Fear Is Not Going to Save Us From AI

Summary

Podcast Summary: Firewall with Bradley Tusk

Episode: Fear Is Not Going to Save Us From AI

Date: June 11, 2026
Guest: Daniel Schreiber (CEO of Lemonade, Founder of Mosaic AI Policy Institute)
Location: P&T Knitwear, 180 Orchard Street, NYC

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Episode Overview

This episode features a compelling discussion between host Bradley Tusk and serial entrepreneur Daniel Schreiber. They explore the intersection of artificial intelligence (AI), employment, economic policy, and the potential end of poverty in an “era of abundance.” Schreiber outlines his Mosaic model—a policy proposal for capturing AI-driven productivity gains and redistributing them via a negative income tax to support society amid widespread job displacement. The conversation balances technical insight, economic history, and pragmatic policy design, all while honestly confronting the future of work and meritocracy in the age of AI.

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Guest Background and Context

[00:27] – [01:54]

• Daniel Schreiber shares his background: English origin, lawyer by training, current CEO and co-founder of Lemonade (a groundbreaking AI-centric insurance startup).
• Lemonade’s aim: Use technology and AI to radically transform the insurance sector, “reinventing it from the ground up.”
• Schreiber credits early adoption of AI in Lemonade’s core strategy, noting, “The very first words of the deck are artificial intelligence, not artificial delays. And this is 2015.” (Schreiber, 04:00)
• The conversation moves toward Schreiber’s more recent work founding the Mosaic AI Policy Institute, a nonprofit think tank focused on policy responses to AI-driven disruption.

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Key Discussion Points & Insights

1. AI’s Impact on Employment and Society

[05:08] – [08:47]

• Schreiber traces his journey from curiosity about AI ("reading Nick Bostrom back in the day") to real-world concerns as CEO: Lemonade expanded customers and gross profit with fewer human employees since the arrival of ChatGPT.
• “We kind of fired thousands of people that we didn’t hire.” (Schreiber, 05:47)
• Schreiber admits excitement as a CEO but concern as a citizen, father, and grandfather: AI’s labor displacement is both a business advantage and a social threat.

[13:01] – [14:49]

• The hosts discuss whether the AI revolution will repeat the patterns of Industrial and Agricultural Revolutions (automation disrupts jobs but eventually creates new opportunities).
• Schreiber cautions: Unlike previous revolutions, AI can replace both “brawn” and “brain,” diminishing human competitive advantages.
• “Anything of value that can be done in neurons running on a piece of protein can be done by neurons running on a piece of silicon, including cooperation. Anything.” (Schreiber, 17:23)

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2. Founding Mosaic AI Policy Institute

[08:47] – [10:21]

• After being “politely thrown out” of policy rooms in Israel for raising early alarms about AI-driven job loss, Schreiber starts Mosaic to fill the policy gap.
• The goal: Bring together advisors and thinkers to develop actionable, forward-looking policy (not just analysis).

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3. The Mosaic Model: Economic Theory and Policy Proposal

a. The Core Thesis

[10:21] – [13:01]

• Schreiber’s central realization: Unlike previous unemployment cycles (where job loss contracts the economy), AI-driven replacement increases production despite reducing employment.
• “The actual pie gets smaller as unemployment grows. The aha moment for me was realizing that when I’m replaced by an agent…production goes up. It doesn’t go down.” (Schreiber, 11:59)

b. Follow the Money: Where Do AI’s Gains Go?

[19:06] – [21:17]

• Displacement by AI shifts saved salary expenses to companies’ profits or passes them to consumers through price reductions.
• "If unemployment doesn't surge, then you won't have those cost savings, you won't have the price drops. But if you do... this will capture, so is the value captured." (Schreiber, 21:17)

c. The Mechanisms: Capturing AI Abundance

• Rising VAT/Sales Taxes: As automation lowers prices, raise VAT/sales tax in lockstep to capture the difference, but keep consumer-facing prices steady.
  • “I follow the CPI. If it’s gone down, then the VAT for that category goes up.” (Schreiber, 23:26)
• Ring fencing corporate tax windfalls: For sectors where profits spike due to AI-driven reductions in costs, separate (“ring fence”) tax revenues above the historical trend to fund social provisions.
• The critical point: No new taxes or price shocks; only new mechanisms for distributing unexpected/extra gains.

d. Preventing Market Abuse

[24:10] – [24:38]

• Schreiber argues for competitive markets, not price controls, with the need for robust anti-collusion and antitrust enforcement—especially in concentrated sectors.
  • “You need to prevent collusion.” (Tusk, 24:37)
  • “That’s right.” (Schreiber, 24:47)

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4. Redistribution: From Theory to Practice

a. Negative Income Tax

[34:29] – [36:08]

• The captured AI gains fund a negative income tax: below a certain income, people receive payments to keep them at a minimal standard, not a universal basic income (UBI), but targeted.
  • “Below a certain level, you get paid money.” (Schreiber, 35:32)
  • This preserves a work incentive since the subsidy phases out as income rises.

b. Policy Design & Implementation Challenges

• Schreiber and Tusk discuss potential risks—especially political “raiding” of funds and the challenge of maintaining clear, earmarked allocation (the “lockbox” problem).
  • "Anything that trusts politicians is a problem." (Schreiber, 40:18)
  • Tusk suggests the possible use of blockchain or independent oversight for transparency.

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5. Alternative (and International) Approaches

[42:11] – [44:20]

• Alternatives: Sovereign wealth funds or giving citizens equity in major AI companies (as floated by Bernie Sanders in the US and, de facto, in China).
• Schreiber reasons: this only works where AI platforms/companies are based; other countries (UK, Israel, etc.) need local mechanisms, hence VAT- and tax-based models.

b. Scalability

• Schreiber asserts Mosaic’s model works broadly in OECD countries, especially in economies with VAT infrastructure, and has gathered international interest and support.

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6. Politics, Public Sentiment, and the Future of Work

[46:28] – [47:23]

• US anti-AI sentiment is especially strong and bipartisan, increasing the urgency to create reassurance and fair redistribution.
• Tusk predicts AI will dominate political discourse by the 2028 US election cycle.

