How Safe Is Your Bike Ride? Using Open Data to Find Better Routes
2026-08-04 14:00 - 18:00 (America/New_York) | NYC PIT Pop Up at The Oculus, 185 Greenwich Street, Shop #LL4345, Level LL4, New York, NY, 10006, United States
Urban planning researcher Peter Furth developed a framework called Level of Traffic Stress (LTS) to measure how stressful streets are for cyclists. Using street data from OpenStreetMap, Tajairi Brown-Neuson applied this framework to rate every street in NYC on a scale of 1–4, based on characteristics like speed limits, number of lanes, and presence of protected bike lanes (1 being most comfortable, 4 being least). They then layered in data from Open Data NYC: fatal and severe injury incidents, plus 311 complaints to identify areas with high double-parking frequency. The result is a map that helps cyclists identify the safest routes—and highlights where infrastructure improvements are most needed.

Beneficial Computing (Day Two)
2026-08-06 14:00 - 18:00
Beneficial Computing is building digital infrastructure to help people navigate complex government benefits systems starting with federal disability benefits (SSI/SSDI). Our project is an AI-powered eligibility screener that helps individuals and frontline service providers understand whether someone may qualify for disability benefits and what evidence or documentation may be needed.
Applying for SSI or SSDI is notoriously complex. The application process can take months or years, has a high initial rejection rate, and requires detailed medical, financial, and work history information. Many eligible people never apply, while human service organizations spend enormous time trying to interpret complicated eligibility rules.
Our tool translates these rules into an interactive chatbot-style screening experience that helps people understand eligibility pathways and prepare for applications. At the Pop Up, we will demo the screener and invite participants to test it themselves. We’re especially interested in feedback from technologists about usability, transparency, and how AI tools can responsibly support public benefits navigation.
We’re excited to include this project because access to benefits is a fundamental part of how people experience government. If public systems are confusing or inaccessible, trust erodes. We believe public interest technology should help translate bureaucratic systems into tools that actually work for people.

City Lens NYC
2026-08-13 14:00 - 18:00
citylensnyc.com
City Lens NYC is a civic technology platform that translates complex New York City data into accessible, usable insights for everyday people. NYC has one of the largest open data ecosystems, but most residents do not have the time, technical skills, or context to actually use it. City Lens closes that gap.
The platform lets users explore neighborhoods, understand zoning and development, ask questions about policies, and see how changes like gentrification, infrastructure projects, or permits affect their communities. It combines data storytelling with an AI-powered interface so users can ask real questions in plain language and get clear answers.
I am excited to include City Lens as a Public Interest Technology project because it focuses on accessibility, transparency, and empowerment. It is not just about data, it is about helping people understand what is happening around them and feel confident engaging with their city. Long term, I want this to become a tool communities, students, and organizers can use to make informed decisions and advocate for change. Showing in real time what translating datasets into visualization for the public looks like.
