Officers speak less respectfully to members of the public who are black than to those who are white, researchers studying police body camera footage say.
The US team developed a way to measure the level of respect, based on the language used by officers during routine traffic stops.
The study is published in Proceedings of the National Academy of Sciences.
It aims to use bodycam footage to help improve police-community relations.
While bodycam footage has been used as evidence in criminal cases – including some where complaints have been made against police – the aim of this study was to turn this continuously gathered footage into data and use that to track and improve everyday policing.
“These routine interactions are important,” said lead scientist Prof Jennifer Eberhardt, “they’re the way most people encounter the police.”
“And people care as much about how they’re treated as whether or not they got a [speeding] ticket.
“It can affect how people view the police, how they think about the police – whether or not they want to co-operate with them.”
Evidence or data?
The study was part of a unique, decade long research collaboration between Stanford University and the Oakland Police Department in California, which began when the department asked Prof Eberhardt to analyse their stop and search data.
“We had location and details [of who was stopped], but we also had the camera’s recording of every the interaction,” she said.
“I figured we could could analyse exactly what’s happening here.”
The Stanford team transcribed 1,000 interactions between police and members of the public, then picked out a random selection of 400 “utterances” made by officers during these dialogues.
They then had a group of volunteers read and rate these utterances, with each one being rated by at least 10 people.
“[Our volunteers] looked at the text without knowing the race of the officer or of the community member,” said Prof Eberhardt.
“The task was to come up with a score that quantified respectfulness, so each utterance was rated for politeness, friendliness and how formal or informal it was.
“Then we looked for what we call the linguistic correlates of that rating- so what words are present when something is scored as more or less respectful.”
Co-author of the study PhD student Rob Voigt explained how the team had used these volunteers’ ratings to develop a computer model that could automatically analyse the utterances – searching and scoring subtle linguistic markers that made an officer’s language more or less respectful.
“Our computer model learns to measure each of these linguistic features,” Mr Voigt said.
“So we can ask, ‘How polite is it when you apologise?’ and it can give us a number.
“So, apologies, calling someone ‘sir’, taking an interest in the person, maybe by saying, ‘Drive safely,’ they’re all perceived as more respectful.
“And then disrespectful features include questions, negatively charged words and using terms like ‘bro’ or ‘man’, or first names rather than titles,” he said.
Prof Eberhardt said they had found “real racial disparity in officers’ language use”.
“But that doesn’t,” she said, “equate to racial bias.
“There could be many reasons why you have these differences we’re finding.
“It could have to do with a particular law enforcement strategy, police policies, the community members’ language or if there’s tension already in a community because of a recent high profile case.
“We’re trying to understand the root, but we’re not taking for granted that it’s bias.”