Challenges

Hack for Black Lives Challenges

Below you will find descriptions of challenges provided by our sponsors! Challenges are meant to inspire our hackers to create positive change for a specific challenge, community, or concept relating to the Black Lives Matter movement. Each challenge is sponsored by one of our partners, and they have provided descriptions and resources for you to best understand how to create a project for the challenge.

When submitting your project, you can indicate if you would like to submit for a specific challenge. Projects for a submitted a given challenge will be reviewed by the challenge sponsor, and they will select specific projects which they would like to showcase, or even continue after the completion of the Hackathon!

Challenges

Improving Covid 19 Tracking

Sponsor: Professor Xanda Schofield, HMC

The COVID Tracking Project collects information from state and federal sources to track COVID-19 cases and outcomes, including with a breakdown by race (https://covidtracking.com/race). This data is important to document how structural inequality leads to different health outcomes dependent on race, but not all states report this information. Data for Black Lives reports similar concerns about inconsistent data availability and the importance of capturing and documenting this information, along with how this data can be misused to police communities instead of to provide community aid (https://d4bl.org/covid19-data.html). A project here would aim to improve data quality and availability for understanding racial disparity in COVID-19 outcomes. Tasks may include

- contacting the regional, state, and federal governmental offices responsible for this data to advocate for better access (see https://covidtracking.com/race/get-better-data),

- implementing code fixes in automatic data collection scripts from posted reports for aggregating dashboards (e.g. https://github.com/d4bl/COVID19_tracker_data_extraction/), or

- performing individual data analysis on the available data at a regional level (e.g., Southern California) and writing a blog post documenting local trends and concerns.

Regulating Algorithmic Bias in facial recognition

Sponsor: Professor Xanda Schofield, HMC

Several recent works, including the documentary Coded Bias (available through Honnold Mudd Library at https://ccl-on-worldcat-org.ccl.idm.oclc.org/oclc/1200171382), have documented how facial recognition technologies can cause societal harm. Specifically, facial recognition software often has worse accuracy on non-White faces, while also coupled with deployment both public and private policing that often targets Black people. In this project, you would investigate your local community's regulation and use of facial recognition: check if police, schools, or public housing use these tools and/or if they regulate their use. Reach out to your city council or local government about regulation and the harms these tools can cause, and/or publicly share a report on this information in some way (e.g. via your own website or a local news organization). This can also be an opportunity to build online data visualizations or an interactive demo/website that showcases how these technologies may cause harm.

As a starting point, the Algorithmic Justice League has a compiled list (https://www.ajl.org/facial-recognition-technology) of a variety of public actions, including state and federal legislation and local community action, to combat the use of facial recognition in the context of policing, schooling, employment, and beyond. Additional resources on how to take action are available via the Ban the Scan campaign from Amnesty International (https://banthescan.amnesty.org/).