Every policy pronouncement from Washington or your state capital carries an implicit promise: Government can deliver what it pledges. Yet when systems collapse under their own complexity — requiring 17-year veterans to “check the rules” against 7,000 pages of regulations — we glimpse democracy’s real crisis. It’s not about politics. It’s about whether this kind of representative government can actually work.

When citizens can’t access unemployment benefits, when 911 calls go unanswered, when promised infrastructure never materializes, the social contract begins to fracture. The resulting frustration fuels the antigovernment populism that has reshaped American politics, creating space for leaders who promise to tear down what doesn’t work.

In this week’s WhoWhatWhy podcast, we speak with Jennifer Pahlka, whose book Recoding America: Why Government Is Failing in the Digital Age and How We Can Do Better examines the archaeological layers of policy that have accumulated in our governmental systems. A former gaming industry executive who brought user-experience thinking to the Obama White House, Pahlka has spent two decades watching promising policies disappear into implementation hell.

In our conversation she reveals how the government’s operating model rewards risk aversion over results. Pahlka describes systems so complex that emergency disaster responses get bogged down in oversight, and applicants for unemployment benefits must fill out forms bloated with legalistic circumlocutions.

This isn’t simply about outdated technology. It’s about the distance between those who craft laws and those who must make them work. As traditional approaches fail, Pahlka argues we face a choice: fix democracy’s operating system or watch it crash entirely.

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(As a service to our readers, we provide transcripts with our podcasts. We try to ensure that these transcripts do not include errors. However, due to a constraint of resources, we are not always able to proofread them as closely as we would like and hope that you will excuse any errors that slipped through.)

[00:00:14] Jeff Schechtman: Welcome to the WhoWhatWhy podcast. I’m your host, Jeff Schechtman. In the grand theater of American democracy, we’ve grown comfortable with a familiar script. The curtain rises on bold policy pronouncements. Legislators take their bows. The audience applauds the vision, the ambition, the sheer audacity of governmental reach. And then the curtain falls. There’s a vast backstage to democracy, a place where soaring rhetoric meets stubborn reality, where good intentions tangle with ancient bureaucratic machinery. It’s a space most of us never see, populated by the millions of people trying to navigate systems that seem designed more for the convenience of government than the citizens it serves. My guest today has made that backstage her life’s work. Jennifer Pahlka has spent two decades in the shadows of power, watching the particular alchemy by which beautiful policies transform, often beyond recognition, as they wind their way through the layers of American bureaucracy. She came to government from an unlikely place, the gaming world, where user experience is everything, and failure is measured in seconds, not years. She brought with her a radical idea that maybe, just maybe, government services should actually work for the people that they’re meant to serve. Through Code for America, through her time in the Obama White House, through creating the U.S. Digital Service, she’s been both architect and anthropologist to a quiet revolution. Not the kind that makes headlines, but the kind that changes how millions of Americans interact with their government every single day. Her book, Recoding America, syncs up to a time when our faith in institutions feels particularly fragile. We’ve watched governments struggle with pandemic response, crumbling infrastructure, and the daily indignities of citizens who can’t access the services their tax dollars funded, not to mention Doge and the current governmental destruction. But what might it mean to actually debug democracy itself? Not through the grand gesture of political reform, but through the patient work of making government legible, responsive, and humane. In an age when artificial intelligence promises to automate everything from warfare to welfare, the question Pahlka  raises becomes existential. Can we preserve human agency and democratic accountability while embracing the efficiency of digital systems? Or are we destined to choose between competent technocracy and messy democracy? The stakes, as we’ll discover, extend far beyond the frustration of government websites that crash or forms that require instruction manuals longer than the forms themselves. They touch the very foundation of democratic legitimacy, the implicit contract that says government, however imperfect, should work for all of us. When that contract breaks down, when complexity becomes a barrier to access, when only those with resources can navigate the system, democracy itself begins to malfunction. This is a story about code, but it’s really about citizenship and about whether the tools we build to serve democracy might ultimately save it. It is my pleasure to welcome Jennifer Pahlka  here to talk about Recoding America, why government is failing in the digital age and how we can do better. Jennifer, thanks so much for joining us here on the WhoWhatWhy podcast.

[00:03:34] Jennifer Pahlka: Well, it’s already a delight to be here, Jeff. Thank you for that incredibly thoughtful and kind introduction.

