Odd Lots - The Theory That Explains Why Everyone Went Crazy

Episode Date: July 1, 2024

Does it feel to you like society has gone crazy? Well, you're not alone. There's a general view that all around the world, in the realms of politics, culture, business, and so forth, a lot of people are losing their minds. So if this is true, what's the reason for it? On this episode we speak with Dan Davies, the author of the new book The Unaccountability Machine: Why Big Systems Make Terrible Decisions - And How The World Lost Its Mind. Dan talks about the field of study known as cybernetics, and the inevitable outcomes of systems that grow more and more complex. This complexity -- which describes many things in the modern world, and leads to what Dan calls "accountability sinks," or entities that basically exist just to be blamed for things that have gone wrong. Dan walks us through how these emerged in the modern world, where things are headed, and how the trend could theoretically be reversed.See omnystudio.com/listener for privacy information.

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Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Widenthall. And I'm Tracy Holloway. Tracy, you know, there's a lot of like concerns about AI, obviously these days. And we, anyone who's like reasonably intelligent can like list tons like maybe like it's going to go rogue and be smarter than us or maybe whatever. But I still think like what or maybe there's just going to be this like flood of disinformation and deep fakes or maybe it's going to put all journalists out of business, which is certainly plausible. But I think, you know, like something I think a lot about is just this idea that regardless of what happens, like we're going to be increasingly sort of trusting like a black box for answers that we really have no idea where those answers.

However you want to describe that come from. Yes, absolutely. And this is something that's come up on the podcast. number of times now. I'm thinking way back to an episode we did that was basically about the black box of algorithms and how difficult it was to understand what goes into them and then what comes out. And then, of course, we recently did that episode on pricing and the idea of algorithmic pricing, the idea of building proxy consumer profiles. And you're right. The issue is we know that there's this new technology. We know that there's all this data floating around. But

we don't entirely know how it is coming to the conclusions or creating the output that it actually is. You know, the pricing thing is interesting because, you know, in a market economy, you know, you could argue it's like, oh, at any given moment, you know, you're being served up to like the optimal price, right? And in theory, even with the most advanced algorithms and stuff, like maybe there's some like this price is happening at the best price for both the seller and the buyer, etc. But I think like people just have a sort of deep intuitive distrust about the fact that like, you know, you can't go there and like touch it and verify it and see like this is why this exists in the state that it is. And I think it's going to create a lot of, I don't know, cultural apprehensions as more and more decisions and more and more things that are that affect our lives just seem to like emerge spontaneously out of the box. Absolutely. I'm thinking of all the people working at Chipotle who are going to have to answer questions about not just portion sizes now, but also questions from customers about are they getting the best price. Have you seen those awful videos that people are taking of the Chipotle workers?

Yeah, I've seen some of them. I can only imagine. Yeah. It's so vile. Anyway, that's a, that's a separate thing. But yes, like all of these things. And you know, it's it's not just with AI, obviously. And like this sort of world exists and increasingly. black boxes, you put in a support ticket, you try to talk to someone in an embassy or a consulate or anything you do and you sort of like send out some requirement or some request to some bureaucracy or some company. And then it moves around. I was on a, I had a flight recently that was delayed for nine hours. And there's like this palpable frustration that everyone feels that the person, you know, standing at the gate like can't answer their questions and they can't get anyone to answer their questions. And it just sort of like, you know, everyone explodes. and everyone knows it's not the gate agent's fault,

but still, like, you know, there's just this frustration. Like, where is the answer to what's going on? Right. And you can't ask a single person because that single person, like the gate agent doesn't have the answers. I think what's happening is, like, society has organized itself in such a way as to devolve responsibility.

And the creation of all this new technology is basically going to, I guess, ramp all of, of that up, right? Like, so it might not even be the gate agent that you're asking in the future. It might be you trying to like, I don't know, ask the algorithm, like, why it decided to bump you versus someone else. Or actually, that already happens, right? There is an algo that dictates, like, who gets bumped from the plane and who doesn't. So, yeah. The other big one, of course, is health insurance and why some claims are suddenly denied and you never get this answer. Anyway, the world is already filled with.

with systems in which we have some question and no one actually can sort of, you know, give you the answer. Yes, absolutely. And I think we might have the perfect guest. We do have the perfect guest. It's someone we've talked to multiple times on the podcast. One of the smartest guys around always interesting, always worth paying attention to. We're going to be speaking with Dan Davies. He is the author of the new book, The Unaccountability Machine, why big systems make terrible decisions and how the world lost its mind. So this should be really fun. Dan, thank you so much for coming back on the podcast.

