The acceptance of evolution: A developmental view of Generation X in the United States.

The public acceptance of evolution remains a contentious issue in the United States. Numerous investigations have used national cross-sectional studies to examine the factors associated with the acceptance or rejection of evolution. This analysis uses a 33-year longitudinal study that followed the same 5000 public-school students from grade 7 through midlife (ages 45-48) and is the first to do so in regard to evolution. A set of structural equation models demonstrate the complexity and changing nature of influences over these three decades. Parents and local influences are strong during the high school years. The combination of post-secondary education and occupational and family choices demonstrate that the 15 years after high school are the switchyards of life.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

A New Method for a Virtue-Based Responsible Conduct of Research Curriculum: Pilot Test Results.

Drawing on Pennock's theory of scientific virtues, we are developing an alternative curriculum for training scientists in the responsible conduct of research (RCR) that emphasizes internal values rather than externally imposed rules. This approach focuses on the virtuous characteristics of scientists that lead to responsible and exemplary behavior. We have been pilot-testing one element of such a virtue-based approach to RCR training by conducting dialogue sessions, modeled upon the approach developed by Toolbox Dialogue Initiative, that focus on a specific virtue, e.g., curiosity and objectivity. During these structured discussions, small groups of scientists explore the roles they think the focus virtue plays and should play in the practice of science. Preliminary results have shown that participants strongly prefer this virtue-based model over traditional methods of RCR training. While we cannot yet definitively say that participation in these RCR sessions contributes to responsible conduct, these pilot results are encouraging and warrant continued development of this virtue-based approach to RCR training.

Developing a Scientific Virtue-Based Approach to Science Ethics Training.

Responsible conduct of research training typically includes only a subset of the issues that ought to be included in science ethics and sometimes makes ethics appear to be a set of externally imposed rules rather than something intrinsic to scientific practice. A new approach to science ethics training based upon Pennock's notion of the scientific virtues may help avoid such problems. This paper motivates and describes three implementations-theory-centered, exemplar-centered, and concept-centered-that we have developed in courses and workshops to introduce students to this scientific virtue-based approach.

A case study of the de novo evolution of a complex odometric behavior in digital organisms.

Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such behaviors in a laboratory setting. We present results of a study in which digital organisms-self-replicating computer programs that are subject to mutations and selection-evolved in different environments that required information about past experience for fitness-enhancing behavioral decisions. One population evolved a mechanism for step-counting, a surprisingly complex odometric behavior that was only indirectly related to enhancing fitness. We examine in detail the operation of the evolved mechanism and the evolutionary transitions that produced this striking example of a complex behavior.

Ontogeny tends to recapitulate phylogeny in digital organisms.

Biologists have long debated whether ontogeny recapitulates phylogeny and, if so, why. Two plausible explanations are that (i) changes to early developmental stages are selected against because they tend to disrupt later development and (ii) simpler structures often precede more complex ones in both ontogeny and phylogeny if the former serve as building blocks for the latter. It is difficult to test these hypotheses experimentally in natural systems, so we used a computational system that exhibits evolutionary dynamics. We observed that ontogeny does indeed recapitulate phylogeny; traits that arose earlier in a lineage's history also tended to be expressed earlier in the development of individuals. The relative complexity of traits contributed substantially to this correlation, but a significant tendency toward recapitulation remained even after accounting for trait complexity. This additional effect provides evidence that selection against developmental disruption also contributed to the conservation of early stages in development.

Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory.

Inclusive fitness theory predicts that natural selection will favour altruist genes that are more accurate in targeting altruism only to copies of themselves. In this paper, we provide evidence from digital evolution in support of this prediction by competing multiple altruist-targeting mechanisms that vary in their accuracy in determining whether a potential target for altruism carries a copy of the altruist gene. We compete altruism-targeting mechanisms based on (i) kinship (kin targeting), (ii) genetic similarity at a level greater than that expected of kin (similarity targeting), and (iii) perfect knowledge of the presence of an altruist gene (green beard targeting). Natural selection always favoured the most accurate targeting mechanism available. Our investigations also revealed that evolution did not increase the altruism level when all green beard altruists used the same phenotypic marker. The green beard altruism levels stably increased only when mutations that changed the altruism level also changed the marker (e.g. beard colour), such that beard colour reliably indicated the altruism level. For kin- and similarity-targeting mechanisms, we found that evolution was able to stably adjust altruism levels. Our results confirm that natural selection favours altruist genes that are increasingly accurate in targeting altruism to only their copies. Our work also emphasizes that the concept of targeting accuracy must include both the presence of an altruist gene and the level of altruism it produces.

Creationism and intelligent design.

Creationism, the rejection of evolution in favor of supernatural design, comes in many varieties besides the common young-earth Genesis version. Creationist attacks on science education have been evolving in the last few years through the alliance of different varieties. Instead of calls to teach "creation science," one now finds lobbying for "intelligent design" (ID). Guided by the Discovery Institute's "Wedge strategy," the ID movement aims to overturn evolution and what it sees as a pernicious materialist worldview and to renew a theistic foundation to Western culture, in which human beings are recognized as being created in the image of God. Common ID arguments involving scientific naturalism, "irreducible complexity," "complex specified information," and "icons of evolution," have been thoroughly examined and refuted. Nevertheless, from Kansas to Ohio to the U.S. Congress, ID continues lobbying to teach the controversy, and scientists need to be ready to defend good evolution education.

The evolutionary origin of complex features.

A long-standing challenge to evolutionary theory has been whether it can explain the origin of complex organismal features. We examined this issue using digital organisms--computer programs that self-replicate, mutate, compete and evolve. Populations of digital organisms often evolved the ability to perform complex logic functions requiring the coordinated execution of many genomic instructions. Complex functions evolved by building on simpler functions that had evolved earlier, provided that these were also selectively favoured. However, no particular intermediate stage was essential for evolving complex functions. The first genotypes able to perform complex functions differed from their non-performing parents by only one or two mutations, but differed from the ancestor by many mutations that were also crucial to the new functions. In some cases, mutations that were deleterious when they appeared served as stepping-stones in the evolution of complex features. These findings show how complex functions can originate by random mutation and natural selection.