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Speaker 1: Welcome to Crash Course, a podcast about business, political, and

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Speaker 1: social disruption and what we can learn from it. I'm

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Speaker 1: Tim O'Brien. Today's crash Course crime trends versus statistics and reality.

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Speaker 1: After many years of reassuring declines, some crime rates soared

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Speaker 1: nationwide during the COVID nineteen pandemic. Homicides jumped about thirty

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Speaker 1: percent in twenty twenty compared to the prior year, and

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Speaker 1: violent assaults rose by more than ten percent. According to

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Speaker 1: a number of different groups that track the data, these

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Speaker 1: trends weren't geographically or politically specific. Residents in cities, suburbs,

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Speaker 1: and rural areas all suffered through that shift, and it

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Speaker 1: didn't matter if they lived in a city run by

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Speaker 1: a Democrat or a Republican. More murders, the data showed,

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Speaker 1: plagued every urban area. On the other hand, robberies, burglaries,

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Speaker 1: and larcenies dropped during the pandemics onset. As the pandemic,

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Speaker 1: war on murder rates andolent crime rates overall settled down,

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Speaker 1: the numbers rose, but not nearly as sharply as they

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Speaker 1: did early on. Another wrinkle, crime statistics are subject to

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Speaker 1: spotty methodology and reporting gaps, making it hard to rely

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Speaker 1: on the data with absolute certainty. Public safety isn't a

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Speaker 1: trivial topic, and there's no question that many Americans say

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Speaker 1: they feel less safe on some streets than they once did,

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Speaker 1: despite the fact that violent crime rates are well below

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Speaker 1: where they were during the nineteen nineties. So what was

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Speaker 1: behind the pandemic surge and murders and assaults and what

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Speaker 1: lessons can residents and public officials draw from what happened.

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Speaker 1: Joining us today to chat about all of this is

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Speaker 1: Ames Growert, a lawyer and expert on crime statistics at

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Speaker 1: the Brennan Center for Justice at the NYU Law School.

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Speaker 1: The Brennan Center is a nonprofit focused on a number

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Speaker 1: of legal and public policy issues, including research into the

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Speaker 1: sources of violent crime. Welcome, Ames, Thank.

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Speaker 2: You so much for having me. It's a pleasure to

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Speaker 2: be here.

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Speaker 1: So set the stage alone a little bit for us. First,

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Speaker 1: tell us a little bit about the work you do

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Speaker 1: at the Brennan Center and how the Brennan Center intersects

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Speaker 1: with crime research and crime statistics.

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Speaker 2: Absolutely so. Our theory of criminal justice reform is that

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Speaker 2: we can have a country that is both safer and fairer,

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Speaker 2: that we can has common sense criminal justice reform policies

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Speaker 2: that lead to a justice system that is fairer to

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Speaker 2: all who are impacted by it. That's including people who

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Speaker 2: are victims of crime as well as people accused of crime,

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Speaker 2: and that while doing so, we can also have a

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Speaker 2: safer country. As a whole. Part and parcel of that

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Speaker 2: research is trying to understand what's actually happening when it

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Speaker 2: comes to crime trends around the country. So around eight

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Speaker 2: years ago, some colleagues before I joined the Brendan Center

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Speaker 2: actually released a report called What Caused the Crime de Client.

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Speaker 2: This is sort of the origin of this work, but

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Speaker 2: it's also very much still relevant to the work we

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Speaker 2: do today. They're thinking was, we need to understand the

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Speaker 2: huge drop off and crime rates that happened between nineteen

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Speaker 2: ninety one and roughly twenty fourteen. Over that course of time,

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Speaker 2: murder rates in the United States the drops of half.

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Speaker 2: Some sociologists call this the Great Crime Decline. It's a

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Speaker 2: rarely remarked upon but incredibly important social phenomenon. So they

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Speaker 2: set out to figure out, you know, why what happened.

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Speaker 2: They came to a couple conclusions, one of which is

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Speaker 2: it's very difficult to untact something that complicated, but a

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Speaker 2: couple of their findings were that improving economic conditions partially

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Speaker 2: helped explain drops in crime nationwide, and that incarceration was

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Speaker 2: not as powerful an explanation as some had expected. So

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Speaker 2: that was the genesis of this work, an idea that

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Speaker 2: we need to you know, understand what's really happening with

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Speaker 2: crime trends across the country, and that you know, we

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Speaker 2: continue to this day to monitor what's happening around the country,

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Speaker 2: keep abreast of the very best research, and contribute our

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Speaker 2: own where we can well.

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Speaker 1: And socioeconomic factors play into our understanding what happened during

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Speaker 1: the pandemic too, So let's get into that a little bit.

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Speaker 1: What happened in the early stages of the pandemic, particularly

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Speaker 1: twenty twenty, that caused homicides and violent crimes to spike.

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Speaker 2: Yeah, just to give you a bit of context, I

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Speaker 2: know you touched on at the top of the show,

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Speaker 2: but the key statistics are we saw the national murder

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Speaker 2: rate increase by about thirty percent year every year from

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Speaker 2: twenty nineteen to twenty twenty. We saw assault increase by

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Speaker 2: around ten percent or so, you know, that's a significant

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Speaker 2: increase in violence. And I think, much like we don't

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Speaker 2: have a complete answer as to, you know, why crime

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Speaker 2: dropped so precipitously between you know, the early nineteen nineties

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Speaker 2: and today. We don't yet have and may not have

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Speaker 2: for a long time, a full accounting of what happened

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Speaker 2: during the COVID nineteen pandemic. When my colleagues and I

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Speaker 2: investigated this to try to figure out, you know, what

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Speaker 2: could explain such a dramatic increase in violence concentrated in

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Speaker 2: such a short period of time. We can do a

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Speaker 2: couple explanations, but we've always been careful, and I just

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Speaker 2: want to re emphasize to your listeners too, that this

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Speaker 2: isn't the full accounting. We're not saying, you know, these

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Speaker 2: are the factors that one hundred percent explained everything that

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Speaker 2: happened since twenty nineteen. I don't know who'll ever get there,

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Speaker 2: but a couple of those factors were Number one, increasing

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Speaker 2: access to firearms and increasing carrying and use of them.

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Speaker 2: And I can go into that at greater length. It's

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Speaker 2: really interesting.

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Speaker 1: So, surprise, surprise, more guns on the street produce more

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Speaker 1: violence against other people. That's about right, I'm shocked to

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Speaker 1: discover that.

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Speaker 2: You know, so often we look for counterintuitive findings, but

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Speaker 2: this just feels very intuitive. It's sometimes these sort of

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Speaker 2: explanations that resonate with us. It's just common sense. There

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Speaker 2: actually is research back into it, and people can push

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Speaker 2: back and say, you know, well, it's true that more

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Speaker 2: guns is an mulos equal more crime. A lot of

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Speaker 2: second and third guns are bought by collectors, but in

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Speaker 2: the pandemic, we actually did see a sort of closer

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Speaker 2: link at least between more guns more crime.

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Speaker 1: There had been years of a surge on guns on

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Speaker 1: the streets that also corresponded with a drop in homicides

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Speaker 1: and violent crimes. So even there, the link is not

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Speaker 1: entirely direct, right, It's.

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Speaker 2: Very complicated yet. So one of the pandemic ara statistics

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Speaker 2: we look at is something that the ATF refers to

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Speaker 2: as time to crime. What that means is when a

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Speaker 2: gun is recovered from a crime scene, how long ago

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Speaker 2: was it lawfully purchased. So it's sort of the time

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Speaker 2: between when a gun enters the market legally and when

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Speaker 2: it turns up at a crime scene. Time to crime

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Speaker 2: actually dropped during the first two years of the COVID

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Speaker 2: nineteen pandemic that suggests there's sort of a closer link

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Speaker 2: between gun purchases and guns being used unlawfully. But frankly,

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Speaker 2: this is an area where we need more research to

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Speaker 2: understand better the link between gun purchases and gun violence.

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Speaker 1: Were there other factors in addition to availability to firearms?

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Speaker 1: Access to firearms?

