⭐⭐⭐⭐⭐ Recidivism In America Essay

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Recidivism In America Essay



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Reducing Recidivism - Valerie Hawes - TEDxKingLincolnBronzeville

The proportion of first-degree murderers who are sentenced to death is small, and of this group, an even smaller proportion of people are executed. Although death sentences in the mids increased to about per year , this is still only about one percent of all homicides known to the police. Of all those convicted on a charge of criminal homicide, only 3 percent — about 1 in 33 — are eventually sentenced to death.

Between , the average number of death sentences per year dropped to , reducing the percentage even more. Mandatory death sentencing is unconstitutional. The possibility of increasing the number of convicted murderers sentenced to death and executed by enacting mandatory death penalty laws was ruled unconstitutional in Woodson v. North Carolina , U. A considerable time between the imposition of the death sentence and the actual execution is unavoidable, given the procedural safeguards required by the courts in capital cases.

Starting with selecting the trial jury, murder trials take far longer when the ultimate penalty is involved. Furthermore, post-conviction appeals in death-penalty cases are far more frequent than in other cases. These factors increase the time and cost of administering criminal justice. We can reduce delay and costs only by abandoning the procedural safeguards and constitutional rights of suspects, defendants, and convicts — with the attendant high risk of convicting the wrong person and executing the innocent. This is not a realistic prospect: our legal system will never reverse itself to deny defendants the right to counsel, or the right to an appeal. Persons who commit murder and other crimes of personal violence often do not premeditate their crimes.

Most capital crimes are committed in the heat of the moment. Most capital crimes are committed during moments of great emotional stress or under the influence of drugs or alcohol, when logical thinking has been suspended. Many capital crimes are committed by the badly emotionally-damaged or mentally ill. In such cases, violence is inflicted by persons unable to appreciate the consequences to themselves as well as to others. Even when crime is planned, the criminal ordinarily concentrates on escaping detection, arrest, and conviction. The threat of even the severest punishment will not discourage those who expect to escape detection and arrest. It is impossible to imagine how the threat of any punishment could prevent a crime that is not premeditated.

Furthermore, the death penalty is a futile threat for political terrorists, like Timothy McVeigh, because they usually act in the name of an ideology that honors its martyrs. Capital punishment doesn't solve our society's crime problem. Threatening capital punishment leaves the underlying causes of crime unaddressed, and ignores the many political and diplomatic sanctions such as treaties against asylum for international terrorists that could appreciably lower the incidence of terrorism. Capital punishment has been a useless weapon in the so-called "war on drugs. It is irrational to think that the death penalty — a remote threat at best — will avert murders committed in drug turf wars or by street-level dealers. If, however, severe punishment can deter crime, then permanent imprisonment is severe enough to deter any rational person from committing a violent crime.

The vast preponderance of the evidence shows that the death penalty is no more effective than imprisonment in deterring murder and that it may even be an incitement to criminal violence. Death-penalty states as a group do not have lower rates of criminal homicide than non-death-penalty states. Use of the death penalty in a given state may actually increase the subsequent rate of criminal homicide. Perhaps because "a return to the exercise of the death penalty weakens socially based inhibitions against the use of lethal force to settle disputes….

In adjacent states — one with the death penalty and the other without it — the state that practices the death penalty does not always show a consistently lower rate of criminal homicide. For example, between l and l, the homicide rates in Wisconsin and Iowa non-death-penalty states were half the rates of their neighbor, Illinois — which restored the death penalty in l, and by had sentenced persons to death and carried out two executions. On-duty police officers do not suffer a higher rate of criminal assault and homicide in abolitionist states than they do in death-penalty states. Between and , for example, lethal assaults against police were not significantly more or less frequent in abolitionist states than in death-penalty states.

Capital punishment did not appear to provide officers added protection during that time frame. In fact, the three leading states in law enforcement homicide in were also very active death penalty states : California highest death row population , Texas most executions since , and Florida third highest in executions and death row population. If anything, the death penalty incited violence rather than curbed it. Prisoners and prison personnel do not suffer a higher rate of criminal assault and homicide from life-term prisoners in abolition states than they do in death-penalty states.

Between and , inmates were murdered by other prisoners. Evidently, the threat of the death penalty "does not even exert an incremental deterrent effect over the threat of a lesser punishment in the abolitionist states. Actual experience thus establishes beyond a reasonable doubt that the death penalty does not deter murder. No comparable body of evidence contradicts that conclusion. Furthermore, there are documented cases in which the death penalty actually incited the capital crimes it was supposed to deter. These include instances of the so-called suicide-by-execution syndrome — persons who wanted to die but feared taking their own lives, and committed murder so that the state would kill them.

