Denver audit inconclusive on police profiling

A Denver audit on Denver police operations was inconclusive on the appearance of racial profiling by officers.

Auditor Timothy O'Brien released the report on Thursday morning, along with recommendations that Denver Police have already questioned.

"Our audit does not conclude that they are engaging in racial profiling," said O'Brien. "What we conclude is that in order to answer that question, you must have more data."

MORE: Read the full audit here.

The audit focused on community policing, also known as "Class 2 Actions."

A "Class 1 Action" is when an officer responds to a 911 call. A "Class 2 Action" is initiated by the officer, through a traffic stop, a pedestrian stop or visiting businesses.

The audit determined that officers do not collect demographic data during "Class 2 Actions" when they do not ticket or cite someone.

"Without the data, they can't design the training appropriately to deter racial profiling if it is going on," said O'Brien.

Officers do track demographic data for those they arrest or ticket. The audit suggests that officers also collect the data during benign contacts with people:

• Date/time/location
• Length of contact
• Date of birth
• Gender
• Race/ethnicity
• Reason for contact
• Action taken/outcome
• Officer ID/badge number

Denver Police do not support that recommendation. In the audit itself, police responded:

"…non-enforcement interactions are often positive for both officers and community members. If officers are required to gather demographic information on all contacts, there is a likelihood that positive interactions could change to negative contacts due to the intrusive nature of the data collection."

"My job is to point out the areas that we think need change, and it's up to the police department, it's up to the mayor, it's up to the council to actually decide whether or not those policies should change," said O'Brien.

Denver Police have a biased-policing policy that prevents officers from making stops based on demographics, like race, ethnicity, gender and sexual orientation.

"How do they know the policy is working? And that's the question that the data can answer," said O'Brien.