Underrepresented Author

Resources that were produced by upcoming or rarely-recognized authors.

Theories of AI Liability: It’s Still About the Human Element

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Author: William A. Tanenbaum, Kiyong Song, Linda A. Malek; Publisher: Reuters; Publication Year: 2022. The following article outlines the 2 basic theories/ideas regarding who is responsible or liable for the actions taken and decisions made by an artificial intelligence (AI). The first argument is that the organization that utilizes the AI is solely responsible for the effects of its outcomes. The second contends that those developed the AI should have to…

Digital Democracy Is Within Reach

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Author: Tristan Harris, Audrey Tang; Publisher: Your Undivided Attention; Publication Year: 2020. The following podcast episode features Audrey Tang, minister of digital affairs in Taiwan. She is a transgender woman that identifies as “post-gender” and the first non-binary person to hold an executive-level position in Taiwan. In this interview, she discusses how she has helped implement greater data transparency in the government and outlines methods…

Datasheets for Datasets

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Author: Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford; Publisher: Microsoft; Publication Year: 2019. The following proposal identifies that as the field of machine learning has grown, we continually see misuse of algorithmic processes or data that reinforces biases or has other ethical and legal concerns. The proposal here is that similar to the electronics agency, each “component” in data should have a description, prompted by questions in 7 categories…

Creating Diverse and Equitable Initiatives in Data Science

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Author: Tiffany Oliver; Publisher: TEDx Talks; Publication Year: 2022. In the following talk, Dr. Oliver talks about her work to address the underrepresentation of women and BIPOC in data science. In 2021, Dr. Oliver created a summer research program at Spelman College, a historically Black women’s college, to introduce Spelman students to data science. There are 2 notable aspects of Dr. Oliver’s…

Credit Scoring and the Risk of Inclusion

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Author: Tamara K. Nopper; Publisher: Medium; Publication Year: 2022. The following article examines the possibilities of alternative data initiatives for mitigating racial inequality in the U.S. credit scoring system This discusses the for-profit credit evaluation system and how alternative data and fundamental shifts in the system that performs credit evaluation can improve the experience for minority users…

AI Ethics vs Data Ethics

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Author: Steven Tiell; Publisher: Ethics of Data; Publication Year: 2020. The following visualization focuses on how a lot of terms surrounding the ethical considerations of data seem interchangeable, yet educating ourselves on what really constitutes ethical data is not something we always consider. Each term has nuance that makes it unique, but they are also all interconnected in a data ethics framework. At the core…

Why It’s So Damn Hard to Make AI Fair and Unbiased

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Author: Sigal Samuel; Publisher: Vox; Publication Year: 2022. The following article introduced the idea of bias in a statistical sense and how bias is interpreted in society. This is an important distinction to recognize and is often overlooked. The author discussed that defining what “fair” is can be very tricky and provided different definitions of “fairness”. An example is procedural fairness: an algorithm is…

Gaps in Measuring and Mitigating Implicit Bias in Healthcare

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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…

Big Data Ethics: Weaving ethics into the fabric of Big Data

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Author: Sahana Rajan; Publisher: Suyati; Publication Year: 2015. The following article discusses how as big data becomes more common, what are the boundaries of data ethics? Intricate data processing can open up the possibility of gaining access to private data. We are influenced daily by big data through personalized advertisements. We need to redefine the boundaries of data accessibility. Every time we click…

How Biased Are Our Algorithms?

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Author: Safiya Umoja Noble; Publisher: TEDx Talks; Publication Year: 2014. The following video initially discusses how the speaker is not the same skin tone as her white mother. She then goes into discussing the cultural revolution that was happening during her childhood in the 70s and 80s. In referencing a study that was done in the 40s based on giving Black children both a Black and a white doll and asking questions…