Oh, thanks very much for inviting me. You know, before we get into the meat of your argument, the unaccountability machine, I'm actually curious about the second half of the title, how the world lost its mind. Because I certainly feel like the world lost its mind, but I'm like a middle-aged boomer, and I feel like, you know, anytime you get to my age,

you're like, oh, the world's gone crazy, the world's gone mad. why is everything so nuts these days? Does we actually know that the world's gone mad? Or is it just because we're all sort of old and cranky now? Everything seems like the world's gone mad. Well, from your own perspective, you can never be sure. But I think there's actually reasonable, objective ways that you can check up on this, just by noticing that the world gets more complicated as it gets bigger.

And it gets exponentially more complicated. and I mean that in the literal mathematical sense because the number of connections grows faster than the number of things, whereas our capability to understand the world, manage it and make decisions doesn't necessarily grow exponentially. So this is the story, I would argue, of economics.

It's the story of any management book that's worth reading because the central problem of management is the world is getting faster, more complicated, faster than you can process. that complexity. What are you going to do about it? How are you going to reorganize? And, you know, we've just been through a global financial crisis. We've just been through a political, what Adam 2 is

called poly crisis. I think there's decent reason to believe it's not just because we're getting older. And it is actually a crisis of the ability to make decisions matched up against the speed and complexity of the decisions that we're having to take. So when we talk about the lack of accountability and making bad decisions. Give us some concrete examples of things that you have spoken about or written about in your book. What are you thinking about here? Well, I mean, there are kind of, there's little trivial, funny examples and there's big, huge, serious examples. So, for example, and I apologize in advance because this is quite disgusting. Oh, is it the squirrels? Would you rather I didn't talk about squirrels? No, you could, oh, this is bad.

Tell us the squirrels. If there are children listening, maybe get them out of the room. Children don't listen to our lives. At the start of this century, there was a craze for squirrels as pets in Europe. And squirrels were being imported from North America and China to be pets. And they had to have the right paperwork. And so one day, a load of 400 of the poor little things showed up in Shiphol Airport in Amsterdam. without any paperwork and without a return address to send them back to.

And it's difficult to know what the airline should have done, but you can't help thinking that there must have been a better solution than what they actually did do, which was that they threw all 400 of them, except for one or two that escaped into an industrial shredder. And this caused an outrage. There were questions asked in the Dutch Parliament, and people immediately started asking, how did this happen, who is responsible? And in fact, the press release from the airline apologising for this is studied as a masterpiece

of crisis PR in business schools. But when they went back to inquire, they ended up realizing that no one had ever really made the decision that that was what they were going to do. The government's biosecurity ministry had set some standards for the importation of small mammals. The airline had set some standards for compliance with that policy. The only people who were expected to make a decision about whether this was grotesque and couldn't be done or not were some low-level employees in a shed at Shipol Airport. And frankly, people who work in sheds aren't usually going to be thinking that they're meant to be second-guessing the government. And so what happened is that you had this phenomenon that turns up a lot of the time at all levels of organization,

which is that something happened which nobody wanted, but was the predictable output of the system that they had created. You can get the news whenever you want it with Bloomberg News Now. I'm Amy Morris. And I'm Karen Moscow here to tell you about our new on-demand news report, delivered right to your podcast feed. Bloomberg News Now is a short five-minute audio report on the day's top stories. Episodes are published throughout the day with the latest information and data to keep you informed. Yes, there are other products like this from a variety of news organizations, but they usually rerun their radio newscasts throughout the day. That's not what we do. We create customized episodes that can only be heard on Bloomberg News Now.

And we don't wait an hour to publish breaking news. When news breaks, we'll have an episode up in your podcast feed within minutes. So you're always getting the latest stories and developments. Get the reporting and the context from Bloomberg's 3,000 journalists and analysts we're all over the world. Listen to the latest from Bloomberg News Now on Apple, Spotify, or anywhere you listen. Yeah, this is, this is, first of all, that's grim, but also like when you're describe it that way, you can see it.