[48:47] – [50:04]

• Schreiber highlights that, beyond economics, AI challenges the philosophical foundations of meritocracy:
  • “An AI economy does real violence to the meritocracy narrative today… If you think your son is worried about just the narrow what job will I have or will my kids have? When you tie that with a sense of unfairness…you're really shaking some of the fundamental philosophy underpinning how the US Economy works.” (Schreiber, 48:47)

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Notable Quotes & Moments

• Daniel Schreiber on AI’s Potential:
  • “We have been premised on the idea that chatbots and machine learning and AIs are going to be able to outperform everything that humans do…This is the moment we've been built for.” (04:00)
• On Mosaic’s Policy Model:
  • “Below a certain level, you get paid money. It’s not quite universal basic income…I need less money to fund my program.” (35:32)
• On Human vs. AI Capability:
  • “Anything of value that can be done in neurons running on a piece of protein can be done by neurons running on a piece of silicon—including cooperation. Anything.” (17:23)
• Tusk on Societal Inequality:
  • “You can't have a world where people are struggling to put food on the table…and then at the same time people have an extra $300,000 to go to a basketball game. That's not sustainable.” (27:00)
• Schreiber on the End of Poverty:
  • “In an era of such abundance, it would just be unforgivable for there to be poverty. Poverty should end in the era of abundance.” (28:08)

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Key Timestamps for Important Segments

• Background on Schreiber & AI in Insurance: [00:27] – [04:38]
• Impact of AI on Lemonade's hiring & labor: [05:08] – [07:31]
• Shift from academic worry to policy action (founding Mosaic): [07:31] – [10:21]
• Economic thesis of Mosaic: [10:21] – [14:49]
• Historical precedent: Comparing AI & the Industrial Revolution: [13:01] – [15:21]
• Venn diagram of human vs. machine capability: [14:49] – [17:23]
• Following the money, VAT/Tax mechanisms: [19:06] – [24:38]
• Antitrust and market competitiveness: [24:38] – [27:00]
• Redistribution model & negative income tax: [34:29] – [36:08]
• Challenges of real-world policy implementation: [36:25] – [40:18]
• International scalability and alternatives (sovereign wealth funds, equity): [42:11] – [44:20]
• AI, public sentiment, and future politics: [46:28] – [48:47]
• AI, meritocracy, and social contract: [48:47] – [50:04]

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Tone and Style

The episode is analytical, candid, and often lightened by humor and relatable references (“William Shatner [and] Le Corbusier—they're kind of very similar”). The hosts balance pragmatic economic policy talk with philosophical questions about work, fairness, and meaning in an age of AI.

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Conclusion

This conversation is essential listening for anyone interested in how AI will reshape work, wealth distribution, and the social contract. Schreiber’s Mosaic model offers a technocratic yet politically aware attempt to “bring everyone along” as society transitions to an AI-powered economy. Both guest and host are clear-eyed about the political and practical hurdles, but optimistic about the potential for bold, creative policy to create a future where abundance is shared rather than hoarded.

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Resources Mentioned:

• Mosaic AI Policy Institute (For the technical paper and infographics)
• Contact: [e-mail] or Bradley on LinkedIn

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Transcript

[A]

Foreign. Welcome back to Firewall. I'm your host, Bradley Tusk. My guest today is someone that I have known for a while now and I'm really excited to have him on, Daniel Schreiber, who I got to know when he was the co founder. He still is the CEO of Lemonade and that's how we met. Although this podcast is not about that. But Daniel, thank you so much for joining us.

[B]

Great to be with you, Bradley.

[A]

So let's just do a little background. I think most, a lot of the listeners probably already know who you are just cause we talk about Lemonade in the show sometimes, but your background, Lemonade itself and then how that all eventually led to the work you're doing now as well with Mosaic.

[B]

Sure. So the remnants of my English accent will tell you that that's kind of where I was from originally. I'm a recovering attorney. I practice law for a very short period of time and I've been clean for 25 years.

[A]

I'm not sure that's long enough yet.

[B]

Yeah, I'm still counting.

[A]

So yeah, I'm proud to say that I am technically a member of the New York bar and have never actually practiced law.

[B]

There you go. Daniela, my wife, we have three boys, a couple of grandkids, and I've been in tech since. Since I left law in the. In the late 90s. So entrepreneurship, entrepreneurship. Bigger companies, smaller companies. And then 11 years ago, co founded Lemonade. And as you say, I've been the CEO ever since. And that's really an attempt to take everything that I and my co founder had done in our careers up to that point and bring it to bear on the world of insurance. So reinventing it from the ground up to using technology in all its facets, direct to consumer AI, machine learning in order to disintermediate the agents, but more importantly, just profoundly change the plumbing. This is an ephemeral product, a statistical product. It is so amenable to disruption and it's like 11% of GDP. So bringing all of that to bear on Lemonade. And it's been an amazing journey.

[A]

Yeah, I mean I was, I forget what the context was, but I was using Lemonade as an example the other day of kind of regulatory capture which we did face right when we were trying. So. So I was lucky to have the opportunity to both invest in Lemonade and then work to get them their insurance licenses in different states. And we certainly faced a plenty of opposition. But I think the point I was making to someone was the reason that it worked I think we ran good campaigns, but much more fundamentally it was a different kind of product and thesis and approach and, and that's what. You can't just run a good political campaign. A good political campaign combined with the right underlying product can succeed. But I think whatever startup I was looking at, I was making the point to my team, like we can do our job, but the there is not there. Right. What was it the thing that you, when you look back and obviously you guys have had tremendous success, but what was that one thing that you think you realized and then kind of executed on that just made Lemonade? It just feels different than everything else, if you know what I mean.

[B]

Yeah. And you know, you go into an Apple Store and everything feels different, but it's a lot of stuff behind the scene that allows that kind of the simplicity of the end user experience belies the complexity beneath. So there's a lot. We changed the business model, we changed the technology stack, we changed the distribution method, the branding. The name Lemonade was such an outrageous name early on. And you know, it's not state or farm or something.

[A]

Right? Yeah.

[B]

Choose dark navy and dark red as our two colors. We went with the bright pink.

[A]

So we have to change the light all out of the deal.

[B]

So really we kind of threw around the tagline of forget everything you know about insurance. And I think that's something that we've tried to live up to.

[A]

Yeah, very much so. And then when was the IPL? Like 1819, something like that?

[B]

No, it was six years ago, almost to the day. Okay, July 2nd will be six years.

[A]

Okay. Obviously great outcome. And you've stayed.

[B]

So what.

[A]

I mean, a lot of times at this point, someone who was the co founder and CEO and had an incredibly successful exit has kind of moved on completely. What has made you choose to kind of keep running the company?

