ShotSpotter pinpoints Cleveland gunfire, and officers get there sooner

In a City-funded evaluation, Cleveland State criminologists found that ShotSpotter alerts were located more accurately than most 911 calls and let officers respond faster. Crime did not fall.

  • 1 for an organization

    The evaluators found that officers can respond faster than to 911 calls and that evidence collection is more likely with ShotSpotter, but they did not measure the response-time difference.

  • Not rated society

    The evaluators found that by itself ShotSpotter does not directly reduce crime, and residents' views of it were mixed.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Partly reported benefit.
Evidence

foundstudiedreportedclaimed

Only the evaluators support the benefit.

Size

No magnitude yet: distribution is not documented.

Compared with

911 calls reporting gunfire in Cleveland. Assumed without a measurement.

The system’s part
Not isolated. The evaluators judged the faster response from the accuracy of alert locations, ShotSpotter's timing data and officer interviews, and they could not evaluate alerts separately from 911 calls. Each alert passes an automated algorithm and then SoundThinking's human analysts, and the report does not separate the two.
Learns from data

Shown. SoundThinking's product page says that audio from reviewed incidents is kept to train the machine learning model that filters detections. The lead document describes the sensors and the human review and does not describe the classifier.

“If an incident is created and sent to our Incident Review Center the short audio snippet is stored permanently for evidentiary purposes as well as to train the machine learning model.” Source

Not yet checked
LimitsCosts and harmsLater outcome

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Benefit type
Reduced Task Time
System
ShotSpotter gunfire detection system (acoustic sensors, an automated algorithm and human review)
Made by
SoundThinking, Inc. (formerly ShotSpotter, Inc.)
Used by
Cleveland Division of Police
Where
Cleveland, Ohio, United States
Stage
Expanding
Date
, when the source was published
Kind
Aggregate result
Broad benefit
Physical health, Operational improvement (crime reduction or prevention)
Collections
Scrutiny and findings
Last revised
1 November 2026

Sources

  1. Evaluation report, by an evaluator that the makers or users commissioned.

    Kent, Stephanie L. and Rachel E. Lovell. Evaluation of the Cleveland Division of Police's Implementation of ShotSpotter. Criminology Research Center, Levin College of Public Affairs and Education, Cleveland State University, August 2025.

    ShotSpotter alerts are more accurately located than most 911 calls, resulting in faster response times for gunfire-related incidents. Given the accuracy with which ShotSpotter is able to detect gunfire and the inaccuracy of the location of gunfire in reported calls, officers can respond faster than with 911 calls.
    The average time from published ShotSpotter alert until officer dispatched (based on CAD creation time) for alerts in Quarter 1 of 2025 was 81 seconds (Median: 78 seconds). In our evaluation, it was not possible to evaluate ShotSpotter alerts separately from 911 calls.
    While the vast majority of the ShotSpotter alerts do not result in evidence collection, evidence collection is more likely with ShotSpotter than without.
    When a sensor detects a sudden noise, the audio is transmitted to an automated algorithm, an AI-based system, which analyzes the audio for gunshot signatures, identifiable patterns, volume peaks, and other unique traits, such as barks or echoes.
    By itself, ShotSpotter does not directly reduce crime. ShotSpotter is not designed for crime prevention, as it is an after-the-fact type of technology, lacking key components necessary for crime prevention.

  2. Other, by the makers. Context or contrary evidence.

    SoundThinking. ShotSpotter Gunshot Detection System, product page.

    If an incident is created and sent to our Incident Review Center the short audio snippet is stored permanently for evidentiary purposes as well as to train the machine learning model.

Details

AI system

Workflow

Sensors covered 13 square miles by June 2024, after a three-square-mile pilot in the Fourth District from November 2020 and a seven-square-mile expansion in spring 2023. Each alert passed an automated algorithm and then SoundThinking's human analysts before publication to the police. All alerts were dispatched as Priority 1 calls.

Follow-up

Conditions for replication

Gunfire must occur inside the coverage area. Officers must be available to respond, and the evaluators found the force strained by a large drop in officer numbers from 2019 to 2024.

Entry details

Sector

Policing (gunfire detection).

Purpose

ShotSpotter built its gunshot detection system to locate outdoor gunfire with acoustic sensors and alert police to each incident.

31 more questions not yet checked

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Cite this benefit

Peter H. Vartanian. (2026). ShotSpotter pinpoints Cleveland gunfire, and officers get there sooner (AIBD-1217). Artificial Intelligence Benefits Database, edition of 2 November 2026. https://petervartanian.xyz/aibd/records/AIBD-1217.html (archived at https://doi.org/10.7910/DVN/AADSII, version 9.0)

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