# ai: apropos of black box approach in machine learning algorithms

<< A black box is a machine learning program that does not explain how it reaches its conclusions, either because it is too complicated for a human to understand or because its inner workings are proprietary. In response to concerns that these types of models may include unjust inner workings—such as racism—another growing trend is to create additional models to "explain" these black boxes. >>

<<  Even when so-called explanation models are created, (..) decision-makers should be opting for interpretable models, which are completely transparent and easily understood by its users. >>

Ken Kingery. Stop gambling with black box and explainable models on high-stakes decisions. Duke University.  May 14, 2019.

https://m.techxplore.com/news/2019-05-gambling-black-high-stakes-decisions.html  

Cynthia Rudin. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence. volume 1, pages 206–215 May 13, 2019

https://www.nature.com/articles/s42256-019-0048-x