[B]

It's been an exhilarating journey and continues to be. And I think some of the stuff we'll talk about tangentially related is we were born and built for the AI era. You know, my founding deck, to my first board meeting laid out a strategy. And the very first words of the deck are artificial intelligence, not artificial delays. And this is 2015. So we have been premised on the idea that chatbots and machine learning and AIs are going to be able to outperform everything that humans do. And focusing all of that energy on insurance. This is the moment we've been built for. Building towards this is no time to leave. Right.

[A]

Makes total sense. But as one does, especially someone as intellectually curious as you, the mind does wander a little bit. And you chose to take on an additional project that I'm really excited about. And that's why you're actually here for the podcast today. When. When did sort of you start thinking about, okay, beyond running an insurance company that's sort of built for the era, I want to tackle some of the larger societal challenges around it. When did you start thinking about that? And then how did that result in you actually taking action?

[B]

So in terms of the mind being piqued and the curiosity, that's been there for a while, and I've been tracking this with interest. I found my old interviews of mine from 2016, 10 years ago, talking about how human level intelligence is 10 to 15 years out and talking about what that means for humanity. So I was apparently. I don't remember this, but the record shares. I've been thinking about this for a while, reading Nick Bostrom back in the day and all these kinds of things. But in the last three years, three and a half years since chat, GPT kind of exploded onto the scene, I've been seeing this in spades at Lemonade, and that's really changed my vantage point from curious to engaged. So the business has tripled its revenues in the last three and a half years or so. Almost gross profit is more than 10x up. We've added close to a million and a half customers, and yet we have fewer employees today than we had when ChatGPT launched. Now, we haven't had to do rounds of layoffs because we've been growing so fast and we've been able to keep things static, but. But we kind of fired thousands of people that we didn't hire, if you know what I mean. The impact for employment is profound, and I see no end in sight. I think we may well be at our terminal size, and in the fullness of time, we might even allow ourselves to shrink further. And as a CEO, I'm unapologetical. I push for this, I promote this. I'm excited by this. It animates me. It's amazing for our shareholders, it's amazing for our customers. As a citizen, as a father, as a grandfather, it gives pause.

[A]

Totally. Iran Shears in town, and I was meeting with him the other day, and he has a new company. And I said, so how many people? He goes, 50. Two. Me, Bruno, and 50 agents. Yeah. And I was like, obviously, he's gonna need to hire more people as he builds this out, is what we put out together. But, like, his point was Very much the same as yours. Okay, so the problem's been apparent to you for a long time because human beings need to work, or at the very least, they need income to live. Right? So you see what the reality is at a company like Lemonade, and that's a company that I think generally pretty much everybody would agree with this, wants to do good, wants to look out for its employees, like it's starting in a good place. Which I wouldn't say is true of every tech company out there. And then was there an aha moment where you're, did the policy idea hit you first and then Mosaic, or was it more that you said, I want to do something and you hired some people and started exploring?

[B]

So about three years ago, as I was seeing this in our numbers, and it moved from just being a theoretical possibility to something concrete, I started doing the rounds. I live in Israel. My concerns are global, if you like, but my action is more local. And Israel is a relatively small economy, relatively tech forward. I have relatively good access to decision makers. And I thought, okay, let's start. This is an OECD country that could be a testbed. And I started doing the rounds and I went to the think tanks, to the equivalence of the Brookings Institute and to major economists and stuff like that, and started sounding the alarm bells and saying, hey guys, we have to start thinking about this. And I was politely thrown out of every room I went into. We're not seeing it in the data is one thing. And I was like, of course you're not seeing it in the data. This is a forward looking thing that I'm trying to warn you about. This is in the rearview mirror. And then there's the other platitude that you get every time, which is, you know, it's always worked out in the past, you know, and the boy who cries wolf kind of phenomenon. And I try to remind them that that story does not have a happy ending.

[A]

Right?

[B]

It's like, that's not best example. And it was actually out of my failure to kind of move hearts and minds that I decided to found Mosaic. And I said, well, if no major think tank and policy institute is going to take this issue seriously, I'm going to have to say at this point,

[A]

the policy solution that we're about to spend a bunch of time on, had it occurred to you, so you were starting with the, okay, there's a problem that needs to be solved. No one's taking this on. Someone needs to do it. And you had the expertise, the money, everything to choose to do that. So then what happens?

[B]

We founded a nonprofit think tank. It's called the Mosaic AI Policy Institute, hired some people, collected an incredible board of advisors for the former chief economist of the state of Israel and the accountant general of the state of Israel and all the leaders of the democratic institutions of Israel. So the kind of state court philosopher of Israel, all different minds, get them all together and started trying to a sound the alarm bell. So talking about AI now, you can't turn on the news or turn over a sheet of paper anywhere without hearing something about AI. But back in 2023, that wasn't the case. People were still in the phase of, ah, you know, it's producing pictures with six fingers. And I try, asked it to do whatever and it wasn't any good. And there was a general skepticism that this will ever amount to anything. So it starts off with sounding the alarm bells and saying, no, no, no, look at the trajectories, don't look at the point in time. Play this forward two or three years, think what that's going to do. And then the real hard work of trying to think about, well, if I had a magic wand, how would I yield or wield that in order to try and capture some of the abundance and make sure that the people who are paying for that abundance with their jobs participate in it?

[A]

Explain the underlying thesis that you guys have.

[B]

Sure. So for me, one of the kind of aha moments was in conversations actually with my elder brother Sri, who's written some books on economics. And I was trying to get him to educate me and it dawned on me, I started doing kind of thought experiments and it dawned on me that kind of by definition, there's going to be enough money in the system for everybody, which is a novelty because we tend to think of unemployment as being a problem of insufficient.

[A]

Is that not always the case though? Like take hunger, right? If you could somehow solve every distribution problem and political corruption problem, transportation problem, everything else, there is enough food grown and produced globally to feed all 8.2 billion people. So is it always that both things exist in equilibrium, but we don't know how to distribute? And now you figure out a way, or do you think it's that AI creates that condition?

[B]

Well, hunger is largely a solved problem. It's actually a good example of how this can get solved.

[A]

There's still a good half a billion to a billion people.

[B]

There's pockets of it. You think about when you and I were younger in the 80s and Bob Geldof was drinking. We don't have that as much yet that anymore. So, but I, I, I, my kind of insight was slightly different, which is unemployment is a scary word. And it's a scary word because in our minds it leads to, you know, soup kitchens and to poverty. And the reason it leads to poverty is because it contracts the economy. So one person is laid off. That means that there is less production happening in their economy. There's also less consumption because that person doesn't have a salary, which means somebody else is now selling less.

