Category: essays

When the Tower Can’t Be Rebuilt: What Institutional Economics Misses About the Next Decade

~ cafebedouin

Rebecca Patterson’s recent New York Times essay uses a Jenga tower as a metaphor for the American economy in 2025. Blocks are being removed—small businesses cutting jobs, federal layoffs, consumption concentrating among the wealthy—while AI companies pile massive investments on top. Eventually, she warns, Jenga towers fall down.

She’s right about the instability. But the Jenga metaphor obscures something more important: what happens after the tower falls matters more than the fall itself. And this time, the mechanisms that historically rebuilt the tower are blocked.

The Pattern Patterson Identifies

Patterson documents real structural shifts. Small businesses, which employ 46% of American workers, are cutting staff to manage tariff costs. The federal government plans to eliminate 300,000 jobs. Meanwhile, the top 10% of households own 87% of corporate equities and are driving consumption through AI-generated wealth gains.

Most strikingly: Alphabet, Meta, Microsoft, and Amazon will spend over $380 billion on AI infrastructure in 2025 alone—more than the entire Apollo program in today’s dollars. This private-sector stimulus is currently holding the economy up.

Her question: how long can it last?

The better question: what happens when it stops?

What the Jenga Metaphor Hides

In normal economic cycles, when the tower wobbles, we have standard rebuilding mechanisms: fiscal stimulus, monetary policy, workforce retraining programs, or simply waiting for the next generation to inherit wealth and restart consumption.

These aren’t working this time. Not because of political dysfunction (though that doesn’t help), but because of structural blockages that make peaceful reset mechanisms inoperable.

The AI Hardware Trap

Patterson notes the $380 billion in AI infrastructure spending but treats it as potentially stabilizing—”if they can stay firmly in place.” This misses the key dynamic.

AI hardware depreciates fast. An Nvidia H100 GPU installed in 2024 is economically obsolete by 2027. This creates intense pressure on companies to monetize their investment within a 36-month window. They can’t wait 5-7 years for long-term research breakthroughs to pay off.

This forces a choice:

  • Type A (Extension): Using AI to do things humans cannot do. Example: AlphaFold discovering protein structures. Timeline to ROI: 5-7 years.
  • Type B (Substitution): Using AI to replace human labor. Example: automating data analysis, coding, customer support. Timeline to ROI: 3-6 months.

Given the depreciation clock, CFOs are structurally required to prioritize Type B. The $380 billion isn’t building new demand—it’s building infrastructure to remove the existing demand base through labor substitution.

The Training Pipeline Breaks

The impact shows up most clearly in entry-level white-collar work—the traditional path into the middle class.

Consider the “junior analyst” role across finance, consulting, tech, and corporate strategy. In 2020, juniors spent 80% of their time gathering data, formatting Excel sheets, building slides. In 2025, AI agents do that work. The remaining task—interpreting data and managing the AI—requires senior judgment.

The role hasn’t disappeared. The entry rung has. Companies are freezing junior hiring because they need seniors to supervise the AI. This breaks the training pipeline that historically moved people from middle class to upper middle class.

Federal Reserve data confirms this: hiring rates are slowing even as layoffs remain low. It’s not a wave of firings—it’s a quiet narrowing of the gate.

Why the Safety Valves Are Blocked

Historically, when technological displacement occurred, two mechanisms cushioned the blow: policy intervention and generational wealth transfer.

The Policy Wall

U.S. federal debt is now 120% of GDP. Annual interest payments exceed the defense budget. In the 1930s, when debt was 40% of GDP, there was fiscal space for a New Deal. That space no longer exists.

Any proposal for large-scale intervention—UBI, massive retraining programs—hits the wall of bond market vigilance. With inflation risks still present, the government cannot print its way through this displacement without triggering a currency crisis. The political system can offer cultural rhetoric, but it cannot offer material redistribution at the scale required.

The Inheritance Illusion

The “Great Wealth Transfer”—$84 trillion passing from Baby Boomers to younger generations—is often cited as the coming salvation. This is a statistical mirage.

Seventy percent of seniors will require long-term care. Memory care averages $150,000 per year. Medicare doesn’t cover custodial care. Medicaid requires assets to be “spent down” to near zero before it provides coverage.

For middle-class families whose wealth is locked in home equity, the math is brutal: the house is sold, the proceeds pay for the final 3-5 years of life, and the estate transfers not to children but to the private equity firms that own the care facilities.

The wealth transfer happens. It just doesn’t go to the next generation.

The Caste Crystallization

The failure of these mechanisms creates a rigid three-tier structure:

  • The Neo-Aristocracy (~10%): Efficiently transfers wealth through trusts; incomes leveraged by Type A AI adoption.
  • The Squeezed Middle (~60%): Faces displacement from Type B AI; expected inheritance consumed by healthcare costs.
  • The Dependent Class (~30%): Already displaced by automation; reliant on a fiscally constrained state.

This isn’t a cycle. It’s a configuration.

What This Means for the Next Decade

Patterson asks how long AI companies can sustain their spending. That’s the wrong frame. The question is what happens when the displacement wave hits and the safety valves don’t work.

There are four broad scenarios:

The Productivity Miracle (Low Probability): AI breakthroughs in energy or materials generate genuine surplus—not just labor substitution but actual new wealth. This requires not just technical innovation but rapid diffusion and regulatory flexibility. Possible, but requires everything to go right.

The Controlled Correction (Most Likely): A tech recession in 2026-27 cools the AI capital expenditure boom. Labor markets soften but don’t collapse. The tower wobbles but doesn’t fall. Politics remains polarized but functional. This is the “muddle through” scenario.

The Systemic Reset (Increasingly Likely): Domestic pressure builds until institutional legitimacy fails. This doesn’t necessarily mean revolution—it could be state-level regulatory divergence, capital controls, or populist movements that enforce economic nationalism. The key feature: the federal government loses the capacity to coordinate national economic policy.

