The invention of the computer has revolutionized science. With respect to finding the essential structures of life, for example, it has enabled scientists not only to investigate empirical examples, but also to create and study novel hypothetical variations by means of simulation: ‘life as it could be’. We argue that this kind of research in the field of artificial life, namely the specification, implementation and evaluation of artificial systems, is akin to Husserl’s method of free imaginative variation as applied to (...) the specific regional ontology of biology. Thus, at a time when the clarification of the essence of our biological embodiment is of growing interest for phenomenology, we suggest that artificial life should be seen as a method of externalizing some of the insurmountable complexity of imaginatively varying the phenomenon of life. (shrink)

I will entertain and reject three arguments which putatively establish that the individuals produced through de-extinction ought to be the same species as the extinct population. Forms of these arguments have appeared previously in restoration ecology. The first is the weakest, the conceptual argument, that de-extinction will not be de-extinction if it does not re-create an extinct species. This is misguided as de-extinction technology is not unified by its aim to re-create extinct species but in its use of the remnants (...) of extinct populations as a resource. The second is the argument from authenticity; the populations produced by de-extinction technologies will be inauthentic if they are not of the extinct species and, therefore, will not be valuable. I argue authenticity is not required in conservation as the value of authenticity varies between people and cultures, and the novelty of de-extinct species will be equally desirable in many cases. The third argument is from retributive justice; we need the de-extinct population to have the same species identity as we owe a moral debt to the extinct population. I find the case for retributive justice unconvincing and argue that acting as if we have a duty to resurrect extinct species will result in a world with less species. Ultimately all the arguments that connect de-extinction technology to species identity fail, leaving us to consider a more complex calculus for the justification of de-extinction in conservation. (shrink)

A reductionistic, bottom‐up, cellular‐based concept of the origins of sentience and consciousness has been put forward. Because all life is based on cells, any evolutionary theory of the emergence of sentience and consciousness must be grounded in mechanisms that take place in prokaryotes, the simplest unicellular species. It has been posited that subjective awareness is a fundamental property of cellular life. It emerges as an inherent feature of, and contemporaneously with, the very first life‐forms. All other varieties of mentation are (...) the result of evolutionary mechanisms based on this singular event. Therefore, all forms of sentience and consciousness evolve from this original instantiation in prokaryotes. It has also been identified that three cellular structures and mechanisms that likely play critical roles here are excitable membranes, oscillating cytoskeletal polymers, and structurally flexible proteins. Finally, basic biophysical principles are proposed to guide those processes that underly the emergence of supracellular sentience from cellular sentience in multicellular organisms. (shrink)

Finding a scientific, third-person explanation of subjective experience or phenomenal content is commonly called the “hard problem” of consciousness. There has recently been a surge in neuropsychological research on meditation in general and long-term meditators in particular. These experimental subjects are allegedly capable of generating a stable state of consciousness over a prolonged period of time, which makes experimentation with them an interesting paradigm for consciousness research. This perspective article starts out with a historical reconstruction of the “hard problem,” tracing (...) it back to Gottfried Wilhelm Leibniz and Emil du Bois-Reymond in the 18th and 19th century, respectively, and the problem of introspection as already acknowledged by Wilhelm Wundt in the 19th century. It then discusses the prospects of research on long-term meditators from a contemporary perspective and with respect to the neurophenomenological research program already advocated by Francisco J. Varela. (shrink)

The history of what we call molecular biology today is not just the story of DNA. Molecular biology emerged from and was supported by a multiplicity of widely scattered, differently embedded, and loosely, if at all connected experimental systems for characterizing living beings to the level of biologically relevant macromolecules. By implementing different modes of technical analysis, these systems created a new space of representation in which the central concepts of molecular biology gradually became articulated. The paper describes the establishment (...) of the rat liverin vitro protein synthesis system of Paul Zamecnik and his group a the Collis P. Huntington Memorial Hospital of Harvard University between 1947 and 1952. Insofar as such systems orient the research activity, they may also prove helpful for the orientation of the historian. Experimental systems „have a life of their own. (shrink)

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods (...) to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed. (shrink)