Progress via Intellectual Progress

Lack of knowledge as the source of stagnation.

While most of progress studies (an emerging field that investigates what causes the progress or stagnation of civilization) is focused on low-level, downstream inputs to human progress, such as energy consumption, institutional design, the science of science, or the history of innovations, it has neglected the most upstream, enabling input—knowledge. 

What is knowledge? Knowledge solves problems.

Knowledge of how to create a fire solves the problem of freezing.

Knowledge of how to control genetics solves the problem of cancer.

Knowledge of how to engineer a fleet of nuclear spaceships solves the problem of asteroid impacts.

Problems do not have to be bad. A good problem is throwing an unforgettable party, writing an inspiring sci-fi novel, or getting to Mars. 

Many of the dominant questions in the field, like "Why have we stopped building A?", "Why haven't we invented B earlier?" or "What happened to our vision of C" have the same answer—because we didn’t know how. We mostly stopped innovating on nuclear power technology because we didn’t know how to prevent the accumulation of regulations. Many of our bright visions of the future from the 70ies were forgotten because we don’t understand how to retain and spread societal optimism in a better future.

Progress is problem-solving. Problem-solving is knowledge creation. Optimism recognizes that all problems are solvable if we create the knowledge in time.

Human progress is described as a product of cultural, economic, and scientific processes. But these are all downstream phenomena. In this essay, I’ll formulate a model of progress as the result of knowledge creation and its growth. If we don’t understand knowledge, we don’t understand progress.

In the first part, I’ll elaborate on these key inputs of Intelligence and knowledge. In the second part, I’ll expand on the model’s supporting functions, cognitive augmentation, education, and, finally, knowledge infrastructure.

High-Level Inputs to Progress

Intelligence, Cognition, Creativity

Intelligence is the core ability that enabled us to solve the problems to survive the harsh environments of our hunter-gatherer ancestors and become earth’s most powerful species.

Without intelligence, creativity, and our ability to create new knowledge, we’d live like apes.

Many definitions of intelligence have been proposed. Max Tegmark, for example, argued that intelligence is the ability to accomplish complex goals. AI researcher Francois Chollet gave a more comprehensive definition in his paper On the Measure of Intelligence as the ability to turn experience into future skills.

David Deutsch defines the related concept of creativity as the capacity to create new explanations. The problem-solving process is driven by conjecturing solutions and criticizing them, using our creativity, until we hit on a solution that solves our problem.

I argue that on the scale of humanity, achieving goals, attaining future skills, or solving problems, can be equated with making progress. Importantly, intelligence, i.e., cognitive processes, can be augmented by technology, as I'll elaborate on below.

Knowledge

Problem Solution Definition

"While awaiting that sight, they had numerous fears as well: fear of storms; fear of mighty, unknown creatures; fear of sickness on board; fear of being becalmed; fear of that wavy immensity opening up all around them; fear of uncertainty. But they also had their charts, their instruments, the technology used to build their vessels. They had knowledge."

—Chiara Marletto

Deutsch summarizes his view on progress in his Principle of Optimism—All evils are caused by insufficient knowledge. Evils include all natural and technological problems, intentional and unintentional. The evil of nuclear war is solved by the knowledge of game theory and international relations. The evil of cancer can be eliminated if we figure out the required gene editing or drug technology. How is that possible?

We can solve these problems because "Either a given technology is possible, or else there must be some reason (say, of physics or logic) why it isn’t possible". Knowledge is what allows us to develop solutions to all our problems.

Accumulation and Evolution

Knowledge evolves. Human knowledge analogously grows through conjecture (mutation) and criticism (variation). Unlike genetic knowledge, human knowledge evolves much faster and does not have a hard limit¹.

The amount of knowledge we can store and process is unlimited, given the technology to do so. Once physically embodied, knowledge tends to cause itself to remain so. We can let our ideas die in our stead. Once we invent planes, the knowledge of their construction lives on in our society, in our brains, in our books, and in the physical plane itself. Note that it only has the tendency. Knowledge can be lost (as in the case of the library of Alexandria) and refuted.

A downstream force against the accumulation and evolution of knowledge are errors or anti-rational memes, especially in our societies' rules and organizations. Errors, among others, consist of conformity seeking, the suppression of curiosity and creativity, and a lack of mechanisms for error correction. On the level of society, "error-corrections" means the removal of bad leaders, policies, and regulations.

What are Anti-rational memes? These ideas rely on disabling the critical faculties of the individual host to cause themselves to replicate. One such meme is religion². The Italian scientist Giordano Bruno was the first to theorize that the universe is infinite but was burned at the stake by the catholic church for his unorthodox ideas. A more contemporary example is how schools inculcate standard patterns of behavior through psychological pressure instead of training and encouraging students’ creativity and curiosity.

So what? 

