DNA face to facial recognition in attempt to find suspect

In an effort to find a suspect in a 1990 murder, there was a police request in 2017 to use a 3-D rendering of a face based on DNA. For Wired, Dhruv Mehrotra reports:

The detective’s request to run a DNA-generated estimation of a suspect’s face through facial recognition tech has not previously been reported. Found in a trove of hacked police records published by the transparency collective Distributed Denial of Secrets, it appears to be the first known instance of a police department attempting to use facial recognition on a face algorithmically generated from crime-scene DNA.

This seems like a natural progression, but it should be easy to see how the pairing of the tech could cause all sorts of issues when someone’s face is poorly constructed and then misclassified with facial recognition. What’s the confidence interval equivalent for a face?

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Unreliable FBI crime data

The Marshall Project and Axios report that the FBI changed their reporting system last year, and 40 percent of law enforcement agencies didn’t submit any data:

In 2021, the FBI retired its nearly century-old national crime data collection program, the Summary Reporting System used by the Uniform Crime Reporting (UCR) program. The agency switched to a new system, the National Incident-Based Reporting System (NIBRS), which gathers more specific information on each incident. Even though the FBI announced the transition years ago and the federal government spent hundreds of millions of dollars to help local police make the switch, about 7,000 of the nation’s 18,000 law enforcement agencies did not successfully send crime data to the voluntary program last year.

I am sure policymakers will definitely be very responsible and cite data appropriately and not cherrypick from incomplete data to push an agenda.

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Inadequate hate crime statistics

For ProPublica, Ken Schwencke reports on a poor data system that relies on local law enforcement to voluntarily enter data:

Local law enforcement agencies reported a total of 6,121 hate crimes in 2016 to the FBI, but estimates from the National Crime Victimization Survey, conducted by the federal government, pin the number of potential hate crimes at almost 250,000 a year — one indication of the inadequacy of the FBI’s data.

“The current statistics are a complete and utter joke,” said Roy Austin, former deputy assistant attorney general in the Department of Justice’s civil rights division. Austin also worked at the White House on data and civil rights and helped develop an open data plan for police data.

Garbage in, garbage out.

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AI-generated voice used to fake phone call and steal money

Reporting for The Washington Post, Drew Harwell describes the case of the fake voice used for bad things:

Thieves used voice-mimicking software to imitate a company executive’s speech and dupe his subordinate into sending hundreds of thousands of dollars to a secret account, the company’s insurer said, in a remarkable case that some researchers are calling one of the world’s first publicly reported artificial-intelligence heists.

The managing director of a British energy company, believing his boss was on the phone, followed orders one Friday afternoon in March to wire more than $240,000 to an account in Hungary, said representatives from the French insurance giant Euler Hermes, which declined to name the company.

Publicly available software that makes it straightforward to impersonate others digitally: what could go wrong?

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AI-generated voice used to fake phone call and steal money

Reporting for The Washington Post, Drew Harwell describes the case of the fake voice used for bad things:

Thieves used voice-mimicking software to imitate a company executive’s speech and dupe his subordinate into sending hundreds of thousands of dollars to a secret account, the company’s insurer said, in a remarkable case that some researchers are calling one of the world’s first publicly reported artificial-intelligence heists.

The managing director of a British energy company, believing his boss was on the phone, followed orders one Friday afternoon in March to wire more than $240,000 to an account in Hungary, said representatives from the French insurance giant Euler Hermes, which declined to name the company.

Publicly available software that makes it straightforward to impersonate others digitally: what could go wrong?

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The Crime Machine

I’m behind on my podcast listening (well, behind in everything tbh), but Reply All covered the flaws of CompStat, a data system originally employed by the NYPD to track crime and hold officers accountable:

But some of these chiefs started to figure out, wait a minute, the person who’s in charge of actually keeping track of the crime in my neighborhood is me. And so if they couldn’t make crime go down, they just would stop reporting crime. And they found all these different ways to do it. You could refuse to take crime reports from victims, you could write down different things than what had actually happened. You could literally just throw paperwork away. And so that guy would survive that CompStat meeting, he’d get his promotion, and then when the next guy showed up, the number that he had to beat was the number that a cheater had set. And so he had to cheat a little bit more.

