Challenges associated with algorithmic decisionmaking from "summary" of Automate This by Christopher Steiner
Algorithmic decision-making poses a myriad of challenges that go beyond the technical aspects of coding and data analysis. One of the most significant challenges is the lack of transparency in how these algorithms arrive at their decisions. Unlike human decision-making, where we can often explain our thought process and reasoning, algorithms can be black boxes, making it difficult to understand why a particular decision was made. Another challenge is the potential for bias in algorithmic decision-making. Algorithms are only as good as the data they are trained on, and if this data is biased in any way, the algorithm's decisions will reflect that bias. This can lead to unfair outcomes, such as discrimination against certain groups or individuals. Moreover, the complexity of algorithms can sometimes lead to unintended consequences. Even...
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