This article examines the intellectual and institutional factors that contributed to the col- laboration of neuropsychiatrist Warren McCulloch and mathematician Walter Pitts on the logic of neural networks, which culminated in their 1943 publication, “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Historians and scientists alike often refer to the McCulloch–Pitts paper as a landmark event in the history of cybernetics, and fundamental to the development of cognitive science and artificial intelligence. This article seeks to bring some historical context to the McCulloch–Pitts collaboration itself, namely, their intellectual and scientific orientations and backgrounds, the key concepts that contributed to their paper, and the institutional context in which their collaboration was made. Al- though they were almost a generation apart and had dissimilar scientific backgrounds, McCulloch and Pitts had similar intellectual concerns, simultaneously motivated by issues in philosophy, neurology, and mathematics. This article demonstrates how these issues converged and found resonance in their model of neural networks. By examining the intellectual backgrounds of McCulloch and Pitts as individuals, it will be shown that besides being an important event in the history of cybernetics proper, the McCulloch– Pitts collaboration was an important result of early twentieth-century efforts to apply mathematics to neurological phenomena.

Recently, historians have focused on Warren S. McCul¬loch’s role in the cybernetics movement during the 1940s and 1950s, and his contributions to the develop¬ment of computer science and communication theory. What has received less attention is McCulloch’s early work in neurophysiology, and its relationship to his philosophical quest for an ‘experimental epistemology’ – a physiological theory of knowledge. McCulloch’s early laboratory work during the 1930s addressed the problem of cerebral localization: localizing aspects of behaviour in the cerebral cortex of the brain. Most of this research was done with the Dutch neurophysiolo¬gist J. G. Dusser de Barenne at Yale University. The con¬nection between McCulloch’s philosophical interests and his experimental work can be expressed as a search for a physiological a priori, an integrated mechanism of sensation.

Much scholarship in the history of cybernetics has focused on the far-reaching cultural dimensions of the movement. What has garnered less attention are efforts by cyberneticians such as Warren McCulloch and Norbert Wiener to transform scientific practice in an array of disciplines in the biomedical sciences, and the complex ways these efforts were received by members of traditional disciplines. In a quest for scientific unity that had a decidedly imperialistic flavour, cyberneticians sought to apply practices common in the exact sciences – mainly theoretical modeling – to problems in disciplines that were traditionally defined by highly empirical practices, such as neurophysiology and neuroanatomy. Their efforts were met with mixed, often critical responses. This paper attempts to make sense of such dynamics by exploring the notion of a scientific style and its usefulness in accounting for the contrasts in scientific practice in brain research and in cybernetics during the 1940s. Focusing on two key institutional contexts of brain research and the role of the Rockefeller and Macy Foundations in directing brain research and cybernetics, the paper argues that the conflicts between these fields were not simply about experiment vs. theory but turned more closely on the questions that defined each area and the language used to elaborate answers.

Key words: Cybernetics, Macy foundation, Neurophysiology, Rockefeller Foundation, Theoretical modeling, Warren S. McCulloch

Excerpt: In 1995, the Leo Apostel Centre in Brussels, Belgium, organised an international conference called “Einstein meets Magritte”. Nobel prize winner Ilya Prigogine held the opening lecture at the conference, and Heinz von Foerster’s lecture was scheduled last… Heinz von Foerster was enchanted by the conference theme and – in the spirit of surrealist Belgian painter René Magritte – had chosen an appropriate title for his talk: “Ceci n’est pas Albert Einstein”. … [H]e was delighted to grant the organisers the following interview, in which he tells us about an even longer journey – that of his remarkable life and scientific career.

Key words: cybernetics, mathematics, interdisciplinarity, Heinz von Foerster

In philosophy, there is an as yet unresolved discussion on whether there are different kinds of kinds and what those kinds are. In particular, there is a distinction between indifferent kinds, which are unaffected by observation and representation, and interactive kinds, which respond to being studied in ways that alter the very kinds under study. This is in essence a discussion on ontologies and, I argue, more precisely about ontological levels. The discussion of kinds of kinds can be resolved by using a semiotic approach to ontological levels, building on the key semiotic concept of representation. There are three, and only three, levels of semiosis: nonor protosemiotic processes without representation, such as physical or causal processes, semiotic processes with representation, such as the processes of life and cognition, and second-order semiotic processes with representation of representation, such as self-awareness and self-reflexive communication. This leads to the distinction between not two, but three kinds of kinds: indifferent, adaptive and reflexive kinds, of which the last two hitherto have not been clearly distinguished.

