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The Forum Guide to Data Ethics
lnbressa
Author: N/A; Publisher: National Center for Education Statistics; Publication Year: N/A. The following resource provides an in-depth framework for data ethics that is generalizable to any team or organization. Integrity, data quality, and security were at the forefront of the framework with thoughtful practical examples and recommendations following each section…
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How Bad Data Keeps Us from Good AI
lnbressa
Author: Mainak Mazumdar; Publisher: TED; Publication Year: N/A. In the following talk, Mainak argues that the biased data is what makes unethical artificial intelligence (AI), not the algorithms. Instead of spending time and money on enhancing algorithms, focus should be on obtaining unbiased data that makes ethical AI possible. He proposes 3 areas of improvement…
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A Data Science Take on Open Policing Data
2020, Bias, Diversity, Equity & Inclusion, Legal & Policy, Podcast, Social Justice, Underrepresented Authorlnbressa
Author: N/A; Publisher: Linear Digressions; Publication Year: 2020. The following podcast episode discusses how the quality of data around policing is hit-and-miss based on region. Reporters of data are those being scrutinized, so there is some self-reporting bias. Human biases are reflected in the data, so it is important to draw conclusions carefully…
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Understanding Data Quality: How Data Quality Problems Arise
Author: Christopher Tozzi; Publisher: Precisely; Publication Year: 2022. The following article discuses how data quality is the data set’s ability to serve a business for its intended use. Data quality is essential because It allows a company to use data to reach its customers effectively. Data quality can be problematic if not dealt with appropriately.…
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