Mathematical models can be opaque from "summary" of Weapons of Math Destruction by Cathy O'Neil
The concept of opacity in mathematical models is a crucial one to grasp. When we say that a model is opaque, we mean that it is difficult for an outsider to understand how it reaches its conclusions. This lack of transparency can be dangerous, as it opens the door for all sorts of biases and errors to creep in unnoticed. One reason why models can be opaque is their complexity. Many mathematical models are highly intricate, involving countless variables and equations. When you're dealing with such a complex system, it can be nearly impossible for a layperson to make sense of how it works. This complexity is compounded by the fact that many models are proprietary, meaning that their inner workings are closely guarded secrets. Another factor that contributes to opacity is the use of black box algorithms. These algorithms operate in a way that is completely hidden from view, making it impossible to trace how they arrive at their decisions. This lack of transparency can be particularly troubling when these algorithms are used to make important decisions that affect people's lives, such as in the criminal justice system or in the granting of loans. Opacity in mathematical models can also stem from the biases of their creators. When building a model, it's crucial to make certain assumptions about the data that is being used. These assumptions can be influenced by the biases of the modeler, leading to skewed results. If these biases are not made explicit, they can lead to unfair and discriminatory outcomes. In order to combat the opacity of mathematical models, it is essential to demand greater transparency. This means opening up the black box algorithms to scrutiny, making the underlying assumptions of the model explicit, and involving a diverse set of stakeholders in the process. By shedding light on the inner workings of these models, we can begin to hold them accountable and ensure that they are not perpetuating harm.
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