietary algorithms and their complexity.
Stanford University
Winter 2023
This course applies fundamental CS concepts to social good problems, including health, government, education, and environment. Students will use their skills to create positive social impact. CS 106B is a recommended prerequisite.
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+ 14 more conceptsUC Berkeley
Fall 2022
This course is an in-depth discussion on the societal impacts of computer technology. The course content is drawn from various fields including sociology, philosophy, economics, and public policy. Students are expected to explore topics like privacy, algorithmic bias, tech policy, and the implications of tech on education and jobs.
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+ 12 more conceptsStanford University
Winter 2023
This course examines the intersections of philosophy, public policy, social science, and engineering in the context of recent computing technology and platforms. Key areas of focus include algorithmic decision-making, data privacy, AI, the influence of private computing platforms, and issues of diversity in tech. Students need to have completed CS106A.
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+ 17 more concepts