I sat in on a CompStat meeting years ago in Los Angeles. I went into it excited to see the data system that helped decrease crime, but I left skeptical after hearing the discussions over such small absolute numbers, which in turn made for a lot of fluctuations percentage-wise. Maybe things are different now a decade later, but I’m not surprised that some intentionally and unintentionally gamed the system.

See also: FiveThirtyEight’s CompStat story from 2015.

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Flawed hate crime data collection

Data can provide you with important information, but when the collection process is flawed, there’s not much you can do. Ken Schwencke, reporting for ProPublica, researched the tiered system that the FBI relies on to gather hate crime data for the United States:

Under a federal law passed in 1990, the FBI is required to track and tabulate crimes in which there was “manifest evidence of prejudice” against a host of protected groups, including homosexuals, regardless of differences in how state laws define who’s protected. The FBI, in turn, relies on local law enforcement agencies to collect and submit this data, but can’t compel them to do so.

Right there. There are no standards or set definitions of a hate crime. Some local agencies participate. Many don’t. Those who participate might only collect partial information.

This data that dates back to 1990 is still in the anecdote phase.

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Police surveillance in a digital world

tracking

Glenn Smith and Andrew Knapp for the Post and Courier investigate the current police practice of keeping digital record of people’s activities.

Law enforcement agencies have for decades used what’s known as field interview or contact cards to document everything from sketchy activity to random encounters with people on the street. But the digital age has greatly expanded the power and reach of this tool, allowing police to store indefinitely reams of data on those who draw their interest — long after any potential link to a crime has evaporated.

As you might expect, there are certainly advantages for law enforcement to have access to such a database when they try to solve crimes. But it gets weird when data is incorrectly recorded or perhaps recorded too much.

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The different trends in American crime

Crime trends in the US

Crime is up? Crime is down? It depends on who you ask and where. The Marshall Project analyzed violent crime trends over the past 40 years to show how things are moving across the country.

In the process, we were struck by the wide variation from community to community. To paraphrase an aphorism about politics, all crime is local. Each city has its own trends that depend on the characteristics of the city itself, the time frame, and the type of crime. In fact, the trends vary from neighborhood to neighborhood within cities; a recent study posited that 5 percent of city blocks account for 50 percent of the crime. That is why most Americans believe crime is worse, while significantly fewer believe it is worse where they live.

They eventually narrowed down trends to four main categories, across 68 cities.

Don’t see what you’re looking for. The data is available for download.

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Bias built in to crime prediction

Predictive policing seems to be playing a bigger role in court decisions these days. People charged with crimes can be given a risk score based on priors and their background, which represents a fuzzy likelihood that they commit a crime again. ProPublica investigates the reliability of these scores, using data from Broward County, Flordia, between 2013 and 2014

The score proved remarkably unreliable in forecasting violent crime: Only 20 percent of the people predicted to commit violent crimes actually went on to do so.

When a full range of crimes were taken into account — including misdemeanors such as driving with an expired license — the algorithm was somewhat more accurate than a coin flip. Of those deemed likely to re-offend, 61 percent were arrested for any subsequent crimes within two years.

So tons of uncertainty.

Then, when you compare scores for blacks and whites, taking into account the types of crimes committed, there appeared to be a bias towards scoring blacks at higher risk. Troubling. I suspect this is related to the mentioned factors like employment and education.

But still, with so much uncertainty case-by-case, should these numbers — that I can only imagine appearing nearly concrete in the court room — even be part of the equation of an individual’s future?

More on the ProPublica analysis here.

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