The Machine Conception of the Organism in Development and Evolution: A Critical Analysis

This article critically examines one of the most prevalent metaphors in modern biology, namely the machine conception of the organism (MCO). Although the fundamental differences between organisms and machines make the MCO an inadequate metaphor for conceptualizing living systems, many biologists and philosophers continue to draw upon the MCO or tacitly accept it as the standard model of the organism. This paper analyses the specific difficulties that arise when the MCO is invoked in the study of development and evolution. In developmental biology the MCO underlies a logically incoherent model of ontogeny, the genetic program, which serves to legitimate three problematic theses about development: genetic animism, neo-preformationism, and developmental computability. In evolutionary biology the MCO is responsible for grounding unwarranted theoretical appeals to the concept of design as well as to the interpretation of natural selection as an engineer, which promote a distorted understanding of the process and products of evolutionary change. Overall, it is argued that, despite its heuristic value, the MCO today is impeding rather than enabling further progress in our comprehension of living systems

From ends to causes (and back again) by metaphor: the paradox of natural selection

Natural selection is one of the most famous metaphors in the history of science. Charles Darwin used the metaphor and the underlying analogy to frame his ideas about evolution and its main driving mechanism into a full-fledged theory. Because the metaphor turned out to be such a powerful epistemic tool, Darwin naturally assumed that he could also employ it as an educational tool to inform his contemporaries about his findings. Moreover, by using the metaphor Darwin was able to bring his theory in accordance with both the dominant philosophy of science in his time and the respected tradition of natural theology. However, as he introduced his theory of evolution by natural selection in On the origin of species in 1859, the metaphor also turned out to have a serious downside. Because of its intentional overtones, his contemporaries systematically misunderstood his metaphor not as a natural mechanism causing evolution to occur but as an agent who works towards particular ends. The difference in success between natural selection as an epistemic tool and its failure as an educational tool is labelled as a paradox. We explain the paradox from a cognitive perspective and discuss the implications for teaching evolution

Acquisition of Autonomy in Biotechnology and Artificial Intelligence

This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could show self-directed behavior as to the determination of their step-wise decisions on courses of action. This question remains largely open and calls for some important qualifications. We try to make sense of the presence of claims of freedom in agency, first in common sense, then by ascribing developmental plasticity in biology and biotechnology, and in the mapping of programmed systems in the presence of environmental cues and self-referenced circuits as well as environmental coupling. This is the occasion to recall attempts at working out a logical and methodological approach to the openness of concepts that are still to be found, and assess whether they can operate the structuring intelligibility of a yet undeveloped or underdeveloped field of study, where a “bisociation" and a unification of knowledge might be possible

The World as Evolving Information

This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex. The paper presents five tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, and complexity principles. These are further used to discuss the notions of life and cognition and their evolution

Complexity and Philosophy

The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This paper reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that knowledge is intrinsically subjective. These developments are being integrated under the header of “complexity science”. Its central paradigm is the multi-agent system. Agents are intrinsically subjective and uncertain about their environment and future, but out of their local interactions, a global organization emerges. Although different philosophers, and in particular the postmodernists, have voiced similar ideas, the paradigm of complexity still needs to be fully assimilated by philosophy. This will throw a new light on old philosophical issues such as relativism, ethics and the role of the subject

Social Situatedness: Vygotsky and Beyond

The concept of ‘social situatedness’, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics

Structures, inner values, hierarchies and stages: essentials for developmental robot architectures

In this paper we try to locate the essential components needed for a developmental robot architecture. We take the vocabulary and the main concepts from Piaget’s genetic epistemology and Vygotsky’s activity theory. After proposing an outline for a general developmental architecture, we describe the architectures that we have been developing in the recent years - Petitagé and Vygovorotsky. According to this outline, various contemporary works in autonomous agents can be classified, in an attempt to get a glimpse into the big picture and make the advances and open problems visible