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REAL-WORLD INTERPRETIVE

PREDICTIVE LAW ENFORCEMENT AND BEHAVIORAL THREAT ASSESSMENT

Global Comparison and Governance Framework

A comparative inventory of predictive policing, threat assessment, watchlisting, traveler-risk analysis, biometric surveillance, public-security platforms, and anticipatory intervention across jurisdictions.

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REAL-WORLD INTERPRETIVE

ANALYTICAL & SAFETY BOUNDARIES

Keep related capabilities, evidence, and authority states separate.

  • Retrieval, matching, identification, association, forecasting, prioritization, threat assessment, and coercive intervention are different functions.
  • Place-based and person-based systems have different targets, evidence requirements, and rights consequences.
  • A source describes a system or claim; it does not automatically establish current deployment, accuracy, effectiveness, legality, or fairness.
  • A human review step is meaningful only when the reviewer has enough time, evidence, authority, independence, and an effective way to reject or correct the output.

Analytical boundary: “Pre-crime” is an analytical label for anticipatory decision architectures, not a single technology or proof that future conduct can be known. Record retrieval is not prediction; identity matching is not prediction of conduct; association is not guilt; a map is not necessarily a forecast; a concern category is not a statistical probability; a score, tier, list, or alert is not lawful grounds for coercive action; formal human presence is not meaningful review without time, evidence, authority, and an effective intervention path. Exact source bytes are preserved, but external claims remain source claims until independently verified.

Simulation safety boundary: Educational and non-operational. No real-person scoring, surveillance deployment, list construction, targeting, coercive workflow, evasion, or system-defeat guidance.

Source basis: 11 exact owner-supplied source instance(s) preserved in the WIP.75 predictive-law-enforcement collection.

LEVEL 1

ORIENTATION

Why this matters

REAL-WORLD INTERPRETIVE

One-sentence brief

Comparative analysis is strongest when it follows function, consequence, evidence, and redress rather than ranking countries on a single technology scale.

REAL-WORLD INTERPRETIVE

Three key points

  1. Technical sophistication and coercive intensity are separate axes.
  2. Person-based systems generally create greater persistent rights risk than aggregate place analysis.
  3. Opacity prevents both fairness analysis and scientific evaluation.
LEVEL 2

WORKING BRIEF

Evidence, context, and limits

REAL-WORLD INTERPRETIVE

Compare complete decision architectures

The relevant unit is collection, identity resolution, inference or prioritization, human interpretation, intervention, retention, and review or redress. Similar technical stacks can produce different consequences under different institutions; simple systems can be highly coercive.

  • Compare function and consequence.
  • Record legal and institutional context.
  • Do not assume democratic or authoritarian use is technically identical in effect.
REAL-WORLD INTERPRETIVE

Use a consistent evidence hierarchy

Official documents, audits, technical specifications, court records, procurement materials, independent evaluations, public-record disclosures, journalism, and allegations support different propositions. Program status and effectiveness should be dated and classified.

  • Label claims and sources.
  • Record research cutoff.
  • Keep unknowns unknown.
REAL-WORLD INTERPRETIVE

Minimum governance controls

Consequential systems require purpose limits, data minimization, provenance, validation, subgroup analysis, notice where compatible with safety, human review, logging, retention limits, correction, deletion, appeal, independent audit, and public reporting.

  • Govern the full lifecycle.
  • Require downstream correction propagation.
  • Treat successor systems as part of the same accountability chain.
LEVEL 3

COMPLETE DOSSIER

Limitations, game links, and review context

DISPUTED / MULTIPLE ACCOUNTS

Known limitations and gaps

  • The owner-supplied reports preserve their own evidence classifications, research cutoffs, and uncertainties; the site does not silently upgrade them.
  • Public information about thresholds, training data, model coefficients, operational modes, interventions, retention, and outcomes is frequently incomplete.
  • Program labels change. Functional continuity must be evaluated rather than inferred from a name alone.
  • Observed arrests, contacts, alerts, or declining crime after deployment do not by themselves establish predictive validity or causal effectiveness.
REAL-WORLD INTERPRETIVE

Related PsychologicalWar.org analysis

No related public page is required to understand this analysis.

REAL-WORLD INTERPRETIVE

Decision matrix

Function, output, and consequence boundary
Function Typical output What it does not establish Primary governance question
Record retrieval Matching stored records Future conduct Are records accurate, relevant, authorized, and correctable?
Identity resolution Probable entity match Guilt or threat How are ambiguity, aliases, and redress handled?
Place forecasting Area/time risk estimate Who will offend or whether patrol reduces crime Does the forecast add value beyond transparent hotspot methods?
Person scoring or prioritization Rank, tier, list, or probability-like output Lawful grounds for intervention What features, thresholds, consequences, retention, and appeal apply?
Behavioral threat assessment Contextual concern and management plan Certain prediction of violence Is the inquiry individualized, multidisciplinary, dynamic, and service-capable?
Watchlisting or screening Match, handling code, screening status, or review request Charge, warrant, or universal action command Who nominated, reviewed, acted, retained, corrected, and provided redress?
REAL-WORLD INTERPRETIVE

Publication audit checklist

Define the target

Is the system estimating a place, event, identity match, victimization risk, offending risk, vulnerability, intent, or information location?