Key words: Peirce, biosemiotics, constructivist, natural kinds, ontological levels, representation, second-order cybernetics, semiotic levels, semiotic thresholds

Context: The problems that are most in need of interdisciplinary collaboration are “wicked problems,” such as food crises, climate change mitigation, and sustainable development, with many relevant aspects, disagreement on what the problem is, and contradicting solutions. Such complex problems both require and challenge interdisciplinarity. Problem: The conventional methods of interdisciplinary research fall short in the case of wicked problems because they remain first-order science. Our aim is to present workable methods and research designs for doing second-order science in domains where there are many different scientific knowledges on any complex problem. Method: We synthesize and elaborate a framework for second-order science in interdisciplinary research based on a number of earlier publications, experiences from large interdisciplinary research projects, and a perspectivist theory of science. Results: The second-order polyocular framework for interdisciplinary research is characterized by five principles. Second-order science of interdisciplinary research must: 1. draw on the observations of first-order perspectives, 2. address a shared dynamical object, 3. establish a shared problem, 4. rely on first-order perspectives to see themselves as perspectives, and 5. be based on other rules than first-order research. Implications: The perspectivist insights of second-order science provide a new way of understanding interdisciplinary research that leads to new polyocular methods and research designs. It also points to more reflexive ways of dealing with scientific expertise in democratic processes. The main challenge is that this is a paradigmatic shift, which demands that the involved disciplines, at least to some degree, subscribe to a perspectivist view. Constructivist content: Our perspectivist approach to science is based on the second-order cybernetics and systems theories of von Foerster, Maruyama, Maturana & Varela, and Luhmann, coupled with embodied theories of cognition and semiotics as a general theory of meaning from von Uexküll and Peirce.

Key words: Perspectivism, semiotics, complex phenomena, social systems theory, differentiation of science, perspectival knowledge asymmetries.

A number of observations are made about the nature of constructivism, with the suggestion that it is a less revolutionary development that has been claimed, and that some accounts imply an unwarranted disregard of the environment. The presentation is meant to be provocative and to invite discussion that may clarify the issues.

Key words: Cybernetics, Variance, Reality

Purpose: Attention is drawn to a principle of “significance feedback” in neural nets that was devised in the encouraging ambience of the Biological Computer Laboratory and is arguably fundamental to much of the subsequent practical application of artificial neural nets. Design/methodology/approach – The background against which the innovation was made is reviewed, as well as subsequent developments. It is emphasised that Heinz von Foerster and BCL made important contributions prior to their focus on second-order cybernetics. Findings: The version of “significance feedback” denoted by “backpropagation of error” has found numerous applications, but in a restricted field, and the relevance to biology is uncertain. Practical implications: Ways in which the principle might be extended are discussed, including attention to structural changes in networks, and extension of the field of application to include conceptual processing. Originality/value – The original work was 40 years ago, but indications are given of questions that are still unanswered and avenues yet to be explored, some of them indicated by reference to intelligence as “fractal.”

Key words: cybernetics, neural nets, learning.

Open peer commentary on the article “Cybernetic Foundations for Psychology” by Bernard Scott. Upshot: Scott’s proposal is well-founded and opens interesting possibilities. We selected some critical aspects of his argumentation and discuss them in the context of the constructivist perspective. We highlight as Scott’s “blind spot” his statement - presented without further argument - of the need for a conceptual and theoretical unification of psychology from the perspective of second-order cybernetics. We find this especially worrisome as it is based on only one version of cybernetics.

Excerpt: The purpose of this essay is to clarify some of the important senses in which the relationship between the brain and the computer might be considered as one of “modeling.” It also considers the meaning of “simulation” in the relationships between models, computers and brains. While there has been a fairly broad literature emerging on models and simulations in science, these have primarily focused on the physical sciences, rather than the mind and brain. And while the cognitive sciences have often invoked concepts of modeling and simulation, they have been frustratingly inconsistent in their use of these terms, and the implicit relations to their scientific roles. My approach is to consider the early convolution of brain models and computational models in cybernetics, with the aim of clarifying their significance for more current debates in the cognitive sciences. It is my belief that clarifying the historical senses in which the brain and computer serve as models of each other in the historical period prior to the birth of AI and cognitive science is a crucial task for an archeology of AI and the history of cognitive science.