[00:03:41] Jeff Schechtman: Well, thank you so much for being here. Appreciate it. We think that so much of the problems that we face with respect to dealing with government, so much of the dysfunction is somehow a problem of lack of money, lack of technology, lack of modernity in terms of technology. But in many ways, it really goes to the culture of these organizations. Talk about that first.

[00:04:06] Jennifer Pahlka: Yeah. I have a line that is sort of from the book, and in fact, my sub stack is named this now, that in business they say that culture eats strategy. In government, culture seems to eat the policy. In other words, you start with a policy intent, but as it gets sort of digested by the hierarchy, the bureaucracy, the culture of the bureaucracy, what comes at the other end is often not what was intended. And it is a little different in government than it is in business. But we see this, you know, I think just not just, you know, behind the scenes, but you see the results of it, I think, in our daily lives. I guess most recently we saw these big bills pass under the Biden administration, and they set a lot of expectations, like we’re going to have rural broadband for millions of people, there were going to be EV chargers, we were going to build a whole bunch of green infrastructure, but it really took a very long time for those to start to roll out, and what happens behind the scenes doesn’t really not make sense to people. And what they really see is just, you know, there aren’t any people in any new homes connected by broadband, we’re only seeing, I think, 47 EV chargers from, you know, many billions of dollars invested in it. And it’s not that those things won’t come, but they’re not coming in the timeframe that citizens expect. And unfortunately, then when you don’t act with great speed, they’re often, you know, rolled back by the new administration. So in fact, some of them may not come. And it’s really complicated to explain what happens behind the scenes. But essentially, every step that a law or policy takes down that hierarchy to sort of the next level down, it essentially becomes a little bit more rigid. Somebody interprets something with, you know, a keen eye to a certain law that maybe others didn’t look at. They take a maximalist interpretation of one thing or another. And by the time, you know, by the time it’s actually operationalized, you know, at the lowest levels of the hierarchy, it’s all about constraints and barriers and not so much about the big, bold ambition that you referenced in your question.

[00:06:38] Jeff Schechtman: How much of it is about fear? There’s an old saying that sometimes applies to big corporations, but it certainly seems more true with respect to government, that you can get in a lot of trouble for not doing anything, but you can get in a lot more trouble for doing something.

[00:06:54] Jennifer Pahlka: I think that that culture of fear is something that means that we need to look in the mirror as regular citizens, as the press, and say, how are we creating that fear? Because it is real. It is often the best thing. Now, some of it has to do with systems that just really need updating. Our civil service system has not been significantly updated since 1978. And it too has been subject to this cascade of rigidity, as I call it, that means that if you get down to sort of the very basic incentives for a public servant, they really derive from that civil service system. Are you going to get a promotion? Are you going to be able to keep your job? And the rigidity that’s been introduced over time into the civil service system means that yes, you are incented very often to do the most risk-averse or take the most risk-averse of any possible options that you have in terms of action. That’s not what the authors of the law intended. It’s not what the people who are counting on this outcome intended, but it’s what the civil service rewards. And I really think that ultimately gets to what this work is. We have these operating models that are stuck in 1978, or some of our procurement stuff is stuck in 1960, where we haven’t taken the time to say whatever outcomes we care about, which is where all the attention goes in the press and in government and in the policy circles, how do we get to that outcome? The operating model of government really determines whether you’re going to be able to get that outcome. Now, we think that whether you can get the policy passed and the politics of getting that policy passed are what determines the outcome. But it’s a lot like Maslow’s hierarchy of needs that says you can’t have self-fulfillment and self-actualization if you’re not fed and clothed and housed. You can’t get in government to the outcomes that you want if you don’t have the right people focused on the right things with purpose-fit systems and the ability to work in test and learn frameworks. That’s our operating model. And the work of updating it is sort of what I’m trying to call people to do.

[00:09:28] Jeff Schechtman: In fact, though, the incentives, as you say, are completely misaligned with the success of the policy.

[00:09:35] Jennifer Pahlka: The incentives are aligned with a civil service system that has been allowed to become bogged down over time because nobody has taken the time to refresh it.

[00:09:50] Jeff Schechtman: One of the other aspects of this is it seems like those that are in charge, those in government, that they’re not really there to implement policy as much as they are to manage it somehow. And that’s a distinction really with a difference. Talk about that.

