Unlocked Labs trains and hires returning citizens to do contract software development work upon release.
Those formerly incarcerated, despite their training and credentials, face barriers in securing high-paying, career-advancing jobs. Our approach enables talented individuals to access upwardly mobile employment upon release.
Our team offers a unique perspective to help develop your project, having an insider's understanding of the current challenges associated with corrections. We'll work with you every step of the way to customize a solution that suits your specific needs.
The Alliance for Higher Education in Prison mobilizes talent and resources toward expanding higher education and academic reentry support services to incarcerated and formerly incarcerated individuals. Entering the next phase of their mission and looking for a new website, the Alliance contracted with Unlocked Labs to determine how to best communicate their action plan.
Our engineering manager and our justice-involved apprentices worked in conjunction with the Alliance to recommend a revamped website design and business model to support higher education initiatives in prison.
Lucy Johnson reported that a Black male with brown hair wearing a black jacket assaulted her in Midtown, next to Johnson's home. She reported the incident to Officer Lee.
[Victim 1] reported that a [race] male with [hair color] wearing a black jacket assaulted her in [neighborhood], next to [Victim 1]'s home. She reported the incident to [Officer 1].
Stanford University's Computational Policy Lab has created a “blind charging” algorithm that automatically removes race-related details from crime reports, thereby minimizing the impact of racial bias in prosecutorial charging decisions.
The lab has hired Unlocked Labs to employ formerly incarcerated developers to build their website in addition to writing test-harnesses and training the AI algorithm itself.This initiative will aid prosecutors nationwide in adhering to the increasing prevalence of race-blind mandates in the evolving legal landscape.
Graduates of our coding education program supported Raj Jaladi in building a natural language processing prototype that predicts whether a legal case or situation involves a violation of an article or amendment of the U.S. Constitution.
Our team members worked with Raj to build out a user interface that allows individuals to input text and generate a response from an AI chat bot trained on case summaries of the Supreme Court. The web-UI consists of a simple text input, where a user can type in a question and/or topic summary, and the response is displayed below the text box.
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