[A]

Right.

[B]

And you get into a spiral.

[A]

Yeah.

[B]

And historically, 1% of unemployment has resulted in about 2 percentage points of contraction in GDP. The actual pie gets smaller as unemployment grows. The aha moment for me was realizing that when I'm replaced by an agent, a chatbot or an AI of one kind or another, production goes up. It doesn't go down. I'm at the beach or I'm at home licking my wounds, but actually the bot is producing 100 fold more than I did. And that's true if I'm a lawyer, if I'm a psychologist, if I'm a coder.

[A]

I mean, we talk about AI as sort of a transformational shift, and it very well may be. But another way to look at it as it's automation, as was the steam engine, as was the car, as was the computer and everything else. Is it something like we've never seen before, or is it just a step change, but still in the tradition of automation, might reduce employment or at least the number of people needed to produce something, but increases productivity commensurately.

[B]

Well, definitely increased productivity commensurately. And we tend to look back at the Industrial Revolution kind of romantically because it ended well and we're all better off and we've got better jobs. Yeah. By the first 50 years, you know, Charles Dickens and slavery in the US and so many ills and wars around the world, colonization, all those things were fueling or fueled by the Industrial Revolution. It was pretty bleak until policy stepped in and started saying, we're not going to send kids down in the mines and we're going to send them to school instead. And it actually required policy intervention to turn all of that.

[A]

That was one like early 18, mid-1800s.

[B]

That's right, it began.

[A]

Yeah.

[B]

And it picked up steam. And the church started saying sensible things and things started getting better. But I don't know that even in places that won the Industrial Revolution, Manchester, Liverpool, London. I don't know that you really wanted to live there during the first few decades. But let's Say, let's go with the happy ending. We'll skip the gruesome middle. I don't have confidence. I don't rule out the possibility, but I don't have confidence that we're in a repeat of the same movie. And the reason I don't have confidence is if you start creating a Venn diagram of machine capabilities and human capabilities. In the Industrial Revolution, you saw that when it came to our brawn, they overlapped. And actually every time they overlapped, they took all the jobs. Right. Nobody is plowing the field by hand anymore. Everything 100% of those jobs. 1790, the first census in the United States. 90 something percent of people said that they were farmers. Today it's 1.3 jobs are gone.

[A]

Yeah.

[B]

The salvation came from the fact that loads of new jobs were created. And the reason I fear that that's not going to repeat is because in that Venn diagram, machines were dumb. They were dumb as a doorknob. They were just brawn, but no brain. We had a monopoly of intellectual prowess and therefore we became lawyers and doctors and podcasters.

[A]

But that is a definite deviation from the historical trend where you have a big economic shift from technology of one kind or another. Right. There is definitely a significant period of disruption that leads to kids in coal mines and slavery or slavery's been around, but things like that. But then historically, those advances created all kinds of new industries and jobs that we couldn't have thought of at the time, but they existed. So you don't think that will be the case here?

[B]

I'm trying not to be definitive. I think we have to start mapping out probabilities and possible futures. And there are possible futures in which there are loads of jobs. My big concern, and I'll put a caveat to this in a second, but my big concern is where is going to be our competitive advantage relative to these machines? Of course there'll be new jobs in new industries. Why will we outperform AIs and robotics in these new jobs? I know how to answer that. About 200 years ago, it's because we had a brain and they didn't. What's the answer? 10, 15, 20 years from now? So new jobs are created. What portion of those jobs do we get? So there'll be some. There are jobs where provenance matters. I want to hear Bradley Tusk. I don't. I care what he thinks. I want to read his book. So provenance matters. I want to watch the World Cup. I probably want humans running around.

[A]

Right. But those are pretty in the Terms of global employment are pretty narrow, so maybe that grows. So this is a little bit of a crazy question. Maybe we'll edit it out. But okay, so when you think about the human advantage, right, so, yes, machines were dumb, we were not. If you go back 100, 200,000 years, from what I've read, obviously Homo sapiens are not the only species of human beings. And the kind of conventional wisdom is that the Neanderthals were bigger and stronger, but dumber. But from what I can tell, that's not true. They actually had bigger brains and were smarter. Where we had an advantage as Homo sapiens is that we were able to cooperate and work together. They were not. And over time, the collective power of cooperation outweighed the individual advantages of Neanderthals. Homo sapiens survived. So there's brain power, there's cooperation. Now, obviously, we're in a moment globally where we feel very zero sum and not in an era of cooperation. But let's just assume that that's not the forevermore. If you're trying to defeat the AI, right, can they cooperate like Homo sapiens have traditionally been able to? And if not, is that an opportunity for a competitive advantage?

[B]

My working assumption is that anything of value that can be done in neurons running on a piece of protein can be done by neurons running on a piece of silicon, including cooperation. Anything.

[A]

Okay.

[B]

I think that anything that you or I know how to do, Bradley, is because we've got neurons that have been forming connections and they are what's performing the work. There's nothing else. We can talk philosophically about consciousness and stuff like that, which I think is one of the most profound philosophical and scientific questions of the day. But they're uninteresting from a production and employment perspective. If you can simulate being a great therapist, I don't care what's going on behind the scenes. If you sound empathic, and there's plenty of studies to show that, I'll fall for it.

[A]

I'm working on a project right now.

[B]

There you go. So that kind of stuff we see at Lemonade, we are dealing with very delicate stuff. You know, your dog just got cancer, your home got burned to the ground. We get far more complaints about answers that humans gave than answers that AIs gave in terms of empathy and support and sensitivity. So I think that you have to assume that there is categorically nothing that you can do in one brain that you cannot simulate on a piece of silicon. And if you accept that thesis, and it's yet to be disproven, theoretically or empirically, then you really are down to relationship stuff. You want to have a hug, you want to sit and have a coffee with your friend. And there is a case to say that will become in the industrial revolution, the service economy suddenly flourished. Nobody see it. Maybe the relational economy will flourish. There are happy ending versions of this, but how much do we want to bank on that? Do you want to just assume that that's what's going to happen?

[A]

Right. Okay, so taking all that, you guys then developed an actual economic thesis that makes a lot of sense to me. So explain what it is.

