All technologies
Every technology the NYC Office of Technology and Innovation has published on this register. Narrow it by what it is for or whether it can identify you.
How to read the colours
Can it identify you?
- Anonymized data
- Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
- Pseudonymous data
- Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
- Identifiable data
- The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.
Who completes the loop?
- Human decides
- This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
- Human executes
- This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
- Autonomous
- This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.
Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.
Showing 10 of 86 published
  AI Assistant for City Staff Productivity and Research Inform · Planning & Decision-making | Office of Technology and Innovation (OTI) | Identifiable data | No fixed location |
  AI Risk Scoring for Child Welfare Prevention Services Risk Assessment & Triage · Planning & Decision-making | Administration for Children's Services (ACS) | Anonymized data | No fixed location |
 AI-Assisted Child Welfare Caseload Forecasting for NYC Planning & Decision-making · Employment & Work | Administration for Children's Services (ACS) | Anonymized data | No fixed location |
AI-Assisted Community Feedback and Sentiment Analysis Inform · Planning & Decision-making | Mayor's Office | Anonymized data | No fixed location |
 AI-Assisted Drafting of City Agencies Reference Dataset Planning & Decision-making | Office of Technology and Innovation (OTI) | Anonymized data | No fixed location |
 AI-Assisted Language Interpreter Allocation for Poll Sites Eligibility & Public Benefits · Planning & Decision-making | NYC Civic Engagement Commission | Anonymized data | No fixed location |
AI-Assisted Random Selection for Citizen Budget Panels Eligibility & Public Benefits · Planning & Decision-making | NYC Civic Engagement Commission | Pseudonymous data | No fixed location |
AI-Assisted Summarization of Community Planning Input Planning & Decision-making · Inform | Department of City Planning (DCP) | Anonymized data | No fixed location |
 AI-Assisted Traffic Signal Control for Midtown Manhattan Mobility · Planning & Decision-making | Department of Transportation (DOT) | Anonymized data | No fixed location |
AI-Assisted Two-Year Jail Population Forecast Planning & Decision-making | Department of Correction (DOC) | Anonymized data | No fixed location |