2019

A 20-Year Community Roadmap for Artificial Intelligence Research in the U.S.

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Author: Y. Gil and B. Selman; Publisher: Computing Community Consortium (CCC) and Association for the Advancement of Artificial Intelligence (AAAI); Publication Year: 2019. The following paper touches on such a broad spectrum of societal facets artificial intelligence (AI) affects and should be considered more closely. The different areas stimulated ideas such as highlighting the AI Open Knowledge network need. Currently the major tech companies have access to a majority of this resource so it is imperative to open…

The Apple Card Didn’t ‘See’ Gender—and That’s the Problem

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Author: Will Knight; Publisher: Wired; Publication Year: 2019. The following article touches on the idea of bias “proxies,” like address information as a proxy for race. It talks about how the Apple Card was offering lower credit limits for women compared to men even though gender was specifically excluded as a variable. The author argues that we should be including those specific variables so that the…

Privacy Wars Fueled by the GDPR

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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…

The Role and Limits of Principles in AI Ethics: Toward a Focus on Tensions

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Author: Jess Whittlestone et al.; Publisher: Conference on AI, Ethics, and Society; Publication Year: 2019. The following research article argues that there are tensions between common principles guiding ethical decision-making about artificial intelligence (AI). They explain 4 key tensions: service quality versus privacy, accuracy versus fair treatment, personalization versus solidarity, and convenience versus dignity. By analogy with bioethics, the authors also argue…

An Ethics Framework for Big Data in Health and Research

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Author: Vicki Xafis, G. Owen Schaefer, Markus K. Labude, Iain Brassington, Angela Ballantyne, Hannah Yeefen Lim, Wendy Lipworth, Tamra Lysaght, Cameron Stewart, Shirley Sun, Graeme T. Laurie & E Shyong Tai; Publisher: Asian Bioethics Review; Publication Year: 2019. The following paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts…

Big Data Ethics Recommendations for the Insurance Industry

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Author: Christian Mottas; Publisher: University of Zurich; Publication Year: 2019. The following article discusses how insurers should not use data that is not related to the insured risk because such behavior will damage the customer’s trust in the insurance industry. Regulators should implement provisions specific to the insurance industry to deter unwanted forms of personalization using Big Data…

Fellowship Recipient Uses Data Science to Fight for LGBTQ Rights

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Author: N/A; Publisher: Berkeley School of Information; Publication Year: 2019. The following article talks about how one student is using data science to better the world. Master of Information and Data Science student and 2019 recipient of the Paul Fasana LGBTQ Studies Fellowship, Christina Papadimitriou is using the fellowship for her research for LGBTQ equality and rights. She has done various works to order to improve…

Teaching Data Ethics: We’re Going to Ethics the Heck Out of This

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Author: Tristan Henderson; Publisher: Association for Computing (ACM) Machinery Digital Library; Publication Year: 2019. The following paper outlines a new Data Ethics & Privacy module that was introduced to computer science students in 2018. The module aims to raise student awareness of current debates in computer science such as bias in artificial intelligence, algorithmic accountability, filter bubbles and data protection, and practical mechanisms for…

The Ethics of Data Visualization

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Author: Tricia Bisoux; Publisher: AACSB; Publication Year: 2019. The following article discusses how graphs can be highly misleading. As an ethical data scientist, it is important to both create visuals that convey the accurate information and not be a part of misinformation and also know how to interpret visuals well. It is important to be aware of biases when making graphs and to know when reading them, that they are not…

Privacy and Data Science: Protecting Sensitive Data in the Age of Analytics

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Author: Tommy Jones; Publisher: Medium; Publication Year: 2019. The following article discusses how with the development of technology, the probability of a company experiencing a data breach becomes higher and higher. There are many data privacy protection technologies emerging but which one should be used and which is the right one is still hard to decide. This article offers 3 major methods of…