[B]

Well, it starts off with kind of a fairly simple methodology which says follow the money. I'm an employer. I let one person go, I let 10,000 people go. In the news today, 100,000 people go, whatever it is. And I replace all of those people with an AI, with a robot, with some agent swarm or whatever it is. I have now saved, for argument's sake, a million dollars on a salary or salaries. Where do those million dollars go? And those million dollars go to one or two places crudely estimated. They'll either I'm in a non competitive market and I just take it to my bottom line. I sell the same number of things for the same price, but I've now got a million dollars less on my expense lines, that drops and my profits zoom up, or more likely, I'm in a somewhat competitive market and the others have the same thing. I have to lower prices, I want to capture more market share and that million dollars gets passed on to the consumer as cost savings yields price erosion. And therefore I sell more stuff, my profits still go up. But you, the consumer, are now buying my service, my widget, and you can imagine, you know, a bus without a bus driver, a taxi without a taxi driver, a lawyer without a lawyer. You can imagine how prices could start collapsing. But those are the two places profits might surge, right? Or consumers benefit and prices might drop.

[A]

Yeah.

[B]

So we said, okay, if we can capture that without changing your kind of lived experience the next day, what would that look like? So one is prices don't need to drop, the cost will drop. But what if we increase value added tax, a sales tax, a consumption tax in a way that is commensurate with the declining prices. So we model that out. So in the US you don't have vat, you have sales tax, you have other versions of consumption taxes. Much of the rest of the world has value added tax as a matter of course. And we started modeling out, not crazy rates, but something like some European countries have, which run into the mid to 20%, a value added tax. And as you start modeling out prices declining. And here's the nice thing, it's two sides of the same coin. If unemployment doesn't surge, then you won't have those cost savings, you won't have the price drops. But if you do, then you do and therefore this will capture, so is the value captured.

[A]

So there's basically the reduction in cost either adheres to the benefit of the shareholder or, or the consumer. Right. Is the money captured that. Then we'll talk about where it goes on both ends. Whether it's a tax on increased profitability due to decreased headcount and the equivalent of a sales tax increase, or is it just on the corporate side in terms of their reduction in cost and profitability as a result? No.

[B]

So it's both things. One is to say stable prices are actually good for an economy. Inflation is bad, but deflation is bad. You want consistency and therefore massive deflation isn't so good. We're going to keep prices stable. The way we're going to keep prices stable is by having a dynamic vat. So VAT will increase in a commensurate rate to overcome the price decline. And then the second, that's one stream that we capture. And then the second one is to say I don't want to raise corporate taxes, I don't want to raise income taxes, but if the revenues suddenly spike because profits spike, then governments are going to get more money than they need. And I want to ring fence those by law and say that too is a source that I'm going to now tap in order to redistribute.

[A]

Right. Okay. So on the VAT sales tax side, I guess the devil is going to be in the details in terms of how you would actually implement this. Even if you assume that all of different stakeholders are being totally honest and well intentioned to try to solve the problem, which at least in the US is never the case. But, but let's start with the sales tax side. So there's clearly a, in that case reduction in the cost of production. And then the effectively what would have been the decrease in the cost of the good is instead held steady and the differential is captured in the form of this tax. When a producer says no, no, no, no, it's not because of AI, it's because my ship had a different route that now is more efficient or because I hired a CFO that was smarter. What is, how do you determine what comes from what?

[B]

Oh, I don't even try. Okay, I follow the cpi.

[A]

That's it.

[B]

That's it. It's gone down. Then the VAT for that category goes up. You, the consumer don't notice anything because you go to the supermarket the next day. Everything is the same. The economy functions well because there hasn't been inflation or deflation. And yet I've now earmarked and captured a big chunk of change.

[A]

And how do you stop the supermarket from saying, you know, we can blame Daniel and increase the, you know, increase prices a little more, blame it on this sort of negative income tax and make more money. How do you stop them from doing that? I mean putting price controls.

[B]

No, I'm not suggesting anything like that. In non competitive marketplaces, profits will surge and we'll talk about this.

[A]

That seems easier to think about. This is the one where I'm a little more confused.

[B]

You need to be in a competitive market, right? Prices will not drop, generally speaking, unless you've got free market. But in those, you know, your supermarket example, we're not seeing Walmart behave in the way that you're kind of worried about. They tend to pass on savings in order to keep the volumes down, etc. They have to and therefore everybody else has to as well. And you get the game theory stuff played out. So I'm hopeful that there's not that much pricing power in a lot of sectors where there's decent competition.

[A]

You just need to prevent collusion.

[B]

You have to prevent collusion, correct?

[A]

That could that be. By the way, that's true for every free market regardless of, of this AI or anything else.

[B]

That's right.

[A]

Monopolistic power, that would be your biggest risk, Right. You would need vigorous antitrust. You know, it's really interesting at least in the US because I know you follow US politics and I think this is actually was pretty supportive of Lina Khan's efforts at the FTC to do antitrust with big tech simply because from my perspective, and I was surprised that I felt like I was the only one who felt this way as an early stage investor. No one ever came to me and said I want to take on Meta or Amazon wherever it was because they were so monopolistic that it was like there was no point. Right. I thought that was bad for innovation because ultimately those companies will grow stagnant like every company does. And if someone people like me aren't seeding the competitors knowing that 99 out of 100 will fail, but if the 1 in 100 isn't seeded to then be able to take the place, then you have a real hole in the economy. And what's interesting in the US is the right actually is somewhat in line with the left on antitrust, which I think is actually a very. Usually I don't like the extreme, but I think it's a very good thing because I think there should be a natural distrust. Because, you know, I see this as a vc, and I'm sure you do angel investing, things like that. So you have some version of it too, which is we pressure our CEOs all the time to do things that aren't necessarily in the best interest of the company or the consumer because we want to return on our investment faster and we want it to be as great as possible. And so you really. The incentive on the corporate side is so much so that this is a case. There are plenty of cases where there's way too much regulation. This is a case to me where, if anything, there's under regulation.

[B]

And I think there's a broader manifestation of some things you're talking about because we're already seeing within AI a massive concentration of wealth. And I think if you were to zoom out a little bit, you can reduce the AI revolution to three words. Capital displaces labor. And the last radius of that is profound. It will affect jobs, but it will affect everything else as well. And that, I think is the heart of the matter. Can we incorporate policies to make sure that people with capital are good for them, let them make money, et cetera, but that some of that accrues to the benefit of the labor?