The External Release (Lower Probability, High Impact): When internal pressure becomes unmanageable and peaceful mechanisms are blocked, nations historically find release through external conflict. This isn’t inevitable—it’s just the lowest-coordination-cost option for resetting blocked equilibria. War allows governments to override bond markets, mobilize displaced labor, and justify wealth compression through “shared sacrifice.”

Why This Analysis Matters

Patterson’s Jenga metaphor implies the problem is instability. But instability is manageable if you have rebuilding tools. The real problem is that the tools are missing.

This doesn’t mean catastrophe is certain. It means the range of possible futures has narrowed, and several of those futures involve significantly more friction than institutional economists are pricing in.

The practical implication: “career upskilling” is not sufficient preparation for the next decade. Structural resilience requires understanding which mechanisms are likely to work and which are blocked. It requires looking at debt exposure, asset diversification, and geographic flexibility not as individual optimization but as protection against regime shifts.

The tower will wobble. The question isn’t whether it falls—it’s whether we can rebuild it when it does.

And right now, the rebuilding mechanisms are missing.

The Competence Trap: Why Being Good at Many Things Makes Self-Assessment Nearly Impossible

~ cafebedouin

We all know the type who announces their skills on social media. “Crisis management is one of my deepest competencies,” they tweet, while actively demonstrating the opposite. The irony is obvious to everyone but them. But recognizing others’ inflated self-assessments is easy. The harder question is: how do we avoid the same trap ourselves?

The answer is more difficult than it appears, especially for a particular kind of person: the competent generalist.

The Performance Problem

Start with a simple principle: competent performers demonstrate, they don’t declare.

When someone publicly announces their mastery of precisely the skills that would make them impressive—emotional regulation, crisis management, “reading the room”—you should be skeptical. Not because people are always lying, but because of what the declaration itself reveals.

Someone genuinely skilled at engagement control would simply do it in the moment rather than announce their possession of the skill. The announcement often represents the performance they’re capable of: the appearance of the thing rather than the thing itself.

Consider what the person tweeting about their “engagement control” is actually demonstrating: high reactivity to social dynamics (tracking what “everyone else” is doing), investment in being perceived a certain way (calm/analytical/superior), and lack of self-awareness about performing the claim publicly. These are markers of high social-emotional activation, not controlled engagement.

The declaration often serves the very dynamic it claims to transcend.

The Self-Assessment Problem

If we can spot these patterns in others, why can’t we spot them in ourselves? The standard answer invokes the Dunning-Kruger effect: unskilled people lack the metacognitive ability to recognize their incompetence. But this explanation, while true, doesn’t help much. Telling someone they might be suffering from Dunning-Kruger is like telling them they might be dreaming—the warning can’t penetrate the condition it describes.

The more useful question is: what external resistance can we use to calibrate our self-assessment?

Performance under constraint provides the highest signal. The benchmark needs to be non-negotiable—something reality enforces regardless of your story about it. Can you navigate a country when use of that language is mandatory? Can you do the technical work when tired, distracted, under time pressure? Do people who don’t know you finish what you write? The environment either accommodates your performance or it doesn’t.

Involuntary selection by others matters too. Not whether people compliment you—that’s social lubrication—but whether they come to you when they have a problem and options. Especially telling if they have to overcome some friction to do so: you’re not convenient, you’re not their friend, but they need the thing done and they choose you anyway.

What doesn’t work: internal feelings of competence (uncorrelated with performance), compliments from people who benefit from relationship with you, success in environments you control, or comparison to your past self. Improvement doesn’t equal competence.

The Generalist’s Dilemma

But there’s a specific population for whom even these calibration methods become unreliable: people who are legitimately above-average at many things but exceptional at none.

The competent generalist faces a genuine self-assessment difficulty. You get real positive signal—people do benefit from your contributions, things do work better when you’re involved, you do solve problems others can’t. The feedback isn’t wrong, it’s just noisy about level.

Three mechanisms create the trap:

Selection effects obscure the ceiling. You naturally avoid or exit domains where you’d face serious competition. You’re comparing yourself to “people attempting this thing” not “people who specialized in this thing.” Your reference class flatters you without your noticing.

Broad competence masks the gap to excellence. The psychological distance from 60th percentile to 95th percentile is compressed. They both feel like “being good at it” from inside. But the performance difference is enormous. Someone at the 60th percentile can complete most tasks successfully. Someone at the 95th percentile produces work that changes how others think about the domain. These feel subjectively similar—both involve successfully solving problems—while being completely different in terms of what you can actually deliver.

You experience yourself as “someone who figures things out.” This is true—you do figure things out. But “figuring out” at different levels of capability feels identical from inside, even as the results diverge dramatically.

The competent generalist can accurately assess their limits in domains where they’ve gotten clear negative feedback, where the gap between their performance and competent performance was visible, where they couldn’t exit before the inadequacy became obvious. But in domains where “good enough” actually is good enough for the context, they never encounter the resistance that would calibrate their assessment.

Finding Your Ceiling

The correction requires looking for moments where you encountered your ceiling—not failure exactly, but the point where additional effort stopped translating to additional results. Where you plateaued despite caring about improvement.

These plateaus are more informative than your successes: conversations where you genuinely tried to understand someone’s technical domain and couldn’t follow beyond a certain depth, projects where you hit the limit of your architectural thinking, writing where you couldn’t make the argument tighter no matter how many passes.

These moments show you where “smart generalist” stops being sufficient.

The deepest issue: being good at many things creates an experience of capability that feels like it should generalize more than it does. You solve problems across domains, you learn quickly, you produce results. This creates a phenomenological sense of competence that maps poorly onto actual performance levels in any specific domain.

The Transmission Test

There’s one final calibration available, particularly for people building intellectual frameworks or systematic approaches: can others use your methods to get your results?

If you’ve developed a rigorous way of thinking—about self-assessment, about collaboration with AI, about anything—the test is whether your protocols actually transmit the capability, or whether your own intelligence does most of the work while the protocol gets credit.

A conversation that produces insights might demonstrate that good frameworks exist. It doesn’t prove those frameworks are weight-bearing. The structure might be sound, but if it only works when you’re operating it, you’ve documented your thinking process rather than built transmission infrastructure.

