Get Full Government Meeting Transcripts, Videos, & Alerts Forever!
Get email alerts on the Artificial Intelligence topic
No spam. Unsubscribe anytime.
Duluth staff outline citywide AI strategy, cite measurable time savings
Summary
City Manager James Riker introduced Data Analyst Dylan Schneiderman’s update on the city’s AI and data-efficiency work: a citywide AI policy and staff training are in place, police are piloting several tools, and reported workflow savings include reducing monthly property-owner updates from three days to three hours.
City Manager James Riker introduced Data Analyst Dylan Schneiderman, who presented the City of Duluth’s newly adopted AI policy and recent data-efficiency projects.
Schneiderman described department-level examples of automation and workflow redesign. He said the Police Department has led internal AI adoption for tasks such as report writing, facial-recognition-assisted review, transcription and crime mapping. He reported specific time savings: monthly property-owner data entry was reduced from three days of manual entry to about three hours, and administration of the HR Wellness Program was shortened from three days to roughly four hours on a quarterly basis. Staff also are consolidating financial data to enable cross-departmental trend analysis.
Council members raised questions about data security, how tools are evaluated and cost projections; staff told the Council some departments are using free versions of tools during early evaluations. Riker emphasized the city has established input guidelines and staff training for safe internal use. No formal action was taken; staff will continue training, refine tool evaluations and return as requested for further direction.
