By relying on flawed data from "summary" of Weapons of Math Destruction by Cathy O'Neil
Relying on flawed data is like building a house on a shaky foundation. The data we feed into algorithms shapes their outcomes, so when that data is faulty or biased, the results can be harmful. Take for example the case of predictive policing, where algorithms use historical crime data to forecast where crimes are likely to occur. If the data used is based on biased policing practices, such as targeting certain neighborhoods more heavily than others, then the algorithm will perpetuate those biases, leading to increased surveillance and policing in already over-policed communities. Similarly, in the realm of education, standardized testing data is often relied upon to evaluate teacher performance and student success. However, if the tests are culturally biased or do not accurately measure a student's true abilities, then the data generated will not reflect reality. This can lead to teachers being unfairly j...
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