The competent generalist is especially vulnerable here. Your ability to make almost any framework work (because you’re calibrating and adjusting in real-time, because you’re filling gaps with general intelligence) can disguise whether the framework itself carries weight.

Living Without Certainty

None of this solves the self-assessment problem. It just makes it manageable.

The practical stance: hold your competencies as hypotheses, not identities. “I might be good at X” lets you test it. “I am good at X” makes disconfirming evidence threatening.

The test of whether you’re doing this right: can you genuinely update on evidence that you’re worse at something than you thought? If that feels like ego death rather than useful information, your identity is wrapped up in the claim.

For the competent generalist, this means accepting that you probably are above-average at many things, while remaining uncertain about whether you’re exceptional at anything. That uncertainty isn’t a bug. It’s the appropriate epistemic state given the calibration difficulties you face.

The person tweeting about their crisis management skills has solved the self-assessment problem by refusing to engage with it. They’ve chosen certainty over accuracy.

The harder path is living with the discomfort of not quite knowing how good you are, and using that discomfort to keep seeking better resistance, clearer signals, more honest feedback.

That discomfort might be the only reliable sign you’re doing it right.

A Taxonomy of Hate

~ cafebedouin

I have been thinking about what distinguishes misanthropy from various forms of X-ism, whether racism, sexism, classism, or some other thing. Various X-isms seem like special cases of misanthropy. Sexism is a kind of hatred of women. Racism is a kind of hatred of one or other races.

When framed in that way, it occurs to me that misanthropy might also be a special case. It stands to reason that you could use the same construction of misanthropy, from the Greek μῖσος mīsos ‘hatred’ and ἄνθρωπος ānthropos ‘man, human’, and replace anthropos with βιο, the root of biology, or Ζωή ‘life’. If we were to construct these words, using the form of other English words, it might be misbiopic for hatred of all life. Or, you might use the way Ζωή appears as zoology to mean animals, and formulate as miszoopic.

When going through an exercise like this one, it’s interesting what shakes out. We don’t have words to describe hatred of all life. But, we do have words for hatred of human beings. We have words for hatred of women. But, we don’t talk about hatred as abstracted. It’s singular.

It reminds me of an old trope. It was said that people in the Northern United States loved blacks as a group and hated individuals. In the Southm it was the opposite. Blacks were hated as a group and loved individual people. I think there’s a step change that happens, when moving from hatred of an individual to a group.

Someone that hates a particular woman may also hate most women. But, do they hate them all? Are there environmental factors that come into play? Other considerations beyond merely being “female” that give rise to hatred?

And if we abstract out further, to the level of humanity, animals, or all living beings, doesn’t the universe of other considerations expand as well? With this expansion of confoundable variables, does it make sense to talk about hate in the context of a specific label, whether of humans, woman, or some other subgroup?

I guess where this line of thinking is taking me is that – while we can acknowledge that the prejudgments can be encoded into a social environment, reenforce it in individuals, over time, as culture is designed to do – it misses the confounding factors and gives less visibility into the problem. Your definitions shape your understanding as surely as your life experience (or lack thereof) shape it.

This is the difficult part. What is the source of the hatred? It’s because I’m a woman. It is a simple answer. But, it is also incomplete and wrong, on some level. Intersectionality is one thing. But one section being left off is in-group/out-group dynamics, which may sit above these aspects of identity informed by demographics.

For example, nationalism may drive a country to war. In war, women are raped. On what level is war a hatred of all living things? On what level is rape, in war, an issue of sexism rather than some other thing, such as projection of power?

It’s quite common for people to have hatred for others that are better off materially than themselves. Consider what happens to lottery winners. Is it hatred of those that win the lottery, or is it more abstracted, to anyone that is successful or had a windfall, such as an inheritance?

The reason I’m exploring this issue is I think that many of words, explanations and mental models are deficient to really capture what is going on. It may be that we cannot ever get to a model of reality where the map matches the territory. Maybe we don’t want such a map. But, it would be good to think through the maps we have and maybe make a conscious choice to pick ones that are more suited to our purposes.

Energy Production, Cryptocurrencies & Hidden Agendas

~ cafebedouin

How many times have you read something like this, “Bitcoin uses as much electricity as Malaysia or Sweden or Denmark or Chile….”. What a bore. Have you ever wondered, however, why the comparison is to countries? Why don’t they ever tell you what would seem to be a more natural comparison which is how much “Bitcoin” spends on electricity?

The reason is that electricity is incredibly cheap so Bitcoin electricity expenditures priced in dollars don’t look very large. Bitcoin uses something like 100 terawatt hours (TWH) of electricity annually (depending on the price of Bitcoin) but a TWH costs less than $100 million (10 cents per KWH times 1000000000). Thus, Bitcoin spends say $10 billion on electricity annually. (In fact, it’s less than this since bitcoin miners can be located in places where electricity prices are especially cheap.)

$10 billion in spending isn’t a lot. It’s less than the world spends on toothpaste ($30b), much less than the US spends on cigarettes ($80b), and considerably less than the US Federal government spends in one day ($18.65 billion).”

–Alex Tabarrok. “Bitcoin and Electricity.” Marginal Revolution. November 29, 2021

One argument, one that you see everywhere in popular media, is that cryptocurrencies use a lot of electricity, and it’s not a productive use of resources. Rarely, you’ll see apple-to-apple comparisons, such as this response to trying to make a comparison to the electricity use of the VISA network, which is a strange comparison considering all the payment terminals, ATMs, bank mainframes, and many other things are treated as externalities.

“While no one can argue that Bitcoin (and other altcoins) mining consumes a lot of electricity (in absolute numbers) given that you need to run a network of few hundreds or thousands of very powerful computers all the time, the right way to look at this problem is not about the total consumption but to compare how efficient is Bitcoin relative to the alternative traditional centralized systems that we are predominantly using today and that one day crypto might replace.