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Speaker 2: Yes, So this is a tough one. I think. You know,

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Speaker 2: when you talk to some people, they will give you

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Speaker 2: a very strong case of this argument, and I'm going

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Speaker 2: to give you the sort of middle way case of

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Speaker 2: the argument, that is that the social disruption caused by

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Speaker 2: the COVID nineteen pandemic had some effect on crime trends,

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Speaker 2: and especially violent crime. This is a tough one because

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Speaker 2: I don't know if we'll ever be able to fully

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Speaker 2: quantify exactly how this relationship played out, What happened, What's

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Speaker 2: the mechanism that explains the link between the onset of

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Speaker 2: the pandemic and violent crime. We might not ever have

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Speaker 2: a full understanding of that, but a couple of mechanisms

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Speaker 2: that we're sort of thinking through are this. When we

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Speaker 2: saw the pandemic begin, the government response was not immediately

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Speaker 2: adequate and not immediately encouraging. So a lot of people

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Speaker 2: and people that we talked to in communities affected by

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Speaker 2: violence said that members of their community lost faith in

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Speaker 2: the government, didn't believe that their institutions were there to

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Speaker 2: keep them safe. At the same time, a lot of

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Speaker 2: basic parts of the community fabric, like libraries, third places

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Speaker 2: so called where people can congregate after work or on

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Speaker 2: the weekends, those shut down or inaccessible programs like community

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Speaker 2: violence intervention initiatives, which are programs run by people at

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Speaker 2: street level to help stop violence, support starts. Those sor

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Speaker 2: programs often have to be run face to face, and

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Speaker 2: you can't do that during a respiratory pandemic. That's just

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Speaker 2: not how it works. So all these factors that sort

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Speaker 2: of work together in the background almost to keep communities safe,

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Speaker 2: all of them sort of fell apart at once, And

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Speaker 2: it would almost be surprising if that had no effects.

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Speaker 2: The question that we ask, and I think researchers need

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Speaker 2: to continue to ask, is what sort of effect did

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Speaker 2: it have? What was the magnitude of that effect?

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Speaker 1: So it would all be under the umbrella of people

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Speaker 1: freaked out, it.

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Speaker 2: Would be more into the umbrella of once in a

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Speaker 2: generation pandemic having untold, difficult to quantify, difficult to really

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Speaker 2: fully appreciate, effects on the social fabric and the sort

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Speaker 2: of informal ties that keep the communities safe.

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Speaker 1: Yeah, people certainly had existential dread. People were reaching out

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Speaker 1: to connect to one another more, and it was uncertain

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Speaker 1: what the pandemic's effects would be. It's interesting to me

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Speaker 1: to contemplate that. Then another stage and thinking was lashing

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Speaker 1: out against other people, you know, either with guns or hands.

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Speaker 1: Yet another statistic in all of that, though, is interesting

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Speaker 1: to me, is that auto thefts also jumped. So in

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Speaker 1: addition to, you know, you had certain kinds of crime

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Speaker 1: to decline, and then you had homicides and assaults jump,

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Speaker 1: but auto thefts jumped too. What are you thinking about that?

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Speaker 1: That's a category to me that's sort of intriguing.

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Speaker 2: Yeah, this is a really interesting one. One way to

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Speaker 2: think about what happened during the COVID nineteen pandemic is

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Speaker 2: how does the onset of a major respiratory virus affect

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Speaker 2: someone's opportunity to commit a type of crime. So retail

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Speaker 2: thefts tended to drop during the COVID nineteen pandemics. People

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Speaker 2: simply weren't going to stores but at the same time,

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Speaker 2: you know, you might not have eyes on your car

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Speaker 2: that you parked up the street a couple of weeks

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Speaker 2: ago because you haven't left your house. That's one factor

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Speaker 2: that might partially explain increasing motor vehicle thefts. But there

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Speaker 2: are a couple others too. One and this comes from

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Speaker 2: a conversation I had with Jeff Asher, who's a fantastic

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Speaker 2: analyst of crime trends. He pointed out that motor vehicle

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Speaker 2: thefts tend to go hand in hand with more serious

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Speaker 2: forms of violence. So, you know, a car is stolen

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Speaker 2: and then used in a drive by shooting, so it's

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Speaker 2: possible that, you know, you would see that type of

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Speaker 2: offense increase alongside murder, which is what we in fact

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Speaker 2: saw during the COVID nineteen pandemic. More recently, there have

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Speaker 2: been security vulnerabilities discovered and a couple of vehicle brands,

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Speaker 2: and there have been videos and stuff.

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Speaker 1: So glad you're bringing this up. You're getting to the

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Speaker 1: TikTok video. Yeah, part of the argument. Excellent.

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Speaker 2: Yeah, there's a social media video explaining how easy it

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Speaker 2: is to short circuit the security defenses of some vehicles.

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Speaker 1: And specifically kias and Hyundais.

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Speaker 2: I believe, Yeah, I believe that's right. And I can't

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Speaker 2: tell you that that explains, you know, fifty percent or

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Speaker 2: whatever percent of the increase in motor vehicle thefts, but

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Speaker 2: it's not trivial. I think that that sort of effect

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Speaker 2: of not just opportunity but means becoming more available might

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Speaker 2: help explain the increase in those offenses as well.

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Speaker 1: So all of the reasons you're giving for why the

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Speaker 1: numbers jumped, both in these separate categories which can be

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Speaker 1: caused by unrelated factors, and then some of the ones

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Speaker 1: that are caused by related factors, none of these are

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Speaker 1: necessarily the reasons that captured the public's imagination as to

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Speaker 1: why homicides and violent crime were rising in year one

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Speaker 1: of COVID nineteen. Tell me about that. What were the

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Speaker 1: reasons that many people latched onto for why this was happening.

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Speaker 2: Yeah, that's the key question. One of the frustrating things

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Speaker 2: about working on crime research and trying to understand the

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Speaker 2: way the criminal justice system works is it's easier to

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Speaker 2: disprove some theories than it is to proved them. That's

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Speaker 2: because the data are very hard to come by sometimes,

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Speaker 2: But when you have a concrete idea. Sometimes you can

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Speaker 2: gather the data you need to actually test the theory,

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Speaker 2: and that's what my colleagues and I have done in

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Speaker 2: some cases, and researchers around the country have done in others.

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Speaker 2: And I'll get to exactly what the data show in

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Speaker 2: a minute. But one of the most popular theories about,

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Speaker 2: you know, why crime rose, especially in New York City,

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Speaker 2: was bail reform. This was a major initiative enacted in

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Speaker 2: twenty twenty that changed the way the state's pre trailer

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Speaker 2: released laws worked, so detension bail were largely taken off

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Speaker 2: the table for our misdemeanors in some lower level felonies.

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Speaker 2: People jumped to the conclusion very quickly that bail reform

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Speaker 2: might explain rising crime in New York City. But when

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Speaker 2: you really kick the tires of that data, it just

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Speaker 2: doesn't add up. For one, as you know, as we've

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Speaker 2: been discussing folent crime and murders rose around the country,

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Speaker 2: it would be very odd, indeed, if bail reform in

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Speaker 2: New York somehow powered a nationwide increase in violent crime.

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Speaker 2: It just doesn't compute. Really. Subsequent researchers backed that up

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Speaker 2: as well, and I'm happy to go into that too.

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Speaker 2: Another point that people argued was that this might be

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Speaker 2: a quote city phenomenon, that this is something that originates

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Speaker 2: in nebulously defined, quote blue city governance. I think this

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Speaker 2: idea is sort of a holdover of the way crime

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Speaker 2: used to look in this country. You know, if you

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Speaker 2: go back to the nineteen nineties, there were multiple thousands

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Speaker 2: of murders in New York every year. Amasite raid in

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Speaker 2: a city like New York was well about the national average,

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Speaker 2: And I think people sort of came to expect that

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Speaker 2: violent crime is a city problem. But fast forward thirty

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Speaker 2: years down the line, that's not quite so true. New

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Speaker 2: York City is one of the safest big cities in

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Speaker 2: the country. It's murder rate is below the national average.

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Speaker 2: So this idea that violent crime was caused by and

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Speaker 2: primarily a problem of cities, it's also simply not true,

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Speaker 2: but became a very prevalent narrative, especially during the early

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Speaker 2: days of the COVID nineteen pandemic. One of the other

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Speaker 2: theories that we've looked into, and others have really taken

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Speaker 2: a lot of time to try to research, is whether

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Speaker 2: the inauguration of district attorneys who believe in criminal justice

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Speaker 2: reform policies. The label you here as quote progressive prosecutors,

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Speaker 2: But I've talked to these people. They don't all subscribe

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Speaker 2: to that label. They subscribe to the idea that they

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Speaker 2: are elected district attorneys who believe in criminal justice reform policies.

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Speaker 2: But one of the arguments against them has been that.

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Speaker 1: We'll still wanting to enforce the law.

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Speaker 2: Indeed, yes, they're elected district attorneys who believe in criminal

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Speaker 2: justice reform as a means of making their community safer,

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Speaker 2: not as a political point. So one of the arguments

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Speaker 2: has done that these so called progressive prosecutors have presided

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Speaker 2: over a rise at crime and helped kick it off

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Speaker 2: in their cities, and the data just don't support that.

