Fewer Prisoners, Less Crime? The Elusive Promise of Algorithms

Early evidence suggests some risk assessment tools offer promise in rationalizing decisions on granting bail without racial bias. But we still need to monitor how judges actually use the algorithms, says a Boston attorney.

Next Monday morning, visit an urban criminal courthouse. Find a seat on a bench, and then watch the call of the arraignment list.

Files will be shuffled. Cases will be called. Knots of lawyers will enter the well of the court and mutter recriminations and excuses. When a case consumes more than two minutes you will see unmistakable signals of impatience from the bench.

Pleas will be entered. Dazed, manacled prisoners—almost all of them young men of color—will have their bails set and their next dates scheduled.

Some of the accused will be released; some will be detained, and stepped back into the cells.

You won’t leave the courthouse thinking that this is a process that needs more dehumanization.

But a substantial number of criminal justice reformers have argued that if the situation of young men facing charges is to be improved, it will be through reducing each accused person who comes before the court to a predictive score that employs mathematically derived algorithms which weigh only risk.

This system of portraiture, known as risk assessment tools, is claimed to simultaneously reduce pretrial detentions, pretrial crime, and failures to appear in court—or at least that was the claim during a euphoric period when the data revolution first poked its head up in the criminal justice system.

We can have fewer prisoners and less crime. It would be, the argument went, a win/win: a silver bullet that offers liberals reduced incarceration rates and conservatives a whopping cost cut.

These confident predictions came under assault pretty quickly. Prosecutors—represented, for example, by Eric Sidall here in The Crime Report—marshaled tales of judges (“The algorithm made me do it!”) who released detainees who then committed blood-curdling crimes.

Other voices raised fears about the danger that risk assessment tools derived from criminal data trails that are saturated with racial bias will themselves aggravate already racially disparate impacts.

ProPublica series analyzed the startling racial biases the authors claim were built into one widely used proprietary instrument. Bernard Harcourt of Columbia University argued that “risk” has become a proxy for race.

A 2016 study by Jennifer Skeem and Christopher Lowenkamp dismissed Harcourt’s warnings as “rhetoric,” but found that on the level of particular factors (such as the criminal history factors) the racial disparities are substantial.

Meanwhile, a variety of risk assessment tools have proliferated: Some are simple checklists; some are elaborate “machine learning” algorithms; some offer transparent calculations; others are proprietary “black boxes.”

Whether or not the challenge of developing a race-neutral risk assessment tool from the race-saturated raw materials we have available can ever be met is an argument I am not statistician enough to join.

But early practical experience seems to show that some efforts, such as the Public Safety Assessment instrument, developed by the Laura and John Arnold Foundation and widely adopted, do offer a measure of promise in rationalizing bail decision-making at arraignments without aggravating bias (anyway, on particular measurements of impact).

The Public Safety Assessment (PSA), developed relatively transparently, aims to be an objective procedure that could encourage timid judges to separate the less dangerous from the more dangerous, and to send the less dangerous home under community-based supervision.

At least, this practical experience seems to show that in certain Kentucky jurisdictions where (with a substantial push from the Kentucky legislature) PSA has been operationalized, the hoped-for safety results have been produced—and with no discernible increase in racial disparity in outcomes.

Unfortunately, the same practical experience also shows that those jurisdictions are predominately white and rural, and that there are other Kentucky jurisdictions, predominately minority and urban, where judges have been—despite the legislature’s efforts—gradually moving away from using PSA.

These latter jurisdictions are not producing the same pattern of results.

The judges are usually described as substituting “instinct” or “intuition” for the algorithm. The implication is that they are either simply mobilizing their personal racial stereotypes and biases, or reverting to a primitive traditional system of prophesying risk by opening beasts and fowl and reading their entrails, or crooning to wax idols over fires.

As Malcolm M. Feeley and Jonathan Simon predicted in a 2012 article for Berkeley Law, past decades have seen a paradigm shift in academic and policy circles, and “the language of probability and risk increasingly replaces earlier discourse of diagnosis and retributive punishment.”

A fashion for risk assessment tools was to be expected, they wrote, as everyone tried to “target offenders as an aggregate in place of traditional techniques for individualizing or creating equities.”

But the judges at the sharp end of the system whom you will observe on your courthouse expedition don’t operate in a scholarly laboratory.