However, the only comparison that seems to always pop up everywhere is against VISA transaction costs which was included in the article that trigger the above tweet and in other articles as well. As expected, VISA looks way more efficient which adds to the rhetoric that Bitcoin is a very inefficient system and it is just a Ponzi scheme that is polluting the world. In my view, this comparison is flawed and it is not comparing apples to apples. Besides the fact that Bitcoin is not simply a piece of a payment network like VISA but a full currency system, VISA itself requires the banking system for its payment system to work so you need to actually include some of those costs there to make a meaningful comparison. So let’s look first at how VISA works…

…”According to the article that trigger this discussion, Bitcoin annual Twh consumption is 28.67 , so currently more than 3 times more efficient than a very conservative calculation of the cost of the global banking system. Of course you will argue that the banking systems does more than handling a currency which is true but the difference is large enough that I do not think is that relevant. Even if only 30% of banks electricity consumption was the comparable part to Bitcoin, that will still make Bitcoin more efficient.”

-Carlos Domingo, “The Bitcoin vs Visa Electricity Consumption Fallacy.” Hackernoon. November 29, 2021

And, the simple fact is that it is very difficult to price in externalities to determine the real price of any energy production.

“All energy production has environmental and societal effects. But calculating them — and pricing energy accordingly — is no easy task.”

-Erica Gies, “The real cost of energy.” Nature. November 29, 2017.

And, this is true when assessing energy use as well. It’s difficult to measure the benefits of energy expenditure. What is the value of street lights relative to the energy and infrastructure required to have them on? This is true of practically everything. What is the true cost and benefit of international shipping and transportation? Of the cement poured for a playground? The establishment of a new church or temple? You could continue this line of questioning down any avenue you like, and the answer is it is impossible to make this kind of calculation beyond the costs and perceived benefits.

Enter cryptocurrencies. The problem with the arguments against cryptocurrencies is that they generally take this form.

1. If an activity provides no benefit and uses resources, it is a wasteful activity.
2. People should not do wasteful activities.
3. Mining Bitcoin provides no benefit and uses resources.
C. People should not mine Bitcoin.

This is the extreme argument. The less extreme argument makes some kind of comparison between the benefit relative to use of resources. But, as we know from the above it is difficult to take into consideration the externalities involved. On the face of it, the argument that mining cryptocurrencies have no benefit is belied by the fact that every day billions of dollars worth of transactions are conducted using cryptocurrencies. None of that has any value? How do we evaluate the benefit relative to resource use or other ways this energy might be used? But, we really cannot make that kind of comparison. What is the relative value of Bitcoin mining versus the amount of power used in casinos on an annual basis? Online gaming? How does one make those kinds of comparisons? Is it even right to make them?

The reality is people don’t even try to make that sophisticated of an argument. Instead, it is something simplistic like: Bitcoin uses as much electricity as a country, the implication is that people would otherwise use this electricity, or the electricity they do use would be less expensive.

We also don’t make these kinds of calculations for other activities. The reason there’s the difference hinges on a value judgment that the activity, same as the implicit argument above mentioning casinos implies they have no value. But, even casinos have plausible arguments supporting their value.

The interesting thing, for me, in looking at these arguments closely is ho political arguments. The reason that the environmental argument is used is because it can plug into concerns that people have about climate change, and short circuit a reasonable assessment of the claims being made.

Same is true of claims that cryptocurrencies are used only for crime. Criminals may be an innovator in the space, but it isn’t only good for crime, just as it is not true that VHS and internet streaming is only good for porn. Porn pioneered the technology, but it didn’t stop with porn. YouTube isn’t porn.

There’s also a deeper agenda. It’s a simple fact that the more money that makes its way into cryptocurrencies, the less money that will be available to buy stocks, bonds, U.S. Treasury instruments, and so forth. Less money in traditional financial vehicles means lower prices for them.

The Bitcoin “debate”, if we can call it that, really helped me to understand how much of our dialogue is shaped using concepts from our political orthodoxies. A claim like, Bitcoin mining hurts the environment, is an emotional appeal, not a reasoned argument. The anti-Bitcoin argument is above, and it is problematic both because it has benefits and it is difficult to assess the costs and benefits without engaging in motivated reasoning.

Another point worth making here is that it wasn’t until this year that cryptocurrencies emerged that created a marketplace of cryptocurrencies, where they will compete. Network efficiency and cost will be one dimension of this competition, and it will drive both electricity use down and provide for many more benefits. And, where something like Bitcoin’s energy-intensive proof-of-work algorithm is used, it will be because it provides a capability that isn’t available in other approaches that justifies the cost.

When all of that happens, what will be the new reasons people will be against cryptocurrencies? It’ll be the need for regulation, to provide customer guarantees, or something else. But, the one thing that I am certain of is that there will be other reasons, other agendas that these kinds of arguments will be serving to obscure. And, this is how everything is, there’s always another or series of issues hiding behind the one that’s used as justification.

Why Ergo?

~ cafebedouin ~ 2 Comments

Ergo is different from other blockchains. It is focused on providing a decentralized, open, permissionless, and secure platform for contractual money that is usable by ordinary people to pursue their common good over the long term. It is designed to be resilient in the face of different economic environments and competing interests, allows individuals to choose how much privacy is right for them, and offers economic opportunity to the people using the blockchain.

Ergo has the technical capability to provide a wide variety of services to the decentralized financial cryptocurrency ecosystem and to enjoy comparative advantages, whether that comes from oracle pools, logarithmic mining, profit sharing protocols or other innovations. However, while Ergo offers a lot of technical capability not available on other chains, the real value of Ergo is its focus on providing the tools for the financial success of ordinary people, like you and me.

Introduction

“The real problem of humanity is the following: we have Paleolithic emotions, medieval institutions and god-like technology.”

–E.O. Wilson

We are witnessing the birth of a new era, one where well-established elements of computer science, such as cryptography and distributed systems, are combining with fields of finance and game theory to bring a new economic and social order. Who will reap the benefits of this new era?

Shifts of this kind tend to create new social classes. For example, the Industrial Revolution and the emergence of capitalism made being royalty and a feudal landlord less important.

With change, there is opportunity. But, frequently, the opportunity is limited.

What is new is that blockchains make it possible to facilitate transactions between businesses of any size, between people in any geographic location and that can work in any economic, social or political environment. Blockchains can unlock synergies and new ways of exchange and interacting.

