Consider Type 2 Diabetes as a parallel: it occurs when the body's insulin signaling system breaks down, causing cells to believe they're starving even while swimming in glucose. Our monetary system may be creating a similar dysfunction at a societal level – false signals of scarcity amid apparent abundance.

Correlation alone doesn't prove causation, but the persistence of this pattern across different cultures and eras suggests a deeper link.

As currency loses its reliability, essential goods like housing and education become disproportionately expensive relative to wages. Families respond by delaying or reducing childbirth, mirroring cells that misread insulin levels and behave as if scarce resources must be conserved.

The usual explanation never made sense to me: societies supposedly have fewer kids as they get richer. Yet history shows the opposite pattern. The Roman aristocrats maintained large families despite their immense wealth. America's post-war generation - the wealthiest ever - achieved record fertility rates. Today's wealthy have even fewer children than average, which this framework explains: wealthy individuals are more exposed to monetary signals through their greater engagement with financial markets.

"Women's education and careers reduce fertility," goes another theory. Yet the Soviet Union combined high female education and workforce participation with strong fertility rates. Saudi Arabia saw massive increases in women's education while maintaining high birth rates until the late 1990s.

"It's urbanization and modern living," others claim. Yet historical London and Paris maintained high fertility throughout their urban growth. Today's megacities in developing nations often have higher birth rates than wealthy countries - the opposite of what the urbanization theory predicts.

A real explanation must work across time and place. These theories don't - but monetary systems might.

The Economic Divergence

When we overlay the expansion of the monetary base against fertility rates from 1959 to 2020, two distinct trends emerge that tell a story of systemic change. As the monetary base expanded—accelerating rapidly after the severance from the gold standard—fertility rates began a structural decline, falling from 3.7 to 1.6 children per woman.

While correlation is not causation, and many social factors contribute to birth rates, the economic signal is difficult to ignore. As the supply of money decoupled from real resources, the cost of the most resource-intensive “project” a human can undertake—raising a family—skyrocketed relative to wages. The expansion of the money supply didn’t create abundance for families; it created asset inflation that moved the goalposts for young parents. Simultaneously, bureaucratic complexity (measured by the growth of federal regulations) expanded, mirroring the biological response of an organism trying to manage a dysregulated system.

The Diabetic Society

In diabetes, repeated insulin spikes create a cycle of inflammation that blunts cells’ ability to sense glucose. In our economy, monetary expansion works similarly. When money is printed, it doesn’t flow evenly; it flows into assets first.

Look at housing: monetary expansion inflates asset prices, making homes “unaffordable.” The bureaucratic response? Rent control, zoning laws, and housing subsidies. Home prices have risen dramatically compared to incomes not because houses got better, but because the measurement system (money) got corrupted.

Families respond to this false signal of scarcity just as cells respond to insulin resistance: they conserve resources. In biological terms, this means metabolizing less energy. In sociological terms, it means reproducing less. The high cost of living is the economic equivalent of cellular starvation amidst plenty.

Historical Parallels

The Late Roman Empire offers a haunting parallel. While we lack the granular data of the modern era, historical records indicate a synchronization between the debasement of the Denarius and the collapse of elite family structures.

As Rome progressively reduced the silver content of its coinage to fund imperial expansion and bureaucracy, the cost of maintaining social status skyrocketed. Historical sources, such as the legal reforms of Augustus, reveal a state desperate to reverse a precipitous drop in fertility among the aristocracy. The state attempted to fix this not by restoring sound money, but through the ius trium liberorum, a suite of laws granting special privileges to parents of three or more children.

It didn’t work then, and similar subsidies aren’t working now. The bureaucratic response (more laws, more complexity) mirrored the defensive inflammation of a sick body, but it failed to address the root cause: the signal carrying the economic energy had lost its integrity.

Modern Acceleration

The main difference between Rome and our era is speed. While Rome’s cycle played out over centuries, we are witnessing these effects in decades. Furthermore, unlike Rome’s localized debasement, today’s fiat monetary system is global.

As major economies simultaneously moved away from sound money backed by precious metals toward pure fiat currencies, birth rates collapsed across the developed world. The transmission mechanism appears to be the same everywhere: monetary expansion leads to asset inflation, which creates a “cost of living” crisis that signals scarcity to young families. Global fertility trends look suspiciously like the inverse of global liquidity trends. Modern financial markets allow these false signals to propagate instantly, convincing an entire generation that despite our technological abundance, we are too poor to reproduce.