Because ultimately, like, all right, here's this awful thing that happened to 398 squirrels. I guess in theory, someone had to, I don't want to get, I don't know, dump the bag into the shredder. I have not researched the details intentionally. That's not a very satisfying answer. I mean, yes, okay, maybe there was someone who did the physical thing. And I guess the entire, you know, operations of the airline and the port and the customer Bureau could like just blame that one person. But that's not a very satisfying conclusion, I guess, in terms of like how this actually

happened. It's funny. I brought this documentary up. I was thinking about this too, like with the destruction of the old Penn Station in New York, which it's like this like extraordinary like, I guess like Roman or Greek building. And they just tore it down to like build the pretty awful. Something hideous. Yeah, something hideous in its place.

And now the new Penn Station is terrible. But it feels like the same thing. Like, how did no one stop and say, like, wait, does this make any sense in the long, in the big picture? Yeah. And the thing is, they'd created a system on the assumption that squirrels would show up in ones and twos and they could be dealt with as individuals. And that, therefore, you would never get into this sort of situation. Because when you build a system, you're always building a model of the world. And if something happens which doesn't fit into your model in the world, your system might do something awful.

and there's a sort of symmetry and a kind of resemblance here with much bigger and more grim things like the Boeing 737 Max, like the LIBOR scandal in financial markets. It's not so much that anyone sat down and said, let's form a conspiracy to manipulate interest rates or let's build a plane that crashes under certain circumstances. It's just that no one set things up so that that wouldn't happen. Do you think, I'm afraid going forward, the squirrels are probably going to be our archetypal example of this. But do you think with the squirrels, for instance, the hyper specificity of the goals or the job roles of everyone involved contributed to the outcome? So in the sense that you have, you know, I guess the Dutch wildlife department who is trying to protect Dutch wildlife. Then you have like the guys at the airport who are charged with actually carrying out these orders. And then you have the airline, which is charged with like looking at the paperwork.

Do those tend to lead to, when taken all together, do those tend to lead to worse outcomes? Yeah, absolutely. It's this kind of fragmentation of the decision, which is a result of the industrialization of the decision. And it's industrialization literally in the Adam Smith sense that you don't have anyone in the pin factory building an entire pin. You have 13 guys all performing one simple operation, and that's a much more productive way to do things. But then when you apply it to decision-making, you have the problem that everyone assumes that everyone else is going to react when something unplanned happens. So, you know, this is, like I say, it's the central problem of every good

management textbook. How do you deal with information? How do you get a drink from a fire, hose, how do you stop yourself from being overwhelmed? The answer is always in some way or another, you build a system to make the decisions for you. But once you've built that system to make the decisions for you, you no longer feel ownership of that decision psychologically. You no longer feel like you're accountable for the decision, because if you were accountable, you might be able to change it. But if you're going to be held accountable for this thing, you haven't really moved that thing on. You haven't really delegated it to the system. You mentioned Boeing, and speaking of Boeing, there was a great blog post back in April from Steve

Randy Waldman, interfluidity, who I consider another one, kind of in your category of people who have basically been writing interesting things on the internet for a very long time. And he has this title was Seeing Like a CEO and this idea that, you know, when Boeing merged with McDonald-Douglas, the McDonald-Douglas CEO became an outside hire and he had to essentially gained some legibility into this new organization that he inherited. And that was the cause for some of this like streamlining and offshore or, you know, um, offshoring things like that. Talk to us like about, you know, you mentioned Boeing and it's more, you know, the crises there that's been going on several years. It's a more severe, serious issue than, uh, the squirrels.

But how do you, you know, how do you think about what happened there? I think about it in, in very similar ways. to Steve Randy Waldman because the, and you know, you see it in Boeing, but it's visible to a greater or lesser extent in very, very many companies, probably the majority of companies today, that the C-suite has an information environment, which is almost completely composed of financial numbers. Because the financial numbers are, you know, taken by them as objective facts. We can't talk long and hard with accountants about how objective. those financial numbers are and how many assumptions go into them, but they arrive on a spreadsheet

looking very much like objective facts about the world. Things like engineering level, in principle, are objective facts, but you have to do a lot more work to find them out and to know what's relevant. And then you have issues like culture and kind of the social environment, which aren't even capable of being quantified. So there's always this tendency, if you're trying to do that thing of manage your own capacity to manage your information flow, that you're going to concentrate on the things that look finite and look manageable. And that's always going to be the financial numbers, which can be a big problem because financial numbers can mislead. You know, you can create illusions in an accounting system the same way that you can with anything