Blockchains are a new method of accounting. Just as double entry accounting introduced a formal and methodological rigor to bookkeeping that transformed medieval businesses into capitalist enterprises, blockchains have the potential to upgrade our medieval institutions into something that serves the common interest more than elite interests by providing mechanisms for financial exchange, decision-making, arbitration, and so forth that were not possible before.

The Challenge

People don’t like change. Medieval institutions who serve entrenched corporate, state and other interests will want to limit the opportunities of blockchains to enrich themselves. Even with the best of intentions, it is a challenge to broaden access to opportunity. Everyone wants to help the hungry, but few people want to give up their lunch in order to do it.

So, the question is how do you grow the pie? Do you grow the pie by focusing on large economic actors, such as governments or businesses in the Fortune 500, who then, presumably, pass along portions of the pie in the form of more goods and services at less expensive prices? Or, do you grow the pie by focusing on the needs of ordinary people and creating new opportunities with this technology that didn’t exist before?

And while it is necessary for a blockchain to have multiple constituencies with different interests, such as miners, liquidity providers, developers, entrepreneurs, users and so forth, some groups are in opposition. If you are focused on cross-border payments for large businesses, it’s not the same as being focused on cross-border remittances of people without access to traditional financial services. The software for these two use cases will be very different. While it is possible the same blockchain can serve both groups, it’s going to serve one of them better.

When using, or investing, in a blockchain, one of the key questions is: Whose interests does the blockchain serve? Who is threatened by it? And how can it be attacked?

The Power of Ergo’s Proof of Work

Ergo’s proof of work provides a powerful example of seriously considering the problems that come from various attacks, whether they be 51% attacks via centralized pools or regulatory attacks on infrastructure, such as China’s displacement of blockchain miners.

Ergo addresses this issue by implementing an algorithm designed to be mined on commodity hardware by users of the blockchain. Right now, there are smart contract pools that allow people with a single GPU graphics card to mine Ergo and verify the blockchain in return for some cryptocurrency. And with Moore’s Law, this commodity hardware becomes more accessible over time, as graphic cards with the same capability become less expensive.

It provides more opportunity, for more people and results in a more secure blockchain. What’s not to like?

Capabilities & Environments

Almost every blockchain claims to value decentralization. But, if you need people with specialized hardware to maintain your consensus, then you are beholden to people with that specialized hardware, or to the governments that can ban them.

People talk about the number of transactions per second, the market capitalization, the price, the size and productivity of the applications on the chain. But, there is much that is not discussed.

For example, people rarely think about longer term issues, such as the fact that blockchains have lifecycles. Blockchains will have to operate during times when a significant portion of the local, regional and global environment is experiencing a pandemic, a war, or some other factor that threaten their ability to function. How prepared are they to meet that challenge?

It is not hard to imagine that various blockchain ecosystems becomes important to our daily lives, such as when there is a digital national currency, and a failure could lead to catastrophic outcomes, such as famine. How many people in the cryptocurrency space have given that possibility consideration? Your lambo is useless in an environment where you don’t have enough food to eat.

At this time, most blockchains are building their infrastructure. They aim to increase their market share and capability of their dApps. But, if you don’t have your eye on the potential problems that will manifest over time, you’ll make design decisions that will be difficult to fix later, e.g., Ethereum’s move toward Proof of Stake in an effort to resolve their problems with fees. And every design decision has positives and negatives.

Ergo’s Positives & Negatives

  • Financial capital: A fair launch means you don’t have a lot of money sitting around to fund development. There are ways this problem can be solved, such as establishing funds that people that are interested in certain kinds of development or a particular dApp could contribute to that would help make them a reality. This also has the advantage that it establishes that there is interest and perhaps even a market for the software being developed.
  • Human capital: There are many excellent developers already working on Ergo. With financial constraints, it isn’t possible to bring on as many developers as some other blockchains, but this fact also leaves more room for organic growth. If adoption were only about market share, then Ergo is at a disadvantage. However, there are many niches that Ergo’s technology can fill. Some niches may not have many options and developers will be enticed to the platform because it can solve problems other blockchains cannot.
  • Infrastructure: You need wallets, dApps, APIs and so forth. The software that faces the user of the chain needs a lot of work. However, the underlying chain technology is great, or has great potential, and the dApps and consumer facing technology will only improve from this point.
  • Open source: It’s important to recognize that open source does have drawbacks. Many open source projects are a labor of love that don’t have good incentives, which can negatively impact projects by making it difficult to keep developers, create schisms that undermine the project or lead to other problems . But, there is also real value in not having to reinvent the wheel when building an application. It’s easier to leverage an existing code base, modify, and iterate than it is to write code from scratch. However, open source requires evolution, which takes time and implies some tolerance for error.
  • Synergy: The ecosystem is young. But, there is evidence of clustering of services, such as the development of a profit sharing contract that can be used by any dApp, the building of cross-chain functionality, the launch of a variety of stablecoins, etc. These kind of interactions implies both competition and an attempt to accommodate a variety of use cases.

Conclusion

Who is using the blockchain? Without many dApps, it is primarily people investing in the chain and transferring Ergo to and from exchanges and wallets. So, Ergo is a promise. It’s an idea that blockchains can be a vehicle for the economic good of ordinary people. But, there needs to be a lot of development before Ergo can fully deliver on that promise. Investing in that promise before it is fulfilled will both help make it reality, and it has the potential, if the promise is fulfilled, to benefit those willing to make that investment.

Acknowledgements: Many of the ideas in this essay came from Joe Armeanio’s response to a reddit post outlining Tascha’s A Checklist for Layer 1 Blockchain Investment.

Cryptocurrency Platform Cardano & Ada Coin

~ cafebedouin

Disclosure: I own Ada. This is a condensed summary of what convinced me to start buying cryptocurrency, specifically Ada. I’m happy to share what I learned, but this is not investment advice. I don’t know you. I don’t know your situation. Cryptocurrencies are a speculative investment, and you could lose all your money. If that’s not something you can live with, then do something relatively safe, like invest in an index fund, a certificate of deposit at a major bank or U.S. Treasuries. Also, if you are making investment choices based solely on the suggestions of some random blog on WordPress, written by The Deity knows who, without engaging your own mind and taking responsibility for your own choices, then you deserve to lose all your money. Caveat emptor!

