Tag: Artificial Intelligence

UnSchool of Data is BetaNYC’s open space unconference for networking, co-creating, and learning. It brings together city residents, technologists, civic leaders, students, advocates, policy nerds, government staff, elected officials, journalists, designers, and more to leverage open data to tackle some of the most pressing issues in NYC and beyond.

It’s a community driven day for turning open data into civic solutions.

UnSchool of Data has these underlying goals:

  1. Convene community members to share civic insights and ideas.
  2. Create processes/projects that people will use for further action.
  3. Foster formal and informal communities of practice and action.

Learn more about UnSchool of Data and how it works at www.schoolofdata.nyc/unschool.

Can you trust the story that data tells about your city? In this 60-minute online workshop, participants will explore a curated slice of NYC’s 311 Service Requests dataset to see how everyday complaints become “data” about neighborhood life, services, and problems. Together, we’ll ask whose experiences appear in the dataset, what gets counted or left out, and how those choices shape the stories we tell with civic data.

Led by Dr. Cecilia Dones, a researcher and strategist whose work bridges data, social science, and AI transformation, the session is designed for curious New Yorkers with no technical background required. After a brief guided tour of a 311 data snapshot, participants will work in small groups on Zoom to pose questions of the data and then use a simple AI text tool to generate short headlines or summaries. Groups will annotate and critique these machine-written “stories,” examining what the AI emphasizes, what it omits, and how context and bias influence its interpretations.

This workshop is ideal for residents, educators, community organizers, public servants, and anyone interested in building data literacy and AI literacy as civic skills. Participants will leave with practical questions they can bring to any AI-generated account of civic life and a clearer sense of why human judgment remains essential when machines translate public data into narratives.

This session explores advanced analysis of NYC residential property sales (2019–2024) using NYC Open Data, with a focus on model improvement and AI integration. Researchers Yue Ru Li and Chunhong Zhao will demonstrate how combining Department of Finance sales data with Department of Buildings permit data can enhance predictive performance. Participants will work through a hands-on Python notebook covering feature engineering, data visualization, and machine learning models, while also learning how an embedded AI assistant can streamline data cleaning, feature generation, and model interpretation.

Food prices are too *&#$ high!

Everyone is talking about grocery price inflation, but how do we really figure out individual item price changes? Let alone keep track of prices across different stores and neighborhoods? In combination with recessionary trends and other food justice issues, it’s stressful for budget-conscious people to make well-informed buying decisions.

This talk will demo an exciting new community tool PriceWise. This web application creates a database of food prices to help families and individuals easily digitize their grocery receipts and work together to pool that data across their community. The tool uses NYC OpenData to connect these prices with stores and neighborhoods.

Designer and developer Shiva Muthiah will talk about how and why they built this tool, and discuss why making food pricing more legible can help policy-makers address food justice challenges.

DataKind builds free and open software in the public interest. Spanning such diverse services as community mapping, predictive modeling, data transformation, data quality checks, and more, DataKind works with social impact organizations to build solutions that are usable, useful, and context-appropriate – and then helps organizations adopt those solutions at scale. This session will feature demonstrations of several of DataKind’s tools, introductory training, access to references, use cases, and paths to learn more and to participate in our software advisory group.  Tools include ladderhub.org, colandrapp.com, getedvise.com, fencelinedata.org and more.

All attendees are welcome and there is no prerequisite level of data literacy, digital literacy, or awareness of free and open source tools. All information and resources will be provided to attendees.

NYC School of Data is BetaNYC’s community conference that demystifies the policies and practices around open data, technology, and service design. This year’s conference helps conclude NYC Open Data Week and features 40+ sessions organized by NYC’s civic technology, data, and design community! Our conversations and workshops will feed your mind and inspire you to improve your neighborhood.

To attend, you need to purchase tickets. The venue is accessible, and the content is all-ages friendly! If you have accessibility questions or needs, please email the BetaNYC team at [email protected].

Thank you to Reinvent Albany for their support as Lead Partner and helping cover conference costs to make it possible to meet in 2026. Additional sponsors include HaydenAI, School of Visual Arts, and The Center for Urban Science + Progress (CUSP) at NYU Tandon. 

If you can’t join us in person, tune into the main stage live stream provided by the Internet Society New York Chapter. Follow the conversation #NYCSoData on Bluesky.

Purchase your tickets here.