Pass condition: The target variable and time horizon are explicit.

Trace the intervention

What operational action follows the score, list, map, flag, or recommendation?

Pass condition: Every downstream consequence and legal authority is identified.

Evaluate the denominator

Are outcomes compared with an equivalent untreated group and separated from police attention?

Pass condition: Precision, recall, calibration, false positives, subgroup performance, and causal limits are reported.

Audit the feedback loop

Can intervention-generated contacts or arrests become future model inputs?

Pass condition: Generated data is identified, discounted, corrected, or isolated.

Protect correction and redress

Can a person discover, challenge, correct, delete, or appeal consequential data and designations?

Pass condition: Notice, retention, correction, deletion, appeal, and independent review are documented.

LEVEL 4

RESEARCH EDITION

Sources, methods, and stable links

REAL-WORLD INTERPRETIVE

Linked reports

  • Predictive Policing after the EU AI Act: PRECOBS in Germany, CAS in the Netherlands, and the Boundary Between Prohibited and High-Risk AIProtected research reference; no public report route in this release.
  • Predictive Policing in the United Kingdom: NDAS, HART, the Gangs Violence Matrix, and AI Crime MappingProtected research reference; no public report route in this release.
  • Hot People: Chicago’s Strategic Subject List, LAPD LASER, and Pasco County’s Intelligence-Led Policing ProgramProtected research reference; no public report route in this release.
  • Detecting Mal-Intent Before an Attack: FAST, SPOT, Quiet Skies, Secure Flight, and U.S. Traveler-Risk AnalyticsProtected research reference; no public report route in this release.
  • Behavioral Threat Assessment or Pre-Crime? The FBI BTAC, Secret Service NTAC, and the Prevention of Targeted ViolenceProtected research reference; no public report route in this release.
  • Predictive Public Security in China: IJOP, Police Cloud, Skynet, Sharp Eyes, and the Expansion of Proactive PolicingProtected research reference; no public report route in this release.
  • Predictive Public Security in China: IJOP, Police Cloud, Skynet, Sharp Eyes, and the Expansion of Proactive PolicingProtected research reference; no public report route in this release.
  • Predictive Policing in India: From CMAPS and CCTNS to State-Level AI Risk and Surveillance SystemsProtected research reference; no public report route in this release.
  • Policing Future Risk in Australia: The NSW Suspect Targeting Management Plan, Operation Tepito, and Successor PracticesProtected research reference; no public report route in this release.
  • The Real-World “Pre-Crime” Landscape: A Comparative Inventory and Governance Framework for Predictive Law EnforcementProtected research reference; no public report route in this release.
  • The Global Evolution of Predictive and Preemptive Law EnforcementProtected research reference; no public report route in this release.
REAL-WORLD VERIFIED

Method and corrections

This page follows the public method for provenance, confidence, source independence, alternative accounts, limitations, review state, and visible correction.

Read the methodView corrections
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Predictive Law Enforcement and Behavioral Threat AssessmentBehavioral Threat Assessment or “Pre-Crime”?A source-bounded examination of BTAC, NTAC, structured professional judgment, targeted-violence prevention, low base rates, services, intervention, and civil-liberties boundaries.Predictive Law Enforcement and Behavioral Threat AssessmentBehavioral-Science Investigative UnitsHow specialized behavioral-science units support investigations, threat assessment, interviewing, research, training, consultation, and case management without becoming mind-reading engines.Predictive Law Enforcement and Behavioral Threat AssessmentDefinitions and Analytical BoundariesDistinguish retrieval, identity resolution, association, mapping, forecasting, person scoring, threat assessment, watchlisting, and coercive action.Predictive Law Enforcement and Behavioral Threat AssessmentEurope and the EU AI Act: Prohibited and High-Risk BoundariesPRECOBS, SKALA, KrimPro, the Netherlands Crime Anticipation System, and the distinction between prohibited individual crime prediction and regulated law-enforcement uses under the EU AI Act. Learning pathPredictive Law Enforcement: Evidence, Psychology, Governance, and RedressA sixteen-step path through terminology, behavioral threat assessment, behavioral-science units, person and place prediction, traveler risk, watchlisting, regional cases, technology lifecycle, evaluation, rights, and redress.
Page complete Global Comparison and Governance Framework Page label: REAL-WORLD INTERPRETIVE