Malcolm Gladwell

Eddie and Finnegan talked for almost an hour. Finnegan was promoting his new podcast, the magnificently titled Finnegan's Take, reminiscences from his years on the force. And at some point, Finnegan starts to speculate about why his path to promotion was so often blocked by his boss.

Eddie and Finnegan talked for almost an hour. Finnegan was promoting his new podcast, the magnificently titled Finnegan's Take, reminiscences from his years on the force. And at some point, Finnegan starts to speculate about why his path to promotion was so often blocked by his boss.

Wait, Chicago police officers are ranked by their complaints the way pop music singles are ranked on the Billboard charts? Yes, they are. The rankings are compiled by an organization called the Citizens Police Data Project. Their website consists of a searchable online database of 250,000 complaints lodged against members of the CPD from 1988 to 2018.

Wait, Chicago police officers are ranked by their complaints the way pop music singles are ranked on the Billboard charts? Yes, they are. The rankings are compiled by an organization called the Citizens Police Data Project. Their website consists of a searchable online database of 250,000 complaints lodged against members of the CPD from 1988 to 2018.

And what you learn from looking at the list is that the distribution of problematic police officers within the Chicago Police Department is not uniform. Those quarter of a million complaints are not evenly sprinkled across all the many thousands of officers in the database. A few cops have a lot of complaints, but the majority have almost none.

And what you learn from looking at the list is that the distribution of problematic police officers within the Chicago Police Department is not uniform. Those quarter of a million complaints are not evenly sprinkled across all the many thousands of officers in the database. A few cops have a lot of complaints, but the majority have almost none.

If you made a graph out of the whole Chicago Police Department, there would be a long low line stretching as far as the eye could see, hovering just above the horizontal axis until the very end, when the line would suddenly jump. As the statisticians would say, the distribution of complaints has a fat tail. And who stands at the very fattest part of the tale?

If you made a graph out of the whole Chicago Police Department, there would be a long low line stretching as far as the eye could see, hovering just above the horizontal axis until the very end, when the line would suddenly jump. As the statisticians would say, the distribution of complaints has a fat tail. And who stands at the very fattest part of the tale?

Jerry Finnegan, recipient of a grand total of 175 complaints.

Jerry Finnegan, recipient of a grand total of 175 complaints.

Finnegan ended up doing 10 years in prison for tax evasion and planning a murder-for-hire plot against a fellow officer. He also cost the city over a million dollars in legal settlements, which, given his position as the Lex Luthor of rogue Chicago police officers, shouldn't be that much of a surprise. Problems with fat tails turn out to be everywhere. Here's another one.

Finnegan ended up doing 10 years in prison for tax evasion and planning a murder-for-hire plot against a fellow officer. He also cost the city over a million dollars in legal settlements, which, given his position as the Lex Luthor of rogue Chicago police officers, shouldn't be that much of a surprise. Problems with fat tails turn out to be everywhere. Here's another one.

New York City has 2,500 automated cameras, which in 2023 handed out 7 million speeding tickets. But are those tickets evenly distributed across all the city's drivers? No. There's a fat tail. There were 186 drivers who got more than 100 tickets in one year. That's an average of one ticket every three to four days. Superspeeders. Most of us get a ticket and slow down next time.

New York City has 2,500 automated cameras, which in 2023 handed out 7 million speeding tickets. But are those tickets evenly distributed across all the city's drivers? No. There's a fat tail. There were 186 drivers who got more than 100 tickets in one year. That's an average of one ticket every three to four days. Superspeeders. Most of us get a ticket and slow down next time.

We take the hint, not the superspeeders. On average, that group of 186 each had $11,000 in unpaid traffic fines. In my last book, Revenge of the Tipping Point, I had a whole chapter on COVID. You know what COVID was? Fat tail. Most of us, when we were infected with COVID, emitted such a small amount of virus that we didn't pose that much of a danger to others.

We take the hint, not the superspeeders. On average, that group of 186 each had $11,000 in unpaid traffic fines. In my last book, Revenge of the Tipping Point, I had a whole chapter on COVID. You know what COVID was? Fat tail. Most of us, when we were infected with COVID, emitted such a small amount of virus that we didn't pose that much of a danger to others.

But there are a very small number of people who, for reasons we don't entirely understand, when they have COVID, produce a massive amount of virus. Superspreaders. Those are the ones who cause outbreaks. I could go on.

But there are a very small number of people who, for reasons we don't entirely understand, when they have COVID, produce a massive amount of virus. Superspreaders. Those are the ones who cause outbreaks. I could go on.

The lesson of New York's super speeders and COVID's super spreaders is that before you figure out how to solve a problem, you have to ask yourself, am I dealing with a skinny tail distribution where everyone plays a roughly equal part in contributing to the issue? Or do I have a fat tail distribution where my problem is a very small number of very rotten apples?

The lesson of New York's super speeders and COVID's super spreaders is that before you figure out how to solve a problem, you have to ask yourself, am I dealing with a skinny tail distribution where everyone plays a roughly equal part in contributing to the issue? Or do I have a fat tail distribution where my problem is a very small number of very rotten apples?