They have other goals to pursue besides optimizing their risk-prediction compliance rate, and those goals exert constant, steady pressure on release decision-making.

Some of these “goals” are distasteful. A judge who worships the great God, Docket, and believes the folk maxim that “Nobody pleads from the street” will set high bails to extort quick guilty pleas and pare down his or her room list.

Another judge, otherwise unemployable, who needs re-election or re-nomination, will think that the bare possibility that some guy with a low predictive risk score whom he has just released could show up on the front page tomorrow, arrested for a grisly murder, inexorably points to detention as the safe road to continued life on the public payroll.

They are just trying to get through their days.

But the judges are subject to other pressures that most of us hope they will respect.

For example, judges are expected to promote legitimacy and trust in the law.

It isn’t so easy to resist the pull of “individualizing “and “diagnostic” imperatives when you confront people one at a time.

Somehow, “My husband was detained, so he lost his job, and our family was destroyed, but after all, a metronome did it, it was nothing personal” doesn’t seem to be a narrative that will strengthen community respect for the courts.

Rigorously applying the algorithm may cut the error rate in half, from two in six to one in six, but one in six are still Russian roulette odds, and the community knows that if you play Russian roulette all morning (and every morning) and with the whole arraignment list, lots of people get shot.

No judge can forget this community audience, even if the “community” is limited to the judge’s courtroom work group. It is fine for a judge to know whether the re-offense rate for pretrial releases in a particular risk category is eight in ten, but to the judges, their retail decisions seem to be less about finding the real aggregated rate than about whether this guy is one of the eight or one of the two.

Embedded in this challenge is the fact that you can make two distinct errors in dealing with difference.

First, you can take situations that are alike, and treat them as if they are different: detain an African-American defendant and let an identical white defendant go.

Second, you can take things that are very different and treat them as if they are the same: Detain two men with identical scores, and ignore the fact that one of the two has a new job, a young family, a serious illness, and an aggressive treatment program.

A risk assessment instrument at least seems to promise a solution to the first problem: Everyone with the same score can get the same bail.

But it could be that this apparent objectivity simply finesses the question. An arrest record, after all, is an index of the detainee’s activities, but it also a measure of police behavior. If you live in an aggressively policed neighborhood your history may be the same as your white counterpart’s, but your scores can be very different.

And risk assessment approaches are extremely unwieldy when it comes to confronting the second problem. A disciplined sticking-to-the-score requires blinding yourself to a wide range of unconsidered factors that might not be influential in many cases, but could very well be terrifically salient in this one.

This tension between the frontline judge and the backroom programmer is a permanent feature of criminal justice life. The suggested solutions to the dissonance range from effectively eliminating the judges by stripping them of discretion in applying the Risk Assessment scores to eliminating the algorithms themselves.

But the judges aren’t going away, and the algorithms aren’t going away either.

As more cautious commentators seem to recognize, the problem of the judges and the algorithms is simply one more example of the familiar problem of workers and their tools.

If the workers don’t pick up the tools it might be the fault of the workers, but it might also be the fault of the design of the tools.

And it’s more likely that the fault does not lie in either the workers or the tools exclusively but in the relationship between the workers, the tools, and the work. A hammer isn’t very good at driving screws; a screw-driver is very bad at driving nails; some work will require screws, other work, nails.

If you are going to discuss these elements, it usually makes most sense to discuss them together, and from the perspectives of everyone involved.

The work that the workers and their tools are trying to accomplish here is providing safety—safety for everyone: for communities, accused citizens, cops on the streets. A look at the work of safety experts in other fields such as industry, aviation, and medicine provides us with some new directions.

To begin with, those safety experts would argue that this problem can never be permanently “fixed” by weighing aggregate outputs and then tinkering with the assessment tool and extorting perfect compliance from workers. Any “fix” we install will be under immediate attack from its environment.

Among the things that the Kentucky experience indicates is that in courts, as elsewhere, “covert work rules”, workarounds, and “informal drift” will always develop, no matter what the formal requirements imposed from above try to require.

The workers at the sharp end will put aside the tool when it interferes with their perception of what the work requires. Deviations won’t be huge at first; they will be small modifications. But they will quickly become normal.

And today’s small deviation will provide the starting point for tomorrow’s.

What the criminal justice system currently lacks—but can build—is the capacity for discussing why these departures seemed like good ideas. Why did the judge zig, when the risk assessment tool said he or she should have zagged? Was the judge right this time?