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Speaker 2: There's a really good study that was co authored by

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Speaker 2: Anna Harvey at NYU's Public Safety Lab that tried to

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Speaker 2: revide a relationship between progressive prosecuters and rise and crime,

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Speaker 2: and she couldn't do it. She just couldn't find any

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Speaker 2: sort of relationship. More researchers coming out on this. Now,

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Speaker 2: that was a popular narrative, but it just hasn't held up.

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Speaker 1: And then moreover in successive years, in twenty twenty one

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Speaker 1: and twenty twenty two, the homicide rate drop, the rate

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Speaker 1: of violent crimes dropped. What changed? Do you have a

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Speaker 1: handle on what was behind that phenomenon.

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Speaker 2: That's a question we're sitting with too. I actually think

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Speaker 2: it does suggest one point. So if you were as

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Speaker 2: we were sitting in the beginning of the COVID nineteen

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Speaker 2: pandemic and wondering, you know, what's happening in the country,

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Speaker 2: why are we seeing crime rates increase so much? If

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Speaker 2: you had a theory that part of this might be

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Speaker 2: due to factors related to the COVID nineteen pandemic, like

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Speaker 2: social disorder, like the shuddering of key institutions that help

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Speaker 2: keep communities safe, you might hypothesize that as the pandemic recedes,

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Speaker 2: we might start to see murder rates go down, and

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Speaker 2: that is in fact what we're now seeing. So I

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Speaker 2: think it's a point of evidence that suggests, but doesn't

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Speaker 2: conclusively prove, that much of the reason that we sew

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Speaker 2: violence spike so much in the early years of the

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Speaker 2: pandemic might be due to these factors related to the pandemic,

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Speaker 2: And as the world sort of returns to normal, as

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Speaker 2: businesses reopen, as people get back to their daily life.

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Speaker 2: As community rhythm's return, that sort of network of safety

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Speaker 2: and invisible bonds that keep us safe sort of re

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Speaker 2: establishes itself. I don't have a complete answer for this question,

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Speaker 2: but I think that's at least one theory worth thinking over.

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Speaker 1: So the lesson to be drawn from that is state

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Speaker 1: away from guns during year one of any lockdown, because

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Speaker 1: that's when people are most likely to fire them.

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Speaker 2: A question we think about too is sort of how

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Speaker 2: to build resilience into communities and how do you build

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Speaker 2: resilience into society as a whole? And trust absolutely and

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Speaker 2: trust I think that's a really good way of putting it.

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Speaker 2: There were some surprising things that we found when we

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Speaker 2: looked into, you know, not just what caused crime to

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Speaker 2: increase in twenty twenty, but you know what solutions people

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Speaker 2: were talking about. There's actually some research these days that

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Speaker 2: medicaid expansion, which we just saw go into place, and

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Speaker 2: I believe it was North Carolina, is actually associated with

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Speaker 2: lower arrest rates and lower rates of priscidivism in some cases.

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Speaker 2: This suggests to me that as you build a society

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Speaker 2: that has a stronger safety net and is more focused

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Speaker 2: on taking care of people. You might help firm up

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Speaker 2: that sort of invisible network that keeps us all safer.

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Speaker 1: On that note, Ames, I'm going to take a quick

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Speaker 1: break so we can hear from a sponsor, and then

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Speaker 1: we will come back in to chat further about all

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Speaker 1: of this. We're back with Ames GROWERDT and we're discussing

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Speaker 1: murder and other crimes during the pandemic and after Ames

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Speaker 1: we talked a little bit earlier about people citing the

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Speaker 1: wrong factors for this spike and murder and viol and

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Speaker 1: assaults during the pandemic and what some of the real

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Speaker 1: factors might have been. You know, we're having this conversation

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Speaker 1: and the context of the data is still recently fresh.

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Speaker 1: The events are still relatively recent, and no one knows

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Speaker 1: for certain, but our goal is to try to really

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Speaker 1: get it real cause and effect so we can get

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Speaker 1: better solutions. How was the narrative around the crime spike

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Speaker 1: during the COVID pandemic and after construct it. I'm interested

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Speaker 1: in that from your perspective. How did that narrative come

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Speaker 1: into the public consciousness, because it's certainly different than some

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Speaker 1: of what we just talked about earlier in terms of

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Speaker 1: the factors that actually informed the spike.

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Speaker 2: Yeah, that's a really good question and something I spend

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Speaker 2: a lot of time thinking about. I'll do my best

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Speaker 2: to give you as clear of an answer as I can,

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Speaker 2: but it's a complicated subject. On the one hand. You know,

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Speaker 2: I think when people see something like the covidanteen pandemic

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Speaker 2: and they see, you know, hard data showing what they're

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Speaker 2: feeling that violence is increasing, people naturally feel afraid and

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Speaker 2: feel concerned for their states, see in the safety their

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Speaker 2: loved ones, and those feelings are valid and important, and

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Speaker 2: we should respect that. Number one one temptation when these

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Speaker 2: very reasonable fears arise, I think it's tempting for some

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Speaker 2: to look for sort of easy explanations. It's tempting to

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Speaker 2: say this is a problem, and here's the solution, and

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Speaker 2: that solution will work tomorrow. When people gravitate to those

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Speaker 2: easy answers, those answers feel good, they might sound attractive,

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Speaker 2: but they might be wrong, and more than that, they

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Speaker 2: might actually end up doing more harm than good. So

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Speaker 2: I think that's one factor, and telling the narrative onward

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Speaker 2: is know, when crime rose, people looked for sort of

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Speaker 2: a single factor answer, you know, crime rose by thirty

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Speaker 2: percent in twenty twenty because of X, and insert into X,

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Speaker 2: you know, bail reform, quote, blue city, something like that.

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Speaker 2: That answer might have a certain narrative and intuitive appeal,

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Speaker 2: it just happens to be wrong. Another factor I think

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Speaker 2: we've seen, and I touched on this a little bit earlier,

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Speaker 2: is I think because of the way that crime trends

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Speaker 2: in the country used to look, people are sort of

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Speaker 2: primed to think of crime as a city issue rather

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Speaker 2: than an American issue, and people are primed to believe

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Speaker 2: that cities like New York are uniquely dangerous, when actually

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Speaker 2: almost the opposite is true. Representative Jim Jordan hosted a

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Speaker 2: field hearing in New York City designed to highlight how

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Speaker 2: crime in the city was increasing. It just happened to

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Speaker 2: be at a time when murder trends in the city

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Speaker 2: were actually declining sharply, and the evidence for rising crime

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Speaker 2: in New York City was simply nowhere to be found.

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Speaker 2: You know, the city, like other places in the country,

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Speaker 2: had experience of crime spike during the pandemic, but by

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Speaker 2: all accounts that spike was in the process of reversing.

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Speaker 2: These narratives, they have an intuitive appeal. It's up to

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Speaker 2: you know, policymakers and other opinion leaders like us in fact,

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Speaker 2: to talk through why those narratives might not actually be

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Speaker 2: true and why there might be other solutions that can

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Speaker 2: make us safer. A colleague of mine who I do

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Speaker 2: some work with, in Hirahman at the Beer Institute. She

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Speaker 2: has a really interesting saying, I think in something that

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Speaker 2: I think about daily. She says, you know, if we

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Speaker 2: focus on the wrong problems, we also focus on the

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Speaker 2: wrong solutions. So if you yourself in a narrative where

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Speaker 2: you think the reason that crime is up is because

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Speaker 2: cities are doing something wrong and bail reform or progressive

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Speaker 2: prosecutor or something like that, you might miss some other

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Speaker 2: solution that has nothing to do with those quote problems

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Speaker 2: and that could actually lead to safer communities down the line.

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Speaker 1: And as I noted at the top of the show,

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Speaker 1: suburbs and rural areas saw a very similar spike to

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Speaker 1: what cities saw. So the idea again that cities themselves

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Speaker 1: are unique kind of breeding grounds or Petrie dishes for

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Speaker 1: violent crime is belied by reality in the data.

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Speaker 2: That's exactly right.

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Speaker 1: Having said that, aims about the similarities of suburbs and

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Speaker 1: rural areas and cities. There is also reality at work here. However,

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Speaker 1: there is no denying that city streets do for a

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Speaker 1: lot of people feel less safe. A lot of small

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Speaker 1: businesses have boarded up, there's less people walking around in

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Speaker 1: the streets, particularly late at night. Homelessness has been on

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Speaker 1: the rise in every big city I think, or at

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Speaker 1: least most of the big ones, and I've visited a

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Speaker 1: number of them since COVID began, and you just notice

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Speaker 1: homeless people wandering in greater numbers in the past, and

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Speaker 1: there is this perception that the streets aren't as safe,

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Speaker 1: even if the data doesn't show us that. Let's talk

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Speaker 1: about that a little bit, because that is a reality

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Speaker 1: based conclusion for a lot of folks.

