IRE and me

IRE Radio · A conversation with Ben Welsh

I'm the guest this week on the podcast published by Investigative Reporters and Editors, the non-profit organization where I started out.

Tune in to hear Nakylah Carter ask me about my accidental induction into the press corps, my first FOIA, the enduring appeal of Good Internet, the industrialization of data journalism, the economic advantages of being a nerd, homework as soulcraft, my reluctant respect for R and the transcendent moments when statistics and shoe leather coalesce.

Below you can find a transcript of our conversation, which I have lightly edited for clarity and concision.

When did you know journalism was your thing? And then how did you nurture it to be the person you are today?

Oh man, we can go way back with this. I'm getting old.

I never set out to be a journalist. It wasn't something I did much in high school or a career goal I went into college with. I was an undergraduate at DePaul University in Chicago, Illinois, after growing up in Eastern Iowa, and I stumbled into journalism accidentally.

I had a job answering phones in the communication department as part of one of these work-study programs, to make a little money while I was in school. And in that job, I was entrusted with some very important responsibilities. One of them was pinning up flyers on the bulletin boards around campus about upcoming events the department was running.

So, I was often the first person to see the notice of new things happening. One day, I was pinning up a flyer and noticed that it was an advertisement for an internship with two journalists taking up residency at the university, Carol Marin and Don Moseley. They were looking for a student to join them.

While I was pinning it up, I thought, hey, that sounds cool. It sounds a lot cooler than this job pinning up flyers on bulletin boards. And because I was the first person to see the flyer, I suspect I was the first person to apply.

I never asked how many other people applied, but I ended up getting that internship despite being ridiculously unqualified and began my journalism career as the grunt assistant to this producer and correspondent team, who were doing weekly television pieces and newspaper columns and some long-form documentaries. So I got into journalism by accident and quickly saw it was a lot of fun. It was a great way to engage with the world and learn about it. It was also a challenge and, maybe, something I could do.

I think that's amazing because I think it's important to understand that everybody's path into journalism is completely different. Can you talk about how you got into the data journalism realm?

Data and the work I do today quickly found me in a public records request.

We got a tip that a local suburb of the city had been rigging legal contracts to rack up money for a local alderman and his allies. To check it out, we filed a public records request asking for a list of every legal contract or fee paid out by the city to this law firm. It was my first FOIA ever.

After a few weeks or months, I can't remember exactly, in the mail came a big, long printout, a computer printout. This was a 1990s or '80s style one where it's an accordion sheet of paper, dozens of pages connected by the little tear strips on the outside. It was all the legal fees, but they were spread out in this dot matrix style across a lot of paper.

We initially had the question, how the heck are we going to make sense of this? I don't remember where I got the idea, but I thought, hey, what if I type it all into a spreadsheet?

So I sat down and did it. It took me a day or two to go through it all and double and triple-check it. But we arrived at a pretty big number, a big enough number to justify the story being on the news. And we got our little scoop, our investigative piece, out of the tip, the FOIA, and the data entry.

With that, I was hooked. One, I saw that data was a shortcut to getting to work on really cool stories, more than just run-of-the-mill stuff, things I found exciting. And as the guy who could sit down and figure out the tech, it might be a niche for me or a place for me to fill that gap and help make those stories happen.

Those two things got me going. I wanted to go further down that road. So I went to the University of Missouri and was a graduate assistant at IRE/NICAR, where I got to focus on not just faking it, but actually learning these skills, learning how to code, learning what real analysis was, getting a lot more practice. That set me off onto the path I still am on today, now more than 20 years later.

You grow so much as a data journalist by practical experience, but also by talking to peers and collaboration and learning other people's tips and tricks. So, I have to talk about your website, palewi.re, because I was like, this is amazing. I wish I'd seen this last year.

What made you want to compile all that information? Because it's not something that you're required to do, but it's amazingly helpful.

It's nothing that happened overnight. It's the accumulation of years and years of chipping stuff together.