Developing an understanding of the roots of these choices can be (as safety and quality experts going back to W. Edwards Deming would argue) a key weapon in avoiding future mistakes.

We can never know whether a “false positive” detention decision was an error, because we can never prove that the detainee if released would not have offended. But we can know that the decision was a “variation” and track its sources. Was this a “special cause variation” traceable to the aberrant personality of a particular judge? (God knows, they’re out there.)

Or was it a “common cause variation” a natural result of the system (and the tools) that we have been employing?

This is the kind of analysis that programs like the Sentinel Events Initiative demonstration projects about to be launched by the National Institute of Justice and the Bureau of Justice Assistance can begin to offer. The SEI program, due to begin January 1, with technical assistance from the Quattrone Center for the Fair Administration of Justice at the University of Pennsylvania Law School, will explore the local development of non-blaming, all-stakeholders, reviews of events (not of individual performances) with the goal of enhancing “forward-looking accountability” in 20-25 volunteer jurisdictions.

The “thick data” that illuminates the tension between the algorithm and the judge can be generated. The judges who have to make the decisions, the programmers who have to refine the tools, the sheriff who holds the detained, the probation officer who supervises the released, and the community that has to trust both the process and the results can all be included.

james doyle

James Doyle

We can mobilize a feedback loop that delivers more than algorithms simply “leaning in” to listen to themselves.

What we need here is not a search for a “silver bullet,” but a commitment to an ongoing practice of critically addressing the hard work of living in the world and making it safe.

James Doyle is a Boston defense lawyer and author, and a frequent contributor to The Crime Report. He has advised in the development of the Sentinel Events Initiative of the National Institute of Justice. The opinions expressed here are his own. He welcomes readers’ comments.

from https://thecrimereport.org

U.S. Gets ‘Abysmal’ Grade on Pretrial Justice

The first baseline measurement of pretrial justice across the U.S. has found most states to be failing, with a few “promising” exceptions, according to the Pretrial Justice Institute.

The first baseline measurement of pretrial justice across the U.S. has found most states to be failing, with a few “promising” exceptions, according to a national advocacy group.

In a study released Wednesday by the Pretrial Justice Institute, authors measured the rates of pretrial detention, use of available risk assessment tools, and the status of money bail systems in every state.

“Needless” incarceration before trail is the primary cause for states’ failing grades: according to PJI’s findings, two thirds of the current U.S. jail population has not yet been to trail.

At the forefront of pretrial justice reform are Washington D.C., where 92 percent of those arrested are released pretrial and no one is detained for inability to pay; and New Jersey, which implemented statewide pretrial services earlier this year, resulting in a 15 percent reduction of pretrial detainees within the first six months.

The report also highlights legislative advances made by Alaska, Arizona, California, Indiana, Maryland, and New Mexico in the area of pretrial justice reform.

While the number of jurisdictions using risk assessment tools has more than doubled in the past four years, authors note that the increase is driven by “a few states and densely populated jurisdictions,” adding that “evidence-based pretrial assessments show that most people released before trial will appear in court and not be arrested on new charges pending trial.”

See also: Risk Assessment: The Devil’s in the Details

The study used money bail as its final measure because “financial conditions play such a large role in needlessly detaining people and giving us a false sense of safety,” according to the authors. New Jersey is the only state to have eliminated money bail, so this is where the U.S. pretrial justice score hovers closest to zero: only 3% of Americans live in a jurisdiction that has eliminated cash bail.

“As long as pretrial systems use money as a condition of pretrial release,” concludes the report, “poor and working class people will remain behind bars while those who are wealthy go home, regardless of their likelihood of pretrial success. This is a fundamental injustice.”

See also: Bail Reform: Why Judges Should Reject ‘Risk Assessment’

This summary was prepared by Victoria Mckenzie, Deputy Editor of The Crime Report. Readers’ comments are welcome.

from https://thecrimereport.org

Is Crime Predictable?

In Philip K. Dick’s “Minority Report,” criminals could be identified before they committed a crime. Computer-generated risk algorithms used by courts to determine whether individuals should be released ahead of trial have brought us a step closer to that world–and our challenge is to use them responsibly, says a George Mason University professor.

Should the increased use of computer-generated risk algorithms to determine criminal justice outcomes be cause for concern or celebration?

This is a hard question to answer, but not for the reasons most people think.

