An official website of the United States government
Abstract Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies—properly conceived as reentrant dynamical flows and not merely as identified groups of neurons—may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.
more »
« less
There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
more »
« less
- PAR ID:
- 10463686
- Date Published:
- Journal Name:
- Biomimetics
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2313-7673
- Page Range / eLocation ID:
- 110
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Natural kinds are widely understood to be the real classifications of things that actually exist in the world. Natural kinds are the categories we tend to aim for when we seek to understand the world, as it really is. Discovering what these real classifications are is often considered to be the project of scientific research in many fields from astronomy and agronomy to zoology and zymurgy. When we discover something unfamiliar to us and we want to know what sort of thing it is, we might ask: ‘what kind is that?’ For instance, in a physics class, we might ask: ‘what kind of quark is that?’, where the answer might be: ‘that is a charm quark’. In biology, we might ask: ‘what kind of plant is that?’, with the answer being: ‘it is a Venus flytrap (Dionaea muscipula)’. Or, in chemistry, we might ask: ‘what element is that?’, with the answer being: ‘lithium’. Knowing that the thing we asked about is a member of that particular kind tells us a lot about it if it is a natural kind. Membership in a natural kind tells us that the thing in question shares many important characteristics with other things that are in the same natural kind category. For example, consider the category of Venus flytraps. All plants that belong to that category share many important characteristics; among these include: perennial flowering, carnivorous eating habits, capable of thigmonastic responses (closing their ‘trap’ when prey alight on their trichomes), ability to photosynthesise, belonging to the family Droseraceae and the kingdom Plantae. Some of these important characteristics and properties have been referred to as ‘essential’ by philosophers because they are the properties that are thought to be necessary for the thing to be a member of that natural kind. That means that if the thing does not have those necessary properties, then it cannot be a member of that natural kind. When we ask the question: ‘what kind is that?’, we do not always discover natural kinds. Sometimes when we ask: ‘what kind of thing is that?’, we find out, for instance, that this thing that we are asking about is green. This means we find out that it belongs to the category of green things. The category of green things is a kind category, but it is not a natural kind. The category of all green things includes the Venus flytrap but also green traffic lights, green tea, guacamole, collards, and dark jade-painted 1978 Ford Mustang sportscars. What all of these things have in common is that they are all green. However, they do not share any other properties or characteristics apart from being green. Green kinds of things are not natural kinds like those mentioned earlier. The kinds that are picked out by the classifications of charm quark, Venus flytrap, and lithium are considered to be very different from the classification of green things. Whilst all charm quarks, all Venus flytraps, and all samples of lithium are each considered to be classifications of natural kinds, the category of green things is not. The philosophical question that arises is: ‘what makes classifications like that of the natural kind that includes all charm quarks natural and classifications like that of all green things not natural?’ Put a different way: ‘what makes something a natural kind and how can we tell the difference between natural kinds and what we might call “artificial kinds”, like the grouping of green things?’ A popular answer to this question is that natural kinds pick out natural groupings whose existence in the world is not dependent upon human interests or activities, whereas artificial kinds pick out groupings whose existence in the world is dependent upon human interests or activities. However, others have provided substantial evidence challenging this claim, arguing that there are at least some natural kinds that are dependent upon human activities and practices for their existence. In addition to questions concerning what qualifies as naturalness in natural kinds and what is the distinction between natural and artificial kinds, philosophical discussion also focuses on the metaphysics of natural kinds and the epistemic value of natural kinds. A perennial question widely debated is whether the classifications used in scientific disciplines – physics, chemistry, biology, neuroscience, geology, linguistics, anthropology, and more –really do map on to a natural classification that really exists in the world. That is, are the ways we partition elements in chemistry, organisms in biology, or quarks in physics, the same partitionings that naturally exist? A lot of the literature on natural kinds relies on using examples that are thought to be quintessential natural kinds, like biological species and chemical elements. But others argue that there is clear evidence that many, if not most, biological species and chemical elements are not natural kinds, especially if membership within a natural kind requires possession of an essential property. Within the discussion of natural kinds, there are also questions with regard to the conditions of membership that challenge the view that natural kinds membership is determined by the possession of a particular essence. Instead of the possession of a particular essence, some argue that membership in a natural kind may instead be determined by the possession of a cluster of properties, a relationship, or something else. In many of these discussions, Plato’s metaphor of carving nature at its joints is used to describe the mapping of natural classifications onto natural kinds by the implied comparison to the butchering of an animal along its natural divisions (knuckles, limbs, etc.) rather than partitioning it in a way that does not coincide with the animal’s body structure. Whilst the metaphor helps explain the nature of natural kinds, it does so by assuming nature is that which is pre-partitioned.more » « less
-
It has been argued that the historical nature of evolution makes it a highly path-dependent process. Under this view, the outcome of evolutionary dynamics could have resulted in organisms with different forms and functions. At the same time, there is ample evidence that convergence and constraints strongly limit the domain of the potential design principles that evolution can achieve. Are these limitations relevant in shaping the fabric of the possible? Here, we argue that fundamental constraints are associated with the logic of living matter. We illustrate this idea by considering the thermodynamic properties of living systems, the linear nature of molecular information, the cellular nature of the building blocks of life, multicellularity and development, the threshold nature of computations in cognitive systems and the discrete nature of the architecture of ecosystems. In all these examples, we present available evidence and suggest potential avenues towards a well-defined theoretical formulation.more » « less
-
Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these systems measure the 'real world' and produce an assessment of the 'world state' - in this case an assessment of some individual trait. Instead of using proxies or scores to evaluate people, they increasingly deploy a logic of revealing the truth about reality and the people within it. While these profiling knowledge claims are sometimes tentative, they increasingly suggest that only through computation can these excesses of reality be captured and understood. This article explores the bases of those claims in the systems of measurement, representation, and classification deployed in computer vision. It asks if there is something new in this type of knowledge claim, sketches an account of a new form of computational empiricism being operationalised, and questions what kind of human subject is being constructed by these technological systems and practices. Finally, the article explores legal mechanisms for contesting the emergence of computational empiricism as the dominant knowledge platform for understanding the world and the people within it.more » « less
-
The ability to engineer complex multicellular systems has enormous potential to inform our understanding of biological processes and disease and alter the drug development process. Engineering living systems to emulate natural processes or to incorporate new functions relies on a detailed understanding of the biochemical, mechanical, and other cues between cells and between cells and their environment that result in the coordinated action of multicellular systems. On April 3–6, 2022, experts in the field met at the Keystone symposium “Engineering Multicellular Living Systems” to discuss recent advances in understanding how cells cooperate within a multicellular system, as well as recent efforts to engineer systems like organ-on-a-chip models, biological robots, and organoids. Given the similarities and common themes, this meeting was held in conjunction with the symposium “Organoids as Tools for Fundamental Discovery and Translation”.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/biomimetics8010110
