Difference between revisions of "Predictive Modeling Algorithms"
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==Introduction== | ==Introduction== | ||
| − | A '''black box algorithm''' is one where the user cannot see the inner workings of the algorithm. It is a rather controversial system, due to the secrecy they contain and the lack of transparency, although its creators defend it as a security and privacy system to avoid data leaks and unfair competition.[https://www.arimetrics.com/en/digital-glossary/black-box-algorithm#:~:text=A%20black%20box%20algorithm%20is,data%20leaks%20and%20unfair%20competition.] | + | A '''black box algorithm''' is one where the user cannot see the inner workings of the algorithm. It is a rather controversial system, due to the secrecy they contain and the lack of transparency, although its creators defend it as a security and privacy system to avoid data leaks and unfair competition.[https://www.arimetrics.com/en/digital-glossary/black-box-algorithm#:~:text=A%20black%20box%20algorithm%20is,data%20leaks%20and%20unfair%20competition.] Black box algorithms are computer programs that make predictions or decisions based on a set of inputs, but the internal workings of the algorithm are not visible or transparent to the user. These algorithms are increasingly being used in areas such as criminal justice, finance, and healthcare, and their use has raised many important ethical and legal questions.One of the main concerns about black box algorithms is the potential for bias and discrimination. Because the internal workings of the algorithm are not transparent, it can be difficult to detect and correct for any biases that may be built into the system. This can lead to unfair and unjust outcomes, particularly for marginalized groups such as people of color and low-income individuals. |
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== Examples of Black Box Algorithms == | == Examples of Black Box Algorithms == | ||
Revision as of 01:09, 27 January 2023
Contents
Blackbox Algorithms
Introduction
A black box algorithm is one where the user cannot see the inner workings of the algorithm. It is a rather controversial system, due to the secrecy they contain and the lack of transparency, although its creators defend it as a security and privacy system to avoid data leaks and unfair competition.[1] Black box algorithms are computer programs that make predictions or decisions based on a set of inputs, but the internal workings of the algorithm are not visible or transparent to the user. These algorithms are increasingly being used in areas such as criminal justice, finance, and healthcare, and their use has raised many important ethical and legal questions.One of the main concerns about black box algorithms is the potential for bias and discrimination. Because the internal workings of the algorithm are not transparent, it can be difficult to detect and correct for any biases that may be built into the system. This can lead to unfair and unjust outcomes, particularly for marginalized groups such as people of color and low-income individuals.
Examples of Black Box Algorithms
COMPAS
As technology advances, more and more decisions affecting individuals are being made by hidden algorithms in our society. One area where this has raised concern is in the criminal justice system, specifically regarding the fairness and due process of these algorithms. One example of a widely-used, yet secretive algorithm is COMPAS (which stands for Correctional Offender Management Profiling for Alternative Sanctions) has been the focus of many legal challenges.