[00:10:06] Jennifer Pahlka: Yeah. I mean, I had a friend who worked on the broadband plan in 2013 who said to me, oh, no, no, I learned this the hard way. You know, we manage, but we don’t implement. And by manage means we hire people, we hire companies to do it. And then the work becomes, you know, the RFP and the contract management, not the actual work of getting the implementation done and done in a way that is faithful to the original intent. But it is, I think, I think it derives really from this very. Core foundational belief that that’s what’s important, that the policy and the politics are what’s important and the implementation is for creatures of less import, for, you know, people sort of lower down in the social status of of of government and particularly of our federal government, that it’s it’s sort of functionaries who will do that work of of hiring the people to get it done. And really, I think that speaks to a concept that that is not talked about that often, but but but first started to be discussed in the 1960s of what is inherently governmental? Like, in other words, what can be done, only done by public servants in agencies and what can be outsourced? And we’ve taken a very, very aggressive view that pretty much everything can and should be outsourced. And in fact, you know, going back to the 60s, there’s really a sense that if this really materially mattered to the policy, it shouldn’t be. If it was just something that you could sort of, you know, paint by the numbers, do what you’re told, then then it could be outsourced. And I think we really have to relook at that and say, you know, what does it mean to manage versus to implement what really needs to be in-house? It’s certainly not saying that we should bring everything in-house, but when we try to outsource things and we to such a degree that we don’t even really know what we’re asking for from the vendor, we don’t really know how the system is supposed to work. We don’t know what good looks like. We really hollowed out government to that extent. Then I think we do great damage to the, you know, to the effort of democracy because we get these very adverse outcomes and we reduce people’s trust and faith in government. And I think relooking at what is inherently governmental is part of that whole reconsideration of the operating model.

[00:13:01] Jeff Schechtman: And in fact, that distrust of government becomes self-perpetuating. You go back to the 80s and you get those, what, 10, 11 words that Reagan always talked about. You know, I’m from the government. I’m here to help. That’s supposed to be somehow terrifying.

[00:13:17] Jennifer Pahlka: I mean, I think that there is some truth to it in the sense that government is trying to do a lot. And as we all know, and I’m particularly vulnerable to this as somebody who gets excited about a lot of things and wants to take on a lot of initiatives. If you try to do a lot of things, but you don’t have the attention span to really focus on them and you don’t have the people empowered to make sure the implementation is going well and faithful to the intent, you will do a lot of things poorly instead of some things very well. So I guess I have a little bit of, I have a little bit of sympathy for that view, that when government shows up and says, we’re going to we’re going to take care of X or Y or Z, sometimes we need to stop and say, wait a minute, there are core things that we have promised the public that we’re not taking care of well. We’re not going to be able to help in these new things well until we get our work in order on the things that we’ve already promised. Or maybe these new things are more important, but we have to have conversations about actual priorities. So so I have some empathy for that viewpoint. But I think the sense where that where that where those words took us was really to a hollowed out government, which I think we can all look back on now and say isn’t really helping anyone. Even conservatives I know who revere Reagan are asking themselves, is this really the way we should be running government? Where is the in-house expertise? How do we get it back? Because that’s going to enable the smaller, more effective government that they want.

[00:15:06] Jeff Schechtman: The one thing that has changed, probably the most fundamental thing that has changed in this period of time that we’re talking about, is that we’re looking at this digital world now and we’re looking at it from a point of view of all these layers that have been piled on to the analog world and trying seemingly trying to fit the digital world on it. I mean, you talk about, in fact, with respect to design, we’re rarely starting from the point of view of saying, what’s the user experience? Usually it’s one of the regulations that we have to tack on first.