Judges around the country are using computer-generated algorithms to predict the likelihood that a person will commit crime in the future. They use these predictions to help determine pretrial custody, sentence length, prison security-level, probation, parole, and post-release supervision.

Proponents argue that by replacing the ad-hoc and subjective assessments of judges with sophisticated risk assessment instruments, we can reduce incarceration without affecting public safety.

Critics respond that they don’t want to live in a “Minority Report” state where people are punished for crimes before they are committed—particularly if risk assessments are biased against blacks.

Which side is right?

Should the increased use of computer-generated risk algorithms to determine criminal justice outcomes be cause for concern or celebration? This is a hard question to answer, but not for the reasons most people think.

It’s hard to answer because there is no single answer: The impacts that risk assessments have in practice depend crucially on how they are implemented.

Risk assessments are tools—no more and no less. They can be used to increase incarceration or decrease incarceration. They can be used to increase racial disparities or decrease disparities.

They can be used to direct “high risk” people towards support and services or to punish them more harshly.They can be implemented in such a broad set of ways that thinking about them monolithically just doesn’t make sense.

Take bail reform, for example.

Bail reform is one of the most active areas of change in criminal justice right now, and risk assessments have been a key part of many reform efforts. The idea behind the current bail reform movement is that pretrial custody decisions should be made on the basis of risk, not resources.

Instead of conditioning pretrial release on the ability to pay bail—which discriminates against the poor—reformers argue that pretrial release should be determined by a defendant’s risk of crime or flight.

Traditionally, risk of crime or flight was evaluated informally by a judge. Now, many jurisdictions are providing judges with computer-generated risk scores to help them decide whether the defendant can be safely released.These risk scores take into account factors like criminal history, age and sometimes even socio-economic characteristics like employment or stable housing.

One of the more popular pretrial risk assessment instruments, called the PSA, was developed by the Laura and John Arnold Foundation in 2013 and has since been adopted in some thirty jurisdictions as well as three entire states. The results have been mixed.

New Jersey has seen a dramatic decline in its pretrial detention rate: the number of people detained pretrial has dropped by about a third since the PSA was adopted in January. Lucas County which hosts the low-income city of Toledo, Ohio, has actually seen an increase in the pretrial detention rate since the PSA was adopted.

And a recent report suggests that Chicago judges have been largely ignoring the PSA. Why such different results in different places?  It’s too soon to say for sure, but there are a number of details related to implementation that could make all the difference.

For one, determining what level of risk should be considered “high” is a subjective determination.

In fact, there is little consensus on this issue: depending on the instrument and the jurisdiction, a high risk classification can correspond with a probability of re-arrest that’s as low as 10% or as high as 42%. 

Editor’s Note: For a critical view on the validity of risk-assessment tools, see Eric Siddall’s Viewpoint in TCR, Aug. 25, 2017.

With the PSA, jurisdictions can decide themselves where to set the cutoff points between a low, moderate, and high risk ranking.

These groupings are important, because many jurisdictions also adopt specific recommendations for each risk classification. For example, New Jersey uses a decision-making framework that recommends pretrial detention only for defendants with the highest risk scores: this has been defined so as to include only about 5% of arrestees.

In Mecklenberg County, another PSA site, generally only defendants who are ranked “low” or “below-average” on their risk score are recommended for release without secured monetary bond, making it less likely that risk assessment will increase release rates very much.

The impact that risk assessments have in practice will also depend on the extent to which judges use them. In most jurisdictions, judges are given the final say, and if they do not want to follow the recommendations associated with the risk assessment they don’t have to.

recent survey showed that only a small minority of judges thought that risk assessments were better at predicting future crime than judges.

If judges are skeptical, what would them motivate them? They will be more likely to use the risk assessment if they are incentivized to do so; for example, if deviating from the recommendations requires a detailed written reason for doing so.

Or, if there is a system of accountability where their actions are tracked and monitored. Finally, it’s always possible to implement risk assessment in a way that doesn’t involve judicial discretion at all.

Kentucky, a leader in the use of pretrial risk assessments, recently revised its procedures so that all low and moderate risk defendants facing non-serious charges are automatically released immediately after booking.

As for racial disparities, we know very little about how these have been impacted by the adoption of risk assessment. But what little we do know suggests that implementation details are important.In a recent study, I found that pretrial risk assessment in Kentucky benefited white defendants more than black, but this was solely because judges in the predominantly-white rural counties followed the recommendations of the risk assessment more than judges in the more racially mixed urban counties.