For example, in , Daniel Colwell , who suffered from mental illness, claimed that he killed a randomly-selected couple in a Georgia parking lot so that the state would kill him — he was sentenced to death and ultimately took his own life while on death row. Although inflicting the death penalty guarantees that the condemned person will commit no further crimes, it does not have a demonstrable deterrent effect on other individuals.

Further, it is a high price to pay when studies show that few convicted murderers commit further crimes of violence. Researchers examined the prison and post-release records of prisoners on death row in whose sentences were reduced to incarceration for life by the Supreme Court's ruling in Furman. This research showed that seven had committed another murder. But the same study showed that in four other cases, an innocent man had been sentenced to death. Recidivism among murderers does occasionally happen, but it occurs less frequently than most people believe; the media rarely distinguish between a convicted offender who murders while on parole, and a paroled murderer who murders again.

Government data show that about one in 12 death row prisoners had a prior homicide conviction. But as there is no way to predict reliably which convicted murderers will try to kill again, the only way to prevent all such recidivism is to execute every convicted murderer — a policy no one seriously advocates. Equally effective but far less inhumane is a policy of life imprisonment without the possibility of parole. Constitutional due process and elementary justice both require that the judicial functions of trial and sentencing be conducted with fundamental fairness, especially where the irreversible sanction of the death penalty is involved.

In murder cases since , 88 percent of all executions have been for this crime , there has been substantial evidence to show that courts have sentenced some persons to prison while putting others to death in a manner that has been arbitrary, racially biased, and unfair. Racial discrimination was one of the grounds on which the Supreme Court ruled the death penalty unconstitutional in Furman. Half a century ago, in his classic American Dilemma , Gunnar Myrdal reported that "the South makes the widest application of the death penalty, and Negro criminals come in for much more than their share of the executions. Our nation's death rows have always held a disproportionately large population of African Americans, relative to their percentage of the total population.

Comparing black and white offenders over the past century, the former were often executed for what were considered less-than-capital offenses for whites, such as rape and burglary. Between and , men were executed for rape, of whom — 90 percent — were black. A higher percentage of the blacks who were executed were juveniles; and the rate of execution without having one's conviction reviewed by any higher court was higher for blacks.

In recent years, it has been argued that such flagrant racial discrimination is a thing of the past. However, since the revival of the death penalty in the mids, about half of those on death row at any given time have been black. More striking is the racial comparison of victims. African-Americans are six times as likely as white Americans to die at the hands of a murderer, and roughly seven times as likely to murder someone. Young black men are fifteen times as likely to be murdered as young white men. So given this information, when those under death sentence are examined more closely, it turns out that race is a decisive factor after all.

The classic statistical study of racial discrimination in capital cases in Georgia presented in the McCleskey case showed that "the average odds of receiving a death sentence among all indicted cases were 4. Baldus et al. Kemp and while the Court did not dispute the statistical evidence, it held that evidence of an overall pattern of racial bias was not sufficient. McCleskey would have to prove racial bias in his own case — a virtually impossible task. The Court also held that the evidence failed to show that there was "a constitutionally significant risk of racial bias In , the U. General Accounting Office reported to the Congress the results of its review of empirical studies on racism and the death penalty. The GAO concluded : "Our synthesis of the 28 studies shows a pattern of evidence indicating racial disparities in the charging, sentencing, and imposition of the death penalty after the Furman decision" and that "race of victim influence was found at all stages of the criminal justice system process Texas was prepared to execute Duane Buck on September 15, Buck was condemned to death by a jury that had been told by an expert psychologist that he was more likely to be dangerous because he was African American.

The Supreme Court stayed the case, but Mr. Buck has not yet received the new sentencing hearing justice requires. These results cannot be explained away by relevant non-racial factors, such as prior criminal record or type of crime, as these were factored for in the Baldus and GAO studies referred to above. They lead to a very unsavory conclusion: In the trial courts of this nation, even at the present time, the killing of a white person is treated much more severely than the killing of a black person. Of the white defendants executed, only three had been convicted of murdering people of color.