[A]

I think the thing that is not understood right now, at least I don't see it, is that if you are just speaking selfishly, when you and I had lunch a couple, I don't know, a month or two ago, we talked about enlightened self interest as a motivating factor. That I think to you and me, kind of makes sense. But I don't know that we see it as much as we would like to across our peers. You're going to get the French Revolution if you don't. I mean, I think we're going to get it without AI, Right? So I'll give you a very specific example. I have next season tickets. I looked yesterday on StubHub. If we sold our four tickets for all three of the home games, do you know how much money we would make? $300,000. So what that means now, I'm not going to because I want to go to the games, but what it means is there are people with enough money to spend $300,000 to go to some basketball games. Now, I didn't pay that much. I pay what the tickets cost, right? But you can't have a world where people are struggling to put food on the table, to pay the electricity bill, to make rent, and then at the same time people have an extra $300,000 to go to a basketball game. That's not sustainable.

[B]

Either way, I agree with you. I think that enlightened self interest does say you've got to find a way to bring everybody along. And more than that, in an era of such abundance, it would just be unforgivable for there to be poverty. Poverty should end in the era of abundance. It should simply end. And then you've got kind of basic principles of equity. You've got stuff like the compensation principle. If I build a factory and I poison your water source, the law is going to come after me and make me compensate the people whose water source. We've all seen the movies. Those are kind of basic principles. This isn't an exact application of that legal principle. But if AI creates massive wealth at the expense of huge swaths of the population, doesn't it need to at least make those people whole, if not do that?

[A]

Right. I think, to me, at least, when we think about this from a marketing and branding standpoint, if you just make the moral case, it's not gonna work, right? So, for example, like I mentioned, I fund and run all these campaigns around the country to the US to mandate universal school meals so that every kid in school gets fed. And we've had a terrible year this year. So I've run bills in six states. I'm gonna lose all of them, except maybe I'll find out next Wednesday about South Carolina. And the thing that I've realized is even five years ago, making the case of like, well, why would we want a kid to be hungry no longer works, right? I have to rebrand the whole thing. And there's arguments around like, well, all the education money we're spending is wasted, or this or crime. I mean, there's ways we can go with it. But I do think that sadly, in order to sell something, the zero sum mentality that has at least gripped the United States right now, I can't speak to Israel as much. Although I would say you're right, your prime minister very much has a zero sum mentality that doesn't work. So let's flip over now to the how you actually figure this out on the corporate profitability part. So what's the mechanism?

[B]

If I can I want to interject with one afterthought based on what you were saying about the hunger and the children. I found myself, when I meet, I've been doing, I've been meeting with the unions, meeting with the largest employees in the marketplace, all that kind of stuff. And I find myself pitching to some of them. I said this to the unions and they took it better than you might have thought. And I've actually written a piece which says we should implement these policies not in case there's unemployment, but so that there will be unemployment. And what I mean by that is look at what happened in Hollywood in 2023. They screwed the whole industry there. As soon as you've got employees who feel vulnerable to the coming of AI, they bring out the pitchforks and they suddenly block it. And now Hollywood is going to lose out because they may signed contracts that they won't use AI, but Silicon Valley didn't sign those contracts. They're going to produce movies for a thousandth of the cost. And all of that for, for an economy, for an industry to remain profitable and cutting edge and for an economy to win, you want wholesale and rapid adoption of AI. And if that means that workers are going to be displaced, you want to give them all stock options or some equivalent so that they feel motivated to see that progress rather than to block that progress. So, and if unemployment is going to happen, you want to be a part of the economy that has the least friction around that and most smoothed path to replacing human. And by the way, we're not going to get too philosophical, but is the role of humans to work or do we go back to ancient visions of a future where we actually don't have to work? Utopia.

[A]

Le Corbusier model.

[B]

Yeah, Star Trek. There's all different visions of a future

[A]

where William Shatner Le Corbusier they're kind of very similar.

[B]

You've got all these kind of versions. So I think there are deep philosophical questions that ensue. But coming back to your question, VAT captures declining prices. I'm not suggesting an increase in tax. I think an increase in capital tax will be equitable. But it also leads to companies that just move to the Cayman Islands or to wherever they need to move. So I'm saying keep taxes exactly the same. You implement the mosaic model tomorrow, nothing changes. Prices are the same, your tax rate is the same, but you suddenly have ring fencing of various sources of revenue in the government. And what that does is. So if there's a trend line of revenues from capital gains tax from corporate taxes, et cetera. If it suddenly changes trajectory, then I want to capture the triangle that is formed.

[A]

So that doesn't require a new tax mechanism.

[B]

It does not. It's really just an allocation of. It's a government. It's a law passed that says any revenues above the historical trend line are going to be ring fenced for this purpose. And again, I'm not going to try and indicate where it comes from. I'm going to.

[A]

You know, it's so interesting. Have you followed this California billionaires tax proposal at all? Okay, so, you know, same. But I did do a deep dive on it. And it just hit me that if they. I don't know if it's gonna pass or not. The prediction markets say no. The polling says yes. My gut, just as a political person, is when there's a referendum, the person in the ballot box says, well, how does this affect me? And the answer's gonna be for 99.99% of the voters, like, I'm not gonna pay this tax. I don't give a shit. But maybe where their fatal flaw actually end up being, and they should have listened to you, is they're using health care as the argument to pass the tax. And there's validity to it, but also everyone knows that there's so much waste and inefficiency and bureaucracy in health care that there's also a very fair cynicism of like, wow, they're just gonna. It's just gonna go to unions or whatever anyway. I wonder if the way you're looking at it said we're gonna ring fence that money to help people who lose their jobs because of AI. That actually might have been. And, but, and the truth is, in government, because having run, went around the budget in Illinois, it's all kind of fungible to a certain extent anyway. That actually might have been a much better narrative for that.

[B]

Next time.

[A]

Yes, next time. All right, so now let's go to the third part of it. And then I want to go to implementation and then some criticisms that I've gotten. So, okay, so now the money's being captured through a VAT or through ring fencing or whatever you want to call it, of sort of a portion of the corporate tax. How does it then go back out to help people? And who does it go to?

[B]

So one of the nice things about these two streams that I'm creating is that they're dry on day one. This is an if then mechanism. If the law passed while we slept last night would come up today, nothing would have changed. All you've created is capture mechanisms. If the abundance happens, if things continue as they were, prices don't suddenly drop, profits don't suddenly surge, you won't collect anything, the reservoir will be dry, and it will mean that nobody's been made up redundant, all is good. So it's actually a low cost thing to implement. Nothing changes dramatically in the economy, which is one of the design principles that we try to implement. Then we say, okay, let's implement a negative income tax. It's not quite universal basic income or universal high income, but it says, let's put a floor on people's earnings. You maintain the motivation to work because the more you work, the more you keep. But if you think about income tax today, the first few thousand dollars you don't pay tax on, then it starts and then it climbs, so it steps up. This would say the same happens in reverse. Below a certain level, you get paid money.