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Speaker 2: Absolutely it is, yes, And when people have that impression,

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Speaker 2: they were reacting to something real. I'm not one to

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Speaker 2: discount people's experiences and fears about their community. I think

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Speaker 2: one thing at work here is people see social disorder,

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Speaker 2: People see hardship in their lives, such as an increasing

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Speaker 2: number of people living on the streets, and they make

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Speaker 2: a sort of intuitive connection between bad and crime. But

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Speaker 2: social disorder and crime are not necessarily one of the same.

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Speaker 2: They might in some cases go hand in hand, but

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Speaker 2: that might be one reason why we see a sort

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Speaker 2: of a gap between the perceptions and realities around the trends,

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Speaker 2: especially in major offenses. These are real problems. They don't

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Speaker 2: want to downplay it. Like I've seen the data on

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Speaker 2: homelessness and Portland, I've seen the data on homelessness in

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Speaker 2: California and New York, and you're right, it is up.

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Speaker 2: But the solutions to those problems might lie outside the

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Speaker 2: criminal justice system, where they might lie in other policy

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Speaker 2: interventions disconnected from the problem of crime in the United.

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Speaker 1: States, and the sense of menace that some people might

436
00:21:14,520 --> 00:21:17,679
Speaker 1: feel from a homeless person doesn't necessarily translate into the

437
00:21:17,680 --> 00:21:20,800
Speaker 1: homeless person whipping out a gun and shooting you or

438
00:21:20,840 --> 00:21:21,439
Speaker 1: assaulting you.

439
00:21:21,600 --> 00:21:24,000
Speaker 2: Right, But you know people's fears about their safety and

440
00:21:24,040 --> 00:21:26,119
Speaker 2: about seeing disorder in their community. I want to make

441
00:21:26,160 --> 00:21:29,359
Speaker 2: sure that we take that seriously, and policymakers should. They

442
00:21:29,359 --> 00:21:31,680
Speaker 2: should just be careful about what solutions we can offer

443
00:21:31,800 --> 00:21:34,200
Speaker 2: to try to build healthier communities for everyone.

444
00:21:34,520 --> 00:21:36,879
Speaker 1: Two of the other sort of marquee incidents that have

445
00:21:37,160 --> 00:21:41,120
Speaker 1: I think also make people worried about cities are shoplifting waves.

446
00:21:41,720 --> 00:21:45,159
Speaker 1: As we know from the data, most shoplifting is carried

447
00:21:45,160 --> 00:21:48,639
Speaker 1: out by a small cohort, often acting in conjunction with

448
00:21:48,640 --> 00:21:52,639
Speaker 1: one another. They're repeat offenders. Again, that doesn't take away

449
00:21:52,640 --> 00:21:55,199
Speaker 1: from the fact that the shoplifting is occurring and it

450
00:21:55,240 --> 00:21:59,560
Speaker 1: appears to be unstopped. Storefronts are shattered, or people walk

451
00:21:59,560 --> 00:22:02,160
Speaker 1: into a retail store and just sweep stuff off the shelves.

452
00:22:02,720 --> 00:22:05,879
Speaker 1: Have you thought about shoplifting it's just a category of

453
00:22:06,280 --> 00:22:08,520
Speaker 1: sort of urban blight, or maybe the data there I

454
00:22:08,520 --> 00:22:11,399
Speaker 1: don't actually know. Is the data similar again across the

455
00:22:11,400 --> 00:22:14,600
Speaker 1: board of shoplifting a problem also in suburbs and in

456
00:22:14,680 --> 00:22:15,760
Speaker 1: rural areas as well.

457
00:22:15,960 --> 00:22:18,639
Speaker 2: This is a challenging question too, because there are a

458
00:22:18,720 --> 00:22:22,000
Speaker 2: number of things that can explain trends in shoplifting. Different

459
00:22:22,000 --> 00:22:26,439
Speaker 2: stores have different strategies or protocols for reporting shoplifting to

460
00:22:26,440 --> 00:22:29,520
Speaker 2: the police. For example, a colleague is a former prosecutor

461
00:22:29,520 --> 00:22:32,280
Speaker 2: mentioned this to me. You know, if I go into

462
00:22:32,640 --> 00:22:36,280
Speaker 2: a convenience store every day one week and steal you know,

463
00:22:36,320 --> 00:22:39,320
Speaker 2: ten dollars worth of property, is it the store policy

464
00:22:39,359 --> 00:22:41,680
Speaker 2: to report me the first time and every subsequent time?

465
00:22:41,840 --> 00:22:43,800
Speaker 2: Is it the store policy to call the police only

466
00:22:43,840 --> 00:22:46,680
Speaker 2: after the seventh and then report every incident. These sort

467
00:22:46,680 --> 00:22:50,560
Speaker 2: of differences in how stores and store owners report shoplifting

468
00:22:50,560 --> 00:22:53,480
Speaker 2: to police can sort of confound our understanding of the data,

469
00:22:53,520 --> 00:22:56,639
Speaker 2: and it makes it very hard to understand precise trends

470
00:22:56,680 --> 00:23:00,119
Speaker 2: in shoplifting around the country and individual cities. One thing

471
00:23:00,200 --> 00:23:02,359
Speaker 2: does seem to be clear, though, and most data that

472
00:23:02,359 --> 00:23:04,240
Speaker 2: we have does point to this, and that is that

473
00:23:04,280 --> 00:23:08,040
Speaker 2: shoplifting has increased in some major cities. In New York City,

474
00:23:08,040 --> 00:23:11,000
Speaker 2: the data seems very clear that shoplifting increased sharply in

475
00:23:11,000 --> 00:23:13,959
Speaker 2: twenty twenty two, and that it actually increased year over

476
00:23:14,080 --> 00:23:16,600
Speaker 2: year for I think going back more than a decade.

477
00:23:16,960 --> 00:23:19,200
Speaker 2: So the problem is very real, even if we need

478
00:23:19,240 --> 00:23:21,480
Speaker 2: better data to fully understand what's going on.

479
00:23:21,880 --> 00:23:24,080
Speaker 1: And tell me. As a last category before we move

480
00:23:24,119 --> 00:23:27,200
Speaker 1: on to other and grander things, or carjacking, that has

481
00:23:27,280 --> 00:23:29,760
Speaker 1: also seemed to have been on the rise in urban areas,

482
00:23:29,800 --> 00:23:33,040
Speaker 1: prekly in places like Chicago, in very stark ways. You know,

483
00:23:33,119 --> 00:23:36,080
Speaker 1: drivers are pulled over by another car, or is they're

484
00:23:36,080 --> 00:23:38,240
Speaker 1: getting out of a car or into a car, they're

485
00:23:38,400 --> 00:23:41,000
Speaker 1: essentially held up and their car is stolen. And that

486
00:23:41,200 --> 00:23:44,320
Speaker 1: seems to be a more frequent and visible crime than

487
00:23:44,320 --> 00:23:45,280
Speaker 1: it was a few years ago.

488
00:23:45,720 --> 00:23:48,159
Speaker 2: That's right, and this is actually a tough crime for

489
00:23:48,200 --> 00:23:49,800
Speaker 2: us to study as well. I feel like I'm saying

490
00:23:49,800 --> 00:23:51,800
Speaker 2: that a lot, but you can get an idea of

491
00:23:51,800 --> 00:23:54,760
Speaker 2: how challenging the data can be. Sometimes. The reason is that,

492
00:23:54,840 --> 00:23:56,960
Speaker 2: until very recently, and I know we'll talk about this

493
00:23:57,000 --> 00:23:59,520
Speaker 2: in more detail, car jacking was not broken out as

494
00:23:59,520 --> 00:24:02,000
Speaker 2: a separate fence studied by the FBI. It was sort

495
00:24:02,000 --> 00:24:04,560
Speaker 2: of rolled into robbery. So in many places we don't

496
00:24:04,560 --> 00:24:07,280
Speaker 2: really have an idea of year to year trends in carjacking.

497
00:24:07,359 --> 00:24:10,119
Speaker 2: The data that we do have does show that it

498
00:24:10,200 --> 00:24:13,160
Speaker 2: is increasing or increased in twenty twenty two. We also

499
00:24:13,359 --> 00:24:15,960
Speaker 2: know from city reports. I think you mentioned Chicago. I'm

500
00:24:15,960 --> 00:24:17,640
Speaker 2: not familiar with the data, but I'm sure you're right.