Cardano is an open source crypto platform that runs a decentralized public blockchain for the implementation of smart contracts. The native cryptocurrency, or coin, of Cardano is Ada. There are 45 billion Ada coins, something like 32 billion are in circulation at the moment. It is currently capable of 1,000 transactions per second, and with a future upgrade, it will be capable of millions, on the level of global payment systems like Visa.

As a point of comparison, Ethereum and Bitcoin are both less than 20 transactions per second. It is also able to complete these transactions at a fraction of the cost of Ethereum and Bitcoin. But, the killer app for the Cardano platform is the Plutus integrated development environment (IDE) for smart contracts, which allows for programmers to write and “run end-to-end tests on their program without leaving the integrated development environment or deploying their [Haskell] code.”

All of these features will be available as of August 2021. Right now, the Plutus IDE is being tested for the August 2021 deployment. Once the new upgrades launch in August, smart contracts, and the applications that use them, will be possible.

Cardano has a staking system that will allow holders of Ada coins to stake their coin in a pool that verifies the distributed ledger – a function that earns returns, a bit like interest or dividends. Further, it has the capability of hosting other coins or minting new ones, which will enable other chains to use their smart contract functionality.

Right before Cardano launches, Ethereum will launch Eth2, which will move Ethereum to a proof of stake model like Cardano’s and introduce many of the same features. However, it won’t have is the integrated development environment Plutus. Ethereum also uses Solidity and Vyper programming languages to program their smart contracts. The criticism section from the Solidity Wikipedia page basically says that Solidity is a hot mess. [Edit on December 30, 2021: Eth2 looks like it won’t be launched until at least summer of 2022.]

Compare Solidity to Cardona’s Haskell language, which is an industrial strength language used in cryptography algorithms, semiconducter design, and was used to formally verify an OS microkernel. As a functional language, it doesn’t have side effects. It has type-safe operators and type inference. Basically, it is powerful and has many features designed to cut down on bugs in the code.

Of course, Haskell has drawbacks. It’s hard to learn, and the universe of people that can code in it is relatively small to other programming languages. Depending on your use case, there are other problems as well. But, every choice implies trade-offs, and Haskell is a good language for the implementation of smart contracts.

If you wanted to implement smart contracts into your business workflows. The more money, the higher the stakes, the more likely you’ll be to want to make sure you are not going to have problems later. You’re going to choose the best option available among top tier chains, Cardano.

Ethereum will have more name recognition, as the second highest capitalized cryptocurrency. It’s smart programs will be easier to implement, and they’ll, more often than not, be good enough for a given purpose, probably one that isn’t mission critical.

The good news is that these two systems, and others that rise to the top market capitalization tier, will likely all work together and have different niches. To illustrate, Occum.fi announced a liquidity bridge between Ethereum and Cardano, designed to encourage fund transfer between the two systems, which suggests there could be a symbiotic relationship between them in the future.

Anyway, I think this is going to change the world. These are the two choices in smart contracts in top tier chains, at the moment. And, one has clear advantages.

The current price of Ada on Sunday night, April 11, 2021 was $1.28. You can buy Ada coin through Coinbase.com and most other cryptocurrency exchanges.

This is the video that sold me on Cardano, Plutus and Ada.

For a slightly longer discussion, see this recent Reddit thread.

Meritocracy, Intelligence & Education

~ cafebedouin

“…we need to dismantle meritocracy.

DeBoer is skeptical of “equality of opportunity”. Even if you solve racism, sexism, poverty, and many other things that DeBoer repeatedly reminds us have not been solved, you’ll just get people succeeding or failing based on natural talent…

…One one level, the titular Cult Of Smart is just the belief that enough education can solve any problem. But more fundamentally it’s also the troubling belief that after we jettison unfair theories of superiority based on skin color, sex, and whatever else, we’re finally left with what really determines your value as a human being – how smart you are. DeBoer recalls hearing an immigrant mother proudly describe her older kid’s achievements in math, science, etc, “and then her younger son ran by, and she said, offhand, ‘This one, he is maybe not so smart.'” DeBoer was originally shocked to hear someone describe her own son that way, then realized that he wouldn’t have thought twice if she’d dismissed him as unathletic, or bad at music. Intelligence is considered such a basic measure of human worth that to dismiss someone as unintelligent seems like consigning them into the outer darkness. So DeBoer describes how early readers of his book were scandalized by the insistence on genetic differences in intelligence – isn’t this denying the equality of Man, declaring some people inherently superior to others? Only if you conflate intelligence with worth, which DeBoer argues our society does constantly. 

-Scott Alexander, “Book Review: The Cult Of Smart
Summary and commentary on The Cult Of Smart by Fredrik DeBoer.” Astral Codex Ten. February 17, 2021.

There’s a lot going on in this review. I’d highlight that Fredrik’s DeBoer’s blog has an RSS feed, which you can add to your RSS reader. I’m looking forward to reading more of his commentary.

Open Question: Is education an unqualified good?

I recently had an online discussion with someone who, in broad strokes, seems to agree with the above position, i.e., if we only had enough education, we would solve much of society’s problems. I think this is a standard U.S. liberal stance, which positions educational attainment as the means for advancement into the middle class.

Education is the great lie of U.S. liberal politics. Lest you think I’m a conservative trying to own the libs, let me first talk about the great lie of U.S. conservative politics in order to draw parallels.

The great lie of U.S. conservative politics is that you can have a global war-fighting capability and small government. The U.S. conservative lie is easy to grasp. There’s obviously a tension between government size and the ability to fight any war, much less a capability that involves nearly a thousand foreign military bases and nearly a trillion dollars of military spending every year, more if we include the debt servicing for past wars.