else. How did we end up here? And I'm thinking specifically to one particular, you know, one particular development in the world of business, which is the creation of the limited liability company. And I guess the clues kind of in the name there. But what were the decisions or the trends that sort of came about in creating the current system? Well, I mean, the limited liability company is certainly a big kind of change. If you think about these things in feedback terms and information terms. And one of the big arguments of the book, is that we should be looking to the mathematics of information theory rather than the mathematics of optimization

to explain and model some of these things. But a limited liability company is an information filter. It tells you that outcomes below a certain amount aren't going to affect you anymore. And that changes your information world. It changes what you care about. But then what I think really started doing the damage so to speak, was the development of the leverage buyout in the 1970s and the shareholder value

movement as it was kind of really kicked off by Milton Friedman's essay on the social responsibility of a business to increase its profits, New York Times 1970, but then built on by just the entire kind of two decades of business school research that followed from that. because again, thinking about it information terms, a leveraged buyout is a massive screaming signal. The requirement to make the payments on debt becomes a signal that swamps anything else you might be thinking of. Because if you are a CEO and you've got LBO levels of debt, that's your priority. You can't think about anything that isn't related to servicing that debt. Let's go back and talk about the sort of big picture ideas in your book.

You talk a lot about this field called cybernetics. And cybernetics is a name sounds like something that they would have come up with in the early 90s, like the Wired Magazine people, like would get into like cybernetics in 91. But actually this field has been around at least since the 1940s. I'm surprised they even had a word like cybernetics in the 1940s. But what is cybernetics? and talk to us about the sort of general framework you use as a sort of to start talking about the stories in your book. Sure. I mean, you're right. It was, it's Second World War kind of talk. It's originally from a word meaning the man who steers the boat. So it's cybernetics in that sense. And the first guy to use it was a scientist working on creating an automated gun site for the United States Air Force.

And the idea here is that there is some quantity that is preserved in an automated gun site between the operator, the radar, the server motors, and all the components of that system, and that component is information. And so at the time, this was Norbert Vina, I'm talking about the scientist in the automated gun sites. another guy working in the same field you might have heard of was Claude Shannon at Bell Labs who was inventing information theory

at Bell Labs and has some fundamental theorems there and in many ways science of cybernetics is information theory applied to control so you might have an information theory kind of piece of maths that tells you

how much bandwidth you need to transmit a given signal and the cybernetic interpretation of that math would be that it's telling you how much capacity you need to manage a system that's of similar kind of noise. So this was all made huge use of in controlling things where you have access to the whole information environment. So a lot of that early maths from the first cyberneticians has just kind of stayed with us. through the invention of the electronic computer, and a lot of it is actually at work in really modern artificial intelligence. Merigai called Ben Rech, who works on recommendation algorithms, and he's quite upfront that a lot of his fundamental mathematical techniques are from the 40s and 50s, just being applied in the context of massively more computing power. What I'm interested in is where you take those kinds of theorems and apply them in a slightly more unrigorous, slightly more metaphorical sense to situations of management and organization where you don't have access to the full information environment.

And you just have to say, we're going to think about this not in an optimising economics kind of neoclassical economics sense. But we're going to think about this as a system that has to be kept under control. And we're going to say, well, how much resource do we need in order to stabilize this system as a system? Which is a kind of abstract way of looking at it. But it's the same fundamental problem of management. How do you get a drink from a firehouse? How do you match your own capacity to manage to the complexity of the thing that you're in charge of? Wait, can you give us a practical example of the application?

of cybernetics, I guess, because it does sound, to your point earlier, it sounds a little bit abstract in my mind. Well, I mean, practical example, I think, is the history of the development of the corporation. So from the first days of the American railroads, which were probably the first really big corporate structures the world ever saw, you have this problem that as the network builds out, it gets more complicated. and the ability of the head office to manage it doesn't grow faster. And you can try and solve that by adding more people.

