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February 12, 2017

Is big data "reinforcing racial bias in the criminal justice system"?

The question in this post is prompted by this Washington Post commentary headlined "Big data may be reinforcing racial bias in the criminal justice system." The piece is authored by Laurel Eckhouse, a researcher with the Human Rights Data Analysis Group’s Policing Project at UC Berkeley, and here are excerpts:

Big data has expanded to the criminal justice system. In Los Angeles, police use computerized “predictive policing” to anticipate crimes and allocate officers. In Fort Lauderdale, Fla., machine-learning algorithms are used to set bond amounts. In states across the country, data-driven estimates of the risk of recidivism are being used to set jail sentences.

Advocates say these data-driven tools remove human bias from the system, making it more fair as well as more effective. But even as they have become widespread, we have little information about exactly how they work. Few of the organizations producing them have released the data and algorithms they use to determine risk.

We need to know more, because it’s clear that such systems face a fundamental problem: The data they rely on are collected by a criminal justice system in which race makes a big difference in the probability of arrest — even for people who behave identically. Inputs derived from biased policing will inevitably make black and Latino defendants look riskier than white defendants to a computer. As a result, data-driven decision-making risks exacerbating, rather than eliminating, racial bias in criminal justice....

We know that a black person and a white person are not equally likely to be stopped by police: Evidence on New York’s stop-and-frisk policy, investigatory stops, vehicle searches and drug arrests show that black and Latino civilians are more likely to be stopped, searched and arrested than whites. In 2012, a white attorney spent days trying to get himself arrested in Brooklyn for carrying graffiti stencils and spray paint, a Class B misdemeanor. Even when police saw him tagging the City Hall gateposts, they sped past him, ignoring a crime for which 3,598 people were arrested by the New York Police Department the following year.

Before adopting risk-assessment tools in the judicial decision-making process, jurisdictions should demand that any tool being implemented undergo a thorough and independent peer-review process. We need more transparency and better data to learn whether these risk assessments have disparate impacts on defendants of different races. Foundations and organizations developing risk-assessment tools should be willing to release the data used to build these tools to researchers to evaluate their techniques for internal racial bias and problems of statistical interpretation. Even better, with multiple sources of data, researchers could identify biases in data generated by the criminal justice system before the data is used to make decisions about liberty. Unfortunately, producers of risk-assessment tools — even nonprofit organizations — have not voluntarily released anonymized data and computational details to other researchers, as is now standard in quantitative social science research.

For these tools to make racially unbiased predictions, they must use racially unbiased data. We cannot trust the current risk-assessment tools to make important decisions about our neighbors’ liberty unless we believe — contrary to social science research — that data on arrests offer an accurate and unbiased representation of behavior. Rather than telling us something new, these tools risk laundering bias: using biased history to predict a biased future.

February 12, 2017 at 12:13 PM | Permalink

Comments

Racial bias in the justice system has been debunked year after year for decades. In addition to think tank studies, there is the ultimate correct measurement of crime, the Household Crime Victimization Survey, before the Obama administration politicized and destroyed it. It showed, every year, that blacks had 5 times the victimization rate as whites. In 95% of victimizations, blacks were the criminals. Try finding the criminal number by race. I challenge anyone to get it. It used to take 15 seconds. It will take you all day to retrieve that chart today.

Because long term secular trends such as aging, blood lead levels, video addiction, obesity epidemic, smoking marijuana affect all races at the same pace, that leaves one factor to explain the racial disparity. Bastardy.

Before whites get too smug, the feminist lawyer has successfully attacked the white family, and its bastardy rate is rapidly catching up to the rate among blacks (70%+), being 40% in the 2010 census. It is likely to be far higher in the 2020 Census. Racial disparity in crime may disappear.

Racial disparity in crime may already have disappeared if one counts the 15 million people who were victims of identity theft. The crime rate is being under-counted by hundreds of millions if not billions a year. This under-count is intentional, and to protect the Obama administration from criticism for his criminal coddling.

Posted by: David Behar | Feb 12, 2017 6:50:38 PM

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