Where Intelligence Comes From: The Theory of Practopoiesis
Neurophysiologist Danko Nikolić has proposed a theory of how life organizes itself, including the organization of a mind. He calls this “practopoiesis” – a general theory of what it takes to be intelligent. It’s equally applicable to biological brains and to artificial intelligence, since it is grounded in cybernetics rather than biology and physiology.
Derived from Ancient Greek praxis + poiesis, practopoiesis means creation of actions. The name reflects the common property found across all the different levels of organization of biological systems: Gene expression mechanisms act; bacteria act; organs act; organisms as a whole act.
In an article published by the Institute for Ethics and Emerging Technologies, Nikolić writes:
It is amazing how intelligent we can be. We can construct shelter, find new ways of hunting, and create boats and machines. Our unique intelligence has been responsible for the emergence of civilization. But how does a set of living cells become intelligent? How can flesh and blood turn into something that can create bicycles and airplanes or write novels?
This is the question of the origin of intelligence.
Although computers calculate millions of times faster than we do, it is we who understand the big picture in which these calculations fit. Even animals are much more intelligent than machines. A mouse can find its way in a hostile forest and survive. This cannot be said for our computers or robots.
The question of how to achieve intelligence remains a mystery for scientists.
Recently, however, a new theory has been proposed that may resolve this very question. The theory is called practopoiesis and is founded in the most fundamental capability of all biological organisms — their ability to adapt.
Darwin’s theory of evolution describes one way how our genomes adapt. By creating offspring new combinations of genes are tested; the good ones are kept and the bad ones are disposed of. The result is a genome better adapted to the environment.
Practopoiesis tells us that somewhat similar adaptation mechanisms of trials and errors occur while an organism grows, while it digests food and also, while it acts intelligently or thinks.
For example, the growth of our body is not precisely programmed by the genes. Instead, our genes perform experiments, which require feedback from the environment and corrections of errors. Only with trial and errors can our body properly grow.
To create intelligent behavior such as thinking, decision making, understanding a poem, or simply detecting one’s friend in a crowd of strangers, our bodies require yet another type of trial-and-error knowledge. There are mechanisms in our body that also contain elaborate knowledge for experimenting, but they are much faster. The knowledge of these mechanisms is not collected through evolution but through the development over the lifetime of an individual.
These fast adaptive mechanisms continually adjust the big network of our connected nerve cells. These adaptation mechanisms can change in an eye-blink the way the brain networks are effectively connected. It may take less than a second to make a change necessary to recognize one’s own grandmother, or to make a decision, or to get a new idea on how to solve a problem.
The slow and the fast adaptive mechanisms share one thing: They cannot be successful without receiving feedback and thus iterating through several stages of trial and error; for example, testing several possibilities of who this person in the distance could be.
Practopoiesis states that the slow and fast adaptive mechanisms are collectively responsible for the creation of intelligence and are organized into a hierarchy. First, evolution creates genes at a painstakingly slow tempo. Then genes slowly create the mechanisms of fast adaptations. Next, adaptation mechanisms change the properties of our nerve cells within seconds. And finally, the resulting adjusted networks of nerve cells route sensory signals to muscles with the speed of lightning. At the end behavior is created.
Probably the most groundbreaking aspect of practopoietic theory is that our intelligent minds are not primarily located in the connectivity matrix of our neural networks, as it has been widely held, but instead in the elaborate knowledge of the fast adaptive mechanisms. The more knowledge our genes store into our quick abilities to adapt nerve cells, the more capability we have to adjust in novel situations, solve problems, and generally, act intelligently.
Our capability to survive and create originates, then, from the adaptive mechanisms that operate at different levels and the vast amounts of knowledge accumulated by each of the levels. The combined result of all of them together is what makes us intelligent.
Nikolić introduces the concept of a practopoietic traverse: “If we can compare two communication channels according to the number of bits of information transferred, we can compare two adaptive systems according to the number of traverses. Thus, a traverse is not a measure of how much knowledge a system has (for that the good old bit does the job just fine). It is rather a measure of how much capability the system has to adjust its existing knowledge for example, when new circumstances emerge in the surrounding world.”
Nikolić continues:
A key requirement for adaptive intelligence is the capacity to observe how well one is doing towards a certain goal combined with the capacity to make changes and adjust in light of the feedback obtained. Practopoiesis tells us that there is not only one step possible from non-adaptive to adaptive, but that multiple adaptive steps are possible. Multiple traverses indicate a potential for adapting the ways in which we adapt.
We can go even one step further down the adaptive hierarchy and consider the least adaptive systems e.g., a book: Provided that the book is large enough, it can contain all of the knowledge about the world and yet it is not adaptive as it cannot for example, rewrite itself when something changes in that world. Typical computer software can do much more and administer many changes, but there is also a lot left that cannot be adjusted without a programmer. A modern AI-system is even smarter and can reorganize its knowledge to a much higher degree. Still, nevertheless, these systems are incapable of doing a certain types of adjustments that a human person can do, or that animals can do. Practopoisis tells us that these systems fall into different adaptive categories, which are independent of the raw information processing capabilities of the systems. Rather, these adaptive categories are defined by the number of levels of organization at which the system receives feedback from the environment — also referred to as traverses.
We can thus make the following hierarchical list of the best exemplars in each adaptive category:
A book: dumbest; zero traverses
A computer: somewhat smarter; one traverse
An AI system: much smarter; two traverses
A human: rules them all; three traverses
Most importantly for creation of strong AI, practopoiesis tells us in which direction the technological developments should be heading: Engineering creativity should be geared towards empowering the machines with one more traverse. To match a human, a strong AI system has to have three traverses.
Practopoietic theory explains also what is so special about the third traverse. Systems with three traverses (referred to as T3-systems) are capable of storing their past experiences in an abstract, general form, which can be used in a much more efficient way than in two-traversal systems. This general knowledge can be applied to interpretation of specific novel situations such that quick and well-informed inferences are made about what is currently going on and what actions should be executed next. This process, unique for T3-systems, is referred to as anapoiesis, and can be generally described as a capability to reconstruct cybernetic knowledge that the system once had and use this knowledge efficiently in a given novel situation.
If biology has invented T3-systems and anapoiesis and has made a good use of them, there is no reason why we should not be able to do the same in machines.
More to read:
- Practopoieses: How cybernetics of biology can help AI
- The original paper on practopoiesis
- Practopoeisis – on Nikolić’s own website