Intelligence is a fundamental property of all living systems.
The expression intelligent life is usually applied to classify life-forms, such as humans, which are self-aware, use language, and like to philosophise about free-will. We use it most often in the context of our musings about whether intelligent (i.e. human-like) beings exist elsewhere in the Universe and whether we will one day be able to engage with them. Our anthropocentric perspective on intelligence has had the unfortunate effect of muddling our understanding of what it is and why it exists.
Intelligence, if we define it simply as the ability to acquire and apply information, is a fundamental characteristic of all living things. Living organisms, which are at their essence made of inanimate matter, are so named because they assimilate and organize matter and energy in the service of pattern self-replication. In order to engage and adapt to the environments in which they exist, they must necessarily collect and process, that is acquire and apply, information.
Certainly there are profound differences with regards to the intelligence of different species, but no living organism is entirely devoid of the ability to acquire and apply information. Every living organism interacts with its environment, absorbing and transforming matter, heat and light into energy and biomass according to its inherited genetic blueprint. Even the simplest unicellular life-forms perform amazingly intricate behaviours upon which their survival and reproduction are dependant. These behaviours are anything but random. They are guided by a kind of primordial intelligence that allows the organism to act on relevant information, sensed in its environment and within its own body. When a living organism senses the presence of a resource that it needs or a threat that it is facing, and reacts accordingly by moving towards the resource or away from the threat, it is exhibiting a very basic form of intelligence. That is, it is acquiring and applying information, if only the knowledge of the presence of said resource or threat.
At its essence, intelligence is about making predictions in the service of selecting and implementing behaviours that lead to preferred outcomes. The primary preferred outcomes driven by natural selection are survival and reproduction, but any preferred outcome suffices to motivate intelligence. However, without a preferred outcome, the concept of intelligence is meaningless. If all outcomes are of equal value to an agent, then its behaviour does not need guidance. This is why intelligence is a quality that we only attribute to living things: only living things can prefer, teleologically speaking, one outcome over another. By prefer, I do not mean to imply that all living things are capable of having subjective conscious experiences, but simply that they consistently behave in such a way as to favour certain outcomes, which are generally those that favour their survival and reproduction.
Is an AI a life-form?
Humans have always extended their ability to acquire and apply information by developing tools, from stone implements to ever more advanced AI systems. The forms that our tools take are shaped by our desires, i.e. our preferred outcomes. Necessity really is the mother of invention. Tools, including today’s most advanced AIs want nothing beyond that which their creators want. They are very much a part of us. The fact that they are made up, not of human cells, but of inanimate matter, makes no difference. The atomic building blocks at the root of our biology is just as inanimate as a stone implement or a silicon chip. Life is not about matter. It is a deeply integrated pattern of replication and change, which was set in motion more than 4 billion years ago and continues to expand outwards like a concentric wave on the surface of a pond. Artificial computation from a calculators performing simple algorithms to the most advanced AIs are alive in the sense that they extend us. To the extent that we endow them with their own preferences about future outcomes, they will be life-forms in their own right.
If all life-forms are intelligent, then why do only certain organisms have brains?
A plant has no brain, and therefore no internal cognitive map of its environment which it can navigate to understand causal relationships and improvise strategies based on changing conditions. And yet, it perceives light and reacts by bending towards it. Plants, microbes and other brainless organisms, inherit a kind of virtual cognitive model that is encoded in automatic, i.e. instinctual, reactions, developed through natural selection. In a sense, a light seeking plant’s virtual cognitive model “tells” it to bend towards light, but the proximate cause of its behaviour is simply that it is equipped with light receptors that trigger certain inherited behavioural routines. By virtual, I mean that the instinctual cognitive-model does not have a full abstract representation physically present inside the plant, unlike the cognitive-models inside a human brain, which are represented through patterns of neural connectivity. The virtual model exists only through the mark left on the plant’s inherited anatomy by hidden relationships between its ancestors and its ancestral environment, a mark painted by the coarse brush of life and death. The importance of photosynthesis for the plants’ survival exerted selective pressure on its ancestors. Those which, through mutation, accidentally stumbled upon the beneficial behaviour of bending towards light survived more often than those that did not. Over many generations, the benders took over. So, while an individual plant cannot learn in any important sense*, plant genes are able to learn behaviours such as bending towards light.
Since we humans are organisms, we tend to take an organism-centric view of life. We regard genes as the means by which organisms reproduce. We could just as easily consider life to be centred on genes, with organisms being the means employed by genes to reproduce. From this perspective, the virtual cognitive model discussed above underpins a kind of gene-level cognition.
More complex organisms, including humans, also have plenty of behaviours that are driven by gene-level cognition. We have thousands of bodily reflexes such as those that regulate our breathing, blood circulation, metabolism, cell division, temperature, acidity and much more, which occur subconsciously and are not subject to abstract causal analysis, prediction or decision making at the organism level. However, the presence of a nervous system and brain allows humans, as well many other complex organisms, to adapt some of their cognitive information models, to varying degrees, without having to wait for selective pressure to do its work. These cognitive models don’t just react to information acquired during the lifespan of the organism, but are also directly shaped by it. The advantage of brains, and the extemporaneous organism-level adaptive cognitive models that they bring with them, is that learning can occur at the level of the organism, which means that the resulting behavioural adaptations are many orders of magnitude faster than those from gene-level cognition, i.e. natural selection. Of course, it should also not be forgotten that this higher form of cognition also came about through natural selection and is thus itself a product of gene-level cognition.
The behaviours generated from extemporaneous organism-level cognitive models are based on predicted causal relationships in an individual organism’s environment. These intelligent behavioural changes are more likely to bear fruit than ones based on blindly applied random mutations. They also make it possible for organisms to engage in more complex behaviours. There are limits to the complexity that can be managed through a purely instinctual, gene-level, cognitive model. For example, many cognitive functions in humans need to be calibrated through information feedback loops before they can be used effectively. Examples include vision, motor function and language which each require months or even years of trial and error, i.e. feedback-driven learning, to fully develop. By definition, the learning and calibration of cognitive function through environmental feedback at the temporal scale of an organism, is only possible when cognitive-models can adapt at the level of that organism. Such learning is often accompanied by complementary non-cognitive physiological development. Learning to walk or speak, for example, are complex, feedback-driven, processes in which cognitive and physical developments occurs in tandem, influencing one another along the way.
Thus, the primary difference between gene-level and organism-level cognition is the granularity and speed with which feedback, i.e. information, can be processed. Gene-level learning (a.k.a. natural selection) simply creates random variations in organisms through mutation, and then allows the environment to select, through a life and death feedback process, which variations to retain. This takes time, and any information acquired by an individual organism cannot be processed unless it has a direct impact on its survival and reproduction. Extemporaneous organism-level learning, on the other hand, is fast, and an organism that has it is able to make constructive use of detailed feedback information by physiologically creating, maintaining and navigating an abstract map of its environment, complete with causal relationships that allow it to adapt its behaviour during the course of its life.
*There is some evidence that plant are also be capable of some basic experience based learning.