[00:15:40] Jennifer Pahlka: Yeah, the digital world, unfortunately, has created more distance between outcomes and implementation in government, whereas in the private sector, often it sort of collapsed that distance. And so you sort of disintermediated, you get it’s instead of having to call a dispatcher, you can have a car show up at your home very, very easily in a way that wasn’t possible before the digital world. And that’s sort of collapsing of distance. But in government, we said, look, oh, there’s got to be a lot of policies and processes around how we build and use digital systems. And so we pulled that must be expertise there that is going to be required. We’ve created rules around procurement that are, frankly, in some ways more complex and hard to learn and also open to interpretation than the expertise that a computer programmer would have. The computer programmers have it easier because at least the computer is going to be pretty consistent in what it does, whereas when you’re trying to navigate this vastly complex procurement infrastructure, you’ve got competing rules and competing views, but like just enormous complexity and knowledge that’s required there. But none of that really contributes to us getting better computer systems. It just creates another layer in between the people who want the outcome or say it’s supposed to run our social security system and the people who are going to deliver the systems that should get that outcome. And that distance is actually very corrosive. So we have, I think, a lot of work to do to figure out how to collapse that distance. But I think the other thing to note about the digital world is not just that government needs to adopt technology in order to operate in it. It’s that it has fundamentally changed society in ways that mean that government has to act more quickly and meet people’s expectations.

[00:18:02] Jeff Schechtman: To that point, expectations have changed dramatically. You used the example of a car before, but in so many respects in the digital world, people’s expectations have changed.

[00:18:13] Jennifer Pahlka: My colleague, Tom Loosemore in the UK, actually defines digital this way. It’s using the principles and practices of the Internet era and business models of the Internet era to meet people’s raised expectations. And so when we think of and I think that speaks to what you were saying earlier, Jeff, about the user experience, if it is about meeting people’s raised expectations, then you start with how is this going to work for the people who need to use it, not get to that all the way at the end of a project when it’s sort of too late to really change it.

[00:18:52] Jeff Schechtman: Talk about the systems that have gotten so complex, particularly with respect to paperwork. And you’ve worked here in California with respect to some of the problems at Employment Development Department and other organizations where if they just became so complex, they literally collapsed of their own weight.

[00:19:11] Jennifer Pahlka: A great example of that is the unemployment insurance system, which sadly, even after all, the attention that it got during the pandemic is really not fixed. And it’s not fixed because the diagnosis that the press seemed to land on when these backlogs of unemployment insurance claims started to develop in early 2020 was, OK, well, the technology is outdated. Many of these systems are built on COBOL. It’s a programming language from the 1960s. I think it was created in 1959. So people can be shocked and outraged that something from the 50s is still in our systems. But really, the COBOL, frankly, did pretty well. The the most compelling way that I learned about about what was really wrong with the unemployment insurance system in California was a colleague of mine was working side by side with a bunch of claims processors at the Employment Development Department in California. This would have been July 2020. We were part of a task force, essentially asked to come in and help clear this this huge backlog. It turned out to be one point three million people who were still sitting there waiting for their for their claim to be processed so that they could buy groceries. And one of the claims processors said to my colleague, Marina Netze, over and over again, well, I have to go check that I’m the new guy. She’d ask a question and he’d say, let me check. I’m the new guy. And after the time that he said, I’m the new guy, she said, OK, so how long have you been here? And he said, oh, I’ve only been here 17 years. But the folks who really know how to process these claims have been here for 25 years or more. So you go look at is that true? Yes. I don’t know the number for California, but famously in New Jersey, the labor commissioner there, when he was asked to testify about why there was a backlog in that state, brought with him boxes and put them on the table in front of him as he testified and continued to point to them. And they were labeled seven thousand one hundred and nineteen pages of active UI regulations in his state. I suspect the number is even higher in California. So if you ask yourself, why is somebody who has been there 17 years still feel like he’s just learning the system and has to go check rules? It’s because there’s probably 10,000 pages of those rules. How do you get 10,000 pages of rules covering a system that’s basically supposed to give people a certain amount of money for a certain number of weeks under certain circumstances? Well, you add and add and you never subtract. And that’s how our system is set up, right, whether it’s the state legislature or the federal Department of Labor or even the courts making decisions that create case law that you have to follow. There’s always more rules to follow. And almost never do we stop and say this system cannot scale because it is so fragile underneath it with accumulated archaeological layers of policy and law and guidance. Now, we look at the sort of corresponding archaeological layers of technology and we blame that, but it can’t really be fixed without blaming the policy accumulation and accretion that underpins those technology layers. And I think that the good news and I’m happy to talk a little bit about this is I’m starting to see a tools coming online that help us attack those 10,000 pages and be the political will to actually do this work, which is underpinned by a recognition that it is simply unsustainable to always add and never subtract.