For me, the annual IRE/NICAR conference is an opportunity to challenge myself and for all of us in our community to come together to say, what do we want to teach each other? What's important? What have we learned in the last year that's worth passing on to other people, that we're excited about, or want to share?

I look at every year's conference as a moment of opportunity and try to drum up new stuff. I've been doing it long enough that I have a playbook for it, a little routine, and I've just been adding incrementally more and more lessons that I've put together, with other people who help me, by the way, of course. And it's become, over time, this collection.

Do you have any favorites or any talks that you have that you look forward to? Because I know some of them you repeat and some of them you tweak. Is there ever one where you wish something like this existed when you first started?

I don't know if I have a favorite child, so to speak. To me, there are a lot of great things about it.

I love coming together with peers and people I respect to help create the classes and that formative experience of us collaborating to take an idea or a technique that hasn't been fully fleshed out and trying to put it on paper and get it across. That creative process is really stimulating and always rewarding to me, and that keeps me doing it.

Then the conference itself is a great experience, but, maybe most of all, is the thing that comes out of putting it on the web and having a little bit of faith in the world. I am often stunned to hear from people on the other side of the planet, who I've never met and never will, who will reach out and say they learned this or that based on a resource we put on the web, not knowing what would happen with it. There's something magical to that, a hit I keep chasing or that I just love.

It reminds me of my own formative experiences on the internet as a teenager in the '90s. I'm old enough to remember life before the web. As a kid in rural Iowa, its arrival was a big deal. The internet was my gateway to the world and such an exciting, stimulating place to learn and connect. To still have experiences like that 30 years later with people in Ukraine or Brazil or wherever else is the magic of technology that I find so rewarding.

You went from not knowing that journalism was something you were interested in to creating a new news desk. How did you know that that is something that the newsroom needed, and how do you operate in that position?

Without sounding too grandiose or self-assured, I think we are entering a new era of data journalism in the commercial media, which is, I think, one of industrialization and specialization.

When I started out at the Los Angeles Times in 2007, the whole idea of putting data on the internet on a newspaper website was still a pretty new one. We weren't the first to do it, for sure, but in our context it was definitely new.

I think a lot of what was going on then, even at the leading news organizations, was experimental. You had small teams of people goofing around, trying to make things happen on the web, often totally separate from their mainline newsrooms.

It's good to remember that the 2008 election was the first one where you had widespread live election results on newspaper and news organization websites, when Obama was first elected. There were examples of that before, but the really kind of first widespread publication of it was that time.

It was an experiment that was then wildly successful. Since then, there have been many other examples running up to coronavirus trackers. You can go down the list of all these different ways of taking data directly to the audience in the form of dashboards and databases and visualizations that aren't traditional stories.

That has gone from an experiment to a widget or a product that we want to manufacture inside the metaphorical factory of the newsroom. It's my view that as we go from experiment to mass production, we need to institutionalize, specialize, and ramp up how we're organized to create these widgets. In my view, that means making a news desk, which is its own little assembly line in the factory, that focuses not on battleship investigative reporting projects, not on one-off graphics to accompany traditional text stories, but instead on these data products, whatever you want to call them, that are incredibly popular with audiences and could also be capital J journalism.

This news applications desk is our attempt to name something that does that. I don't know if I love the name. If you have a better name, I'd love to hear it. But that's what we mean. That's what we're trying to do here at Reuters. We're trying to create a group of people who focus on making that type of thing.

We're moving towards a time where people almost expect data to be in the story. It's become way more normal. So I think it's amazing that you guys are thinking about this.

We can't forget that. Data journalism grew out of the investigative reporting tradition, or at least a large part of it did — there are many streams and strands — but the IRE/NICAR tradition is one that stems back to investigative reporting, which is what I was trained in and what I love and respect.

I've done a lot of it in my career. But the justification for that type of work, for the investment, for the dollars to be spent to fund it, is typically one that's based on prestige and public service, which are two of the very high callings of our profession. But in a time of decreasing resources and brutal disruption to the economic model that supports journalism, it can be difficult to justify jobs and investment in data journalism if it's strictly seen as a prestige project.

