Are sexes natural kinds?

Asking whether the sexes are natural kinds amounts to asking whether the categories, female and male, identify real divisions in nature, like the distinctions between biological species, or whether they mark merely artificial or arbitrary distinctions. The distinction between females and males in the animal kingdom is based on the relative size of the gametes they produce, with females producing larger gametes (ova) and males producing smaller gametes (sperm). This chapter argues that the properties of producing relatively large and small gametes are causally correlated with a range of other properties in a wide variety of organisms, and this is what makes females and males natural kinds in the animal kingdom. The chapter concludes with a discussion of the relationship between sex and gender: while the difference between the sexes is biologically grounded, the difference between genders is socially based. Since gender depends in part on the perception of sex, whether or not gender is real or not does not depend on whether sex is, since social reality is constituted in part by our perceptions. The claim that sexes are natural kinds in the animal kingdom does not imply that the biological differences among female and male humans do and should have social consequences

Open problems in artificial life

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated

On Fodor on Darwin on Evolution

Jerry Fodor argues that Darwin was wrong about "natural selection" because (1) it is only a tautology rather than a scientific law that can support counterfactuals ("If X had happened, Y would have happened") and because (2) only minds can select. Hence Darwin's analogy with "artificial selection" by animal breeders was misleading and evolutionary explanation is nothing but post-hoc historical narrative. I argue that Darwin was right on all counts. Until Darwin's "tautology," it had been believed that either (a) God had created all organisms as they are, or (b) organisms had always been as they are. Darwin revealed instead that (c) organisms have heritable traits that evolved across time through random variation, with survival and reproduction in (changing) environments determining (mindlessly) which variants were successfully transmitted to the next generation. This not only provided the (true) alternative (c), but also the methodology for investigating which traits had been adaptive, how and why; it also led to the discovery of the genetic mechanism of the encoding, variation and evolution of heritable traits. Fodor also draws erroneous conclusions from the analogy between Darwinian evolution and Skinnerian reinforcement learning. Fodor’s skepticism about both evolution and learning may be motivated by an overgeneralization of Chomsky’s “poverty of the stimulus argument” -- from the origin of Universal Grammar (UG) to the origin of the “concepts” underlying word meaning, which, Fodor thinks, must be “endogenous,” rather than evolved or learned

Minimal model of self-replicating nanocells: a physically embodied information-free scenario

The building of minimal self-reproducing systems with a physical embodiment (generically called protocells) is a great challenge, with implications for both theory and applied sciences. Although the classical view of a living protocell assumes that it includes information-carrying molecules as an essential ingredient, a dividing cell-like structure can be built from a metabolism-container coupled system, only. An example of such a system, modeled with dissipative particle dynamics, is presented here. This article demonstrates how a simple coupling between a precursor molecule and surfactant molecules forming micelles can experience a growth-division cycle in a predictable manner, and analyzes the influence of crucial parameters on this replication cycle. Implications of these results for origins of cellular life and living technology are outlined.Comment: 9 pages, 10 figure

Biomimetic Emotional Learning Agents

This extended abstract proposes a type of AI agent comprised of: an autonomous real-time control system,\ud low-level emotional learning (including a simple\ud knowledge base that links homeostatic/innate drives to sensory perception states), and a novel sliding-priority drive motivation mechanism. Learning occurs in both phylogenetic and ontogenetic training