501
00:24:18,000 --> 00:24:21,120
Speaker 2: But we know in Washington, DC carjackings definitely have increased.

502
00:24:21,560 --> 00:24:24,000
Speaker 2: As to why it's a tough question, I go back

503
00:24:24,000 --> 00:24:27,159
Speaker 2: to something I mentioned earlier. There might be some correlation

504
00:24:27,280 --> 00:24:30,440
Speaker 2: between types of motor vehicle theft and other more serious crimes.

505
00:24:30,480 --> 00:24:32,840
Speaker 2: As you steal a car, you carjack a car to

506
00:24:32,880 --> 00:24:34,960
Speaker 2: be used in a more serious efense down the line.

507
00:24:35,119 --> 00:24:37,040
Speaker 2: It could be that those types of defenses go hand

508
00:24:37,040 --> 00:24:37,400
Speaker 2: in hand.

509
00:24:37,760 --> 00:24:40,720
Speaker 1: And is there like a psychology of crime that when

510
00:24:40,760 --> 00:24:44,920
Speaker 1: you see categories of crime as a resident spike, whether

511
00:24:44,960 --> 00:24:48,320
Speaker 1: it's murders or assaults, it leads you to believe that

512
00:24:48,359 --> 00:24:51,480
Speaker 1: every kind of crime that could take place might take

513
00:24:51,520 --> 00:24:54,760
Speaker 1: place and will also increase. And that sort of feeds

514
00:24:54,840 --> 00:24:57,720
Speaker 1: on itself, and people can get into that space without

515
00:24:57,880 --> 00:25:01,320
Speaker 1: necessarily finding easy ways to reverse the fears they're feeling.

516
00:25:01,760 --> 00:25:03,679
Speaker 2: I think that's true. It goes to a sort of

517
00:25:03,840 --> 00:25:06,280
Speaker 2: broader concept. I think people of all types like to

518
00:25:06,280 --> 00:25:09,560
Speaker 2: see accountability and like to see people, you know, face

519
00:25:09,600 --> 00:25:12,440
Speaker 2: consequences for their actions. So if they see people committing

520
00:25:12,480 --> 00:25:15,080
Speaker 2: crimes and facing no consequence for it, it leads them

521
00:25:15,080 --> 00:25:18,280
Speaker 2: to draw broader conclusions about the health of society and

522
00:25:18,320 --> 00:25:21,040
Speaker 2: the moral fabric of their communities. That might be one

523
00:25:21,040 --> 00:25:23,040
Speaker 2: way that we see fears about one type of crime

524
00:25:23,119 --> 00:25:26,000
Speaker 2: bleed over into another. Sort of an interesting thing if

525
00:25:26,040 --> 00:25:28,560
Speaker 2: you ask people what types of crime they're most worried about,

526
00:25:28,920 --> 00:25:31,359
Speaker 2: it really depends on the community. Number One, when we

527
00:25:31,400 --> 00:25:34,200
Speaker 2: saw violence brise in twenty twenty, it was very very uneven.

528
00:25:34,400 --> 00:25:37,160
Speaker 2: The violence spiked more in New York city, for example,

529
00:25:37,520 --> 00:25:40,320
Speaker 2: in neighborhoods that have always been for have always struggled

530
00:25:40,359 --> 00:25:42,800
Speaker 2: with violence, so that increase might not have been as

531
00:25:42,880 --> 00:25:45,520
Speaker 2: visible to other people. But often you see people are

532
00:25:45,560 --> 00:25:48,280
Speaker 2: more worried in some cases about what we in the

533
00:25:48,320 --> 00:25:51,480
Speaker 2: policy field might call relatively lower level offenses, as in

534
00:25:52,000 --> 00:25:54,480
Speaker 2: not the most serious offenses known to law enforcement, but

535
00:25:54,560 --> 00:25:58,000
Speaker 2: crimes like shoplifting, crimes like turnstile jumping, things like that.

536
00:25:58,080 --> 00:26:01,400
Speaker 2: Those sort of crimes can definitely affect people's perception of safety.

537
00:26:02,080 --> 00:26:04,680
Speaker 1: And this is a good moment to point out that

538
00:26:04,720 --> 00:26:08,360
Speaker 1: it is our neighbors and fellow Americans at the lowest

539
00:26:08,920 --> 00:26:13,159
Speaker 1: part of the socioeconomic ladder who experience the brunt of

540
00:26:13,240 --> 00:26:17,280
Speaker 1: violent crime increases, particularly homicides and violent assaults. So within

541
00:26:17,320 --> 00:26:20,680
Speaker 1: those statistics, they don't apply in a blanket and uniform

542
00:26:20,720 --> 00:26:24,520
Speaker 1: way across our society. They really affect usually the most

543
00:26:24,600 --> 00:26:26,679
Speaker 1: vulnerable and disadvantaged people the hardest.

544
00:26:26,840 --> 00:26:30,200
Speaker 2: That's absolutely right. There's a complicated relationship between poverty and crime,

545
00:26:30,280 --> 00:26:32,720
Speaker 2: but if you look at cities around the country, you

546
00:26:32,800 --> 00:26:35,600
Speaker 2: tend to see violence and rising crime in twenty twenty

547
00:26:35,920 --> 00:26:38,920
Speaker 2: clustered in communities that have suffered from other disadvantages. Those

548
00:26:38,920 --> 00:26:41,439
Speaker 2: sort of inequalities have always existed, you know, you go

549
00:26:41,560 --> 00:26:44,000
Speaker 2: back years, you'll see the same sort of prends. They

550
00:26:44,000 --> 00:26:47,120
Speaker 2: simply became more exaggerated or pronounced during the COVID nineteen ten.

551
00:26:47,040 --> 00:26:50,280
Speaker 1: Dem let's take another break, games, then we'll come right back.

552
00:26:55,480 --> 00:26:58,000
Speaker 1: We're back, and I'm having a conversation about crime and

553
00:26:58,040 --> 00:27:02,359
Speaker 1: the COVID nineteen pandemic with Aames Groward. Ames, I think

554
00:27:02,400 --> 00:27:05,480
Speaker 1: we have a data collection and data analysis problem around

555
00:27:05,560 --> 00:27:09,760
Speaker 1: crime statistics that transcends politics and disagreements, and maybe it

556
00:27:09,800 --> 00:27:13,080
Speaker 1: even makes them worse from my perspective, But I was

557
00:27:13,119 --> 00:27:14,480
Speaker 1: wondering what you thought of that.

558
00:27:14,480 --> 00:27:17,119
Speaker 2: That's absolutely right. Someone we've worked with before, a law

559
00:27:17,160 --> 00:27:19,680
Speaker 2: professor John faff I'm going to borrow point that he makes,

560
00:27:19,720 --> 00:27:22,000
Speaker 2: and that is we have up to the minute data

561
00:27:22,040 --> 00:27:25,800
Speaker 2: on the economy, unemployment data, jobs created, et cetera. But

562
00:27:25,840 --> 00:27:29,080
Speaker 2: when it comes to our data on crime, until very recently,

563
00:27:29,200 --> 00:27:31,400
Speaker 2: we had to wait almost a year, nine to ten

564
00:27:31,480 --> 00:27:34,560
Speaker 2: full months between the end of a year and the

565
00:27:34,760 --> 00:27:38,600
Speaker 2: release of national crime data by the Federal Bureau of Investigation.

566
00:27:38,800 --> 00:27:40,720
Speaker 2: So be give you an example. If you wanted to

567
00:27:40,720 --> 00:27:44,199
Speaker 2: see national crime data on twenty nineteen. You had to

568
00:27:44,200 --> 00:27:46,919
Speaker 2: wait until late September twenty twenty for that data to

569
00:27:46,960 --> 00:27:50,960
Speaker 2: come out. That's nowhere close to the real time data

570
00:27:50,960 --> 00:27:54,920
Speaker 2: that policymakers need to actually craft interventions and understand what's

571
00:27:54,960 --> 00:27:59,560
Speaker 2: happening in their community relative to communities around the country now.

572
00:27:59,600 --> 00:28:01,640
Speaker 2: To be sure, local data is much more up to date.