Our criminal justice system essentially reserves the death penalty for murderers regardless of their race who kill white victims. Both gender and socio-economic class also determine who receives a death sentence and who is executed. Women account for only two percent of all people sentenced to death , even though females commit about 11 percent of all criminal homicides. Many of the women under death sentence were guilty of killing men who had victimized them with years of violent abuse. Since , only 51 women have been executed in the United States 15 of them black.

Discrimination against the poor and in our society, racial minorities are disproportionately poor is also well established. It is a prominent factor in the availability of counsel. Fairness in capital cases requires, above all, competent counsel for the defendant. Yet "approximately 90 percent of those on death row could not afford to hire a lawyer when they were tried. As Justice William O. Douglas noted in Furman , "One searches our chronicles in vain for the execution of any member of the affluent strata in this society" US The demonstrated inequities in the actual administration of capital punishment should tip the balance against it in the judgment of fair-minded and impartial observers. Justice John Marshall Harlan, writing for the Court in Furman , noted "… the history of capital punishment for homicides … reveals continual efforts, uniformly unsuccessful, to identify before the fact those homicides for which the slayer should die….

Those who have come to grips with the hard task of actually attempting to draft means of channeling capital sentencing discretion have confirmed the lesson taught by history…. To identify before the fact those characteristics of criminal homicides and their perpetrators which call for the death penalty, and to express these characteristics in language which can be fairly understood and applied by the sentencing authority, appear to be tasks which are beyond present human ability. Yet in the Gregg decision, the majority of the Supreme Court abandoned the wisdom of Justice Harlan and ruled as though the new guided-discretion statutes could accomplish the impossible.

The truth is that death statutes approved by the Court "do not effectively restrict the discretion of juries by any real standards, and they never will. No society is going to kill everybody who meets certain preset verbal requirements, put on the statute books without awareness of coverage of the infinity of special factors the real world can produce. Evidence obtained by the Capital Jury Project has shown that jurors in capital trials generally do not understand the judge's instructions about the laws that govern the choice between imposing the death penalty and a life sentence. Even when they do comprehend, jurors often refuse to be guided by the law.

The effect [of this relative lack of comprehension of the law]… is to reduce the likelihood that capital defendants will benefit from the safeguards against arbitrariness built into the… law. Even if the jury's sentencing decision were strictly governed by the relevant legal criteria, there remains a vast reservoir of unfettered discretion: the prosecutor's decision to prosecute for a capital or lesser crime, the court's willingness to accept or reject a guilty plea, the jury's decision to convict for second-degree murder or manslaughter rather than capital murder, the determination of the defendant's sanity, and the governor's final clemency decision, among others.

Discretion in the criminal justice system is unavoidable. The history of capital punishment in America clearly demonstrates the social desire to mitigate the harshness of the death penalty by narrowing the scope of its application. Whether or not explicitly authorized by statutes, sentencing discretion has been the main vehicle to this end. But when sentencing discretion is used — as it too often has been — to doom the poor, the friendless, the uneducated, racial minorities, and the despised, it becomes injustice. Mindful of such facts, the House of Delegates of the American Bar Association including 20 out of 24 former presidents of the ABA called for a moratorium on all executions by a vote of to in February The House judged the current system to be "a haphazard maze of unfair practices.

In its survey of the death penalty in the United States, the International Commission of Jurists reinforced this point. Despite the efforts made over the past two decades since Gregg to protect the administration of the death penalty from abuses, the actual "constitutional errors committed in state courts have gravely undermined the legitimacy of the death penalty as a punishment for crime. The ALI, which created the modern legal framework for the death penalty in , indicated that the punishment is so arbitrary, fraught with racial and economic disparities, and unable to assure quality legal representation for indigent capital defendants, that it can never be administered fairly.

Thoughtful citizens, who might possibly support the abstract notion of capital punishment, are obliged to condemn it in actual practice. Unlike any other criminal punishments, the death penalty is irrevocable. Speaking to the French Chamber of Deputies in , years after having witnessed the excesses of the French Revolution, the Marquis de Lafayette said, "I shall ask for the abolition of the punishment of death until I have the infallibility of human judgment demonstrated to me. Since , in this country, there have been on the average more than four cases each year in which an entirely innocent person was convicted of murder. Scores of these individuals were sentenced to death.

In many cases, a reprieve or commutation arrived just hours, or even minutes, before the scheduled execution. These erroneous convictions have occurred in virtually every jurisdiction from one end of the nation to the other. Nor have they declined in recent years, despite the new death penalty statutes approved by the Supreme Court. Disturbingly, and increasingly, a large body of evidence from the modern era shows that innocent people are often convicted of crimes — including capital crimes — and that some have been executed.

