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Root Out Bias in Decision‐making                                         53














                          Figure 11.1  Muller–Lyer optical illusion with and without frame.


             Implications
             Learning how to spot and avoid bias in your own decisions will give you a new appreciation
             for how insidious bias is and how difficult it is to eliminate. You will not get anywhere preach-
             ing about bias while hiding your own. So, smart data scientists and CAOs strive first to lead
             by example.
               This discussion underscores why it is so important that CAOs and, to a lesser degree, all
             data scientists advance a data‐driven culture.
               Thus, the real work of data scientists and CAOs involves lessening the bias that creeps into
             their own decision‐making along with leading by example. Finally, as opportunity permits, the
             real work involves helping decision‐makers recognize and then reduce their biases as well.
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