573
00:28:01,680 --> 00:28:04,680
Speaker 2: I could pull up New York City's constant portal right

574
00:28:04,720 --> 00:28:06,600
Speaker 2: now and it would have data that's probably less than

575
00:28:06,640 --> 00:28:08,920
Speaker 2: a week old. Depending on the day of the week,

576
00:28:08,960 --> 00:28:11,679
Speaker 2: it might be, you know, yesterday. But when we don't

577
00:28:11,720 --> 00:28:14,440
Speaker 2: have national data, or when we have delayed national data,

578
00:28:14,480 --> 00:28:16,520
Speaker 2: it also has an effect on the narrative. So to

579
00:28:16,560 --> 00:28:19,639
Speaker 2: give you an example, you know you will hear policymakers

580
00:28:19,680 --> 00:28:23,480
Speaker 2: talk about rising crime in major cities. Over the past month,

581
00:28:23,480 --> 00:28:26,440
Speaker 2: I've heard many policymakers on the federal level talk about

582
00:28:26,480 --> 00:28:28,840
Speaker 2: rising crime in major cities. In every case, they're citing

583
00:28:28,920 --> 00:28:31,400
Speaker 2: data from twenty twenty. You know, that's three years ago.

584
00:28:31,600 --> 00:28:34,240
Speaker 2: Why aren't they using more recent data? Why aren't they

585
00:28:34,280 --> 00:28:36,679
Speaker 2: aware of more recent data? And the answer is not

586
00:28:36,720 --> 00:28:39,680
Speaker 2: necessarily bad faith. The answer might be in part that

587
00:28:39,840 --> 00:28:42,400
Speaker 2: we have such a delay between the year that we're

588
00:28:42,400 --> 00:28:45,000
Speaker 2: interested in studying and when crime data actually come out

589
00:28:45,240 --> 00:28:47,080
Speaker 2: that it sort of takes a while for the public

590
00:28:47,120 --> 00:28:50,360
Speaker 2: to understand and adjust to what those data show. There's

591
00:28:50,360 --> 00:28:54,000
Speaker 2: sort of a lag time between our reality of national

592
00:28:54,040 --> 00:28:57,080
Speaker 2: crime trends and our perception of what those trends actually

593
00:28:57,080 --> 00:28:59,560
Speaker 2: look like. And it's actually gotten worse in the past

594
00:28:59,560 --> 00:29:02,239
Speaker 2: couple of years due to transition of the way the

595
00:29:02,280 --> 00:29:04,760
Speaker 2: FBI calculates crime data, which I could talk to you

596
00:29:04,800 --> 00:29:05,960
Speaker 2: about as well well.

597
00:29:06,000 --> 00:29:09,600
Speaker 1: Since you mentioned the FBI, My Bloomberg Opinion colleague Justin Fox,

598
00:29:09,920 --> 00:29:12,560
Speaker 1: who loves to crunch and examine numbers around all sorts

599
00:29:12,560 --> 00:29:16,640
Speaker 1: of things, has been particularly frustrated by the FBI's methodology.

600
00:29:17,200 --> 00:29:20,120
Speaker 1: He recently wrote this about how the FBI colates data

601
00:29:20,160 --> 00:29:23,760
Speaker 1: around four major crimes to analyze violent crime rates, and

602
00:29:23,800 --> 00:29:27,200
Speaker 1: I'm quoting Justin here. To calculate violent crime rates, the

603
00:29:27,280 --> 00:29:30,840
Speaker 1: FBI simply adds together the incidents of the four violent crimes,

604
00:29:31,240 --> 00:29:33,560
Speaker 1: meaning the rate ends up being determined by the most

605
00:29:33,560 --> 00:29:39,000
Speaker 1: common ones, robbery and especially aggravated assault. That's not great.

606
00:29:39,440 --> 00:29:41,560
Speaker 1: What do you think of Justin's thoughts on that?

607
00:29:41,800 --> 00:29:44,280
Speaker 2: Your colleague is absolutely right to make the problem even

608
00:29:44,320 --> 00:29:47,120
Speaker 2: more stark when people talk about the overall crime rate,

609
00:29:47,280 --> 00:29:49,800
Speaker 2: what they tend to be referring to is the incidences

610
00:29:49,800 --> 00:29:52,800
Speaker 2: of the four violent offenses that Justin referred to, plus

611
00:29:52,880 --> 00:29:55,600
Speaker 2: the three property crime offenses historically tracked by the FBI,

612
00:29:55,760 --> 00:29:59,440
Speaker 2: so burglary, larceny, motor vehicle theft. But when you add

613
00:29:59,440 --> 00:30:02,640
Speaker 2: all those together, larceny is far and away the most

614
00:30:02,680 --> 00:30:06,240
Speaker 2: common offense, overwhelming all of them. So when people talk

615
00:30:06,280 --> 00:30:08,400
Speaker 2: about the quote crime rate, there's often a risk that

616
00:30:08,440 --> 00:30:10,920
Speaker 2: you're really talking about the larceny rate with some other

617
00:30:11,000 --> 00:30:13,720
Speaker 2: crimes thrown in there. It's a very sort of blunt

618
00:30:13,800 --> 00:30:15,880
Speaker 2: way of looking at crime trends.

619
00:30:15,640 --> 00:30:18,040
Speaker 1: And skewed statistically skewed.

620
00:30:17,920 --> 00:30:20,800
Speaker 2: Yes, especially because we actually saw this phenomenon in the

621
00:30:20,800 --> 00:30:25,760
Speaker 2: COVID nineteen pandemic. Larcenies have fallen for starting in nineteen ninety,

622
00:30:25,760 --> 00:30:28,520
Speaker 2: they fill every year until I think twenty twenty two.

623
00:30:28,760 --> 00:30:31,400
Speaker 2: So you could look at quote overall crime data in

624
00:30:31,440 --> 00:30:34,560
Speaker 2: twenty twenty and see a decline in crime rates twenty

625
00:30:34,640 --> 00:30:37,560
Speaker 2: nineteen to twenty twenty. So you could hear people say, well,

626
00:30:37,600 --> 00:30:40,200
Speaker 2: the murder rate is up and respond with well crime

627
00:30:40,280 --> 00:30:44,560
Speaker 2: is down, and you're both right. But if you're discounting

628
00:30:44,560 --> 00:30:47,480
Speaker 2: a thirty percent spike in murder. By looking at larceny data,

629
00:30:48,160 --> 00:30:48,760
Speaker 2: you're just not.

630
00:30:49,280 --> 00:30:50,560
Speaker 1: Doing apples and oranges.

631
00:30:50,680 --> 00:30:53,440
Speaker 2: Yes, as oranges. You're not doing the real analysis the

632
00:30:53,440 --> 00:30:55,200
Speaker 2: public needs. That's part of the challenge of it.

633
00:30:55,800 --> 00:30:57,880
Speaker 1: So how do we get better data so we all

634
00:30:57,920 --> 00:30:59,960
Speaker 1: have better confidence in what we're talking about?

635
00:31:00,280 --> 00:31:01,920
Speaker 2: So here I actually have some good news for you,

636
00:31:01,960 --> 00:31:03,960
Speaker 2: which I think we're all eager for. At this time,

637
00:31:04,320 --> 00:31:06,640
Speaker 2: the FBI is in the process of a transition to

638
00:31:06,800 --> 00:31:10,880
Speaker 2: something called the National Incident Based Reporting System. So when

639
00:31:10,960 --> 00:31:14,840
Speaker 2: that transition is done, we will have two things. Number One,

640
00:31:15,040 --> 00:31:18,480
Speaker 2: we'll have a system that tracks a much wider array

641
00:31:18,480 --> 00:31:22,240
Speaker 2: of offenses in much greater detail. So we won't just have

642
00:31:22,360 --> 00:31:26,520
Speaker 2: data on larsenies. We'll have data on larceny dash, shoplifting,

643
00:31:26,920 --> 00:31:30,320
Speaker 2: larceny dash, by fraud, larceny dash, you know, every variety

644
00:31:30,360 --> 00:31:33,000
Speaker 2: of every variety of crime. That's going to allow for

645
00:31:33,920 --> 00:31:38,120
Speaker 2: much richer, more thoughtful analysis of crime trends year over year.

646
00:31:38,240 --> 00:31:40,440
Speaker 2: And you can actually see that in some work already,

647
00:31:40,520 --> 00:31:43,040
Speaker 2: because many cities have already adopted this new system. You

648
00:31:43,120 --> 00:31:44,880
Speaker 2: can see that in some work by the Council and

649
00:31:44,960 --> 00:31:48,720
Speaker 2: Criminal Justice A great nonprofit organization. They put together an

650
00:31:48,760 --> 00:31:52,440
Speaker 2: analysis of shoplifting trends across the country using NYBERS data,

651
00:31:52,480 --> 00:31:54,600
Speaker 2: which is how people in my field refer to the

652
00:31:54,680 --> 00:31:57,640
Speaker 2: National Incident based Crime Reporting System, and they had a

653
00:31:57,680 --> 00:32:01,000
Speaker 2: much richer look at what's actually happening shoplifting around the country.

