Resources that discuss ideas, methods, programs, regulations, protections and case studies when collecting and utilizing data.
Author: Tim Dutton; Publisher: Medium; Publication Year: 2018. The following article explains the current political landscape of artificial intelligence (AI). It goes into the competitive nature of technology around the world and how countries are in competition to see who can implement better AI solutions. “AI policy is about maximizing AI’s many benefits for our economy and societies, while minimizing its…
Author: Thomas J., McNabb S.; Publisher: Global Health Data Methods; Publication Year: N/A. The following article discusses how misuse in health range from a physician not informing their patient about the risks of a procedure they will perform to the manager of a public health data system not protecting the confidentiality of patient records. Public health systems must protect the confidentiality of sensitive information while ensuring practitioners…
Author: Thomas Davenport, Jeanne Harris; Publisher: Harvard Business Review; Publication Year: 2007. The following article provides a similar flow to 5 Dysfunctions of a Team in which a scenario is first used to get important themes in business analytics and ethics across for later discussion. The scenario describes a grocery company that has a massive dataset based on its customers’ cards and what they buy, and they were thinking about selling this…
Author: N/A; Publisher: The Global Indigenous Data Alliance; Publication Year: 2022. The following guidelines set out the minimum requirements for Indigenous-designed data approaches and standards, which can be generalized to all approaches and standards to data ethics surrounding marginalized communities. They show the current inadequacy of consent and data privacy protections, and highlight community-controlled…
Author: N/A; Publisher: Belfer Center for Science and International Affairs, Harvard University; Publication Year: N/A. The following article discusses how biases and systems that routinely exclude and oppress have spread from the physical world into the technological world. TAPP Project, from the Harvard Kennedy School, works to ensure that emerging technologies are developed and managed in ways that serve the overall public good. It has 3 main principles:…
Author: Stephen Zorio; Publisher: Amazon: Science; Publication Year: 2020. In the following article, panelists discuss the tradeoff between accuracy and privacy when dealing with sensitive situations and machine learning (ML) models. They provide a relevant example with the pandemic outbreak, where accurate contact tracing can be more important than respecting user privacy and this highlights two problems: bias and…
Author: Shlomi Hod, Karni Chagal-Feferkorn, Niva Elkin-Koren, Avigdor Gal; Publisher: Communications of the ACM; Publication Year: 2022. The following article explains ways that data science is meeting the legal space and how lawyers are being involved in the design of artificial intelligence and programs. It also mentions a course that is being offered to law students that focuses on data science and computer science spaces specifically…
Author: Rowena Rodrigues; Publisher: Journal of Responsible Technology; Publication Year: 2020. The following article looks at how ethical issues such as algorithmic transparency, cybersecurity vulnerabilities, unfairness, bias and discrimination, lack of contestability, legal personhood issues, intellectual property issues, adverse effects on workers, privacy and data protection issues may result in serious liability for damage and lack of accountability as…
Author: Rick Buck; Publisher: Wirewheel; Publication Year: 2021. The following article describes how each and every year there are new privacy laws that may be put into place that we as users of exploring and interpreting need to understand and be aware of. Without doing so, there could be repercussions for both us and the company we are working for making us subject to both lawsuits and financial penalties…
Author: Richard Water; Publisher: Financial Times; Publication Year: 2021. The following article discusses how big tech companies are using “Dark Patterns” in order to nudge their userbase into certain patterns of behavior. In a “race to the bottom” for market share and profits, these algorithms are based on reinforcement learning which creates a feedback loop in order to increase the likelihood users take an action. These…