[00:23:24] Jeff Schechtman: Does that argue for fixing the system or pulling the system out by the roots almost and starting over or, as you talked about before, completely outsourcing it?

[00:23:36] Jennifer Pahlka: I think completely outsourcing it simply will not work. But from the other two options, it is really about what the moment allows for. Even just a year ago, if you had said pulling it out by the roots, I think everyone would have said that’s simply not going to happen. We’re now in a moment, I think, of real disruption, and I think that disruption is going to get worse as the federal government continues to do things very differently than it did before. And the impact on states and municipalities is going to be budget cuts that are more significant than we’ve seen in past decades. This is both going to be very difficult, very unpleasant and very painful, but also it’s going to open up the opportunities to do less incremental change and more really profound change that may, in fact, in the long run, serve us well if a lot of efforts that are really focused on the public interest start to shape that environment, right? If we just sort of let it happen, it’s not going to go well. But if we say we know what’s wrong here and we know how to do this in such a way that will actually get us the service that we want. I think actually we should take advantage of that moment and say, let’s do what incremental changes we can as they’re offered for us. But let’s take advantage of the fact that change is going to happen and put things like fundamental transformation of a system, as you said, pulling it out by the roots on the table in a way that it hasn’t before, and really evaluate, is that the right thing? Is that the right thing? For example, with unemployment insurance, it was very hard to get people in power to understand that it was simply not going to work to create a national back end. That’s what everyone’s solution was. Look, there’s 53 of these for the states and territories that manage UI. And why is each state doing one on its own when we could create a core piece of technology that each state could adapt to its own work? The reality is that unemployment insurance comes from the Social Security Act of 1939, I think. Is that correct?

[00:26:09] Speaker 3: I think that’s right, yes.

[00:26:10] Jennifer Pahlka: Yeah. So I mean, we’re talking about almost 90 years of each state customizing their program so significantly that there really isn’t that much in common in terms of how they administer it. You would think there would be, but it’s a very, very heterogeneous landscape right now. And so, if you really cannot manage the failure or, I guess, relative failure and success of 53 different systems, you cannot nationalize just the technology. But you could say, and I’m not saying this is the right argument, but we need to be putting these options on the table. You could say this needs to be actually a federally managed system, not a state run system. There are significant downsides to that if you’re a state that does not agree with the federal government, whatever political cycle we’re in, and there are huge tradeoffs. But we are making tradeoffs now without accurately assessing the impact of each of those tradeoffs. And we’ve got to have a different conversation that allows for that.

[00:27:20] Jeff Schechtman: Are there examples, though, of legacy systems that have been modernized without being pulled out by their roots? We were talking about California’s unemployment before. It’s better, but it’s certainly still problematic because those legacy systems in so many fundamental ways just don’t change certain aspects.

[00:27:42] Jennifer Pahlka: There are a few examples of true modernization in the sense that I would hold us accountable to a different definition of modernization, which is that you don’t just update the technology, you do the policy and process simplification alongside the creation of new technology. So often when we talk about modernization, what we mean is you take those 7,119 pages they’re still active, for instance, and you’re moving the system that you have from an on-premise system to an in-the-cloud system. And it isn’t better. And that’s why people get so disappointed, because we’re comparing them to the performance of systems that are in the cloud today that were built on greenfield opportunities, not huge, huge policy and process legacies. There are examples of really great modernization that don’t necessarily get all the way to that back end. And I think this is an important point to make. Look at, for instance, Direct File, which the IRS rolled out for the 24 filing season. People loved this piece of technology. It got amazing reviews. I think something like 90 percent of people said that when they use Direct File to file their taxes, it improves their trust and faith in government. That’s not often a place that you expect government to excel, like we’re taking money from you. But they felt really good about it. Now, these are low income people who likely qualified for some tax credits. So maybe that has to do with it. But it was really a very simple interface. And this team that built it at IRS built it in a agile, user-centered, iterative way that made sure that when people went to use it, they had a very seamless experience for the most part. They did not go back and say, we got to start by getting all of the IRS’s legacy databases updated. We’re not going to try to move their data centers into the cloud. It really just started with a different front end. That means there’s a lot of work left to do at the IRS to smartly update systems where we have vulnerabilities. But I like that it demonstrates that you can get a long way with starting with the user experience. And sometimes we really don’t need to port these COBOL systems. What we need to do is ask a little less of them. But they actually may be the right solution and can chug along quite well. I mean, when you book an airplane ticket, the back end of that has a lot of COBOL in it, too. And we are seeing failures in, say, Southwest has had some troubles. The airlines are having troubles, not in the booking systems. But yeah, legacy systems are starting to break in a lot of places. And so you eventually have to get there. But I think we misdiagnosed this when we say the most important thing is to get these governmental entities off of legacy back ends, when in fact what we really could do is just reduce the policy and process complexity, focus on front end work, and then, you know, over time figure out what’s a safe and reasonable way to do that back end work, some of which will actually not need to be done. In some cases, the COBOL should stay, to be honest.

