Since May 2020, Black Lives Matter protesters have taken to the streets to exercise their right of free speech, only to be assaulted with tear gas, rubber bullets, and beatings by law enforcement. One protester from New York recalls lying in a pool of blood on the road, before being arrested and denied medical attention.

As the BLM Movement continues, protesters grow increasingly fearful that they will be abused and arrested by law enforcement. Our HackRice project seeks to protect these protesters by matching them with the right pro bono lawyer for their specific situation, allowing them to feel secure when using their voices for social justice.

What it does

We begin by prompting the protester to fill out a questionnaire, so that our matching algorithm can determine which pro bono lawyer is best for them, depending on a variety of differently weighted parameters (including protester’s location, case area of expertise, preferred language, racial group, etc.) Then, our algorithm returns the top three best-match lawyers for that specific protester, with all necessary information.

We also implemented an Application page on the website, where pro bono lawyers can volunteer their services for those in need. They simply input their information into the form, and we automatically add it to the database, so that they can be matched with protesters in the future. We also have a Donate page, which provides links to external sources with similar missions

How we built it

Our website was built with JavaScript, as well as HTML and CSS in a React framework. We stored our databases in Airtable, and we implemented our fillable forms using Formik.

Challenges we ran into

Challenges that we ran into included choosing a database. We considered using Google Sheets, MongoDB, which provided a low-level and high-level solution. In the end, we chose Airtable, combining elements of both to provide us with a continuously updating database service.

Accomplishments that we're proud of

We are proud of completing a project that we initially deemed ambitious and difficult to complete under the given time parameters. We connected to a database of lawyers, retrieved information from it, put the information into an algorithm, and determined which three lawyers would be the best fit for a particular individual or user. We created forms to take the user’s location, languages, case areas, racial groups, etc., in order to customize this process. We also use a form for pro bono lawyers that allows them to be added to the database and included in future searches.

What we learned

We learned a great deal of technical skills, such as working with new API and processing data into an algorithm.

What's next for No justice. No peace.

Our team plans to increase the scope of our solution to the national scale. There has been a sizable amount of data and publicity on pro bono lawyers since the protests began, and therefore we plan to increase the size of our database to span across the nation. This way, protesters in any city in the United States can find the pro bono lawyers that are best matched with them.

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