He was convicted largely based on eyewitness testimony made from the back of a police car in a dimly lit lot near the crime scene. This sample of freakish and arbitrary innocence determinations also speaks directly to the unceasing concern that there are many more innocent people on death rows across the country — as well as who have been executed. Several factors seen in the above sample of cases help explain why the judicial system cannot guarantee that justice will never miscarry: overzealous prosecution, mistaken or perjured testimony, race, faulty police work, coerced confessions, the defendant's previous criminal record, inept and under-resourced defense counsel, seemingly conclusive circumstantial evidence, and community pressure for a conviction, among others.

And when the system does go wrong, it is often volunteers from outside the criminal justice system — journalists, for example — who rectify the errors, not the police or prosecutors. To retain the death penalty in the face of the demonstrable failures of the system is unacceptable, especially since there are no strong overriding reasons to favor the death penalty. Prisoners are executed in the United States by any one of five methods; in a few jurisdictions the prisoner is allowed to choose which one he or she prefers:.

These systems will affect us at the personal level as well. Earlier I mentioned social engineering. Most phishing emails are generic and easily tagged as spam. The more effective phishing emails—the ones that result in people and companies losing lots of money—are personalized. For example, an email that impersonates the CEO to someone in the finance department, asking for a particular wire transfer, can be particularly effective. AI has the potential for every one of those hacks to be microtargeted: personalized, optimized, and individually delivered. Advertising messages are bulk broadcast cognitive hacks. AI techniques have the potential to blend aspects of both of those techniques.

The addition of robotics will only make these hacks more effective, something Kate Darling chronicled in her book The New Breed. We see faces everywhere; two dots over a horizontal line looks like a face without any trouble. This is why even minimalist illustrations are so effective. If that something speaks or, even better, converses, then we believe it has intentions, desires, and agency. Robots are no exception. We can experience nurturing feelings towards adopted children, and we can feel the same instincts arise when we interact with the children of friends or even strangers—or puppies.

At least some of our response is inspired by the appearance and behavior of children. Children have large heads in proportion to their bodies, and large eyes in proportion to their heads. They talk with a higher-pitched voice than adults. And we respond to all of this. Artists have taken advantage of this for generations to make their creations appear more sympathetic. Cartoon characters are drawn this way, as far back as Betty Boop in the s and Bambi in In the live-action movie Alita: Battle Angel, the main character had her eyes computer-enhanced to be larger. Anthropomorphic robots are an emotionally persuasive technology, and AI will only amplify their attractiveness.

As AI mimics humans, or even animals, it will hijack all the mechanisms that humans use to hack each other. But a large face paired with a small body makes us think of it as a child. Because we humans are prone to making a category error and treating robots as living creatures with feelings and intentions, we are prone to being manipulated by them. Robots could persuade us to do things we might not do otherwise. They could scare us into not doing things we might otherwise do. AIs will get better at all of this. Already they are trying to detect emotions by analyzing our writings, 52 reading our facial expressions, 53 or monitoring our breathing and heartrate.

And, like so many areas of AI, they will eventually surpass people in capability. This will allow them to more precisely manipulate us. As AIs and autonomous robots take on more real-world tasks, human trust in autonomous systems will be hacked with dangerous and costly results. But never forget that there are human hackers controlling the AI hackers. All of the systems will be designed and paid for by humans who want them to manipulate us in a particular way for a particular purpose. The competition has been a mainstay at hacker gatherings since the mids.

These days, dozens of teams from around the world compete in weekend-long marathon events held all over the world. People train for months. Winning is a big deal. The competition occurred in a specially designed test environment filled with custom software that had never been analyzed or tested. The AIs were given ten hours to find vulnerabilities to exploit against the other AIs in the competition, and to patch themselves against exploitation. A system called Mayhem, created by a team of Pittsburgh computer-security researchers, won.

The researchers have since commercialized the technology, which is now busily defending networks for customers like the Department of Defense. Mayhem was invited to participate as the only non-human team, and came in last. You can easily imagine how this mixed competition would unfold in the future. AI entrants will improve every year, because the core technologies are all improving. The human teams will largely stay the same, because humans remain humans even as our tools improve.

