Understand, Manage, and Prevent Algorithmic Bias: A Guide for Business Users and Data Scientists

© Tobias Baer 2019

Tobias BaerUnderstand, Manage, and Prevent Algorithmic Biashttps://doi.org/10.1007/978-1-4842-4885-0_18

18. The Data Scientist’s Role in Overcoming Algorithmic Bias

Tobias Baer¹ 

(1)

Kaufbeuren, Germany

 

As our journey through the world of algorithmic bias has shown, data scientists are facing a formidable challenge, where age-old societal practices and biases, business owners, users, naughty datasets, and the tired brain of the data scientist all might conspire to introduce algorithmic bias. At the same time, data scientists have a lot of powers to contain algorithmic biases through thoughtful modeling choices. In this final part of the book, we will discuss in greater and more technical detail the most important techniques for ...