Author: Sally Arif; Publisher: National Library of Medicine; Publication Year: 2021. The following article focusses on how recent studies have shown that healthcare providers hold unconscious bias through the use of the Implicit Association Test (IAT). The IAT was developed in 1998 and is the now the most readily available computerized online tool used to measure and bring awareness to unconscious bias in published literature…
Author: Robin Hauser; Publisher: TED; Publication Year: N/A. In the following talk, Robin Hauser talks about unconscious bias in artificial intelligence (AI) algorithms. As part of producing her new movie about unconscious bias, she became interested in finding out whether it would be possible to create AI without bias. As she came to find out, it is oftentimes harder to create unbiased algorithms for multiple…
Author: James Arvanitakis, Andrew Francis, Oliver Obst; Publisher: The Conversation; Publication Year: 2018. The following article discusses how, as analysts, the main 2 ethical questions that are being asked are 1). What data should be collected and 2). How should the data be used? However, we should also ask and see who gets to make the decision in the first place. As it stands right now, the people who hold all the power to make the decision in how we use…
Author: N/A; Publisher: Miro; Publication Year: N/A. The following visualization highlights the impact of bias in several aspects of the machine learning lifecycle. One point discussed frequently is the patterns of bias and discrimination baked into data sets. This image highlights that the real world patterns of discrimination and inequality are the source of the bias in our data sets…
Author: Christina Pazzanese
Publisher: The Harvard Gazette
Publication Year: 2020
Summary: The following article starts off by talking about all the different ways in which AI or machine learning can help improve society and business. At first, AI was thought to just automate simple and repetitive tasks. However, it turned into being much more useful than originally thought. “Firms now use AI to manage sourcing of…
Author: Cathy O’Neil; Publisher: TED Talks; Publication Year: 2017. The following video highlights the dangers of blind trust in algorithmic models. O’Neil suggests that algorithms are much less scientific and objectively truthful than commonly perceived. Instead, they are opinions embedded in code, and we are often “injecting biases into algorithms by choosing what data to collect”…
Author: Carolyn Y. Johnson; Publisher: The Washington Post; Publication Year: 2019. The following article describes how algorithms are created with the intention of eliminating bias, such as racial bias, but there are variables that can accidently profile individuals. The Washington Post reports that a widely used medical algorithm favors white patients over sicker Black patients even though race was…