A Potential Solution

Thankfully, this time around we have new tech. Bitcoin can provide a better foundation for money than precious metals ever could. It's perfectly verifiable, highly liquid, and extremely difficult to confiscate. This means that once Bitcoin is adopted as the foundation of money, the State won't be able to easily force people off it. The question is whether we will adopt it in time, or if the system needs to reset once more before the patch is installed.

Sources

• Federal Reserve Bank of St. Louis (FRED) - Monetary Base (M0) data

• United Nations World Population Prospects (2024) - US Fertility Rates

• Office of the Federal Register - Annual Pages Published

• Butcher, Kevin, and Matthew Ponting. (2014). "The Metallurgy of Roman Silver Coinage: From the Reform of Nero to the Reform of Trajan" - Silver content of denarii

• Hug, Angela G. (2014). "Fecunditas, Sterilitas, and the Politics of Reproduction at Rome" - Roman fertility data

• The Digest of Justinian, Alan Watson (1984) - Administrative complexity data

However, after some time, the owner of the Arcade notices a peculiar behavior. The model that first won every game now started to lose some games, but the number of games played increased. The total number of wins increased. 

Kids that come to the arcade to play get quickly discouraged if they lose 100% of the time, but if they sometimes get to win, they stay longer and play more games. The model has learned a truth about reality beyond the game’s mechanics. Remember that the information that the model has access to is the movements of the arcade’s joystick and buttons. 

The model does not know (let’s think of it as a person for a moment since it can help grasp the idea) that the kids exist, and even if it did, it would not be able to comprehend it. The model does not know why losing sometimes helps deliver on its optimization function; all it knows is that it does. 

The model is a metaphor for us. The probability that we see reality as it is is 0% (Mark, Marion, Hoffman, 2010). What we perceive through our senses is the equivalent of joystick movements and button presses. They offer a connection to reality, but they tell us nothing of its true nature; even if they did, we would likely be unable to comprehend it. 

Reference

Mark, J., Marion, B., Hoffman, D., 2010. Natural selection and veridical perceptions. Journal of Theoretical Biology 266 (2010) 504–515

The opportunity

Twitter would make $4.8b a year if they charged $12/year for a handle to their ~400m users (it costs $12 to renew a .com domain). For comparison, their total revenue for 2021 was $5.1b. Not every user would pay, but more income could come from auctioning off new names and taking a commission from secondary market sales. We check for available domain names at my company and match Twitter handles when creating a new brand. Spending at least $10k on a Twitter handle would make sense if we spend $100k on a domain name. 

People do not like to pay for things they used to get for free, but you do not own it when you do not pay for your handle. Many use a Twitter account as their online presence, and 12$/year is an excellent deal for gaining more control over your identity. 

Better business, better product

Twitter is struggling with spam, impersonations, and scams, and these issues would mostly go away if the platform charged for handles. Twitter scams are profitable because automation and free access to the platform result in marginal costs—even tiny income per targeted user amount to substantial revenue at scale. This business model falls apart if they pay $12 per account. 

Users could still create free accounts, but their handles would be their ID: a string of numbers – hard to remember and not prestigious. They would have to pay for a short handle, and real users would have a mix of followers who pay for handles and those who do not. 

Embracing the ecosystem

Relying on advertising revenue puts Twitter at odds with startups building its ecosystem. Advertising makes up over 85% of Twitter’s revenue, so they cannot tolerate startups “stealing eyeballs”. At the same time, every startup building on Twitter’s social graph and the naming system adds value to the Twitter platform, and Twitter needs a new business model to embrace them.

Imagine you could have your Twitter handle automatically reserved for you on Clubhouse, Substack, and other products. As a user, you would benefit by having consistent branding without fighting over the same handle everywhere. It would remove a layer of complexity for startups and make it easier to build critical mass. And the more successful the startups using Twitter’s naming system, the more money Twitter would make because more people would pay for handles. 

Imagine you could automatically follow the same people on Clubhouse that you follow on Twitter (and the other way around). Startups could integrate with Twitter’s social graph since their interests would be aligned. Every startup building on Twitter’s social graph would expand it, making it even more valuable. 

Social Graph as a Platform

Twitter has stopped short of its potential, and what is holding it back is the business model built around advertising. Dependence on advertising incentivizes keeping the platform closed. Twitter needs to become as open as possible and embrace the role of the social graph as a platform. To do that, they need to cut their dependence on advertising revenue. 