654
00:32:01,000 --> 00:32:04,040
Speaker 2: It was really interesting. Their finding was, as we discussed,

655
00:32:04,040 --> 00:32:05,720
Speaker 2: that it's a real problem in New York. But so

656
00:32:05,800 --> 00:32:09,080
Speaker 2: number one, we'll have a richer analysis of what the

657
00:32:09,160 --> 00:32:12,000
Speaker 2: data actually look like. Number two will actually have more

658
00:32:12,000 --> 00:32:15,000
Speaker 2: timely data. The FBI is in the process of rolling

659
00:32:15,000 --> 00:32:18,000
Speaker 2: out quarterly reports, so rather than have to wait for

660
00:32:18,320 --> 00:32:21,480
Speaker 2: September October every year for your dose of national crime data,

661
00:32:21,840 --> 00:32:24,960
Speaker 2: every quarter you should get a little more data on

662
00:32:25,000 --> 00:32:27,720
Speaker 2: the national picture. That data will still have a lag time,

663
00:32:27,800 --> 00:32:30,120
Speaker 2: it will still be fairly stale by the time you

664
00:32:30,160 --> 00:32:31,880
Speaker 2: read it, but you won't have to wait a year.

665
00:32:32,040 --> 00:32:34,080
Speaker 2: And I think that's the real improvement and should help

666
00:32:34,160 --> 00:32:37,440
Speaker 2: policymakers come to better and more thoughtful and more timely

667
00:32:37,480 --> 00:32:41,000
Speaker 2: conclusions about crime data. I can't give you unallied good

668
00:32:41,040 --> 00:32:44,760
Speaker 2: news here though, because although this new system is going

669
00:32:44,760 --> 00:32:48,840
Speaker 2: to be fantastic when it's fully implemented, implementation is going

670
00:32:49,000 --> 00:32:50,680
Speaker 2: better than it was a year ago, but it's not

671
00:32:50,760 --> 00:32:54,600
Speaker 2: going great. That's because to switch over to the system,

672
00:32:54,920 --> 00:32:58,040
Speaker 2: police departments, that is, the agencies that report crime data

673
00:32:58,200 --> 00:33:01,080
Speaker 2: up through their state to the federal government, have to

674
00:33:01,320 --> 00:33:04,360
Speaker 2: rework their computer systems and their way of tracking crime data.

675
00:33:04,480 --> 00:33:07,239
Speaker 2: That takes time, that takes money, it's difficult to do,

676
00:33:07,440 --> 00:33:10,280
Speaker 2: take staff, and many departments, through no fault of their own,

677
00:33:10,400 --> 00:33:12,000
Speaker 2: don't have the ability to do that and.

678
00:33:11,960 --> 00:33:14,320
Speaker 1: Happen, including some pretty big ones, some.

679
00:33:14,400 --> 00:33:17,120
Speaker 2: Very big ones in fact, so Florida and Pennsylvania remain

680
00:33:17,200 --> 00:33:20,600
Speaker 2: big blind spots and the incident based reporting system, as

681
00:33:20,640 --> 00:33:21,520
Speaker 2: does New York City.

682
00:33:21,760 --> 00:33:25,560
Speaker 1: Right, and you've mentioned now two different states in a city.

683
00:33:25,920 --> 00:33:29,800
Speaker 1: How reliable is data comparing one state to another or

684
00:33:29,840 --> 00:33:32,640
Speaker 1: one city to another when when you see these sort

685
00:33:32,680 --> 00:33:35,600
Speaker 1: of comparisons about what's safe and what isn't, what's a

686
00:33:35,680 --> 00:33:37,120
Speaker 1: crime written place and what isn't.

687
00:33:37,520 --> 00:33:39,760
Speaker 2: Yeah, let me put it this way. You know, the

688
00:33:39,840 --> 00:33:42,479
Speaker 2: FBI's role is they seek to standardize the data to

689
00:33:42,520 --> 00:33:45,280
Speaker 2: the extent possible between cities so that you can make

690
00:33:45,400 --> 00:33:48,560
Speaker 2: these comparisons insofar as they're possible to be made at all.

691
00:33:49,000 --> 00:33:51,760
Speaker 2: But that can definitely be a little challenging. Even with

692
00:33:51,920 --> 00:33:55,920
Speaker 2: that standardization. The one data point that we sort of

693
00:33:56,120 --> 00:33:58,920
Speaker 2: know is accurate and reflects, you know, what is actually

694
00:33:58,920 --> 00:34:01,880
Speaker 2: happening on the ground is murder. Because of the tragic

695
00:34:01,960 --> 00:34:04,320
Speaker 2: nature of defense. At the end of it, someone has

696
00:34:04,360 --> 00:34:06,560
Speaker 2: lost their life, and that tends to be reported to

697
00:34:07,000 --> 00:34:10,680
Speaker 2: many different authorities. So murder counts, murder rates tend to

698
00:34:10,680 --> 00:34:13,920
Speaker 2: reflect the actual number of those offenses committed in a community.

699
00:34:14,040 --> 00:34:16,520
Speaker 2: But the same might not be true of larceny. The

700
00:34:16,560 --> 00:34:18,960
Speaker 2: same might not be true of burglary in all cases,

701
00:34:19,000 --> 00:34:20,279
Speaker 2: you know I'm thinking of You know, I had my

702
00:34:20,360 --> 00:34:22,600
Speaker 2: bike stolen in Brooklyn, and I certainly never told the

703
00:34:22,640 --> 00:34:26,240
Speaker 2: police that bike was gone. So those sort of challenges

704
00:34:26,280 --> 00:34:28,839
Speaker 2: and reporting rate also might have an issue a way

705
00:34:28,880 --> 00:34:33,279
Speaker 2: of confounding comparisons between jurisdictions, It's not impossible. Those comparisons

706
00:34:33,320 --> 00:34:37,240
Speaker 2: are certainly meaningful, but they might not fully reflect facts

707
00:34:37,280 --> 00:34:39,160
Speaker 2: on the ground. They might come close to it. More.

708
00:34:39,760 --> 00:34:42,480
Speaker 1: You mentioned murder again, and we started talking about murder

709
00:34:42,520 --> 00:34:45,560
Speaker 1: in this happy episode we're having, and I wanted to

710
00:34:45,600 --> 00:34:48,680
Speaker 1: ask you, given this spike in the homicide rate in

711
00:34:48,760 --> 00:34:52,000
Speaker 1: twenty twenty, and it's cooled down subsequently, but it's still

712
00:34:52,080 --> 00:34:55,880
Speaker 1: higher than it had been. What aren't we doing about

713
00:34:56,200 --> 00:35:00,560
Speaker 1: homicide and violent crimes that could address that more directly?

714
00:35:01,440 --> 00:35:04,480
Speaker 2: That is the question. Two metrics that I've been thinking about,

715
00:35:04,520 --> 00:35:05,719
Speaker 2: and I'm going to refer to the work of some

716
00:35:05,719 --> 00:35:09,320
Speaker 2: other scholars in the process, are clearance rates and response times.

717
00:35:09,440 --> 00:35:12,279
Speaker 2: So the clearance rate is you can think of it

718
00:35:12,440 --> 00:35:15,360
Speaker 2: very roughly as the rate at which police solve an offense.

719
00:35:15,680 --> 00:35:18,560
Speaker 2: So it's the ratio of crimes in which an arrest

720
00:35:18,640 --> 00:35:20,799
Speaker 2: has been made or in which an arrest is impossible

721
00:35:21,200 --> 00:35:23,520
Speaker 2: to the number of crimes that are actually reported to them.

722
00:35:23,520 --> 00:35:25,480
Speaker 2: So if you have four murders in a given year,

723
00:35:25,520 --> 00:35:26,920
Speaker 2: and you make an arrest in three of them, your

724
00:35:26,920 --> 00:35:30,520
Speaker 2: clearance rate is seventy five percent. Unfortunately, seventy five percent

725
00:35:30,640 --> 00:35:33,279
Speaker 2: would be an outlier clearance rate in many cities in

726
00:35:33,280 --> 00:35:36,120
Speaker 2: this country. We've seen clearance rates below fifty percent in

727
00:35:36,160 --> 00:35:38,520
Speaker 2: some major cities, and in Chicago one year I think

728
00:35:38,520 --> 00:35:41,080
Speaker 2: it was below thirty percent. That suggests that, you know,

729
00:35:41,120 --> 00:35:43,520
Speaker 2: quite literally, people can get away with murder, and that's

730
00:35:43,680 --> 00:35:46,360
Speaker 2: very dispiriting, that's horrifying. I think we need to figure

731
00:35:46,360 --> 00:35:48,680
Speaker 2: out exactly what's happening and see if we can figure

732
00:35:48,680 --> 00:35:51,319
Speaker 2: out a way to increase clearance rates so people who

733
00:35:51,320 --> 00:35:55,360
Speaker 2: commit these most serious of offenses are actually brought to justice.

