The output data this deployed system produces when it operates — decisions, content, and actions.
The AI produces numeric measurements over time — sensor outputs, derived quality scores, forecasted values. Examples: an hourly air-quality score for a plaza, a predicted ridership curve for tomorrow, an aggregated noise-level reading published to a public dashboard.
The AI produces location, route, region, or floor-plan output. Examples: a wayfinding route shown on a kiosk, a heatmap of foot-traffic density, a geofence boundary published to downstream systems.
The AI produces records of what people did — paths walked, items selected, dwell times, interaction patterns. Examples: a weekly report of most-visited destinations, a session log of touchscreen interactions, an inferred route someone took through a venue.
The AI produces output containing biological signals from a person's body — face templates, voice embeddings, gait vectors, gesture sequences. Examples: an enrolled face template stored downstream, a voice embedding for later matching, a gait signature exported to another system.
The AI produces a binding determination about a person — eligibility, classification, ranking, or yes/no. Examples: an access-control system deciding to open a gate, an automated benefits eligibility result, an automated screening that rules someone out.
The AI produces new content — text, images, audio, or video that did not exist before. Examples: an LLM-written service advisory shown on a sign, a synthesized voice announcement played over a public-address system, a generated illustration on a digital kiosk.
The AI produces administrative output — schedules, routes, occupancy estimates, budget allocations, or other records about how a place or service runs. Not about any one person. Examples: an optimized trash-collection route, a school occupancy projection, a recommended budget allocation for next quarter.
The AI triggers something in the physical world — a door unlocking, a light turning on, an alert sounding, signage changing, HVAC adjusting. Examples: a turnstile that opens on facial match, a public-address alert played automatically, an HVAC adjustment commanded by a building model.
The AI produces an advisory output — a suggestion, forecast, risk score, or ranking. Distinct from a binding decision because it advises rather than determines. Examples: a signage system suggesting an alternate route based on predicted crowding, a forecasted demand curve for tomorrow, a recommended next destination on a kiosk.
The AI produces output about health, finances, beliefs, sexuality, immigration status, or other categories that carry legal and social risk. Examples: a triage priority assigned at a clinic, an eligibility result sent to a benefits portal, an inferred protected attribute exported downstream.
Live API response from GET /schemas/ai@2026-05-06-beta/categories (this category) and GET /schemas/ai@2026-05-06-beta/elements?category_id=output_dataset.
{
"id": "output_dataset",
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"locale": "en",
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"prompt": [
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"name": [
{
"locale": "en",
"value": "Personal Information"
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"description": [
{
"locale": "en",
"value": "How identifiable the data is when this system produces it. The element name says what the output is about; this colour says how directly it identifies a person."
}
],
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{
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"value": "Anonymized data"
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{
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"value": "Output about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so the result can’t reasonably be tied back to an individual."
}
],
"color": "#4A90D9"
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{
"id": "pseudonymous",
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{
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"value": "Pseudonymous data"
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"description": [
{
"locale": "en",
"value": "The output is labelled with a token (hash, ID, template) that lets this system tie the result to the same person across events without revealing a name. Reidentification is possible with extra information."
}
],
"color": "#9575CD"
},
{
"id": "identifiable",
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{
"locale": "en",
"value": "Identifiable data"
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],
"description": [
{
"locale": "en",
"value": "The output names a person directly (name, address, account, recognisable face or voice, plate) or carries a token this system resolves to legal identity in the same step."
}
],
"color": "#FFD700"
}
]
}
}[
{
"id": "output_about_a_measurement",
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"description": [
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"locale": "en",
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"description": [
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"locale": "en",
"value": "The AI produces location, route, region, or floor-plan output. Examples: a wayfinding route shown on a kiosk, a heatmap of foot-traffic density, a geofence boundary published to downstream systems."
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"symbol_id": "spatial",
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{
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{
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"description": [
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"locale": "en",
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"authoring_guidance": [],
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"symbol_id": "biometric",
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"title": [
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"description": [
{
"locale": "en",
"value": "The AI produces a binding determination about a person — eligibility, classification, ranking, or yes/no. Examples: an access-control system deciding to open a gate, an automated benefits eligibility result, an automated screening that rules someone out."
}
],
"authoring_guidance": [],
"examples": [],
"sources": [
{
"type": "regulation",
"title": "EU AI Act Article 3(1) — output class \"decisions\"",
"url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
"citation": "Regulation (EU) 2024/1689, Article 3(1)."
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{
"type": "regulation",
"title": "EU AI Act Annex III — High-risk decision domains",
"url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
"citation": "Regulation (EU) 2024/1689, Annex III — biometric ID, employment, essential services, justice, migration, education."
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"symbol_id": "dm_accept-or-deny",
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{
"id": "output_generated_content",
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"description": [
{
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"value": "The AI produces new content — text, images, audio, or video that did not exist before. Examples: an LLM-written service advisory shown on a sign, a synthesized voice announcement played over a public-address system, a generated illustration on a digital kiosk."
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"authoring_guidance": [],
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"sources": [
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"url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
"citation": "Regulation (EU) 2024/1689, Article 3(1)."
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{
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"url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
"citation": "Regulation (EU) 2024/1689, Article 50."
},
{
"type": "standard",
"title": "NIST AI 100-4 — AI Risk Management Framework",
"url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-4.pdf",
"citation": "NIST."
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{
"type": "standard",
"title": "C2PA — Coalition for Content Provenance and Authenticity",
"url": "https://c2pa.org",
"citation": "C2PA."
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"symbol_id": "generated_content",
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{
"id": "output_operational_data",
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"description": [
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{
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"description": [
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"locale": "en",
"value": "The AI triggers something in the physical world — a door unlocking, a light turning on, an alert sounding, signage changing, HVAC adjusting. Examples: a turnstile that opens on facial match, a public-address alert played automatically, an HVAC adjustment commanded by a building model."
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"authoring_guidance": [],
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"sources": [
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{
"type": "other",
"title": "Apple App Store privacy labels — Sensitive Info / Health & Fitness / Financial Info",
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"citation": "Apple."
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