[00:31:40] Jeff Schechtman: The other part of the question, let’s take the IRS, for example, how much policy did they have to iterate in order to do the front end changes that they did?

[00:31:50] Jennifer Pahlka: They didn’t really iterate on core policy. They don’t have that rule. But they were able to iterate on the sort of lowest level of sort of guidance and interpretation of that policy with a lens towards what people actually would understand. Right. They were able to work through different wording of questions or instructions by testing it with people. And that’s incredibly powerful. But, you know, you’re of all the places I think we could politically have a chance of doing policy and process simplification. The IRS, the tax code is just so politically fraught that it’s not where I would start. With something like unemployment insurance, there will be stakeholders who do not want things to change. But I think there’s a far greater likelihood that we can use the tools that we have at hand today to do some of that simplification. I’m really eager to see these AI tools get used that way. In fact, later today, I’ll be talking on a webinar with Dan Ho from the Stanford Reg Lab, who has a model called STARA. It stands for Statutory and Regulatory Research Assistant. And it’s a an AI model that was custom designed to ingest enormous amounts of policy law, regulation, municipal code and help you understand where you have conflicting, outdated, vestigial provisions that could come out. Now, those are the ones that no one’s really going to have a constituency for. No one’s going to object to those going out. But I think the next phase of that is the things that may have a constituency, but we can start to articulate why some of this complexity in, say, UI regulations is causing so much cost and harm to people and really have a conversation about whether those things could be brought down. I mean, could you describe an unemployment insurance system that worked well in 200 pages instead of 10,000? I think you could. And I think we would be far better off for it. We would spend far less money administering the system. We would have far better ability to scale it in times of need. It would be far more understandable to people. Right. It wouldn’t it would feel more human and less bureaucratic. And I think we start to have the tools to do that. But we’ve got to figure out the right places to do it. And I think David Chu, the city attorney of San Francisco, has been the pioneer in this looking just at things like boards and commissions or the number of reports that are required and saying some of the stuff is unnecessary. We’re going to do the hard work of subtracting instead of adding. The next phase is to get to programs where it really hits the public and do that same work there.

[00:34:57] Jeff Schechtman: And it’ll be interesting to see how the public responds when as they know more of this going on and things like the IRS and as they see it in certain communities and municipalities, because there’s also, on the other hand, California is another good example where certain forms to fill out for certain benefits are 10, 12 pages long.

[00:35:17] Jennifer Pahlka: I think they’re better now. But I think overall, we still have a problem. I mean, think about I used to work on our Code for America when I was there, worked significantly on Supplemental Nutrition Assistance Program, where I don’t know how many pages it was because the online application had two hundred and twelve questions in Michigan. A wonderful group there used to print out the SNAP application and take the pages end to end and roll it up in this. It was so huge. I don’t remember the number of pages, but I do remember seeing it, you know, someone put this roll on the floor and roll it out down an enormous hallway. I mean, it would take minutes to just walk how long that was. And, you know, that comes from this attitude of start from government needs instead of starting from user needs. That’s better in Michigan now. It’s better in California now. But think about things like how you’ll get your rebates if you buy a heat pump under the Inflation Reduction Act incentives. Did we apply the same sense of user centered design to that problem? In many states, we didn’t. And it’s going to have the same impact that long applications for SNAP had in those states, which is to decrease the number of people who use them and decrease the impact of the policy itself.

[00:36:47] Jeff Schechtman: What did the experience of Doge that we just have all witnessed over the past several months, what did that do from a practical standpoint, as you see it, but more importantly, what it did from a public perception standpoint?