Thanks to Rhys Lindmark for reading a draft of this.  

Discuss on Twitter

If Bitcoin is to develop its economy, it will need some form of high-risk capital. Sooner or later, we will see the first VC fund or an AngelList syndicate denominated in BTC. I.e., the managing partners only receive carry if they return more bitcoins than they raised.

There are already hedge funds operating this way. For example, Adamant Capital. Other examples are the early bitcoin-denominated stock markets such as Havelock, GLBSE, MPEX, and a fund of funds, Bixin. But trading differs from venture capital. VCs, take long-term positions compared to traders. They must find investments that will outperform BTC over 5 years. Not 5 weeks or 5 days. It is not surprising we have not seen them yet. We will see them because of two functions driven by the growing market cap.

1. Slowing of BTC’s price growth in relative terms

2. The growing size of the investment opportunity in companies charging their fees in BTC or denominated in BTC. Several examples of such businesses include exchanges, crypto-lending, etc. Even if their fees are charged in USD, the number of dollars they get correlates with BTC's price.

Activist capital

The Venture Era of Bitcoin will have social implications. Allocating capital is a form of influence often used to further ideological causes. Silicon Valley dominates the venture capital market today. Silicon Valley is mainly progressive, and so is VC. Many firms seek to invest in startups working on global warming. They also often push for gender and racial diversity on boards of directors. Funding a military-oriented startup would almost certainly limit one’s ability to participate in many other rounds.

It is reasonable to expect similar dynamics to emerge in the Bitcoin VC market. Investors will value libertarian causes, such as protecting personal freedoms, as much as Silicon Valley VCs value progressive ones.

Thanks to Mattia Gagliardi, Tuur Demeester, PlanB, Ken Seiff, and Nic Carter for reading this draft. 

Illustration: Livija Daudze; editing: Peter Cooper

This post was also published as a tweetstorm.

Link

Here are some gold nuggets: 

“The common denominator of success --- the secret of success of every man who has ever been successful --- lies in the fact that he formed the habit of doing things that failures don't like to do.”

"As to calling habits, unless you have deliberately formed the habit of calling on people who are able to buy but unwilling to listen, then unconsciously you have formed the habit of calling on people who are willing to listen but unable to buy." 

"First of all, your purpose must be practical and not visionary. Some time ago, I talked with a man who thought he had a purpose which was more important to him than income. He was interested in the sufferings of his fellow man, and he wanted to be placed in a position to alleviate that suffering. But when he analyzed his real feeling, we discovered, and he admitted it, that what he really wanted was a real nice job dispensing charity with other people's money and being well paid for it, along with the appreciation and feeling of importance that would naturally go with such a job."

"But Mr. Gray, there's no inspiration in logic. There's no courage in logic. There's not even happiness in logic. There's only satisfaction. The only place logic has in my life is in the realization that the more I am willing to do for my wife and children, the more I shall be able to do for myself." 

Credit: I discovered the pamphlet in The Knowledge Project’s newsletter

There were many attempts at creating a self-sovereign identity³. I am not aware of any design that fulfills all three criteria.

A common approach is nesting an identity in the existing infrastructure, e.g., nation-state-issued identity cards. The user goes through a KYC process and proves his or her existence^{4 5}. This serves as a source of scarcity.

This solution is Sybil-resistant, but it violates the requirement for preserving privacy and self-sovereignty. Proof-of-Authority shares this flaw⁶.

Another approach assumes providing a Proof-of-a-Unique-Human⁷. This methodology can, in theory, be independent of centralized 3rd parties. The identity is derived from a unique feature of the human body — its biometrics. The peer-to-peer process of human-driven checks is designed to ensure the correctness of provided information.

It is questionable whether this system can be secure. However, if this assumption is granted, it still falls shorts of the self-sovereignty and privacy-preservation requirements. It assumes a single identifier issued to each person and needs a verification process.

Finally, solutions are utilizing Web-of-Trust (WoT) approach⁸. In this scheme, anybody can create and control an identity. Anybody can also become an issuer of an identifier. Its validity is defined through the network of connections with other identities.

There is no source of scarcity here. This makes it susceptible to Sybil attacks.

Scarcity of human

The trilemma exists because we do not have a decentralized source of scarcity for human capital.

