Resources that discuss holding oneself or group accountable for their actions.
Author: N/A; Publisher: ParsonsTKO; Publication Year: 2021. The following video discusses how data storytelling is essential for any good data scientist. This makes it even more important for data scientists to be aware of privacy concerns, and avoid bias, and misinterpretation. This video includes panelists that all have expertise in the data ethics and regarding public relations. For example, if you publish a…
Author: Xiaofeng Tang, Eduardo Mendieta, Thomas A. Litzinger; Publisher: Science and Engineering Ethics; Publication Year: 2022. The following article discusses how a lack of training in ethical theories and related pedagogy has kept many engineering faculty members from teaching data ethics, an important aspect of engineering research that has become more salient in recent years. This paper describes the development of a module, which includes concepts, cases, policies, and…
Author: Winston Thomas; Publisher: CDO Trends; Publication Year: 2022. The following article starts by questioning who the authority on data ethics will be, especially as cultural and legal definitions vary by region and nation. Jay Upchurch, the CIO of SAS, says concerns about how to address and solve data ethics problems led the company to create its Data Ethics Practice (DEP). The DEP is a cross-functional global team to…
Author: Will Horvath; Publisher: Data Science Ethics; Publication Year: 2019. The following article discusses how with countries fighting against the growing threat of privacy invasion (and many losing), Europe implemented in 2018 the General Data Protection Regulation (GDPR) that provides the ‘most sweeping protection of user privacy rights yet passed in the world.’ France’s CNIL used the GDPR to fine Google for $57 million…
Author: Mark D. Wilkinson et al.; Publisher: Nature; Publication Year: 2016. The following article focuses on the need to improve data handling in order to ensure the reproducibility of results published in scientific literature. It sets forth the FAIR data principles (Findability, Accessibility, Interoperability, and Reproducibility). The article argues that FAIRness is a prerequisite for proper data management and stewardship. The…
Author: Wanda Curlee; Publisher: Project Management Institute; Publication Year: 2022. The following article covers the application of data ethics in projects and it provides a framework that this website approves of. The author provides an overview of guidelines that they followed when creating their framework. One that was eye-catching was to go beyond the letter of the law. Laws have not caught up to data science and so it’s up to…
Author: Vindu Goel; Publisher: The New York Times; Publication Year: 2014. The following article focuses on issues prompted by controversial studies by Facebook. The first, in 2014, measured how users’ emotions were impacted by an adjustment to the kind of content appearing in their news feed. The second, from 2010, sent notifications to users reminding them to vote, and found that notifications that showed a list…
Author: N/A; Publisher: Stanford Encyclopedia of Philosophy; Publication Year: 2020. In the following article, Dr. Müller at Stanford discusses why artificial intelligence (AI) system scandals are covered differently in the media. For a problem to qualify as a problem for AI ethics would require that we do not readily know what the right thing to do is. In this sense, job loss, theft, or killing with AI is not a problem in ethics, but whether these…
Author: Vidhi Chugh; Publisher: Medium; Publication Year: 2021. The following article describes how as a data scientist, if you want the product you are working on to be “[artificial intelligence (AI)] for good,” then it is inevitable to encounter some situations such as biased data, biased models, or biased implementation. This article illustrated forms of what data bias can be and there is no one solution for all. But…
Author: Veterans Affairs Department; Publisher: Federal Register; Publication Year: 2022. The following article explains the Department of Veteran Affairs (VA)’ changes in data ethics and the implementation of their new data ethics framework. The government had been concerned of the data ethics in the VA and decided to implement a framework that was developed for the department. This includes the access, sharing, and use of veterans data…