In other words, the increased racial disparities brought on by risk assessment were caused by regional trends in use, not by the bias of the instrument.This pattern might have been reversed if training, monitoring, and accountability in urban areas were higher.

Furthermore, risk assessment is more likely to reduce racial disparities if it is used to replace monetary bail. Since black defendants tend to have lower incomes, they tend to be less able to afford bail than white defendants.

One study shows that half the race gap in pretrial detention is explained by race differences in the likelihood of posting a given bond amount.

Megan Stevenson

We already live in a “Minority Report” state: the practice of grounding criminal justice decisions on predictions about future crime has been around a long time. The recent shift towards adopting risk assessment tools simply formalizes this process—and in doing so, provides an opportunity to shape what this process looks like.

Instead of embracing risk assessment wholeheartedly or condemning it without reserve, reformers should ask whether there is a particular implementation design by which risk assessment could advance the much-needed goals of reform.

Megan T. Stevenson is an economist and Assistant Professor of Law at George Mason University. She welcomes comments from readers.

from https://thecrimereport.org

Bail Reform: Why Judges Should Reject ‘Risk Assessment’

Tools that use algorithms to determine whether to detain accused individuals before a trial are increasingly being used across the country as an alternative to the bail system. But the vice president of the Los Angeles County Association of Deputy District Attorneys argues that the tools also lead to tragedies.

If you aren’t following bail reform, you may not be aware that accompanying the attempt to eliminate bail across the country is the touting of “risk assessment tools” to determine who should be detained on bail before trial.

Eric Siddall

The chief proponent of such tools is the Arnold Foundation, which maintains that its own “risk assessment tool” is a cutting-edge way of providing an objective assessment in this area.

The tool’s principal developer, (former New Jersey attorney general Anne Milgram), has said she introduced “rigorous statistical analysis” to the process in order to “moneyball criminal justice.”

Editor’s Note: 38 jurisdictions currently use the tool developed by the Arnold Foundation.

However, the use of this tool has led to the wholesale release of violent criminals—and tragedy.

Three recent examples in New Mexico, New Jersey and San Francisco illustrate my point.

A story published by the conservative website The Daily Wire said the assessment tool has led to virtually every defendant arrested in New Mexico for a violent crime being released without bail.

The story quoted a report from Albuquerque NBC affiliate KOB4, saying, “Even with the highest rate of failing to appear in court and the highest rate of new criminal activity for a defendant, the tool still recommends that person[s] be released on their own recognizance unless the prosecutors have filed for preventative detention.”

In New Jersey, according to the Washington Post, the tool determined that a man jailed for illegally possessing a gun was not a danger and recommended his release.  Days later, that man hunted down a rival and shot at him 22 times, killing him.  The family of the victim is now suing the Arnold Foundation, amongst others, for the death.

In San Francisco, the online website SFGate reported that a man suspected of murder was released days earlier after being arrested for possession of two guns.  According to the website, the judge, relying on the assessment tool, rejected the District Attorney’s office recommendation that the man be kept in jail on a probation violation.

A spokesman for the DA’s office was quoted as saying the use of the tool has caused “many instances of contention.”

He continued: “As it relates to this case along with many other cases, we have a disagreement with how that risk assessment is being calculated. They suggested release with certain conditions, and the judge carried out that recommendation and this defendant was released.”

The Arnold Foundation argues that its tool is needed because “failing to appropriately determine the level of risk that a defendant poses impacts future crime and violence, and carries enormous costs–both human and financial.”

The examples in New Mexico, New Jersey and San Francisco certainly attest to the truth of that statement.

Additional Reading: Risk assessment tools have triggered a contentious debate in the criminal justice community. In June, the Supreme Court refused to hear the case of a Wisconsin man who was sentenced to six years in prison by a judge who consulted the results of a  risk assessment algorithm.The plaintiff argued that the use of the algorithm violated his rights to due process. 

The tools represent a threat to the bail bond industry, which has backed two federal lawsuits seeking to end the algorithm’s use.