[00:37:04] Jennifer Pahlka: I think Doge, in a certain sense, did everyone a favor by making this agenda top of mind for a while. The way they executed it also, I think, made people realize that it matters how you do it. I think their work is deeply unpopular. It was very popular in concept. People really like the idea of it. But when they started doing it, they saw that it wasn’t necessarily being done in a way that was consistent with the public’s expectations. And I hope that means that people now have an appetite for Doge done right, if that’s a phrase that we could use. I think what people intuit but don’t necessarily express is that if you looked at the Doge that was announced. So, for instance, the Washington, no, it wasn’t Washington Post, it was the Wall Street Journal op-ed that Vivek Ramaswamy co-wrote with Elon Musk. And I strongly suspect that Vivek Ramaswamy wrote it and and Elon’s name was put on it. He talked a lot about deregulation in that and that that scared a lot of people on the left because deregulation can certainly mean letting corporations sort of do whatever they want that may not be in the public interest. But what’s interesting to folks like me about that, that term is that the biggest thing government regulates is itself and it ties itself into knots with its own regulation and really decreases its capacity to deliver. So I’ve been for a long time, for instance, a champion of changing the Paperwork Reduction Act. In fact, I’d like it repealed. It’s an old law from the 90s that, in fact, only makes paperwork in government far, far worse. Not only does it create paperwork for civil servants that I think serves very little use, I’m not saying it’s no use, but certainly not worth the incredible delays that it causes and the extra work that it causes. But it also results in more paperwork for the public, which is exactly the opposite of the intention of the law. Changing the Paperwork Reduction Act would be deregulation. And I hoped that Doge would go when they started to try to operate in government. It was new to them. I think most of the people in Doge didn’t have a background in government. They would realize that this work of deregulating government itself and freeing it to act more quickly and more to the point, to the outcome, is something that they would have the power to do. I mean, they had the incredible backing of the president. There was more attention on Doge by orders of magnitude than, say, the U.S. Digital Service, which was its precursor, had from previous administrations. And it had a, I’m speaking of in the past tense, it had a Republican trifecta. And so it could easily, the people of Doge could easily have come in and said, here is our agenda. We’ve learned that these nine things are really holding us back. Let’s take a legislative package to Congress and get these things undone. They didn’t do that. And I think the people, I think the public realizes that, though they may not put it in those words. What that means, though, is that work of removing policy and process to make government truly more effective and efficient still remains to be done. And I hope that the public still has an appetite for it.

[00:40:53] Jeff Schechtman: Which really asks the question, as we wrap this up, whether we have to think about this on a smaller scale, that we have to use the states as kind of living laboratories and see how this can work better on a more manageable state level and hopefully use that as a model, whatever states are more effective at it.

[00:41:17] Jennifer Pahlka: A hundred percent. And in fact, that’s where a lot of my work is going. I continue to work with federal government, but the states very much need to show that DOJ can be done right, can be done in the way that the public is asking for, and that fundamentally will leave government better than we found it. I also think cities, I’ll tell you a little story that that connects, I think, our lived experience to this whole agenda. Last year, I was in Oakland where I used to live, middle of the summer. So I had all the back doors open. I was doing Zoom calls, regular kind of day, had a break, wrapped up my call, went into my bedroom and found a man there going through my stuff. He had my drawers open. I screamed and ran out of the house. And of course, I had my phone in my hand and I called 9-1-1. It took three minutes for them to hang up. I called back and it took another five minutes and I was disconnected. On the third time, I waited seven minutes before someone picked up the phone. I told them what was happening. They said, we will send some police. The police showed up two days later. Even though at the time when I called, there was actually still a man on the scene. And instead of getting outraged about this, and by the way, I was fine, I didn’t I think he was mentally ill and not violent, so I feel very lucky. But I also thought about what it would mean for someone else who had less luck to have that kind of response time. But instead of getting outraged, I got kind of curious and I went and read about the Oakland Police Department and found that not only does it have a significant staff shortage and it’s a very long time to hire and train people, but also it’s subject to 10 different oversight boards. Cops have to go through 19 different policies in their head and check off 19 different boxes before they’re allowed to pursue a subject. They spend 80 to 90 percent of their time on paperwork, usually, you know, inputting data into one system and then inputting it again into a different system, which is a terrible way to do things. And then yet another system similar on 9-1-1, you know, this we can’t staff. The reason no one picked up the phone is that we can’t staff these positions because of enormous numbers of constraints and lots of other things as well. And to me, I thought this is this is why this happened to me. There was a reason, right? I am working on this concept of state capacity, and I don’t mean this. It’s at the state level. I mean, the administrative capacity, the ability of a government at any level to achieve its policy goals and meet the expectations of the public. And what’s holding Oakland back is not that their police officers are lazy and don’t care. When they came, they were hugely apologetic. They know they are not hitting the bar. And they also know that, as I do, that we have created so many constraints and traps and oversight. We’ve really bogged them down in ways that we that we can be undone. Like, yes, you can get more police officers. But what if you could have them spend 40 or 30 percent of their time on paperwork instead of 80 percent? If you could wave a magic wand and do that, you’ve doubled the capacity of the police department. And that’s the conversation we need to be having. This is how, you know, the field that I work in, this updating of government for the modern era comes, you know, all the way you can connect the dots all the way from, say, poor implementation of the Inflation Reduction Act or the the BEAD program to, you know, connect people to new broadband all the way down to does a city in our country pick up the 911 call? Do people feel safe? And it’s everything in between. State capacity is at the core of these.