You can get a great improvement by adding wireless telegraphs, but fundamentally at some point, this railroad is going to grow big enough that you have to devolve. You have to split it into branches, and you have to give autonomy to some of the subsidiaries, because that's the only way that you can match the bandwidth of the management to the bandwidth of the control problem. So I'd say that what we always see in any big organization is that it grows, it gets more complicated, it tries to deal with that by adding more resources at head office, it ends up not being able to keep up, and then it reorganizes. and the reorganizations almost always either involve pushing responsibility down to the shop floor or down to the branches,

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What are accountability sinks? The accountability sink is just, it's a name for a particular move of cybernetics that I notice a lot of, of these days, which is when you consciously break the feedback links from the subjects of a particular decision to yourself or to the unit that's kind of meant to be making it. So your gait agent, Joe, is just a classic example of the accountability sync because they talk to you with the voice of a corporation and they say that this is the policy, there's nothing I can do to change it, and then you only able to talk back to them as a human being like yourself. So you can't get mad at them because it's not their decision. They communicate.

People do get mad. Just to be clear, I did not get mad at my nine hour. There's a video of Joe out there somewhere. There's no video. I just sat there and I like closed my eyes. And I did stand around because I was sort of curious the gate banter, but I did not get mad. I just want to establish that. Yeah, but then you might ask them, and I will confess I've done this, I've asked someone politely for the phone number of someone who I can call up who is responsible for that decision. And it's not the policy. You can't get that phone number. The whole point of this was to create a sink into which unpleasant feedback can be poured and dissipated harmlessly. And when you start thinking about these things in terms of accountability sinks, you start seeing them everywhere.

because everywhere that there's a policy that can't be broken and no feedback to the person who could get the policy changed, that's an accountability sink. That's a way that someone has protected themselves from the consequences of their decisions, possibly at huge cost to the organization that they're working for, but possibly not. I guess I'll ask the obvious question, which is how do we break out of accountability sinks? And I think the frustration with everyone is that, you know, you feel powerless when you're caught in one, when you can't get the answer that you want or when you can't speak to the decision maker and try to reason with them or explain why this might be a one-off or a peculiar situation. And then it just feels like the idea of actually starting to break apart some of these sinks and move to more of an era of personal accountability. The book stops here and all of that. Skin in the game. Yeah.

There we go. It just seems further and further away. Well, it is. And the horrible answer to your question, Tracy, is that maybe we can't or maybe as individuals we can't. And that's actually, in my view, potentially very bad news for society because all of this sync, you know, all of this negative emotion from people about the way the world is goes into the sinks. But like any sink, it piles up and it piles up. And then after a while, it all spills out. and then suddenly we get things like Brexit in the UK or kind of first go of Donald Trump in the USA.

We get people who are used to being decided upon and used to being ignored, getting steadily more and more dissatisfied with the system. And then finally, they start to use the only power left to them to just use their votes in a way that says, I am no longer satisfied with this. This is no longer tolerable to me. I'm going to use my vote to tear this system apart. And so with all these things, you can divert these things for a while, but it's at the cost of building up fragility. Yeah, I have to say, you know, I didn't finish your book. I read about, I'm about halfway through, but it did leave me fairly nihilistic or pessimistic that it's like these are these inexorable, centrifugal. or centripetal forces I can never remember which is which and they're pulling us into all of these sort of high stress decisions and it's really bad and things are going to keep breaking and we're going to get angrier and angry. We talked about AI in the beginning and a sort of provocative idea that you talk about in your book is the idea of the corporation as it exists and as we've

known about it as already a proto AI. So you go to Chad GPT and you put in a request and something things spits out and it's impressive, whatever. But that actually this is just sort of a specific example of what the corporation has been for a long time. Absolutely. I mean, and this is the beauty of abstract math. It describes things without you needing to know what they actually are. These are all just decision-making systems. Add a conversation with someone at the European Commission the year before last, because in Europe they passed in act saying that if a decision is made affecting you, like to turn you down for health insurance, then if that's made by an algorithm, you have a right of explainability. So you have a right that someone can explain to you

why that algorithm made that decision for you. And I thought, that's quite good, but it's kind of ironic that this decision is coming from the European Commission. So I asked the guy who works there, well, you know, when you make a decision like that, what right of explainability do I have from you? And the answer is, ha, ha, ha, no, none at all. Um, All these things are basically working in the same way. The AI is working like the corporation, which is working like the government, and the same problems of information management affect them all. But it's not as nihilistic as you think, in my view,