A potential solution could be derived from a decentralized organization system⁹. In this case, the scarcity stems from the organization's value and can be attributed to each contributor. Contributors can serve as attributes for an identity.

However, for this to serve as a basis for a universal identity system, these organizations would have first to become massively popular. Even when expanded through WoT. 

Another approach could be based on a social graph of personal cryptocurrencies¹⁰. It is a similar idea to WoT. However, the value of social connections gets priced because each connection offers an upside but carries risk for both sides.

This idea is highly experimental and is yet to be tested. There are open questions about whether this approach would be possible to fulfill the privacy requirement. Even if this concern could be resolved, it’s a partial solution at best — it prices in trust between actors, not their expertise or contributions.

A universal design would be possible if a source of scarcity were available as an objective metric. Proof of Work introduced an abstraction of financial capital in the form of an objective metric.

A missing piece is a similar metric providing an abstraction of human capital.

This essay was also published on Twitter as a tweetstorm.

Read next: Attention as a Source of Scarcity for Decentralized Identity Systems.

Thanks for reading an early draft and/or providing feedback to Trent McConaghy, Remco Bloemen, Joe Andrieu, Phil Windley, Jack du Rose, Balázs Némethi. 

1. Joe Andrieu, Kevin Gannon, Igor Kruiper, Ajit Tripathi, Gary Zimmerman, “Clearer Identity Through Correlation”: https://github.com/WebOfTrustInfo/ID2020DesignWorkshop/blob/master/draft-documents/identity-crisis.md

2. For instance, one cannot gain more voting power in a governance model using the identity system. One cannot claim more allocations in investment rounds divided to give equal participation to many participants.

3. Christopher Allen, “The Path to Self-Sovereign Identity” https://t.co/1gkrF2T9Xd

4. Telegram Passport https://telegram.org/blog/passport

5. Civic https://tokensale.civic.com/CivicTokenSaleWhitePaper.pdf

6. POA Network: https://github.com/poanetwork/wiki/wiki/POA-Network-Whitepaper

7. Mohammad-Javad Hajialikhani, Mohammad-Mahdi Jahanara, “UniqueID: Decentralized Proof-of-Unique-Human”: https://arxiv.org/pdf/1806.07583.pdf

8. Sovrin https://sovrin.org/wp-content/uploads/2018/03/Sovrin-Protocol-and-Token-White-Paper.pdf

9. Colony.io https://colony.io/whitepaper.pdf

10. UBI Circles https://github.com/CirclesUBI/docs/blob/master/Circles.md

Heros are usually associated with mythical characters fighting monsters. In practice, groups mimic this pattern by rewarding individuals with influence¹ to incentivize them to take risks. However, these risks can include championing one side in forming conflict with other groups. Thus, a way to gain influence is to take responsibility for a conflict with an opposing group².

This can be as simple as publicly expressing an opinion in today's world.

Of course, these risks include many personal consequences, such as losses of business opportunity, public conflict, a backlash against one’s project, etc. Psychologically taxing ad hominem attacks frequently manifest in this environment.

watching someone get dragged on Twitter for an opinion I secretly agree with pic.twitter.com/j8udY5pubd

— Alex Griswold (@HashtagGriswold) April 26, 2018

Heavy influence can come to those willing to champion one group in an attack or defense against others. A time-tested strategy is to attack individuals expressing certain ideas instead of the ideas themselves. This represents a significant risk to an individual hero, but the reward can be massive in the form of support from other members of his or her group³.

Groups face risks in democratic societies. Less powerful groups are often marginalized by more powerful ones. The hero effect is an important mechanism because vulnerable groups get easily marginalized without it.

Groups need individuals to express their views, but more importantly, to articulate a strong position when confronted by other voices. This way, society can incorporate broader ideas in establishing a consensus.

Thanks to Tre Dudman, and Jason Civalleri for reading the early draft.

This thinking has also been published as a Twitter thread.

1. The rewards take the form of attention and/or money, which are two quantifiable metrics of influence; https://maciek.blog/what-is-influence

2. David and Goliath is a biblical example of this dynamic. After defeating Goliath, David becomes the king of the Israelites. Source: https://www.biblegateway.com/passage/?search=1+Samuel+17&version=NIRV

3. Jordan Peterson's story is a good example of this. He voiced views held by a large but silent group. A more powerful group silenced them by enforcing a social penalty. Peterson incurred the cost. As a result, he was rewarded by the group he took the risk for. In this case, the support came in the form of influence, defined as attention and financial resources. In this video, Peterson explains how the more he gets protested, the more support he receives through Patreon:

Dictionary.com provides the following definition:

“1. a person or thing that influences: 2. a person who has the power to influence many people, as through social media or traditional media”[1]

This is not helpful. It does not indicate what could be a quantifiable metric to measure “influence.”