But, how is education like war? Isn’t education an unqualified good? The similarity is that just as small government caps one’s ability to fight wars, there is a demand limit on education. Most education is vocational instruction. People go to school in order to get a credential that gives them a better chance of getting a job. The education is, in large part, a secondary effect to the real demand for better employment opportunities.

It’s also possible to juice this demand. For example, I know of one university, and I imagine it is a feature of most universities, where jobs that used to employ people straight out of high school now require a university degree. The university, by implementing this requirement, increases demand for its product. But, does being an administrative assistant in the university organization really require this level of training? Does one need a Bachelor’s degree in communication, business, English, etc. in order to answer the telephone, write a Word document or navigate an Excel spreadsheet? Aren’t these skills acquired in the high school curriculum these days (and if not, shouldn’t they be)?

And you can see this happening at a broader scale as university administration has become professionalized. Instead of professors running university business in addition to their teaching, professors teach and the university business has been outsourced to administrators.

And, it’s not just universities. The same phenomena is happening across industries. It’s true of every level of government. It’s true of most industries, but particularly those that are tied closely to government. Look through the top industries by GDP in the United States: healthcare, durable goods manufacturing, food & travel, retail, etc. Almost everywhere you look, advancement implies management.

So, people go to school to learn a vocation. You get in the door, and then, in order to advance, no matter what industry you are in, you need to get into management. Leaving us to wonder, what exactly is vocational education for? Further, how large is the real need for managers, as opposed to front-line workers?

If you think it through, it is obviously a con, no different in its contradictions than talking about small government and global war. Management, by definition, has to be small. So, no amount of education is going to improve the lot of people getting educated to qualify for those relatively few positions. The only way that education works is if there are paths of advancement that actually require an education and aren’t management.

For example, if Dragon Naturally Speaking has taken over all the transcriptionist jobs, if Level 5 artificial intelligence has taken over from the teamsters, if 3D printing technologies have reduced the number of people working at construction sites, if fast food can become a largely automated process, etc., what will become of those people doing those jobs?

The most likely outcome is that there will be a compression of people into low skill jobs, driving down wages for everyone. There will be some people that will move into positions of managing machines. Someone will have to check on the artificial intelligence drivers, to make sure the results are as intended and to intervene when it starts to become very Sorcerer’s apprentice. But, the net is less jobs for people and more jobs for machines.

And, this is where the education argument starts to look plausible. People can be trained and are needed to supervise and inspecting the work of machines. In some ways, we are already preparing for that world, where people in low skill jobs are treated as if they are machines. For example, see some of the discussion about the conditions in Amazon warehouses and how that is breathing new life into the labor movement.

But, in the end, there is limited demand for education. Most people go through the process of getting an education credential for the vocational dividends that pays. But, it is clear that the university model and the push for education doesn’t deliver on its promise. And, when people are sitting on a mountain of debt and cannot find work, are they going to sell the educational dream to their children?

Another detail worth consideration, did the COVID-19 pandemic finally show that the promise of MOOCs are not something that can be delivered using the university model and university price points? At the very least, the focus on education and how it is delivered needs to be completely rethought. And, as DeBoer points to a deeper problem, our society’s focus on intelligence and expanding it through education is a fundamentally flawed project, as bad as small government and global war-fighting.

Fascists in Need of a Punch

~ cafebedouin

“Fascism: a political philosophy, movement, or regime (such as that of the Fascisti) that exalts nation and often race above the individual and that stands for a centralized autocratic government headed by a dictatorial leader, severe economic and social regimentation, and forcible suppression of opposition

—Merriam-Webster.com Dictionary, s.v. “fascism,” accessed January 24, 2021, https://www.merriam-webster.com/dictionary/fascism.

When I think of fascism, I think of uniforms and the threat of violence. Want to wear a Hawaiian shirt with tactical gear and carry a gun? Into wearing a white hood and burning a cross on someone’s yard you don’t like? You might be a fascist.

In the United States, there are fascist elements baked in. We have ideas that “America” is exceptional. After the Capitol riot of 2021, there was a great deal of talk about the Capitol building being “sacred”. Sacred can mean dedicated to a specific use. But, the more common use implies religion and a deity. What religion is the Capitol building dedicated to? The religion of America.

It is understood that America is white, Anglo-Saxon, and Protestant. America might be a melting pot, but there’s no question what the dominate flavor should be, at least among the fascists.

Then, we have a system of government that has concentrated much of its power into the hands of the President, putting the “sacred” functions of government into the hands of one person. There are even ideas like the unitary executive theory that argue that the President has complete authority over executive functions.

Autocratic control by a dictatorial leader is a feature of the U.S. system. It only requires someone to use it that way with sufficient cooperation from the other branches of government to make it a reality. The 45th President demonstrates the point.

Once you have autocratic government, then severe economic and social regimentation and forcible suppression of the opposition is not far behind. Who is the opposition? It can be some specific group: Jews, immigrants, Muslims, Mexicans, aborigines, Germans, Arabs, Igbo, etc. Or it can be a group fabricated whole cloth, a catch-all term indicating an ideology or an imaginary distinction: Jacobians, anarchists, socialists, communists, terrorists, or antifa.

Every age has its opposition to the status quo, whether it’s anarchists organizing for an eight hour work day; the American Taliban, pushing for the return of a white, Christian orthodoxy; American revolutionaries and/or reformers fighting George III, Lincoln or Jim Crow; etc. All are dangerous to the established order. Whether you think the danger is good or not depends on your values. However, fascist values, with an authoritarian leader and a strong state subordinating the individual or individual states, are also American values. The United States has had its fair share of cult of personality leaders, and in some ways, great man (or woman) narratives tie into the individualist streak of our culture.

Labeling opposition as socialists or neonazis is standard in every kind of politics. It is a time-honored way of reducing nuance and creating The Other that can serve as a catalyst for cohesive action. The target of these labels largely doesn’t matter. They just have to be The Other and someone that opposes, or could oppose, the political project. Fascists do have a unique advantage that such thinking is built into their philosophy of authoritarian control and a national culture.

At the level of the nation, there is little an individual can do. You can only hope in institutions and in good people.