Eventually the AIs will routinely beat the humans. It will be years before we have entirely autonomous AI cyberattack capabilities, but AI technologies are already transforming the nature of cyberattack. One area that seems particularly fruitful for AI systems is vulnerability finding. Going through software code line by line is exactly the sort of tedious problem at which AIs excel, if they can only be taught how to recognize a vulnerability. The implications extend far beyond computer networks. Already AIs are looking for loopholes in contracts. This will all improve with time. Modern AIs are constantly improving based on ingesting new data and tweaking their own internal workings accordingly.

All of this data continually trains the AI, and adds to its experience. The AI evolves and improves based on these experiences over the course of its operation. There are really two different but related problems here. The first is that an AI might be instructed to hack a system. The other is that an AI might naturally, albeit inadvertently, hack a system. Both are dangerous, but the second is more dangerous because we might never know it happened. After 7. And was unable to explain its answer, or even what the question was. That, in a nutshell, is the explainability problem. Modern AI systems are essentially black boxes. Data goes in at one end, and an answer comes out the other. It can be impossible to understand how the system reached its conclusion, even if you are a programmer and look at the code.

Their limitations are different than ours. In , a research group fed an AI system called Deep Patient health and medical data from approximately , individuals, and tested whether or not the system could predict diseases. The result was a success. Weirdly, Deep Patient appears to perform well at anticipating the onset of psychiatric disorders like schizophrenia—even though a first psychotic episode is nearly impossible for physicians to predict. What we want is for the AI system to not only spit out an answer, but also provide some explanation of its answer in a format that humans can understand. Explanations are a cognitive shorthand used by humans, suited for the way humans make decisions. AI decisions simply might not be conducive to human-understandable explanations, and forcing those explanations might pose an additional constraint that could affect the quality of decisions made by an AI system.

In the near term, AI is becoming more and more opaque, as the systems get more complex and less human-like—and less explainable. They will invariably stumble on solutions that we humans might never anticipated—and some will subvert the intent of the system. These are all hacks. You can blame them on poorly specified goals or rewards, and you would be correct. You can point out that they all occurred in simulated environments, and you would also be correct. But the problem is more general: AIs are designed to optimize towards a goal. Imagine a robotic vacuum assigned the task of cleaning up any mess it sees. He trained an AI by rewarding it for not hitting the bumper sensors. Any good AI system will naturally find hacks.

If are problems, inconsistencies, or loopholes in the rules, and if those properties lead to an acceptable solution as defined by the rules, then AIs will find them. We all learned about this problem as children, with the King Midas story. When the god Dionysus grants him a wish, Midas asks that everything he touches turns to gold. Midas ends up starving and miserable when his food, drink, and daughter all turn to inedible, unpotable, unlovable gold. We also know that genies are very precise about the wording of wishes, and can be maliciously pedantic when granting them.

The genie will always be able to hack your wish. The problem is more general, though. In human language and thought, goals and desires are always underspecified. We never delineate all of the caveats and exceptions and provisos. We never close off all the avenues for hacking. Any goal we specify will necessarily be incomplete. This is largely okay in human interactions, because people understand context and usually act in good faith.

We are all socialized, and in the process of becoming so, we generally acquire common sense about how people and the world works. We fill any gaps in our understanding with both context and goodwill. If I asked you to get me some coffee, you would probably go to the nearest coffeepot and pour me a cup, or maybe to walk to the corner coffee shop and buy one. You would not bring me a pound of raw beans, or go online and buy a truckload of raw beans. You would not buy a coffee plantation in Costa Rica. You would also not look for the person closest to you holding a cup of coffee and rip it out of their hands.

You would just know. The audience laughed, but how would a computer program know that causing an airplane computer malfunction is not an appropriate response to someone who wants to get out of dinner? In , Volkswagen was caught cheating on emissions control tests. The result was that the cars had superior performance on the road. Volkswagen got away with it for over ten years because computer code is complex and difficult to analyze.

Basically, the scientists tested the car without the software realizing it. Or of ethics. Again, this is a story of humans cheating. And because of the explainability problem, we humans might never realize it either. Unless the programmers specify the goal of not behaving differently when being tested, an AI might come up with the same hack. The programmers will be satisfied. The accountants will be ecstatic. And because of the explainability problem, no one will realize what the AI did. And yes, now that we know the Volkswagen story, the programmers can explicitly set the goal to avoid that particular hack, but there are other hacks that the programmers will not anticipate.