[00:45:39] Jeff Schechtman: And finally, is there an industry we can look at, even in the private sector or the public private sector, that has gotten this right, that is regulated, that has been able to implement policy and do it in an efficient way? I mean, certainly it seems better in the medical world. We see it in fintech. Just talk about that before we wrap it up.

[00:46:02] Jennifer Pahlka: Most people will tell me when they read the book, oh, I work at a big company and we have a lot of the same problems of bureaucracy as you do, and I think that’s a very fair point. The difference, of course, is that a company with a CEO may have a board, but it does not have Congress as its boss and it does not have some of the incentives for sort of performative actions that our political system is enforcing in this day and age. And so I do think it’s it’s very related and it’s a point well taken. But I do think government has different constraints. I mean, where you see and this is where you see industries having developed, it’s really because they got they were forced to by competition. And I think we have to come up with a way that we refresh and transform without competition because that’s we’re not going to have that in government. There are advances in the health care world that I think we could learn from. There are mostly, though, better front ends to a still really overly complex health care system that that just obscure the complexity for the user. And, you know, I can now make an appointment at my doctor a lot more easily than I used to because they’ve they’ve created these portals. One medical, I think, has done a good job of this. But the back end work of an overly complex system still means that if you end up in a difficult health crisis, you will you will hit up against the limits and deficits of our health care system, which are deeply, deeply tied to the deficits in our operating model in government. I will also say, though, that some of the most exciting work I see in federal government is coming out of the Centers for Medicare and Medicaid Services. The story I tell kind of at the end of my book about a team that did it right is the team that implemented a law after the ACA, after the failure of the HealthCare.gov website. They were asked to implement MACRA, the Medicare Excess and CHIP Reauthorization Act. And they did a very good job of it through all of the tactics and strategies that we talk about in the book and through really empowered public servants who felt they could speak up and say, we’re not going to make this more rigid every time it goes down the stack. We are not going to interpret those laws and guidance in such a way that makes it maddening for doctors to use the system, for instance. And when they launched that program, the call centers were were braced for the kinds of complaints that they always get from the ecosystem. This is terrible. We hate this. And instead, people were calling and saying, I must be on the wrong website. This is so easy to use. So it can be done. And it requires, I think, a whole set of changes. And as you as we started out talking about in the culture of the bureaucracy where you’ve got change agents really fighting to do things in a different fundamental model.

[00:49:22] Jeff Schechtman: Jennifer Palka, her book is Recoding America, Why Government is Failing in the Digital Age and How We Can Do Better. Jennifer, I thank you so very much for spending time with us here on the Who What Why podcast.

[00:49:34] Jennifer Pahlka: I really enjoyed it, Jeff. Thank you so much for having me.

[00:49:36] Jeff Schechtman: Thank you. And thank you for listening and joining us here on the WhoWhatWhy podcast. I hope you join us next week for another WhoWhatWhy podcast. I’m Jeff Schechtman. If you like this podcast, please feel free to share and help others find it by rating and reviewing it on iTunes. You can also support this podcast and all the work we do by going to whowhatwhy.org/donate.