Research Article

A piece of writing that conveys research that was performed. The authors convey why and how the research was performed and its outcomes.

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

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Author: Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al.; Publisher: Arxiv; Publication Year: 2016. The following article discusses how machine learning applied blindly runs the risk of amplifying biases in data. Word embedding, a popular framework for representing text data as vectors that has been used in many machine learning and natural language processing tasks, poses such a risk. The authors demonstrate that even word embeddings…

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…

It’s Good to Share: Why Environmental Scientists’ Ethics Are Out of Date

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Author: Patricia A. Soranno, Kendra S. Cheruvelil, Kevin C. Elliott, Georgina M. Montgomery; Publisher: National Library of Medicine; Publication Year: 2015. The following article discusses how as data-sharing policies and ethics have become more prevalent in the sciences, the field of environmental sciences has not really caught up. This article further describes how in order for environmental science to be a more inclusive field, the scientists need to make the datasets that are serving as a basis for their…

Case Study: An Ethics Case Study of HIV Prevention Research on Facebook: The Just/Us Study

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Author: Sheana S. Bull, PhD, Lindsey T. Breslin, MSSW, Erin E. Wright, MA, Sandra R. Black, DVM, Deborah Levine, MA, John S. Santelli, MD; Publisher: Journal of Pediatric Psychology; Publication Year: 2011. In the following article, Table 1 is a very helpful resource to look at as a data professional when considering ethics. This article, and the table referenced, is discussing a case study where Facebook tried to deliver a sexual education program to youth and young adults. This is a very common area in the data industry where an algorithm is made to send…

An Introduction to Data Ethics

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Author: Shannon Vallor, William J Rewark; Publisher: Santa Clara University; Publication Year: N/A. The following article provides a deep dive into the risks and benefits that data can present. After that, the authors talk about what ethical issues or concerns may arise when working with data. The authors of the article take both perspectives in their article: user-based and people who are given access to the data. The authors also point out what dangers…

Algorithmic Bias in Data-Driven Innovation in the Age of AI

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Author: Shahriar Akter, Grace McCarthy, Shahriar Sajib, Katina Michael, Yogesh Dwivedi, John D’Ambra; Publisher: International Journal of Information Management; Publication Year: 2021. The following paper provided a thorough framework for algorithmic biases in data driven innovation (DDI) phases. It listed the scope and impact of bias across different phases in a data driven project, and it stated that both humans and machines should be involved in the process without relying fully on artificial autonomy. The data driven process…

Algorithmic Accountability

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Author: Hetan Shah; Publisher: National Library of Medicine; Publication Year: 2017. The following article reviews ways in which researchers can improve trustworthiness. The authors argue that transparency alone cannot lead to accountability. Additionally, legislation for equitable machine learning algorithms may be useless because of the rise of social media networks collecting data. Certain countries are guilty of “digital…

Artificial Intelligence in Education: Addressing Ethical Challenges in K-12 Settings

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Author: Selin Akgun, Christine Greenhow; Publisher: AI and Ethics; Publication Year: 2022. The following article discusses the current and proposed uses of artificial intelligence (AI) in promoting educational outcomes for K-12 students. It asserts that, if unchecked, AI algorithms can perpetuate systematic and human biases, especially against groups who are disadvantaged based on factors such as nationality, race, language, or…

Ethical and Legal Challenges of Artificial Intelligence-Driven Healthcare

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Author: Sara Gerke, Timo Minssen, and Glenn Cohen; Publisher: National Library of Medicine; Publication Year: 2020. The following article is dense, but its biggest takeaway is the impact of getting things wrong is extremely high in the healthcare sector. If an algorithm recommends an incorrect or unsafe oncology treatment, it could cost a patient their lives. The practical example of this is simply having bad training data, but it can also take a bias skew. When…

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…