Eric W. Siddall is Vice President of the Los Angeles Association of Deputy District Attorneys (ADDA), the collective bargaining agent representing nearly 1,000 deputy district attorneys who work for the County of Los Angeles. This is an edited version of an essay that appeared earlier this month on ADDA’s website. Readers’ comments are welcome.

from https://thecrimereport.org

NJ Bail Reform Works; Prosecution, Defense Complain

New Jersey’s use of an algorithm to advise judges on pretrial release “is what the new vision of American justice looks like,” NBC News reports. Six months into the new practice, New Jersey jails are already starting to empty, and the number of people locked up while awaiting trial has dropped.

New Jersey’s use of an algorithm to advise judges on pretrial release “is what the new vision of American justice looks like,” NBC News reports. Created by data scientists and criminal-justice researchers, the algorithm — one of dozens of “risk assessment tools” being used around the U.S. — promises to use data to scrub the system of bias by keeping only the most dangerous defendants behind bars, regardless of socioeconomic status. Six months into the new practice, New Jersey jails are already starting to empty, and the number of people locked up while awaiting trial has dropped.

It’s also clear that data is no wonder drug. The new system — driven by years of research involving hundreds of thousands of cases and requiring multimillion-dollar technology upgrades and the hiring of more judges, prosecutors and court workers — still produces contentious decisions about who deserves freedom and who does not. Police officials and prosecutors complain about the release of people charged with gun crimes, fleeing police, attacking an officer, sex offenses and domestic violence, and of those who keep getting re-arrested. In at least two cases, people have been killed by men who’d been released on earlier charges. The bail bond industry, facing extinction, has backed two federal lawsuits seeking to end the algorithm’s use. Defense lawyers and civil rights advocates say people who pose little risk have been ordered detained, only to be given plea deals or have their charges dropped. They fear that authorities are exploiting the new system to generate convictions. It remains unclear whether the new approach will reduce racial disparities, drive down crime rates or be fiscally sustainable. If it works in New Jersey, it could become a model for the rest of the nation.

from https://thecrimereport.org

Bipartisan Senate Bill Prods States Toward Bail Reforms

The proposal by Democrat Kamala Harris and Republican Rand Paul would authorize total spending of $10 million a year for states that replace cash bail with a system that considers community risk, not a defendant’s ability to pay. New Jersey has already moved forward with a system that some call a model for the nation.

U.S. Sen. Kamala Harris, a California Democrat, has introduced bipartisan legislation to prod states to reform their bail systems, reports the San Jose Mercury News. The new bill, which Harris co-wrote with Sen. Rand Paul, a Kentucky Republican, and was introduced yesterday, would spend $10 million annually for three years on grants for states that reform their bail systems.

Most courts in the U.S. require money bail, holding defendants in jail before trial until they pay. Advocates say cash bail is unfair to poor defendants who haven’t been convicted of a crime.

Under Harris’ bill — her first major bipartisan legislation — states would be eligible for a grant if they enact reforms such as replacing money bail with systems based on assessing a defendant’s risk to the community, releasing inmates before trial in most cases, or appointing public defenders at the earliest stages of pretrial detention.

In a New York Times commentary, Harris and Paul wrote, “Our justice system was designed with a promise: to treat all people equally. Yet that doesn’t happen for many of the 450,000 Americans who sit in jail today awaiting trial because they cannot afford to pay bail.” They said their proposal encourages better data collection, empowers states to build on best practices, and holds them accountable.

Some states have already moved to change their approach to bail. New Jersey, for example, is shifting away from “money-based” pretrial justice through pretrial risk assessment in a system NPR describes in the latest episode of its “Planet Money” podcasts as a “model” for the nation.

from https://thecrimereport.org

Why the Money Bail System Needs to End

As little as three days behind bars has been shown to make someone more likely to be rearrested later. So requiring individuals to put up money bail or await their trial behind bars not only discriminates against the poor, but risks public safety.

Photo by Steve Snodgrass via Flickr

Photo by Steve Snodgrass via Flickr

Americans love money. We have an almost magical belief in its ability to make things better.

That may explain why for so many years we’ve placed our trust in money bail—the practice of making people pay money to be released from jail while awaiting their day in court.

We believe it will make people behave. Yet a growing body of research shows that this practice doesn’t achieve its purpose, and that people show up in court at the same high rates whether they pay money up front or not. All money bail guarantees is that defendants with money can go home no matter how dangerous they might be, while poor people (no matter how little danger they present) stay in jail unnecessarily—at tremendous cost to themselves and their communities, to taxpayers and, paradoxically, to public safety.

