August 2020
Beginner
344 pages
10h 23m
English
Content preview from 97 Things About Ethics Everyone in Data Science Should Know
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Chapter 71. Equally Distributing Ethical Outcomes in a Digital Age
Keyur Desai
Data is an incorruptible raw material that is analyzed to reveal and prove the Truth—essentially, “Data is Truth.” This is a notion that has erroneously permeated society ever since data was first used for scientific understanding in the mid-17th century. What is closer to reality is that, when used incorrectly, data is a corruptible raw material that can be physically manipulated to derive a truth/insight that suits an originator’s own interests or to derive a truth/insight that fits an originator’s conscious or subconscious bias. I like how author Stephen Jay Gould succinctly and poignantly phrased this in his book The Mismeasure of Man (W. W. Norton): “Expectation is a powerful guide to action.” Recent and distant history is littered with examples of individuals and communities who have been wrongly affected by actions justified by the biased analysis of data or algorithms. Data can impact the dynamics of power, human life, health, knowledge, beliefs, and welfare. Algorithms can reinforce oppression and inequality and can tie into surveillance capitalism. What I like to think is that “Data is Truth only when used with ethics and integrity.”
To reveal its truth, data must be used with integrity and ethics throughout its entire supply chain. That is, data must be used ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.