BusinessDictionary.com provides a better clue:

“Individuals who have the power to affect purchase decisions of others because of their (real or perceived) authority, knowledge, position, or relationship.”[2]

Per this definition, one could quantify the change in the overall purchases due to a given influencer’s actions.

The word “influencer” is usually used in relation to media figures with large social media following. Justin Bieber and Paris Hilton can serve as an example.

It is true that if one of them endorses a product, such as a new line of perfume or a movie, it is likely to impact sales. These sales can be quantified; therefore, one can confirm that these people are indeed influencers. This seems to validate an assumption that large social media following equals an influencer.

However, the chairman of the Central Bank, with 0 social media presence, has the power to impact purchase decisions much larger degree; By changing interest rates.

Does this mean he/she is an influencer? Per this definition, yes.

It is not a given that somebody with a high follower count can make an impact. A recent New York Times story revealed that a significant portion of the Twitter following is fake.[3]

The number of followers is not a conclusive indication of whether somebody is or is not an influencer.

Furthermore, are we ready to accept that influence can only be measured by the ability to affect purchases? It would be too limiting and thus incorrect.

Cambridge Dictionary provides a more holistic definition:

“Someone who affects or changes the way that people behave.”[4]

This seems to be a broad enough definition, but it leaves us with no quantifiable metric.

Let’s try to put this into perspective.

As proved before, Paris Hilton (17.8M followers [5]) is an influencer. She has the power to affect people's behavior which can be quantified in the value of purchases that result from that behavior change.

Vitalik Buterin (630k followers [6]) is also an influencer. Had he endorsed a line of perfume, it would likely have had little result in sales. However, his endorsement for a crypto-related startup would result in a massive investment round and talent flocking to the company.

This change of behavior can be quantified in monetary terms. None of them are purchases.

Paris Hilton has also dabbed in crypto. She endorsed Lydian Network, which per her tweet, she would raise $100M in an ICO [7]. The project raised ca. 1/10 of its goal [8].

The fact that the project underperformed is inconclusive evidence that Hilton has no influence. However, it is reasonable to assume that she has little ability to help crypto startups raise money by endorsing them. One could argue that her endorsement can be counterproductive. It may decrease the project's legitimacy in the eyes of industry insiders.

Why is that? There are probably more people who follow Hilton’s endorsements than crypto-insiders who will be put off by them. It should still be a net gain.

This perspective is missing an important caveat: an average insider will have much more resources at his/her disposal than Hilton’s average follower.

Among Butterin’s followers, multiple people could single-handedly provide $100M in funding.

Some of these people may even follow Hilton. It is likely to be for entertainment purposes rather than to gain investment advice. Despite getting their attention, she is not influencing them in this context. She still might be able to influence them in other contexts, e.g., choice of perfume.

Both of the above count for a change of behavior. However, there is a quantitative difference between influencing somebody for a $100M investment and a $100 purchase of perfume.

Therefore, a true influence seems to be a result of combining the following:

1. How many people pay attention

2. How many of these people and to what degree are going to change their behavior

3. How many resources do those people command on average

Definition and Metric

I suggest the following definition of “influence” that encompasses all three points:

“Ability to cause reallocation of capitals.”

This definition refers to various types of capital that exist in our society. These are primarily: financial, human, social, and political capitals. They are exchangeable. [9]

Reallocation may happen between the type of capital and the object of allocation in one company or another, this or that product, left or the right candidate.

This metric is quantifiable because the capitals can be exchanged for one another. Therefore, any sort of influence – be it in fashion, politics, business, or pop culture can, in theory, be boiled down to this metric.

The reallocation of capital is quantifiable in theory. Tracking it, however, is extremely hard, if not impossible.

Furthermore, per this definition, one needs to trackability. Knowing how influential somebody has been in the past (value of capitals they caused reallocation of) is not directly translatable to the current ability.

There is a high correlation. In most cases, this would be a metric providing accurate results. However, one can identify scenarios in which it would be vastly inaccurate. An example of such a scenario is an investment that an influencer has caused a lot of capital to get allocated to. This was a terrible decision, and now people who listened to him or she is disappointed. They will not listen again.

