Bias present in algorithms from "summary" of Automate This by Christopher Steiner
The bias present in algorithms is a thorny issue that often goes overlooked in the world of automation. Algorithms are designed with specific goals in mind, but they can inadvertently perpetuate bias due to the data they are trained on. For example, a machine learning algorithm used to screen job applicants may be biased against certain demographics if the training data used to develop the algorithm contains discriminatory patterns. This bias can have far-reaching consequences, as algorithms are increasingly used to make important decisions in various industries, from finance to healthcare to criminal justice. If left unchecked, biased algorithms can perpetuate unfair practices and deepen existing inequalities in society. One of the main challenges in addressing bias in algorithms is the lack of transparency in how these algorithms work. Many algorithms are proprietary and their inner workings are closely guarded secrets. This makes it difficult to identify and c...
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