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They help us decide what to watch, what to read, and some even make it easier to parallel park. But even an allegedly unbiased algorithm can't overcome biased data or inconsistent implementation. Because of this, we have what's called the "Ripple Effect Trap. " According to the researchers: When a technology is inserted into a social context, it has both intended and unintended consequences. Chief among the unintended consequences are the ways in which people and organizations in the system will respond to the intervention. To truly understand whether introduction of the technology improves fairness outcomes, it is not only necessary to understand the localized fairness concerns, as discussed above, but also how the technology interacts with a pre-existing social system. In essence, this means that by giving judges the choice to use the algorithm at their own discretion, we're influencing the system itself. Human intervention doesn't make a logic system more logical. It just adds data that's based on "hunches" and "experience" to a system that doesn't understand those concepts.