So that's bad news, maybe. But the good news is, and I think we often undersell this good news, is that these data products I'm talking about, your live election result or your coronavirus tracker, yes, these are public service and, yes, they ought to be seen as prestigious. They've won some of the highest awards, but they are also popular.

Last year at reuters.com, the most popular thing all year was the live election results done by our team in London, led by Jon McClure. The most popular thing in the history of the Los Angeles Times, where I used to work, the most read piece of journalism in the one hundred and whatever year history of the L.A. Times, was its coronavirus tracker. And I suspect the same is true for The New York Times and many other news organizations. We shouldn't sell ourselves short. We're making things people want.

A lot of people say journalists and math don't go together. A lot of journalists aren't set up naturally to do data. What is your advice for someone who wants to get into that realm? It's a hot commodity right now.

That's your advantage. If other people are avoiding it and you're willing to take it on, that's going to give you the edge. That's going to give you the front foot.

I think you should not listen to people discouraging you from going down this road if it's where you want to go. Because we know it's where things are headed and it's valuable. So, don't be afraid to have the confidence to do it. Surround yourself with people who agree with you, and find mentors and role models who'll help you move down that path. It's a lane that's wide open.

I don't know if I can rewind. What would I tell younger me? Study harder in high school? I don't have any regrets or any big things like that. There's the reassurance I think we all need when we're young, that I needed like everyone else, which is that if you work hard, it will pay off.

I've seen that in my own life, and I've seen it in many others. I encourage people to, I almost said, lean in. I won't say lean in. I'll say work hard and be a good person, and it'll work out. So that's what I would tell myself because I was a nervous young country kid in the city.

As far as the work, you have got to have high standards for yourself, and you can't cut corners. You have got to do the work. I think that means coming in every day like you have something to prove, not being afraid of challenges, and realizing that it's by pushing through them that you're going to do something you're proud of. Don't be lazy. It's the same message, maybe, but what I believe. I think it's all about progress and push and not giving up.

So I have to ask some things. Do you prefer Python or R?

I'm definitely a Python person, but I respect R and, really, it's about the results. So, I think there's a lot of great and talented people who work in R, but Python's obviously superior.

I agree. I wholeheartedly agree. And then I wanted to ask, what is your favorite data journalism memory? A story, or maybe an interview, or something that happened where you thought this is the career for me.

There's that first story I told you earlier, where the light bulb went on that this could be something for me.

The most powerful moments are often, and maybe it does go back to investigative pieces, when statistics and data lead me to someone's doorstep and help both me, the journalist who's trying to figure out the story, and more important in the moment, and maybe in the cosmic sense, the person who lived the story, better understand what the heck happened to them in life, particularly if it was something bad.

I did a series of stories about the local 911 system in Los Angeles, where we uncovered a lot of systemic flaws in how emergency care is delivered, in how the fire department is run. Some of the most powerful memories I have are where the statistics would tell us there's this kink in the system, there's this inefficiency, there's this problem, and it could be having bad effects out there in the world.

Then we followed the data, individual calls, out to doors and then we knocked to see what really happened in this case or that case where the data says something maybe went wrong. What we found often is, yeah, it did go wrong.

So, there's this way in which you discover a story based on a spreadsheet. But then also there's this powerful moment of connection with the person on the other end of the journalistic exchange, where you help them understand why something bad happened in their life and help them be part of an effort to describe and share that with their community so that maybe it can be fixed and it doesn't happen to someone else.

To me, those moments where statistics and shoe leather connect with the subject are the magic that data makes possible. Because when you don't just go off your own bias or instincts, when you let the math and science lead the way, you can have these powerful moments of discovery. They're not the same as Albert Einstein and E equals MC squared or whatever, but they are powerful.

I struggle to describe it, and it would be almost impossible to give you every detail of what that feels like without writing a novel. But those moments of discovery and connection, where statistics and shoe leather meet, are intense.