Another way to think of this is this: somebody who spent $1M is not necessarily a millionaire. They did have a $1M in the past, but it’s not conclusive evidence of whether they have one now.

This metric accurately tracks past influence but is not present. The right metric would provide insights into the state of affairs at the current moment.

This leaves us with one candidate — attention.

Attention is the common denominator in all interactions that result in a reallocation of capital. [10] Therefore, by tracking who pays attention to whom, one can predict the ability to cause said reallocation.

If A and B pay attention to C, C is an influencer. How influential C is depends on the level of influence A and B have.

Often attention flows bi-directionally. C can both influence B and be influenced. Nevertheless, some imbalance will remain in most cases, where one person is more influential than the other.

To put this in perspective, think of a group of friends where some people are into fitness. C has been working out for many years and is in great shape. She knows nutrition and has done many sports. Both A and B listen when she gives them advice.

B started getting seriously into this topic a couple of months ago. He is keen to learn and does a lot of his research. Sometimes he brings up information C was unaware of, so she pays attention to what he says.

A is a couch potato. He went to the gym for the first time recently, and he is in bad shape. His friends might respect his expertise in other fields, but they will disregard his opinions when it comes to fitness.

There is likely somebody else that C pays a lot of attention to. Perhaps a personal trainer or internet fitness guru. By influencing C, D indirectly influences A and B, even if they are unaware of it.

These dynamics exist both in small and large groups.

Attention and Money

The graph could as well illustrate flows between Bitcoin wallets. This is no coincidence.

Attention is the equivalent of money.

One can cause the reallocation of capital indirectly by impacting others. One can also cause the reallocation of capital with the capital in their control.

Maciej Ołpiński introduced a useful framework to think about this. In Userfeed’s whitepaper, he talks about “horizontal relevance,” which is context-independent. This is money and assets, which are universally acceptable. “Vertical relevance” is context-dependent, such as social standing, reputation – or rankings and feeds. [11]

I’d like to suggest another framework — thinking about this in the context of entities and identities.

Entities’ influence is measured in money.

Identities’ influence is measured in attention.

This is helpful in understanding influence beyond the context of people. And it is important to do so.

Each Bitcoin wallet is its entity. Its influence depends on how much money it stores. A person can create a thousand wallets and thus control a thousand entities. A single wallet can be controlled by multiple people.

The same dynamic applies to identities.

We can have multiple identities. Anonymous Twitter accounts often gain significant influence in the crypto community. This influence is detached from the ‘real’ identity of the person(s) controlling an account. Multiple people can control this online identity.

Anonymous identities can become more influential than the ‘real’ ones. The “Satoshi Nakamoto” identity is almost certainly more influential than the real identity of the person or people behind it.

But these are outliers in a peculiar community. As a society, we are distrustful of anonymity, and we discount anonymous contributions.

We have developed methods for evaluating the credibility of real name identities. We use job, academic and other titles. We associate people with institutions they represent or accolades they received. Reputation transfers rely on 3rd parties as much as money transfers.

Replacing financial 3rd parties is not enough to build a decentralized society. We also need a way to replace the reputation 3rd parties.

The key to doing that is measuring the reputation of individual identities. And we can’t measure what we can’t quantify.

Thanks to Maciej Ołpiński and Tomasz Kolinko for reading the draft of this post.

[1] Source: http://www.dictionary.com/browse/influencer, accessed on Feb 11, 2018

[2] Source: http://www.businessdictionary.com/definition/influencers.html, accessed on Feb 11, 2018

[3] Source: The Follower Factory, https://www.nytimes.com/interactive/2018/01/27/technology/social-media-bots.html, accessed on Feb 20, 2018

[4] Source: https://dictionary.cambridge.org/dictionary/english/influencer, accessed on Feb 11, 2018

[5] Source: https://twitter.com/parishilton, accessed on Feb 11, 2018

[6] Source: https://twitter.com/VitalikButerin, accessed on Feb 11, 2018

[7] Source: Paris Hilton is supporting an ICO backed by a man who was convicted of domestic violence, http://www.businessinsider.sg/paris-hilton-backs-ico-lydian-celebrities-endorsing-cryptocurrencies-2017-9/?r=UK&IR=T, accessed on Feb 11, 2018

[8] Source: 

https://lydian.io/

, accessed on Feb 11, 2018

[9] Money can buy work and expertise, reputation, or political support. Human capital – one’s skills, abilities, knowledge, and time can be exchanged for money, reputation, or political support. Reputation and connections may allow one to raise or make money, gain political capital or convince people to lend their skills and time to their cause. Finally, political capital may lead to winning elections, which grants one direct access to resources (money, human capital) and can affect his/her reputation in the communities he or she chooses to support.

