Police are telling ShotSpotter to alter evidence from gunshot-detecting AI (vice.com)

Article summary

Police are allegedly asking ShotSpotter, a company that uses AI to detect gunshots, to alter evidence in criminal cases. In one case, a ShotSpotter analyst manually overrode the algorithms to reclassify a sound as a gunshot, which became a key piece of evidence in a murder trial. The company's technology has been criticized for its lack of transparency and potential for false positives. ShotSpotter's evidence has been withdrawn in several cases after being challenged by defense attorneys.

Main themes

• ShotSpotter accuracy
• Police evidence
• AI bias
• Crime reduction
• Community trust
• Mass surveillance
• Racial profiling

What commenters say

• The use of ShotSpotter as evidence in criminal trials is problematic due to its potential for human bias and error.
• The high rate of false positives from ShotSpotter alerts can lead to wasted police resources and decreased trust in the system.
• ShotSpotter can still be a useful tool for police, even with its limitations, as it can provide faster response times to true positive shootings.
• The cost of ShotSpotter, $33 million per year for the city of Chicago, may not be justified by its effectiveness in reducing crime.
• The lack of transparency and accountability in ShotSpotter's algorithms and analysis process undermines its credibility as a forensic tool.
• Relying on community reports and building trust with the public may be a more effective way to reduce crime than using ShotSpotter.
• The use of ShotSpotter as a standalone piece of evidence is not sufficient and should be supported by other forms of evidence.
• The potential for ShotSpotter to be used as a tool for mass surveillance and racial profiling is a concern that needs to be addressed.