The lesson of the genie is that there will always be hacks the programmers will not anticipate. If your driverless car navigation system satisfies the goal of maintaining a high speed by spinning in circles—a real example 79 —programmers will notice this behavior and modify the goal accordingly. The behavior may show up in testing, but we will probably never see it occur on the road. Much has been written about recommendation engines, and how they push people towards extreme content. Similarly, in , an AI taught itself to play the s computer game Breakout. It was just given the controls, and rewarded for maximizing its score. One solution is to teach AIs context. You can think about solutions in terms of two extremes. The first is that we can explicitly specify those values.

That can be done today, more or less, but is vulnerable to all of the hacking I just described. That is many years out AI researchers disagree on the time scale. Most of current research straddles these two extremes. Of course, you can easily imagine the problems that might arise by having AIs align themselves to historical or observed human values. Whose values should an AI mirror? A Somali man?

A Singaporean woman? The average of the two, whatever that means? We humans have contradictory values. We humans are often not very good examples of the sorts of humans we should be. The feasibility of any of this depends a lot on the specific system being modeled and hacked. For an AI to even start on optimizing a solution, let alone hacking a completely novel solution, all of the rules of the environment must be formalized in a way the computer can understand. Goals—known in AI as objective functions—need to be established. The AI needs some sort of feedback on how well it is doing so that it can improve its performance. Sometimes this is a trivial matter. The rules, objective, and feedback—did you win or lose? This is why most of the current examples of goal and reward hacking come from simulated environments.

Those are artificial and constrained, with all of the rules specified to the AI. What matters is the ambiguity in a system. That ambiguity is difficult to translate into code, which means that an AI will have trouble dealing with it—and that there will be full employment for tax lawyers for the foreseeable future. Most human systems are even more ambiguous. An AI would have to understand not just the rules of the game, but the physiology of the players, the aerodynamics of the stick and the puck, and so on and so on. Probably the first place to look for AI-generated hacks are financial systems, since those rules are designed to be algorithmically tractable.

This ambiguity ends up being a near-term security defense against AI hacking. Some may be due to a surge of gun purchases during the pandemic. Some may be traceable to the erosion of trust between the police and public following the murder of George Floyd in May One factor that can be ruled out, though, is the adoption of more lenient criminal justice policies, including the early release of some prisoners, in liberal parts of the country.

Killings have risen in all parts of the country , just as much in Republican-led cities as in cities with Democratic mayors, and just as much in counties with and without progressive prosecutors. And, in fact, as the worst days of the pandemic have receded in New York City, homicides have fallen as well. It was clear from early that overcrowded prisons and jails would help the virus spread rapidly. Even before the pandemic, far too many people were dying violently in the United States. Fortunately, there is growing evidence that gun homicides between non-intimates — the kind of killings that have risen sharply over the past year and a half — can be reduced dramatically by violence reduction programs concentrated on the relatively small number of people, places, and social interactions responsible for most of the street violence in a given city.

These programs are not easy to carry out successfully, and they are even more difficult to sustain over the long term. Pairing focused deterrence with social services and peer-to-peer counseling, they require trust and collaboration between police and community groups, close analysis of local patterns of violence, restraint on the part of police and prosecutors, a strong commitment to helping individuals exit cycles of violence, and an institutional framework that can survive leadership changes, budget crises, and the inevitable calls for tougher approaches when, as in and , homicide rates begin to climb.

Ceasefire identified a relatively small number of groups responsible for the bulk of youth shootings in Boston and targeted their members with threats of criminal enforcement along with offers of economic support and social services if they refrained from gun violence. The program relied on consultation and coordination between the police department, a range of other municipal agencies and nonprofit groups, and inner-city clergy. A more recent, successful version of the Ceasefire approach, in Oakland, California , has focused on adult shooters rather than juveniles reflecting differences between homicide patterns in Oakland and Boston and has deemphasized the role of the police while expanding the role of peer-to-peer counseling.

It often takes several tries, stretching over years, before a city finds the right approach, appropriately tailored to local circumstances. And even the most successful programs, like those in Boston and Oakland, are not panaceas: both cities have seen increases in gun violence during the pandemic. Still, we know these programs can work. Those gains began to disappear in the early s when the program was discontinued, then were recovered when the program was restarted. The results in Oakland were similarly impressive: both homicides and nonfatal shootings were cut in half. We also know that there are ways to reduce violent encounters between the police and the public, and ways to curtail prison violence , and ways to help victims of abuse within families and intimate relationships protect themselves from getting killed.

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