Being a data professional: give voice to value in a data driven society
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ORIGINAL RESEARCH
Being a data professional: give voice to value in a data driven society Don Gotterbarn1 · David Kreps2 Received: 9 July 2020 / Accepted: 2 November 2020 © Springer Nature Switzerland AG 2020
Abstract Data Analytics needs to have ethical standards. There are numerous examples of why this is so, and the paper cites four particularly egregious ones. The paper offers both reasons why such standards are currently missing or inadequate, and how they might best be introduced, or refined. Some Codes of Ethics, such as the Software Engineering Code of Ethics and Professional Practice, the ACM and IFIP Codes of Ethics, and the Web Analyst’s Code of Ethics are discussed, compared, and contrasted. The paper offers a comparative study, to help inform the process of the drawing up of guidelines where it is best undertaken, within the profession itself. Keywords Data analytics · Ethics codes · Professionalism
1 Introduction The central claim of this paper is that Data Analytics needs to have ethical standards. Our contribution is to isolate both reasons why such standards are currently missing or inadequate, and how they might best be introduced, or refined. Without appropriate standards, data analytics professionals can find themselves contributing to public harm, or, where they are resisting such harms, lacking the coherence and professional muscle a dedicated and properly focused Data Professional Code of Ethics might give them. The public harm to which data analytics professionals are currently contributing is well documented. Just four headline-grabbing examples will paint a picture of a profession in crisis. First, the much-publicized scandal around the now defunct data-harvesting firm, Cambridge Analytica, in which the personal data of Facebook users was used for the microtargeting of often deliberately misleading political adverts [6, 7]. Second, Hoan Ton-That’s new facial recognition app, Clearview AI, being used already by law enforcement agencies ranging from local police forces in Florida to the F.B.I. and the Department of Homeland Security [20]. Clearview * David Kreps [email protected] Don Gotterbarn [email protected] 1
East Tennessee State University, Johnson City, USA
National University of Ireland, Galway, Ireland
2
AI incorporates a database of more than 3 billion images scraped from Facebook, YouTube, and other websites, and facial recognition software enabling you to take a picture of someone’s face with your smartphone, and immediately see other photos of them in the app—all too often revealing their identity [20]. Third, the epidemic of covert web tracking means that almost any website we now visit will be sending data about us to dozens of third parties, without our knowledge or consent, data which may follow us on Bluetooth and Public WiFi into physical public spaces, linking our behavior online with our physical movements and purchasing activity. As the Electronic Frontier Foundation author Bennett Cyphers describes it, “Corporations have built a hall of one-way
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