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Where does intelligence come from?

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.

This problem has puzzled many theorists and scientists, and it is particularly important if we want to build intelligent machines. They still lag well behind us. 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.

Our genes contain an elaborate knowledge of which experiments need to be done, and this knowledge of trial-and-error approaches has been acquired through eons of evolution. We kept whatever worked well for our ancestors.

However, this knowledge alone is not enough to make us intelligent.

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 distance could be.

Practopoiesis states that the slow and fast adaptive mechanisms are collectively responsible for 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.

Therefore, our intelligence seems to come from the hierarchy of adaptive mechanisms, from the very slow evolution that enables the genome to adapt over a lifetime, to the quick pace of neural adaptation expressing knowledge acquired through its lifetime. Only when these adaptations have been performed successfully can our networks of neurons perform tasks with wonderful accuracy.

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.

About the Author: 

danko-nikolicDanko Nikolić is a brain and mind scientist, running an electrophysiology lab at the Max Planck Institute for Brain Research, and is the creator of the concept of ideasthesia. More about practopoiesis can be read here


Related Articles: 

  • Nikola Danaylov has interviewed me on practopoiesis.
  • The original paper on practopoiesis can be downloaded as an open access publication.
  • The fast adaptation mechanisms can be referred to as anapoiesis.
  • Practopoiesis may solve some notoriously difficult long-standing problems in neuroscience and philosophy of mind.
  • The most important concept in practopoietic theory is that of adaptive traverse. This is also the concept that happens to be most difficult to understand as to begin thinking about life and intelligence in terms of an adaptive poetic hierarchy.
  • Different adaptive mechanisms i.e., evolution, gene expression, fast adaptation, interact through practopoietic cycle of causation.
  • This is how the mind is organized according to practopoietic theory
  • Practopoiesis bears implications for creation of artificial intelligence and has resulted in proposing AI-Kindergarten.
  • At the time of publishing this post practopoiesis has been standing for many months in the list of the most read articles at the Journal of Theoretical Biology.

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  • Pedro Marcal

    The practopoeisis theory is problematic because it identifies a third level of control but does not define the mechanisms by which it achieves it. In contrast neural networks have shown how many layers can achieve the required ‘logic’ and control ( delayed rewards for example). It’s not surprising that evolution seems to have followed a similar path. The digital resolution of symbolic equations is a triumph of man’s intellect ( I also regard it as intelligence). So is the construction of rules in an ‘expert system’ ( multi multi layers of control).

  • Danko Nikolic

    Dear Pedro, thank you for the comment. I am always happy to receive suggestions for improvement. You are right that we need to know ” … the mechanisms by which it achieves it.” I have offered partly an answer to that in the above article; it discusses the mechanism of fast adaptation, by which anapoiesis (aka, the third level of control) is achieved.

    But one needs more. There are two directions in which we all want to know more.

    First, we may want to know about the biological mechanisms that underlie fast adaptation. What we know today is that this must have to do with the dynamics of ion channels on neuron membranes. But it is too early to tell what exactly happens. More empirical work is needed.

    Second, we may want to know more on how this is supposed to work mathematically. I am working on it. I hope to have a nice paper out at some point soon. Granted, neural networks are worked out mathematically much better than is practopoiesis.

    But let me also point out that this incompleteness is not really a “problem” for the theory. A real problem would be when some empirical evidence clearly contradicts a theory. But it seems that this is not the case, or at least we don’t know of such a problem yet.

    In contrast, deep learning and traditional neural networks have actually what could be called serious “problems” due to contradicting empirical evidence from neuroscience. Back propagation is the most famous problem. Another one is the fact that the brain exhibits fast adaptation, which neural network ignore (i.e., pretend it does not exist).

  • Pedro Marcal

    Dear Danko, thank you for explaining practopoeisis further, particularly your current direction. At the biological level, have you considered the theoretical and experimental work of SOC for fast adaptation? I think for neural networks, the delayed rewards Q theory of Watkins in his thesis at Cambridge U. May well be regarded as a fast adaptation mechanism. This was employed by Hassebis
    et al in AlphaGo. I look forward to and wish you well in your further work on practopoeisis.

  • Danko Nikolic

    Hi again. If by SOC, you mean self-organized criticality, the answer is yes, I did. I also did myself experimental work on SOC in form of neuronal avalanches. So, I am familiar with the topic.

    Regarding Q theory or any other feedback related learning, such methods do not have properties that would qualify them for playing the role that practopoiesis has assigned to slow adaptation processes. What is requires is the ability to change the learning rule. When there is one slower learning mechanism that determines the rules of learning for another faster learning mechanisms, then we are talking about practopoiesis. Q-theory has nothing similar to that.

  • balayogi
  • Dan Vasii

    What if practopoiesis – ability to adapt – is a consequence of intelligence? Then the truth is that we perceive it upside down and inside out – exactly the opposite.

  • Danko Nikolic

    Dear Dan,

    Thank you for the comment and please appologize my slow reply. Of course what you say is in a way true. More intelligent agents will adapt better. However, this probably would not be a useful way of decomposing the problem scientifically. Science needs fundamental principles that are simple. Only then it works well. Considering intelligence more fundamental than adaptation, would not be simple, as the problem of where the intelligence comes from would still be open.

  • Dan Vasii

    The problem it is in a way of a kind of emergency, but not that much. Actually there is a religion that explains where from intelligence comes – the Baha’i Faith. Its Founder, Baha’u’llah, advanced a very interesting approach. He explains that each kingdom constitutes the basis for the next – the mineral, the vegetal, the animal and the human. Each kingdom possessed the fundamental capacity of the previous – mineral/accretion, vegetal/growth and multiplication, animal/movement and perception(senses) and human/abstract intelligence. So, abstract intelligence is a datum for humans and a sort of impossibility for animals. That is why we have AI animal grade – it can fetch data like a dog (Watson/IBM), but we do not have human grade AI. We have to separate the two kinds in order to analize them. As long as they are interlocked, they cannot be clearly analized. Animal grade AI is for humans a sort of OS – it keeps them alive and ready to react in a similar way to animals for emergencies. But abstract thinking is what makes us humans – and animals are unable to perceive humour, arts, sciences, all that humans strive to create and enjoy.

  • Wayne lewis

    Couple things not appreciated in the practopoesis model. 1) there is substantial evidence that endosymbioants influence our thoughts and emotions 2) in a very real sense organisms are relational subjects/objects, we don’t interact with an objective environment, rather, we are intimately part of the process of cocreation. In the words of Fritjof Capra paraphrasing Humberto Marturana life, (and by extension consciousness and intelligence) is fundamentally a (comutual) cognitive process.Danko Nikolic

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