First and foremost, Welcome! Willkommen! Bienvenue!

Thank you for visiting the Sentencing By Numbers project repository. This document (the README file) is a hub to give you some information about the Sentencing by Numbers project.

Governments are using technology to decide prison sentences, provide medical care, or give access to affordable housing. These decision-making tools are made from algorithms to measure "risk" in the United States and assign "social scores" to individuals in China. Although this technology touches on many facets of our daily lives, these tools are often implemented without user consent. Communities should have a right to dismantle these “black boxes” and evaluate whether these tools are perpetuating racial, ethnic, and economic biases. Citizens have the right to know whether governments are churning data, embedded with biases, into a perpetual cycle of erroneous results.

We aim to strengthen the public knowledge of how algorithmic technology may be undermining data privacy by (1) sharing information on specific tools and practices governments are currently using to surveil their citizens, and (2) developing hands-on workshops for residents to create their own community-centered solutions for protecting their personal data. We hope this project will foster digital literacy and help the public understand the computational limitations of algorithmic tools.

Please join us during the Global Sprint to dismantle these black boxes and help the public reveal what is behind the curtain of these machines.

Example Projects

1. Algorithm Zine -- "Algorithm Killed the Radio Star"

2. Algorithm Game Scenarios are given and the participant decides if they agree or disagree with the case study. Example: An algorithm is used to determined whether to remove a child from their home.

3. A webtool of over 100 algorithmic tools used in USA. Global Sprint participants could help contribute to asking questions about data or with visualization

4. There is an open sourced algorithm used for predictive policing. Participants could examine it and use REAL data sets to analyze the source code

The Sentencing by Numbers project would like your input on how we could increase the transparency of algorithms designed and used by governments in the public sector. Are you a computer scientist with a background on AI? Or are you may be a talented visual artist. Or someone who is good at reminding your team lunch is ready? We welcome your ideas and unique talent, and will not discount anyone's contribution.

Advance knowledge or experience with algorithms, machine learning, or statistics will contribute to this project by creating models or tests to evaluate public domain tools or reverse engineer proprietary tools. A critical part of understanding how algorithms make decisions is to review the dataset that “trains” the algorithm. Participants will play an essential role in helping our team analyze datasets consisting of public safety and incarceration statistics.

Beginners intersted in using data visualization skills could also assist with developing infographics from data that are accessible to local criminal justice advocacy leaders, legal aid institutions and national networks focused on the intersection of big data and criminal justice in municipalities nationwide, and media.

This project adheres to Mozilla's Code of Conduct OR code of conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to [EMAIL].

Join us at the Mozilla's Global Sprint May 10-11, 2017! We'll be gathering in-person at sites around the world and online to collaborate on this project and learn from each other. Get your #mozsprint tickets now!