AI-Predicted High School Acceptance Chances for Students
What it is for
Education & Learning
- The system supports high school application decision-making for eighth-grade students and their families by showing predicted acceptance chances for each school they consider in the MySchools portal.
NYC AI Use Case Register — MySchools Probability of Acceptance
Inform
- Information is presented to students and parents to help them decide what high schools to apply to, displayed as a 'high,' 'medium,' or 'low' icon alongside each school listing in the MySchools application.
NYC AI Use Case Register — MySchools Probability of Acceptance
- Run by
- NYC Public Schools (NYCPS)
- Where
- No fixed location
- Kept
- Not stated by the NYC Office of Technology and Innovation.
- Shared with
- Not stated by the NYC Office of Technology and Innovation.
What it is for
This tool estimates the likelihood that a student will receive an offer from a specific New York City public high school, displayed as "high," "medium," or "low" while the student is choosing schools to apply to. It uses student records and admissions characteristics — such as grades, borough, priority group, and school admissions method — to calculate these probabilities. The model was developed by MIT researchers and integrated into the NYC MySchools application. Students and families should know that the scores are advisory only and do not determine admissions outcomes.
What it collects and what happens to it
Data taken in
Sensitive personal information
Identifiable data
- Student records including grades, district or borough, and priority group. These are personally identifiable records drawn from NYC Public Schools' student information systems and used at runtime to compute acceptance probabilities.
NYC AI Use Case Register — MySchools Probability of Acceptance
About behaviour
Identifiable data
- The student's in-progress high school selections within the MySchools application — the schools a student is actively considering or adding to their list — are used as runtime input to trigger and display the probability score for each chosen school.
NYC AI Use Case Register — MySchools Probability of Acceptance
Operational data
Anonymized data
- Data about New York City public high schools used by the model, including each school's admissions method (open enrollment or screened), historical offer patterns, and other school-level characteristics. This is not tied to individual students.
NYC AI Use Case Register — MySchools Probability of Acceptance
Processing
Classification & Prediction
- The model classifies the likelihood of a student receiving an admissions offer from a specific school into one of three tiers — 'high,' 'medium,' or 'low' — based on the student's admissions characteristics and the school's admissions method. Computed daily for students actively using the MySchools portal.
NYC AI Use Case Register — MySchools Probability of Acceptance
What it does
Deciding (Analytical AI)
Human decides
- The system scores and classifies each student–school pair into a 'high,' 'medium,' or 'low' acceptance probability tier based on admissions characteristics. The student and family retain full decision-making authority over which schools to apply to.
NYC AI Use Case Register — MySchools Probability of Acceptance
Outputs
A recommendation or prediction
Identifiable data
- A probability-of-acceptance indicator displayed to a specific student — shown as 'high,' 'medium,' or 'low' — for each high school they are considering in their MySchools application. The score is advisory and does not determine whether the student receives an offer.
NYC AI Use Case Register — MySchools Probability of Acceptance
Run by
NYC Public Schools (NYCPS)
- NYC Public Schools is the accountable agency that deployed the probability-of-acceptance feature within the MySchools application. The Division of Instructional and Information Technology integrated the MIT-developed model into the production system.
NYC AI Use Case Register — MySchools Probability of Acceptance
Built by
Massachusetts Institute of Technology (MIT)
- Researchers affiliated with MIT developed the probability-of-acceptance model and trained it on data about New York City public high schools. MIT provided professional services to build and supply the underlying algorithm.
NYC AI Use Case Register — MySchools Probability of Acceptance
Kept for
Not stated by the NYC Office of Technology and Innovation.
Shared with
Not stated by the NYC Office of Technology and Innovation.
Stored
Not stated by the NYC Office of Technology and Innovation.
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.
- AI registerNYC Automated Decision Systems — MySchools Probability of AcceptanceNYC Public Schools, Division of Instructional and Information Technology, 2025 AI Use Case Register entry.
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- AI registerNYC AI Use Case Register — MySchools Probability of Acceptance
- Register entryPublished by the NYC Office of Technology and Innovation. Reference 9ebff332. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
What you can do
Ask about this system
Questions go to the NYC Office of Technology and Innovation, not the vendor.
Your rights
- Right to Algorithmic TransparencyStudents and families have the right to understand that the 'high,' 'medium,' or 'low' icon in MySchools is produced by an AI model trained by MIT researchers on NYC public high school data, using inputs such as the student's grades, district, priority group, and the school's admissions method. The NYC AI Use Case Register entry for this tool is publicly available at https://enrollmentsupport.schools.nyc/app/answers/detail/a_id/3652.
- Right to Be Informed of AI UseStudents using the MySchools application should be informed that the acceptance-chance icon is AI-generated and advisory, not an official determination of admissions eligibility. Under NYC's Automated Decision Systems policy, residents may contact NYC Public Schools to learn more about how this system operates. The register entry is publicly accessible as the primary transparency disclosure.
Risks and safeguards
- Reputational harmA student labelled 'low' chance may be discouraged from applying to schools they could realistically attend, producing a self-fulfilling cycle that disadvantages students from under-resourced backgrounds or historically underrepresented groups if the training data reflects past inequities.Safeguard: The tool is framed as informational; the register notes a pilot specifically designed to encourage 'high'-likelihood students who were not considering high-performing schools to apply, partially counteracting chilling effects. However, no explicit fairness audit, disaggregated accuracy reporting, or opt-out mechanism is described in the register entry.
- Loss of autonomyStudents and families who anchor heavily on the displayed probability tier may constrain their school choices to those rated 'high' or 'medium,' narrowing aspirations in ways the register's stated purpose (information presentation) does not intend. The pilot described in the 2025 update — proactively notifying students of 'high' likelihood schools they hadn't considered — also raises questions about how algorithmic nudges interact with student self-determination.Safeguard: The score is advisory and the student retains choice; however, the register entry does not describe transparency notices explaining the model's limitations, accuracy, or how to override its suggestions.