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Information and Knowledge
Principle #7: Systems send and receive information, and encode knowledge
The seventh principle of systems science states that systems send and receive information and they encode knowledge.
We often think about information and knowledge as properties of the human mind, but in reality they can be found operating within any type of system. Cells, mycelial networks, and blockchains all use information and knowledge to achieve their purpose.
This piece will provide formal definitions of information and knowledge that can be applied to all systems. We will then explore the role that these phenomena play in allowing complex adaptive systems to successfully navigate their environment by examining how Ethereum maintains its censorship resistance in a constantly changing and increasingly hostile world.
“In fact, what we mean by information—the elementary unit of information—is a difference which makes a difference…” — Gregory Bateson, Form, Substance and Difference
Information is a measure of surprise. It is the amount of uncertainty that is removed from an observer after they receive a message.
When you flip a coin, you aren’t certain if it will land on heads or tails. When it lands on heads, uncertainty has been reduced to zero. The outcome is certain and you have gained information about the event.
When an entrepreneur starts a new enterprise, they are uncertain about whether or not people will purchase their product. Their first sale reduces a bit of uncertainty, the sale is a message from the market informing them that there is at least some demand for what they are producing. With each additional sale, uncertainty about the venture’s future is removed and information is gained.
Information flows are what allow a system to achieve environmental fitness in a constantly changing world by reducing the uncertainty they experience as they work to achieve their purpose.
Claude Shannon’s information theory defines information mathematically as the negative log of the probability of a message occurring.
The more probable it is that an event will occur, the less information we receive when it does.
Knowledge is the internal structure in a system that allows it to manage information flows, maintain stability, and successfully navigate its environment.
For humans, conscious forms of knowledge are embodied in the networks of neurons in our brains. When we learn something new by receiving information about something that affects us, our neurons undergo rewiring or strengthening of existing connections. Receiving information causes our brain cells to create new axonal connections where needed in order to support the representation of what we now know.
After 10,000 coin flips, we have accumulated knowledge about random coin flips which allows us to determine and know that the chance of a fair coin landing on heads is roughly 50/50.
After two years and 1 million sales, the entrepreneur has accumulated significant knowledge that will inform their future endeavors. This is consciously experienced as a knowing of what types of customers enjoy the product, how often they make purchases, and what sort of improvements or features they’ve requested that could be implemented to increase sales. The neuronal networks in the entrepreneur’s brain have grown and changed structure in a way that allows for all of this new information to be stored and retrieved.
Knowledge is what helps systems navigate successfully in the world. It enables them to comfortably exist in the flows of their environment and handle the future with systemic adequacy.
Mathematically, we can simply define knowledge as the inverse of information.
Knowledge = 1/I.
The more you know, the less you will be surprised. This theory implies that it is impossible to have absolute knowledge of any event.
Maintaining Censorship-Resistance in Ethereum
Last year, Ethereum received a set of significant surprises which informed the system that its censorship-resistance was under threat.
This was alarming as Ethereum’s capacity to be a reliable and credibly neutral platform upon which anyone can deploy programs that run forever depends on this property remaining intact.
“Censorship-resistance in decentralized cryptoeconomic systems is not just a matter of making sure Wikileaks donations or Silk Road 5.0 cannot be shut down; it is in fact a necessary property in order to secure the effective operation of a number of different financial protocols.” — Vitalik Buterin, The Problem of Censorship
In August 2022, The United States Treasury Department placed sanctions on Tornado Cash. Tornado Cash is a “coin mixing” service that helps Ethereum users maintain privacy when transacting on the public network.
The treasury placed a set of Ethereum addresses associated with Tornado Cash to its “Specially Designated Nationals List.” This action effectively banned American citizens from using the tool or transacting with the sanctioned addresses.
A few days later, a software developer who worked on Tornado Cash was arrested in the Netherlands on suspicion of “concealing criminal financial flows and facilitating money laundering through the mixing of cryptocurrencies through the decentralized Ethereum mixing service Tornado Cash.”
Previous uncertainty around whether or not nation-states would sanction pieces of software was eliminated. They would.
In response to this unexpected development in the environment, a series of internal and external information flows have guided Ethereum’s response and added to its knowledge about a potentially existential threat.
Internal Information Flows
Internal information flows are essential for allowing systems to maintain structure and function.
After the sanctions were placed, there was a surge in the number of validators that started blocking transactions from Ethereum addresses that had been placed on the sanctions list. If enough validators choose to block a transaction, it will not be included in the blockchain. The user trying to make the transaction is censored.
Each time a validator chooses to block a transaction it provides the Ethereum system with information about how likely it is that it may eventually lose censorship resistance. The higher the percentage of censored transactions in each block, the less uncertainty there is.
Today, it sits at 46%.
This accumulated data which lives on the Ethereum blockchain represents a form of knowledge about how Ethereum’s likelihood to lose censorship resistance has fluctuated over time. Individuals who stake Ether can use this knowledge by deciding to withdraw support for validators who censor, an action which will inform the system about how much its maintainers value censorship resistance.
External Information from the Environment
Externally, systems must receive and process information from the environment in order to successfully adapt.
Last week a Federal Court affirmed the Treasury Department’s right to place sanctions on Tornado Cash. This is a message to Ethereum which informs it by reducing uncertainty about how many other subsystems of the U.S. government will side with the Treasury.
The decision will be appealed in a Fifth Circuit review, a process which will reveal more information. This could eventually lead to the U.S. Supreme Court hearing the case and making a judgement that provides a very high degree of certainty.
If the Treasury decides to sanction additional pieces of software, that will provide important information about what other sort of behaviors within public blockchain ecosystems the U.S. government considers unacceptable.
In order to survive and continue functioning as designed, Ethereum will need to be constantly aware of what’s happening in the regulatory environment so it can adapt as needed.
Information and knowledge are essential concepts for making sense of system behavior, dynamics, and evolution over time. Formal mathematical definitions of the terms will prove useful in our search for rigorous methods of analyzing and designing systems.
As always, for a much more detailed treatment of this subject please see the source material for this series, Principles of Systems Science.