[10] Examples may include: convincing somebody to buy something, invest in a business, apply for or accept a job, move from one place to another, donate money to a political campaign, etc.

[11] Source: Userfeeds – an open protocol for establishing information relevance in crypto-economic networks, https://userfeeds.io/Userfeeds_Protocol_Whitepaper_[Draft].pdf, accessed on 22 Feb 2018

Gnudarve made an insightful observation. Reading this comment, I realized that I experienced this myself, too. I was puzzled. I could not explain why it is so powerful.

It took me time to realize that it is similar to an officer yelling at his soldiers, “HOLD THE LINE!”

Contrary to what Hollywood may have us believe, pre-gunpowder battles were surprisingly bloodless. Battles looked like two masses trying to push each other back, with relatively few people getting killed.

Until one side started running away.

If you were a soldier watching a mass of enemy charging at your lines, you had a very important choice: do I hold or run?

That is not an easy choice. Both can mean life or death. It depends on how your comrades are going to behave.

If the line breaks and you are the first to run, you can stay alive better.

If it holds and you run, you will likely be executed.

That is not an easy choice. Your life depends on it. There is no clear answer. And you have to choose RIGHT NOW.

It must have been reassuring to hear the officer screaming, “HOLD THE LINE,” and everybody responding cheerfully.

It rings a bell to what is going on when the price of a cryptocurrency starts dropping by 30% within a couple of hours. I am not implying that it is the same stress that the soldiers experienced. But the psychological mechanism is similar.

Seeing somebody posting an encouraging meme and many people commenting underneath is reassuring. You get the feeling that you know where others stand.

It may seem trivial, but it is not.

History is full of examples proving that a more disciplined army can beat a much larger force.

The Roman army is famous for that. They became an unstoppable military force after Marian reforms in 107 BC. Gaius Marius professionalized the Roman army and introduced a new structure of units. One of the innovations was the creation of Centurions.

Centurion was a professional officer who trained and led his soldiers in battle. They were known for brutal but effective methods of demanding discipline. This gave the Roman army superpowers.

When these first-line officers got killed, often the whole unit fell apart and fled. That is true for the Roman army and many other armies that came after them.

Meme creators play a similar role to a Centurion. All the people up-voting, commenting, retweeting, liking, etc., are like the soldiers uniting in a cheer.

It is a binary piece of information, and memes are an efficient tool for passing it. It is a way of solving the Prisoner’s Dilemma at scale.

Romans and many other armies divided their raw and veteran units. The main reason was that veterans were less likely to break. The more experienced units a given army had, the stronger it was.

Armies and crypto communities are, at some level, the same thing: a group acting towards the same goal and, using Kevin Simmler’s terminology, a superorganism.

In this context, it is not unreasonable to assume that memes and intensity of reactions could be an indicator of the maturity of a given community. I.e. is it a veteran unit or raw recruits.

This, in turn, leads to the conclusion that it could be a signal for predicting how resistant a coin will be during a crash.

This Reddit thread may not be just a joke after all:

“BTC dropping due to lack of quality 11k memes. Closest support line is at 9k Vegeta memes.”

VCs have tried using data to improve their investment decisions. They had moderate success. The problem is that it’s difficult to collect comparable startup data sets.

Netflix has it all for content.

It knows exactly who is watching what, when, and for how long. They track cast and genres. Traditional producers don’t come close to that level of insight.

Data allows Netflix to predict the popularity of content more precisely.

It doesn’t mean they are right every time. But they do have a higher rate of successful bets. And this translates into better unit economics.

Kissmetrics published an analysis that gives an idea of how impactful this is:

“When a network green lights a show, there’s a 35% chance it succeeds and a 65% chance it gets canceled. At the time of this writing, Netflix has 7 TV shows, of which 5 have been renewed for another season. If this rate can continue for years, the Netflix success rate will be about 70%.”

Netflix has become an investment vehicle with elaborate data collection operations.

The content production business (tv, movies, standup specials, etc.) is larger than cable. Streaming has eaten cable. Netflix could extract rent from its streaming business. They instead use it to generate data and dominate content production.

