From the course: Ethics and Law in Data Analytics

A Data oath

From the course: Ethics and Law in Data Analytics

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A Data oath

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- So you heard from Nathan about Ethical Data Practice as it relates to Moral Maximums, what one ought to do, even if there are no legal repercussions, and from Eva, you heard about the legal side of things, where it's we have restrictions, perhaps a moral minimum provides sort of the guardrails for data practice. But what should a practitioner actually look at day to day to inspire her or him to do ethical data work? I look to other disciplines to draw inspiration for this and healthcare comes to mind. There's this old guy name Hippocrates, who lived way back when, and created what's called the Hippocratic Oath for healthcare practitioners. And what's fun is it's sort of inspiring, it's declarative, I swear by this or that to do these things well, but it's actually used in modern healthcare, often times it will be framed or referenced, and that's mainly to provide some sort of ethical guideline for healthcare work. And in data, we don't really have the centralized version of this, but there are examples out in the wild. Perhaps maybe one is UN's 1985 Declaration for Statisticians. And it's extensive, it's focused on best practices as a relate to that sub-discipline. It's extremely long and thorough and great, but I doubt a lot of data practitioners have read it. So we're going to reference it in the further notes, but please take a look at that if you like, it is a good example but it's a little dated. Another one would be Certified Analytics Professional's Code of Conduct, and this one's fun, it is focused on the obligation of others, and not a lot about what I as a data practitioner am going to do, perhaps. Maybe missing that fun, declarative aspect of I swear by this or that. So I'm going to take another crack of this and give you what I call an updated Data "Oath", and it's perhaps what I would say, if I were doing data work to do data ethically and do it well. So you can say it with me, you can put it on your wall, so I, as a Data practitioner, will promote the well-being of others and myself, that's hearkening back to Nathan's work on the ethic stuff, while striving to do no harm with data, perhaps to the legal side, through professional application of analytical techniques, number one. And I do my job well. I know how to interpret p-values and correlation and not bump into causation, I know how to do data visualization well, proper cleaning and transforming and analysis of data sets, that's all part in parcel of doing analytics well, and of course, fundamental to our job. And maybe next would be humility and analytic claims, so that's maybe a step farther with the correlation stuff moving into predictive analytics, moving into more of these inferences that you make. Perhaps you give some confidence interval range of what you're claiming, you speak with as much honesty and humility as you can when it comes to these analytic products. And also, hopefully what this course is prepping you to do is to anticipate legal and regular Tory needs, and that goes without saying. And almost in transparency in computation and documentation, is also something that's going to reoccur throughout the modules in this course, where we want to share what's happening in the data processing and in the output space, so that we can avoid things like bias and protect privacy, and all those things that we're going to investigate in the next modules. And lastly I'd say, fidelity to this oath beyond the bottom line, and that's maybe in ethics we call it a supererogatory claim to promote people and encourage them to do good with their data work beyond corporate bottom lines or individual success for the good of society and the world of large. Thank you.

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