because that means that these things can be subject to the same kinds of solutions. If we think about the original reason for building the accountability sink, it was that someone felt overwhelmed by information and so didn't feel that they were responsible for the decision and so wanted to cut the link of accountability. If you can put the AI in the loop in such a way that the decision maker is more able to manage their information flow, then they don't have so much need to break the feedback links

because they've got more functional ways to deal with them. I have a theoretical question, which is, what does accountability actually look like for a decision taken by an algorithm? Is it that like we understand the factors that went into the model and like the decisions within the model that spat out a particular outcome? Or is it that the person who is using the algo, you know, decides to think more thoughtfully about how they're using it. That's a really interesting question which I'm going to think for two seconds. Yeah, go for. And waffle before answering, which is that I think the basic definition of accountability in the decision sense in my view is that you're accountable for a decision exactly to the extent that you are able to change it. So in terms of a decision made by an AI, it is accountable if it could be made.

to make a different decision by new information being provided to it. So the crucial thing is not so much having someone to point at and attribute moral responsibility to. The crucial thing is to have some link between the subject of the decision who can just say, let's review this, let's have a court of appeal. And if the ALGO still thinks that this decision needs to be done, If the ALGO still thinks I'm not an insurable risk, then maybe I've been, maybe I still don't agree with that, but at least I know I've been heard. It's not coming to me just simply as a one-way communication channel. You know, making a more optimistic view, so you said something interesting

or important, which is that for a company, the financial numbers are the closest thing, the closest form of information that is at least like objective in some sense. But then there's all these other things like how well is your engineering team working together? How is the culture that are just inherently much more difficult and they're all kinds of like consultants and other companies that try to like answer this for executives and, you know, rank employees on different things. Aaron Levy, you know, he's the CEO of Box and he's one of the few like tech CEOs who tweet some interesting stuff from time to time. But he said he had this recent thread about how his company is using AI. And he said, you know, the exciting thing is, you know, we have some data,

but then we have all this unstructured data that exists in our company. And we've never been able to do with anything. It's probably like chat logs from customer support and all this. And he said the exciting thing for them is the prospect of turning all of this sort of unstructured, unusable information that the company has into something that can be essentially searchable and that insights can be gleaned from it. Is there a story or is there a path in your view where artificial intelligence can actually make some of these other parts of a system more legible and more interactive and more concrete to the executives in a way that brings that other data on par with the financial data? I mean, I really hope so. I mean,

that kind of one thing that Aaron Levy could do that would be really radical would be to open up as much of that data as possible to the investors and let them pass it and have that as a main channel of communication of corporate performance rather than generally accepted accounting principles. Because if you think about that phrase, that's an accountability sink right there. What are these accounting principles? They're generally accepted. Can I change them? No, that would not be generally accepted. What if this is completely irrelevant set of metrics to my business? Well, you still have to do it in exactly this way, even if it's not presenting what you think is actually generating value.

And in a world where we've got better ways of processing bulk information like that, then I think there's a real question about whether gap is something that we should be so fixated on, whether we should be thinking that the only way to report corporate performance is in a way that's optimized basically for a guy with a green eye shade sitting on a desk in the beginning of the 20th century flipping through printed reports and accounts. You know, that's not the way that we process information anymore. And so maybe that shouldn't be the way that we report information anymore because, as you say, these assumptions that go into gap earnings start driving decisions, and they were never meant

to drive decisions. It's interesting, Tracy, now thinking about it in the financial sense, how many of these accountability sinks, like even like performance benchmarks, right? It's like, oh, we beat the S&P or whatever. It's like, why the S&P, et cetera. Well, you know, it's there, right? We could point to it and we could say it. But like once you start thinking of them in all of the indices and measures, we cite you

could see, Tracy, how they like serve that purpose of just like, yeah, look, this is what we measure against. Oh, yeah, of course. I mean, incentives matter, right? Like, that's something that we say over and over again on this podcast. And when it comes to accounting, okay, just to push back a little bit, but like there is an argument to have standardized accounting rules so that we don't always end up with companies running off and creating community adjusted EBITDA and things like that.

But on the subject of incentives, I wanted to ask, you know, I. I read David Graber's bull's bullshit jobs this year, and it's still sort of looming large in my memory. And I guess my question is, how much overlap is there between the accountability issues that you describe in your book and the way specific jobs, especially middle management, are structured? And I don't mean to trigger you because I know that you mentioned in the book that you got into it a little bit with Graber over a different subject. But if you want to talk about that, too. Oh, I miss David so much. as we used to wind each other up so badly.