The nation’s highest court has already held that release before trial should be the norm and detention should be the carefully limited exception. How, without money bail, would we decide who qualifies for this “carefully limited exception” and must be detained while criminal charges are being resolved?

The answer: Pretrial risk assessment.

It is part of the process that helps courts and judges determine who presents enough risk of danger to community safety or of failing to appear in court that they qualify to be admitted to jail before trial.

Currently, on any given day America’s jails hold nearly 500,000 unconvicted people—most of them charged with nonviolent offenses—at a conservatively estimated cost of $14 billion a year. Putting these presumed innocent men and women in jail is not only a waste of resources that could be better spent elsewhere (or returned to taxpayers), but it also jeopardizes these people’s health, employment, education—even custody of their children.

And because as little as three days behind bars has been shown to make someone more likely to be rearrested later, it actually makes us all less safe.

The story of Maurice Walker, the man at the heart of a federal class action lawsuit against the City of Calhoun, Georgia, illustrates the flaws of money bail. Arrested as “a pedestrian under the influence,” Walker spent six days behind bars because he couldn’t afford $160 bail. That amount was not based on a calculated risk that he might flee from justice or commit crime in the community.

Neither did it account for his extremely limited fixed income or his serious mental health issues. And, of course, it did nothing to make the city of Calhoun safer, or to connect Walker with services or treatment.

Like similar cases successfully brought against other counties and cities, Walker’s lawsuit contends that detaining people like him simply because they cannot afford to post money bail violates the Equal Protection Clause of the U.S. Constitution, which requires that all people be treated the same before the law.

Pretrial risk assessment is a straightforward and commonsense alternative to money bail.

Pretrial risk assessment tools consider a number of factors that have been shown to be accurate predictors of pretrial failure—a history of missed court dates, for example, or whether the current charge is for a violent offense. They then weigh these factors to help courts make informed decisions about who should be admitted to jail. It is a far superior process than relying only on fixed bail schedules or individual judge’s intuition, experience—and in some cases, bias.

The possibility that courts might currently be making biased decisions is real—and troubling.

Money bail disproportionately impacts people of color, who are more likely to become trapped in the criminal justice system because they cannot afford to pay their way out. Moreover, bail amounts assigned to African-American men are, on average, three times higher than those for white men with similar backgrounds. In contrast, the analysis of a pretrial risk assessment tool developed by the Laura and John Arnold Foundation showed scores for Black and white defendants that were virtually identical.

Pretrial risk assessment is already being used across the country—and it’s working. Kentucky, for example, assesses the risk of nearly every arrested individual, and in the past five years it has reduced its pretrial detention rate from 32% to 25% at the same time the rate of crimes committed by people on pretrial release fell by 15%.

Washington, DC has virtually eliminated money from its pretrial system and detains only 12% of all arrested people. Combining a robust pretrial risk assessment program with community supervision for medium-risk individuals has led to a court appearance rate of 88% and a public safety rate (staying arrest-free before trial) of 89% in DC.

There is strong support for replacing money bail with risk-based pretrial practice, driven by a growing awareness that what we’ve been doing—using money bail and guesswork—isn’t working. Justice system leaders, including chief justices, law enforcement and legislators, understand this.

And the general public does, too. In recent polling, 70 percent of likely voters agreed that risk, not money, should determine who we keep behind bars after arrest and before trial. This support is high across different political and racial groups.

Still, some are skeptical about using a formula to inform court decisions about whether an individual should be released or jailed before trial. That’s why all pretrial risk assessment systems must be fully transparent about what factors they measure and how the results are used. Decisions about people’s liberty should be made in open court, on the record, and should be defensible based on the facts at hand.

Our country is in the midst of an unprecedented conversation about criminal justice. Much of that debate focuses on harsh sentencing laws and pardons—solutions that come after the fact. Fixing the front end of the system—by ensuring that fewer people are jailed unnecessarily before trial and those who truly pose a danger are detained—will have the greatest impact on problems further on.

Cherise Fanno Burdeen

Cherise Fanno Burdeen

And the first step in solving our pretrial challenges is to shift from money bail to evidence-based pretrial risk assessment.

Cherise Fanno Burdeen is the chief executive officer of the Pretrial Justice Institute, a national organization working to advance safe, fair, and effective pretrial justice that honors and protects all people. She welcomes readers’ comments.

 

from http://thecrimereport.org