Lee and Tisch discuss stop-and-frisk data and racial equity tracking

And then the deputy speaker had to leave, but she wanted me to ask this question.

Another goal of going back to the, I think, the racial equity plan.

Another goal of NYPD's in the preliminary racial equity plan is to quantify, track, and analyze racial disparities in stops, risks, and searches in an effort to reduce those disparities.

This is listed as a medium-term goal to be completed by 2028.

Do you have any data on stop and frisk from data collected from the How Many Stops Act that the council passed?

So with regard to the How Many Stops Act, as part of that law, we put out data with regard to level one, level two, and level three, and level three encounters.

So that data is put out.

I believe it's quarterly.

I have the data.

So investigative encounters, 2025, full year.

Level one.

2 million plus.

Level 2, 31,159.

Level 3, 26,405.

For context perspective, that number was 680,000 in 2011.

Which went level three?

Yes.

Okay, 680.

So we went from 680,000 level three stops in 2011 to 26,405 level three stops in 2025.

Got it.

And this year, so far, we have about 16% less or fewer stops, level three stops.

Okay, across, okay, level three, okay.

Okay, and how will the training initiative goals affect this aspect of the department's work, and how will this review inform you of the relevant units and commands for retraining?

So we've created something called the Racial Disparities Review Committee.

And that's something, it's part of the plan, it's also something we're doing with the monitor, right?

So there's actually, the monitor team are quite involved and obviously don't want to speak for the monitor.

But what we're doing is we are looking at data, doing that in a very deliberate way and thoughtful way, working off of a model that the monitor's team used and sort of further developing that out ourselves.

And in looking at that, to the extent you have outlier commands, we want to understand what's happening, what's driving disparities, and just really in part to understand it, but then

if there are disparities that we can't account for, making sure we can address them.

So we're looking at department level data, the department as a whole and trends over time, but then also we want to understand what's happening in any outlier commands.

Okay, great.

And then how do you track that data?

Is it by borough?

Is it by precinct?

So again, we're sort of developing kind of an internal model, building off of the monitors team's work.

And we have

both sort of in-house talent, people we've hired to work on this.

We also have some external help as well.

And then again, that model is still being built out.

We're not there yet.

This is a very complicated process, right?

It's going to play out over time.

But in doing that, we're looking at department-level data.

We can look, ultimately, we'll be able to look at borough-level, command-level data as well.

We're not, again, but this is very much a process that's going to play out over many months.

Great.

Okay.

Thank you so much, and I'll pass it to Chair Felice.