[A]

Does it matter if you lost your job because of AI? Not at all. So how is that not universal basic income?

[B]

Only because it's not universal. You wouldn't get only.

[A]

Oh, I see. Because only. Right. I even. You met with Andrew, right?

[B]

Yes.

[A]

And so I don't remember enough about Andrew's original proposal. His was just a flat out. Even if you made $1 billion a year, you still get your three grand a month or whatever it is.

[B]

That's right.

[A]

Got it. And you're. Yeah. And yours is much more.

[B]

It's a flaw.

[A]

Yeah, yeah, yeah. I mean, it's in the same way that all kinds of programs are faced, basically have cutoffs one way or another.

[B]

I need less money to fund my program than he would to fund his.

[A]

Right.

[B]

Because I'm not cutting you a check and not cutting myself a check.

[A]

So what's the. Have you thought at all about the actual mechanism for how this happens? Is it like an annual rebate check? Is it like people getting a check in the mail every month? Like, what's the execution?

[B]

The paper that we wrote, we've written a fairly robust economics paper. And I'll just say go to mosaicmodel.org

[A]

I mean, I will say it's a little technical, but if you like this podcast. First of all, the website's excellent and very easy to follow. The infographic is perfect. I read the paper. It was not the easiest thing to read, but if you like this, it's worth taking a shot.

[B]

Yeah. So in the paper. And again, just mosaicmodel.org will take you there. And thanks for the plug. We don't get into implementation. This is an economic model. But I think that what you'd really look to do is to simulate the paycheck. And you'd use the same plumbing of income tax. Income tax knows how to take money away, knows how to give rebates. The plumbing already exists, the machines exist. This wouldn't be a heavy lift. You'd do a reversal of that.

[A]

So let me throw two things at you to either defend or think about. And again, I only have the perspective of the US but one would be I don't. As someone who's run budgets, I don't necessarily feel comfortable that what you just said is what will actually happen if the money goes through the normal taxation and appropriation process. Because I just think about when I was deputy governor in Illinois and I had to pass a budget every year in order to get either the basic spending done or the stuff that I cared about. From a policy standpoint, I had to buy off people constantly, right? I had to agree to build prisons we didn't need. I had to agree to fund road projects we didn't need. I mean, all kinds of shit, right? So it's just not a simple rational one to one mechanism. And I kind of think that, I don't think know that I wouldn't have found a way to raid that money. You know, I probably would have been one of your few true, true, true believers, right? So I don't know. I remember when Al Gore was running for president, he had this idea of sort of a black, black box mechanism or lockbox, whatever it was for prescription drug rebates. I don't know that we don't need some version of that. And by the way, this may be one of the few things that blockchain would actually be useful for. So I just, again, maybe the Israeli system is more honest and has more integrity.

[B]

No, I wouldn't accuse it of that.

[A]

Facetious here, but that's number one that would absolutely concern me. I'm trying to write my second thing, but either way, one is I do think that I would be very cautious about the normal mechanism of taxation and appropriation because money has a magic way of disappearing.

[B]

Let's delay on that for a second and I would love your counsel. This is your wheelhouse, not mine at all. Looking back to the industrial revolution we spoke earlier about, there was a turning point. The turning point had an important political kind of analog, which is suffrage expanded. And so long as only the landed gentry had voting rights, it was very easy to dismiss the needs of the Charles Dickens characters. And as more and more people got to vote, suddenly politicians had to start passing laws that shared some of that wealth and cared for some of those poor people.

[A]

Imagine if we had mobile voting.

[B]

I'm all for that. So if only 2% of people are AI unemployed, then none of this is necessary and it won't be popular. But even today, you see what's happening to Eric Schmidt, being shouted down and all that kind of stuff before any of this has actually materialized. It's becoming something of a political issue.

[A]

I gave a speech at a shul in Upper west side last night and a woman came up to me afterwards and said, I just lost my job and it's because of AI. And as she's saying, I'm thinking that's probably not accurate. I believe you lost your job. And I didn't feel like getting into a long thing with her. I was like, oh, I'm sorry to hear that. But yes, I think the theory and the anxiety at the moment probably outweighs the reality today.

[B]

So I think anything that trusts politicians is a problem. And Elon Musk has suggested that we just print money and that's entirely at the trust of politicians. We can come back to that one in a second if you want. But I think if we could get the plumbing in place, I would like a situation where their politicians try to raid it. And one of the things that people campaign on is I'm going to raise the. The negative income tax. I'm going to lower it. I think that'd be a legitimate thing. Democracy to fight over.

[A]

Yeah, yeah, yeah, that, that is. That is definitely interesting. So there's an article about you and Bloomberg and if it ran today or yesterday, but just ran.

[B]

Yep.

[A]

And so there was something in there that I thought was utterly fascinating. I'm wondering if this kind of hit you the same way, which is so one could. I mean, some of the arguments they use against you just felt like very predictable, normal rhetoric. Right. In fact, the woman they said was a senior research fellow. I'm like, I bet she's a political person and not an economist. But. But let's put that aside. One could argue that there's an alternative free market, even more free market approach, which is forget about your whole mechanism of taxation and distribution, just give everyone equity in the companies are going to make money and as fiduciaries of that company, as the share price increases because of the production savings, they will benefit from it. And the person who. I don't know that he meant to, but they called for that in the article was Bernie Sanders. Right. He talked about a sovereign wealth fund to have equity in these companies. Trump in many ways, although I don't think he's thinking about it this way. I think his is just take extractive at all times, but has done a version that with Intel. Right. So is, have you thought about and is there an alternative approach where instead of money going in and out through positive and negative income tax, it's equity in the company's benefiting instead?

[B]

First of all, I love seeing new ideas come out. I think that this is exactly the time to have vigorous debate and start trialing different things and experimenting. So I think that that all makes sense. That creates its own difficulties. Can you spot the next anthropic? Are you going to do it? Take. And by the way, I think the news today on Bloomberg was also that Trump is suggesting making investments in these firms and taking equity also in anthropic. Sam Altman even suggested it. There is discussion.

