Sensitive Data

Downside of Fitness Trackers and Health Apps is Loss of Privacy

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Author: Victoria J. Palmer; Publisher: The Conversation; Publication Year: 2016. The following article starts off with a bold statement to capture the audience, saying the public have now become the study subjects and the collection tools. This article focuses heavily on the risks of health tracking through apps. As much as health apps can be an asset, if not handled properly sensitive data can easily be brought public. One example is…

How to Make Your Data Project Ethical by Design

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Author: Tom Jongen; Publisher: Medium; Publication Year: 2021. The following article gives a bit of background on the current issues with using data for malintent. He then outlines some of the necessities of working with data, and what companies should require of those who work with sensitive data. The first point is to create experts in ethical thinking. They do this by training data experts on data security and the…

Introduction to Data Ethics

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Author: N/A; Publisher: Odyssey Learning Project; Publication Year: 2018. The following video does an excellent job of breaking down the extensive and complicated challenge of data ethics into its most basic and essential parts. First, the author dives into the idea of sensitive data, which they define as “personally identifiable information.” They explain that it is essential to be careful about how this type of data is…

Protecting Lives & Liberty: How Contact Tracing Apps Can Foil Both COVID-19 and Big Brother

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Author: Nicky Case; Publisher: ncase.me; Publication Year: N/A. The following resource considers how should we balance leveraging sensitive data to combat important social issues (e.g., COVID-19 contact tracing) while ensuring data privacy? One answer is the DP-3T protocol used to automatically trace contact between individuals using location-based data from mobile devices. However, even with a…

DynamoFL Aims to Bring Privacy-Preserving AI to More Industries

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Author: Kyle Wiggers; Publisher: TechCrunch+; Publication Year: 2022. The following article covers how federated learning allows machine learning (ML) models to be trained on sensitive data without having it housed on multiple different servers and/or machines. Healthcare data (especially as pandemic data was coming in quickly), financial data, and user device logs currently use this technique. However, the state of…

Privacy & Security Perspectives: Interoperability, Prospects for HIPAA Refresh, More

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Author: Bill Siwicki; Publisher: Healthcare IT News; Publication Year: 2020. The following article features a conversation highlighting the importance of keeping multiple perspectives in mind for any kind of technology development that requires sharing of sensitive data. It is important to have ongoing conversations about the benefits and risks of the new norm…