However, the process described above also happens in microcosm at the interpersonal and local levels. Local chapters of Proud Boys, booj and other fascist groups precede the appearance of those ideas on a national stage.

Look for the uniforms. It could be as simple as a color, an article of clothing, etc. Of course, these are also signs of tribalism. The key questions are whether these groups use violence and how.

Neo-nazis may have bad ideas. But, you cannot kill ideas, even bad ones. You can kill and arrest people, however. Sometimes, this is necessary, out of a sense of self-defense of the body politic.

Targeting people raise the stakes on violence. Generally, non-violent resistance raises the moral stakes. It reaches good people by creating opportunities to engage their conscious. But, again, there are individuals that do not respond to this approach. Some people aren’t in touch with their goodness or their conscious. Some people only understand the language of social censure and/or violence.

Violence is a dangerous tool. It is often self-perpetuating. But, it sometimes cannot be avoided. Some fascists, the violent ones trying to dominate a local space who don’t heed non-violent resistance, simply need to be punched. You need to speak to people in languages that they can understand, whether they be moral, violent or other.

Trauma & Transformation

~ cafebedouin ~ 1 Comment

Psychologists like to talk about trauma. If you have experienced X, then it must have been a traumatic experience. But, this is a function of the lens with which they view the world.

Our experience of the world tends to form a lens of interpretation. An emergency room physician — who, by definition, sees emergencies in their community — will think emergencies are normal. It will shape they way they view the world.

The same is true of every line of work. If you are a police officer, you will have developed a heightened sense of whether a situation matches a pattern where people are likely to be breaking the law. If you are an insurance claims adjuster, you will have seen a lot more outlier events and might view certain activities as more risky than others, when they might not be.

The same phenomena applies to psychologists and psychiatrists. They have seen people in their worst psychological condition, and they know to what depths we can all sink. But, the selection bias is such that the people that don’t need their help might be viewed as damaged people that just don’t know that they need their help. But, how often, in most circumstances in life, do we need help and not know it? This situation is unusual, not commonplace.

The problem is that trauma is just one story. We have the ability to overlay onto our experience a whole host of manufactured fictions. And while trauma may have a time and a place, I’d argue that trauma as a primary narrative should be reserved for experiences and situations which truly require assistance from a professional. Most situations don’t.

One person’s apocalypse is another’s day-to-day. If you need help, by all means, get it. There’s nothing wrong with getting it from psychologists or most any other place, if it benefits you. However, I’d argue that we are all much more resilient than we know, that trauma below most thresholds is the means through which we trigger the adaptation response and become stronger – mentally, physically, etc. – in response to our environment. This is not a negative nor should the focus be on the trauma, but in the adaptive response to it.

Of course, there’s taking it to the level of Neitzsche: “What does not kill me makes me stronger.” If you have had a limb cut off, it is unlikely you will become “stronger” in any meaningful sense of the term. But, on the other side, painful experiences do help to build psychic muscles. Doesn’t it make more sense to view most negative experiences as positive forces driving our development over the narrative of trauma?

Why Do We Talk to One Another?

~ cafebedouin

Open Question: Why do we talk to one another?

“…To varying degrees, there is an uncrossable chasm between you and everybody you care about.

There are two ways you can interpret this. One is the depressing route: to believe that your friends are not really your friends and that you don’t really know them. That you will never really know anybody at all. Or you can take the more optimistic route: it’s not that you know your friends less than you thought you did, it’s that you know strangers more. You don’t need to have an established relationship to help someone. Even transient moments have meaning.

This second route is the one my colleagues and I take every time we pick up the phone. Conversations on a phone helpline are different from normal conversations in two ways: we make few assumptions about the caller or their background, and our goal is for the caller to reach a better emotional state than when the conversation started.”

-Natalia Dashan, “Working on a suicide helpline changed how I talk to everyone.” Psyche.co. November 9, 2020.

I find this quote interesting. For me, conversations are about ideas. I talk to people because I want people to know something, or I want to know something. However, I generally view people’s emotional states as their own problem. Managing our emotions is, arguably, one of the defining features that separate human beings from animals.

On the other hand, I recognize that my view is certainly the minority, if not an outlier. Most people’s conversations is primarily emotional in nature, where they are talking about their feelings and want other people to talk about theirs.

My experience is shaped by my relationships with people with Cluster B personality disorders. I have many posts on this topic, e.g., A Narcissist’s Prayer, Hoodoos, Toxic People, Psychic Vampires, Sucking Black Holes, The Unhappy & The Unlucky, etc. The common tactic of people that manipulate others is to get them to talk about themselves, and then, they use this information to their advantage.

In my view, trying to manipulate someone else’s emotional state, even if you are doing so with their benefit in mind, is still manipulation. In certain circumstances, such as when you are working on a suicide help line, this may be appropriate behavior. People are calling in crisis are because they need help. You are there to help them. So, these kinds of interactions are kind of built in.

However, I’m not as comfortable thinking about helping the people in my life this way. This is the kind of behavior that underlies the paternalism that most parents engage in with their children, that what they are doing is for their own good. However, it is often “their own good” from our perspective and not theirs, which can often not be their good but our own. How is this different from the behavior of a Cluster B personality? I’m not sure it is different.

Yet, on the other hand, creating environments where people can grow and be supported emotionally is something most of us want. Individually, we can increase our vocabulary that helps us describe, understand and experience our feelings, using tools such as The Feeling Wheel or the guidebook, “Staying With Feelings“. But, maybe one piece I’ve been missing is that this kind of development ultimately has to be processed through our relationship with others.

The rub, and the thing that is very much not clear to me, is how do you make sure that what you are doing is about getting to a better emotional state for everyone rather than getting a better emotional state for ourselves or manipulating other people’s emotions for some other ends. I find this question difficult, one where I have thought it is best to let people deal with their own emotions and try not to be involved with it. But, I’m thinking, in this moment, that this is naive. Every conversation has an emotional component, and we cannot pretend that we don’t have, at least, some responsibility for the kind of emotional environment we are creating, both for ourselves and others.

I don’t have any answers here. However, I do think these are good questions worth much deeper exploration.