734
00:35:55,760 --> 00:35:58,920
Speaker 2: That's one factor. Anna Harvey, a researcher who I mentioned before,

735
00:35:59,000 --> 00:36:02,279
Speaker 2: is also some thought into studying police response times, which

736
00:36:02,320 --> 00:36:05,040
Speaker 2: in some jurisdictions can be quite high, and that also

737
00:36:05,040 --> 00:36:06,920
Speaker 2: can lead you a feeling of impunity. You know, if

738
00:36:06,920 --> 00:36:08,799
Speaker 2: by the time police show up it's an hour later,

739
00:36:09,080 --> 00:36:11,080
Speaker 2: it's much more difficult to solve that crime. So these

740
00:36:11,080 --> 00:36:13,560
Speaker 2: are two statistics that feed into each other, but I

741
00:36:13,600 --> 00:36:16,720
Speaker 2: don't want to talk exclusively about those two metrics. Another

742
00:36:16,760 --> 00:36:19,680
Speaker 2: promising intervention we've seen is something called the community violence

743
00:36:19,680 --> 00:36:23,600
Speaker 2: intervention programs. These are models where people from the community

744
00:36:23,800 --> 00:36:27,640
Speaker 2: build nonprofit organizations and employ people from the community to

745
00:36:27,719 --> 00:36:30,880
Speaker 2: help stop violence before it starts. So a model that

746
00:36:30,880 --> 00:36:33,279
Speaker 2: I've seen in Newark, New Jersey, which is quite near

747
00:36:33,320 --> 00:36:35,719
Speaker 2: to me, you will see people who have experienced in

748
00:36:35,719 --> 00:36:39,680
Speaker 2: the criminal justice system spend time in their communities, hear

749
00:36:39,719 --> 00:36:43,280
Speaker 2: what's happening here about nascent fights that might be brewing,

750
00:36:43,360 --> 00:36:45,839
Speaker 2: hear about conflicts that might be brewing, and then find

751
00:36:45,840 --> 00:36:48,920
Speaker 2: the people affected by those conflicts and try to put

752
00:36:48,920 --> 00:36:50,480
Speaker 2: a stop to it. Try to say, you know, I

753
00:36:50,560 --> 00:36:52,440
Speaker 2: understand what you're going through, but violence is not the

754
00:36:52,480 --> 00:36:55,920
Speaker 2: solution here. These sort of programs, when they work, they

755
00:36:55,920 --> 00:36:58,120
Speaker 2: are very effective. New York is one of very few

756
00:36:58,160 --> 00:37:00,920
Speaker 2: cities that didn't see homicide rates in create appreciably in

757
00:37:00,920 --> 00:37:03,879
Speaker 2: twenty twenty, for example. But they're very hard to get right,

758
00:37:03,960 --> 00:37:07,719
Speaker 2: and they typically require more money and more professionalization and

759
00:37:07,760 --> 00:37:10,360
Speaker 2: more staff than they're ever given. So this is a

760
00:37:10,400 --> 00:37:13,040
Speaker 2: promising option that I'm glad to say. Here's another piece

761
00:37:13,040 --> 00:37:15,600
Speaker 2: of good news. The Biden administration has actually taking a

762
00:37:15,640 --> 00:37:18,720
Speaker 2: serious interest and promoting and investing in ames.

763
00:37:18,760 --> 00:37:21,200
Speaker 1: I always like to ask guess what they've learned that

764
00:37:21,360 --> 00:37:23,399
Speaker 1: is an aha or a new thing to them about

765
00:37:23,440 --> 00:37:26,920
Speaker 1: the subject we're discussing. In your longtime observer of crime trends,

766
00:37:27,880 --> 00:37:31,680
Speaker 1: what did you learn watching the way that crime statistics

767
00:37:31,680 --> 00:37:33,960
Speaker 1: took shape in the early parts of the pandemic and

768
00:37:34,040 --> 00:37:36,600
Speaker 1: where they are now and the kind of public debate

769
00:37:36,640 --> 00:37:38,280
Speaker 1: we had around all of that.

770
00:37:38,280 --> 00:37:40,560
Speaker 2: That's a great question to think through. One thing I've

771
00:37:40,640 --> 00:37:44,920
Speaker 2: learned is statistics don't always reflect people's experience. We actually

772
00:37:44,960 --> 00:37:46,719
Speaker 2: see this in the economy as well. To bring it

773
00:37:46,840 --> 00:37:49,319
Speaker 2: near to a topic that always care about. The data

774
00:37:49,360 --> 00:37:51,680
Speaker 2: may show one thing, but people may feel another thing.

775
00:37:51,800 --> 00:37:54,799
Speaker 2: So there's a real gap often between people's perceptions of

776
00:37:54,840 --> 00:37:57,920
Speaker 2: safety and the actual data. And the reasons for that

777
00:37:57,960 --> 00:38:00,760
Speaker 2: may be really complicated. They may be because we've discussed

778
00:38:00,800 --> 00:38:04,239
Speaker 2: the data don't quantify the offenses that people are actually

779
00:38:04,280 --> 00:38:06,879
Speaker 2: worried about. But whatever the reason for that gap, we've

780
00:38:06,920 --> 00:38:09,239
Speaker 2: just got to take people's perceptions seriously. And it is

781
00:38:09,280 --> 00:38:12,239
Speaker 2: no answer to someone who's worried about their safety to say, well,

782
00:38:12,239 --> 00:38:14,920
Speaker 2: technically crime is down. That's non answer. That's not an

783
00:38:14,920 --> 00:38:17,800
Speaker 2: answer that helps bring us to a safer and more

784
00:38:17,840 --> 00:38:20,040
Speaker 2: just place. Games.

785
00:38:20,080 --> 00:38:22,360
Speaker 1: We're out of time. Thank you for coming on today.

786
00:38:22,640 --> 00:38:23,000
Speaker 2: Thank you.

787
00:38:24,160 --> 00:38:27,240
Speaker 1: Ames Groward is an expert on crime statistics and Senior

788
00:38:27,280 --> 00:38:29,960
Speaker 1: counsel at the Brennan Center for Justice at the NYU

789
00:38:30,160 --> 00:38:33,960
Speaker 1: Law School. Here at Crash Course, we believe that collisions

790
00:38:34,000 --> 00:38:39,120
Speaker 1: can be messy, impressive, challenging, surprising, and always instructive. In

791
00:38:39,160 --> 00:38:42,040
Speaker 1: today's Crash Course, I learned that the perception of crime

792
00:38:42,440 --> 00:38:45,840
Speaker 1: can almost be as influential for people as the reality

793
00:38:45,840 --> 00:38:48,960
Speaker 1: of crime itself and has to be taken into consideration

794
00:38:49,239 --> 00:38:53,000
Speaker 1: when we're coming up with policies to address crime. What

795
00:38:53,080 --> 00:38:55,319
Speaker 1: did you learn? We'd love to hear from you. You

796
00:38:55,320 --> 00:38:58,400
Speaker 1: can tweak at the Bloomberg Opinion, handle at Opinion or

797
00:38:58,480 --> 00:39:02,120
Speaker 1: me at Tim O'Brien using the hashtag Bloomberg Crash Course.

798
00:39:02,640 --> 00:39:05,480
Speaker 1: You can also subscribe to our show wherever you're listening

799
00:39:05,560 --> 00:39:08,160
Speaker 1: right now and leave us a review. It helps more

800
00:39:08,160 --> 00:39:11,200
Speaker 1: people find the show. This episode was produced by the

801
00:39:11,239 --> 00:39:15,680
Speaker 1: Indispensable and always Lawful Anna Maazarakis and me. Our supervising

802
00:39:15,719 --> 00:39:19,400
Speaker 1: producer is Magnus Hendrickson, and we had editing help from Sagebauman,

803
00:39:19,560 --> 00:39:24,080
Speaker 1: Jeff Grocott, Mike Nize and Christine Vanden Bilart. Blake Maples

804
00:39:24,080 --> 00:39:27,000
Speaker 1: does our sound engineering, and our original theme song was

805
00:39:27,040 --> 00:39:30,759
Speaker 1: composed by Luis Gara. I'm Tim O'Brien. We'll be back

806
00:39:30,840 --> 00:39:32,560
Speaker 1: next week with another Crash Course