Netflix’s actions seem to confirm this theory.

The content they are focused on is the type that benefits the most from large troves of data. Netflix states on its website:

“We are not a generic “video” company that streams all types of video such as news, user-generated, sports, porn, music video, gaming, and reality. We are a movie and TV series entertainment network.”

New York Times, in its piece on Netflix, quoted an investment bank analyst, Michael Pachter, saying:

““Netflix,” Pachter concluded, “is caught in an arms race they invented.” He compared Netflix to a rat racing on a wheel, staying ahead only by going faster and faster and spending more and more: As its costs continue to go up, it needs to constantly generate more subscribers to stay ahead of others.”

What this view is missing is that Netflix is playing a long game. The content it is producing is going to pay a dividend over time. It is reasonable to grow the subscriber at break-even or loss. It seems this is what they are doing.

This strategy pays off two-fold.

First, Netflix can gather more data. This means better investment decisions. Second, returns on the content that has already been produced improve. It has already been paid for. Now it gains a new audience.

The content that Netflix owns can also be monetized outside of its subscription service. Reed Hastings admitted that this is an option in a letter to shareholders (April 17, 2017):

It seems like Netflix is getting less out of its content than other companies. This comparison is missing accounting for the value of data that is leveraged to lower the cost of buying new content. Source: Investopedia

First, Netflix can gather more data. This means better investment decisions. Second, returns on the content that has already been produced improve. It has already been paid for. Now it gains a new audience.

The content that Netflix owns can also be monetized outside of its subscription service. Reed Hastings admitted that this is an option in a letter to shareholders (April 17, 2017):

“Since our members are funding these films, they should be the first to see them. But we are also open to supporting the large theater chains.”

Innovators Dilemma

Netflix is disrupting content production the way Clayton Christensen described it in Innovator’s Dilemma. First, they dominated categories that were not attractive to established players.

Standup specials are a good example. Netflix owns this category. And it didn’t have to fight for it. It’s not the type of content big studios were interested in. Now Netflix is expanding its territory with star-studded movies.

Reed Hastings told investors that Netflix’s main competitor is sleep. The argument was that there is space for more than one streaming service.

And that’s true for now.

Amazon

Jeff Bezos seems to think along the same lines. He also said that there is space for more than one streaming service.

Bezos was asked why Amazon Video is not on all devices. He explained that having their player was not possible or too expensive.

This is telling. It’s reasonable to assume that Amazon wants to collect viewership data. They are also making significant investments in content.

Netflix is still doing better. It has more experience and has accumulated more data. However, it seems plausible that Amazon can be a threat to Netflix.

It is the only entity I can think of that may be able to get better unit economics. All things equal (subscribers, pricing, content bets), Amazon makes more money. Amazon Video is bundled with Amazon Prime, so it drives overall sales.

Margins

Capital flows where it can get the highest returns. With better unit economics Netflix and Amazon can raise enough money to put old players out of business.

Then they will have to compete with each other, not over subscribers, but the content. This will drive the prices up and the margins down.

Amazon will likely try to take over Netflix at some point in the future. It might have an advantage in unit economics and can afford to bleed its rivals on margins until they agree to sell.

This would not be the first time it happened.

Innovators are often called “startups” and Distributors “corporations.” This nomenclature is counterproductive for understanding the innovation landscape because “startup” is associated with young age and small size, while “corporations” with being large and old.

Neither age nor size is a predisposition to belonging to one group or another. A young, small company can be a Distributor, and a large and old one can be an Innovator. But they cannot be both at the same time.

A common misconception from executives at Distributor-type companies is that they need to adopt more of the startup culture to become more innovative.

I believe this assumption to be false. Assuming the goal is to become more competitive and not switch to another type.

Innovators are risk tolerant; Distributors are risk-averse.

Innovators are experimentation-oriented, and Distributors are process-oriented.

These qualities exclude each other. If you want to become better at running experiments, your ability to maintain efficient processes has to decline, and the other way around.

Instead of attempting to become more innovative, Distributors should strive to create mutually beneficial relationships with Innovators. This way, both types of organizations can focus on what they are good at and combine the benefits of fast-paced experimentation and efficient delivery to customers.

[1] I understand “innovation” as new solutions to known or new problems. I do not qualify incremental improvements, e.g., more computation power of new generations of processors, as innovation for this consideration.