And I got into an different argument that's not mentioned into the book over bull-should jobs. Because it's just like, if you're saying that middle management is a bullshit job, then you're saying that the cerebellum is a bull-shaargon. The middle management exists precisely because of all the metrics and all the financial and non-financial metrics

on the chief executives dashboard, are massive information-reducing filters. The middle managers are the people who carry the knowledge of the ways in which those metrics can misrepresent reality and how to cure the problems which arise when someone's in danger of making a decision. The first thing a bad company does before it creates something like the LIBOR scandal or the 737 Max is thin out the ranks of its middle management. And this particularly, without wanting to relit the gate arguments with David Gray, but particularly since he's not around anymore to answer back, in his day job as an anthropologist, David was so subtle and intelligent about the ceremonian roles of elders and people who built consensus among hunter-gatherers to decide on what bands they would do.

And then when you have those exact same problem solving and dispute resolving jobs happening, you know, in the offices at Bloomberg or a law firm, suddenly he thinks that they're bullshould jobs. So that's a bit of a personal hobby horse. But basically all those or very many of those bullshould roles are actually the preservation of the information systems and the memory of organizations. Who was Stafford Beer and why does he loom so large in the story you tell about the world? Well, Stafford Beer was the father of management suburbanetics. He was the guy who first said, you can take the mathematics of information theory and apply it to industrial organization. He was also David Bowie's favorite management consultant. He was very, very influential on Brian Eno and the development of Ambient Mutants.

music. He was a hippie. He tried to, it's not clear that this was a joke, but he did try to invent a computing pond where the growth of algae would correspond to the solutions of differential equations. That's going to be my summer project. I've got a pond with algae. Yeah. The problem was that he used to feed them iron filings to make them grow, and after a while, the entire pond became magnetic. But he was just this crazy, larger-than-life figure who did these incredibly successful management consulting assignments, but just somehow never quite was able to get on with enough people in the corporate world to really get his ideas across. And then he ended up in Chile in 1972 with this incredibly romantic but ultimately doomed

project to reinvent socialism for the 21st century. under the IAN day government, which, I mean, realistically, it was never going to work because the computing resources were completely disproportionate to the task. But it never got a fair trial, obviously, because the Pinochet coup happened about 11 months after he started the project. So what do we talk a little bit more about, like, the current day? You know, I started in the conversation, like, kind of, not disagreeing, but questioning the premise, like, the world has lost its, has the world really lost its mind or just the three of us in this conversation getting old and angry. What do you see?

Like when you think about like applying, you know, we talked about Boeing and you mentioned the LIBOR scandal. But how are these things when you look around the world today and you look around whatever apparent world losing its mind, what are you saying? I think the number one thing I'm seeing. And this is a point where David Graber had it absolutely right is debt. You know, we have so many cases at presence of companies. where you have plenty of people who know exactly what they need to do, what investments they want to make,

but they can't have any plans which stretch out any further than the next debt repayment. And to a large extent, that's because of leverage buyouts and management acting in anticipation of the risk of a leverage buyout. but this really is a degradation of the higher functions, the brain functions of the corporations of the Anglo-Sphere world. The practice of firing middle managers, because you don't know what they do, is also demonstrably, in my view, making corporations stupider. It might have been that at the start of the LBO boom in the 70s, there were too many of these guys on soft jobs with country club memberships and private jets and whatnot,

but we've clearly gone too far in the other direction in my view. And then we've got the frightening tendency of government organizations to outsource absolutely critical functions, which means that all of the knowledge of the systems that they're meant to be regulating and dealing with. What's an example of that? Right. Best example currently thinking. I think just the question of infrastructure building, for example, in the UK, where there's a river crossing to the east of London, which is being responsible for generating the largest pile of paper ever brought together in one place in the history of humanity.

And the reason for that is that the people who are meant to be deciding what an appropriate level of consultation is don't know anything about environmental impact studies and building bridges anymore. So they commission reports. They commission reports from professional services firms and professional services firms want to generate repeat business. And so you've got this situation where the people who are meant to be seeing the whole system as a system don't really understand it anymore because they've outsourced all of their engineering knowledge, all of their economic and environmental knowledge. And as a result, the UK or the London Department for Transport are going to be paying as much as 10 times as much as it should reasonably cost to build a bridge over the River Thames. It's interesting that you single out debt as a sort of deciding factor versus share price, because this is the one we hear a lot about in the context of corporate short-termism and people usually trying to hit a specific share price metric that may or may not be tied into their compensation.