[A]

I would argue he's in trouble.

[B]

Could be. Yeah, could be. But I have to say that that is a solution that may or may not work in the US doesn't work anywhere else. There is no anthropic in the uk. There is no anthropic in Israel for that matter. Right. So it's only here you have the. But really the huge multi trillion dollar companies are really only here.

[A]

Well, ironically, in a totally different system. There is another place, China.

[B]

Sure.

[A]

Right.

[B]

They could do something similar.

[A]

Yes, they could. Now they do. They do. Right. I mean, in a weird way, there might be the ideal place to do what you're talking about because the political and democratic process that will make the execution of this not from a technical standpoint, but from a political standpoint difficult actually doesn't exist there.

[B]

But you think about.

[A]

And the trillion dollar companies do, countries

[B]

outside of Silicon Valley.

[A]

Yes.

[B]

The law firms are still going to lay off lawyers in Birmingham. Not Alabama, but Birmingham UK and in Paris and in Tel Aviv and taxis. And every other profession is going to have the same dynamic, but there's going to be no anthropic. All of those dollars are going to flow back to the U.S. yeah.

[A]

Okay, so it only works in the

[B]

U.S. you can tap that. Probably should in some form or fashion,

[A]

but okay, so then that flips to the next. So I've become a evangelist for Mosaic since you showed me everything and I've been bringing it up in a lot of meetings and things like that. I think I've talked about it on the podcast before already and one Pushback I've gotten is okay, that's great. It's very cute. Israel is this tiny little country, super tech forward. Sure. Can never work here or anywhere else. What's your kind of answer to that, if there is one?

[B]

I think in most of the OECD countries it works just fine. So I met with members of the British government and discussed it with them and they really liked it as a principle. But actually the kind of structure where VAT is a central source of government revenue is common to all of the European countries and many countries beyond as well. So I think it is actually scalable. The US has its own unique advantages and disadvantages. So I don't know that you can just copy paste it. But the principle that says follow the money, it's going to yield either reduction in prices and or increases in profits. See if you can tap those without disrupting the economy, the economy as it currently functions and create some mechanism. Negative income tax is the one I'm advocating for, by the way. It has people on the right and the left who support negative income tax. This is not a party political painted kind of solution. I think that those broad principles and going back to the basic building blocks, that is universal.

[A]

Right. And by the one other thing working in favor of all of this is, and it's my substack for next week's about this, which is the public sentiment that's negative around AI and the regulatory response, which is just a reflection of politics around AI, is completely in the US bipartisan. When Trump on Tuesday announced, and it was a very industry friendly, very, very light executive order, but still that the government has to get advanced copies of models to review them before they released to the public or released to other companies. To me that was this indication that the worm has turned. And even Trump, who's been an AI proponent and Stargate, no panel stuff. Right back to most, even he was like, I gotta do something right before the elections in November. And states across the board this year, it could be on data center construction, it could be on chatbot content and disclosure, it could be on usage of AI in healthcare, I mean across the board. But not just seeing laws passed and regulations enacted, but I mean the NAIC rules you saw that obviously been adopted by 24 states. Very bipartisan.

[B]

Yeah. I actually think while the exact mechanics of the Mosaic model may need adaptation for the US in many ways the US needs it most urgently. The anti AI sentiment in the US doesn't exist anywhere else in the world. In China, everybody's amazingly pro AI, but Also in Europe and elsewhere, people are feeling much more sanguine about it than in the US So if you want to.

[A]

Is that because they're removed in Europe from it, like to your same point that we have all the companies? Is that why?

[B]

I don't know. You'd have thought that that actually makes them anti America and they might have been, but we're not seeing that. And I think that because that is the dynamic that's beginning to form. Nobody is taking the steps necessary to reassure young kids this. It's going to be okay. You're going to be for sure participants in the abundance that's created. If you don't start creating that narrative and showing you taking actions, you're going to totally.

[A]

Right. So I was with my son, I asked my son a couple months ago with a 17 year old kid who goes to a, you know, super fancy high school in Manhattan, will go to a great college in a year. We'll have a big safety net. You know, he's as lucky as you can be. Right. And I said to him, like, what's your biggest societal concern? And he said, job opportunities in the age of AI. Right. And if he's worried, I don't. You can't really be positioned much better than him. Right. And you know, maybe you're like an elite Olympic athlete or something that can't be replaced by AI. That's about it. And so, yes, I mean, I think the anxiety is unquestionably there, which I do think creates. And this is something I'd love to help with, an opportunity to take the principles of Mosaic, think about a U.S. application of all of it and start introducing to the bloodstream. Because I do believe that 2028 elections will be the AI elections. Right. If 2026 is affordability and they're connected, obviously, especially in what you're talking about. But I think 2028 will be AI and I think that it is highly likely the Democrat wins in 28 and they will win amid a surge of anti AI sentiment. They will misinterpret it as I should just be anti tech, doctrinaire. All technology is bad, which you've already seen the far left adopt that position, which of course will only do more to hurt poor people than anything else. But that does create the opportunity here to really put this in the bloodstream.

[B]

I think you're right. And I'll layer one other thing. It's a little abstract, but I think it may start percolating in interesting ways. An AI economy does real violence to the meritocracy narrative today, there's a lot of distribution issues and very uneven distribution of wealth in their economy. But there is a story that says, well, contribution is uneven, and there is some correlation between how hard you work and how smart you are and how risk forward you are and how much wealth you'll accumulate. And that's the meritocracy story and the American Dream. And if you work hard and study hard and play harder, all that kind of stuff in an economy where we are not working, where it is not my brain, but it's a synthetic brain that's doing the work, and it's not how many hours I put in, it's how many tokens I can afford that is determining how much wealth I generate, the underlying philosophy of meritocracy takes a real hit. And if you think your son is worried about just the narrow what job will I have or will my kids have? When you tie that with a sense of unfairness of these people have wealth not because they tried hard, they worked harder, they went to a better college, but because they can afford more tokens, you're really shaking some of the fundamental philosophy underpinning how the US Economy works.

[A]

Yeah, for sure. All right, Daniel, thank you so much for joining us. This was awesome. Firewall is recorded at my bookstore, PNT Netware, located at 180 Orchard street on the Lower east side of Manhattan. We'd love to hear from you with questions, feedbacks or idea for a guest. Just email me at Bradleyirewall Media or find me on LinkedIn. And to keep up with what's on my mind mind in my latest writing, please follow my new [e-mail] thanks again for listening.