Knowledge evolves, accumulates, and is the raw, abstract resource we need to solve problems and make progress. However, knowledge accumulation is also hindered by anti-rational memes.

Galileo Demonstrating the New Astronomical Theories at the University of Padua, Félix Parra (1845 - 1919)

Indirect Inputs to Progress 

Now that we outlined the two main inputs of progress, let's look at the indirect inputs of the model.

Cognitive augmentation

Humans have used tools for millions of years, augmenting their bodies, writing for thousands of years, augmenting externalizing and sharing knowledge. Only a few decades ago, we invented computers.

Cognitive augmentation is the field of using computers and other tools to augment our cognitive and intellectual abilities.

We rely on these capabilities to effectively solve problems, i.e., progress.

Cognitive augmentation enables innovation and problem-solving. Humans could only design nuclear reactors or supersonic planes in the first place because we developed complex simulation and computer-aided design software. These simulations and computations would not have been possible with the unaided brain that evolution created. As Einstein remarked, "My pencil and I are more clever than I".

Education

Education is the supported process of acquiring new knowledge in a systematic way to solve complex problems. We can't expect a child to be able to design an electoral system. One way to support the child to get there is to provide them with increasingly difficult examples or simulations of the problems they want to solve.

Later in their lives, they might actually start working on designing an electoral system for an innovative charter city and publish a seminal paper on social-choice theory.

If our education system (and our knowledge infrastructure) works efficiently, this knowledge will now be presented and explained to young students curious about social-choice theory.

I.e., it is effectively fed back into our collective pool of knowledge once the knowledge is created.

I'll expand on the Education System’s flaws in later articles. For now, I recommend Brian Caplan's work for a rigorous economic analysis.

Knowledge Infrastructure

I first grasped the concept of Knowledge Infrastructure while reading my friend Will Bryk's article on the High-Quality Information Society. It starts with two aliens talking about humans, our accomplishments, and our flaws.

Humans are smart: 

• It took us 124 years from discovering atoms to splitting them. 

• It took us 58 years from our first flight to our first space flight.

• Computers became 2^40, so a trillion times more powerful in the last 80 years.    

Humans are also stupid: 

• Many of our most significant inventions were driven by war, i.e., the goal of killing each other. 

• Our education system is largely the same as it was 300 years ago.

Knowledge Infrastructure is the process and technology we utilize to transfer knowledge from one person to another. This process includes informing others about open problems and promising ideas. Inefficient knowledge infrastructure leads to a lot of unnecessary and duplicated work.

It is similar to software infrastructures, such as the internet, improvements in CPU technology, or, recently Etherium, which enables completely new capabilities. But we can also observe this effect on a smaller scale. At Facebook, this is called the Facebook Moore's Law, the phenomenon of Facebook’s product engineers continually benefiting from the efforts of platform and infrastructure engineers.

Knowledge Infrastructure also includes processes that eliminate false theories and criticize erroneous conjectures. One example of such a false claim is the harmfulness of GMO foods. This idea was mainly spread by the non-profit Greenpeace and caused millions of people to die because they were prohibited from being supplied with gene-modified rice.

Knowledge infrastructure is common to every part of the model. I'll expand more on this concept and category in the future.

Model

Thus I propose this abstract model of progress driven by intellectual progress. The primary input of this model is our existing knowledge and our cognitive processes.

These are combined to solve problems, i.e., create solutions, explanations, inventions, and companies, which leads to progress, i.e., technical, moral, political, scientific, and economic progress. This problem-solving process is facilitated by education (mainly in the first part of a person's life) and cognitive augmentation. New knowledge generated is fed back into our input pool of knowledge via education and our knowledge infrastructure.

Summary

The model shows that if we want to make progress, humanity should devote more of our thinking and resources to revolutionizing education and knowledge infrastructure. 

Since there is no infallible, true knowledge and every system has flaws, we need to create processes that allow for criticism and error correction in all parts of society. In the last few thousand years, we've developed a dynamic society, one that actively encourages and facilitates conjecture and criticism. However, during the previous 50 years, we've become more static (see Thiel and Cohen). We forgot our dreams of fast travel and flying cars. We are more pessimistic. We can't accept this stasis if we want to see humanity thrive and progress.

This piece opens up several questions; How do we measure intellectual progress? What are practical steps to improve our education system and knowledge infrastructure? What cognitive augmentation technologies could significantly improve our intellectual abilities?

What's next on Scaling Knowledge?

In future articles, I'll explore the intersection of (complex systems) scaling laws of knowledge infrastructure, the burden of knowledge, curiosity, epistemology, and cognitive augmentation.

1. For comparison, the algorithm that also makes up our intelligence is contained by the 50-100k protein-coding genes. This limit is also called the genomic bottleneck.

2. Religion is a meme that does not allow its followers to question the worldview or laws of nature proclaimed by that religion. Once a child is indoctrinated with that religion, they don’t question it and, in turn, teach it to their own children.