Yeah, I think I'm right on that. I know that people disagree with me, but we had share prices in the 50s and 60s, and we didn't have this kind of problem of short-termism. The difference is that now we've got takeovers, particularly private equity in LBOs, but also in general the use of debt in takeovers. And that makes the share price more salient, because any incumbent management knows

that if the share price falls, it makes them vulnerable to a takeover. So to my mind, I think it's not so much, the share price as the exaggerated importance of short-term financial metrics, which is partly through the share price, but much more just simply because of leverage. One of the things that you mentioned the UK bridge, and it's 10 times more expensive than it needs to be in a pile of paperwork, I mean, this is probably the number one thing that, like, you know, people I follow on Twitter talk about all the time, which is just how hard it is

to build anything in the United States. States and the interlocking systems of environmental regulations and NIMBY's and everything else. And it's the big challenge of the IRA. And it feels like listening to this. It's just accountability sync after accountability sink is to blame. It's absolutely. And it's accountability sinks being put up because the people who were meant to be taking the decisions and who in the 1950s and 60s did take the decisions are no longer really able to. They've not got the confidence of their decisions.

They're not sure they're going to be able to defend them in litigation. And it's mainly because they've lost their executive functions with successive staff cuts and retirements and outsourcing contracts. Dan Davies, it's so great to catch up with you. It's fascinating conversation, fascinating way of thinking about the world. Highly recommend everyone check out your book, The Unaccountability Machine. Thank you so much for coming back on Outlaw. Thanks for ever so much. It's always a pleasure.

Tracy, I really, I love talking to Dan. First of all, I just like hearing his voice. You know, I do think like accountability sinks is now going to be one of those phrases that I'm just going to now start seeing everywhere. And, you know, there's a whole industry like McKinsey, right? Like that's like, you know, it's like, oh, get someone else to lay off your workers, et cetera. Like you just start seeing how big that is everywhere. Well, this is what I was thinking. You know, you brought in the U.S. example of building infrastructure or other energy products.

And I kept thinking back to Jigger Shaw and his point about the lack of institutional memory. of how to build nuclear power plants, right? It's not necessarily that it's so complicated to get environmental permits and things like that, although that is certainly a part of it. But it's also that the people who used to do this haven't been doing it for a long time or are no longer around.

And that kind of goes to Dan's point about middle management being the sort of like, what's the word I'm thinking? Connective tissue. Connective tissue is a good one of like institutes. memory. Yeah. No, it's totally true. You know, in defense of the NIMBY, you know, I keep mentioning this New York documentary I'm watching and I got to the... Oh, yeah, I want to watch that. You got to watch it. But I got

to the episode where it like really talks about like Robert Moses and just like plowing these big highways through neighborhoods and putting up these like terrible like terrible housing projects that are like, you know, sort of... Right. Continuously prioritizing highways. That is someone who did not have the problem of NIMBY. or a million different interlocking constraints on him. Like there are drawbacks to when someone has like too much autonomy. And it's sort of like, yeah. But now it does seem arguably we've gone too far in the other direction

in which everyone just clings to their accountability sink and can't get anything done. Everything is a collective decision. Therefore, no individual can be held responsible. Yeah. I feel like there must be a reasonable middle ground. And yet I don't know. I'm trying to think if I know of like any organizations that have completely cracked like the nut. Just for a little while.

Yeah, collectivism versus individual responsibility. I don't know. Well, on that note, shall we leave it there? Let's leave it there. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Joe Wisenthal.

You can follow me at the stalwart. Follow our guest, Dan Davies. He's the author of the book, The Unaccountability Machine, why big systems make terrible decisions and how the world lost it's mine. Go check it out. His handle is at D Squared Digest. Follow our producers, Carmen Rodriguez, at Carmen Armin, Dashel Bennett at Dashbot, and Kale Brooks at Kail Brooks.

Thank you to our producer, Moses, Andam. For more OddLod's content, go to Bloomberg.com slash oddlots. We have transcripts, a blog, and a newsletter, and you can chat about all of these topics 24-7 in our Discord. Discord.g.g. slash oddlots.

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