As part of the Honors When Machines Decide Praxis Lab on Big Data and Machine Decision-making, students explored the increasing use of automated decision-making in society.  These opaque systems operate silently in the background, with little transparency, yet make decisions that significantly impact us in virtually every facet of our life. For more information on the year-long class, see the course Marriott Library Subject Guide at here

Learning Resources

Below are some valuable resources that helped educate us on Machine Learning, and we hope will help educate you as well

This report by the previous presidential administration identifies potential dangers involving algorithms, and the Obama Administration's presented solutions to those problems.

The key article that ignited our concerns regarding Sentincing algorithms

ProPublica's excellent continued coverage on Machine Learning and it's possibility for Bias.

The set of best practices we have compiled and believe should be followed during the implementation of Machine Learning algorithms into criminal Justice Sentencing.

A fasacinating article which showcases the lack of accountability we can hold Machine Learning algorithms to.

A example of unintentional bias appearing with the algorithms used by Amazon for Prime Shipping.

A bit of a catchy headline, but an interesting delve into the possibility for algorithms to develop biases nonetheless.

Algorithms are also being used in predictive policing. This video explains how that works

Our machine learning algorithm, used to train a model based on YOUR decisions in Justice.exe.