In The Ethics of Food, Gregory E. Pence brings together a collection of voices who share the view that the ethics of genetically modified food is among the most pressing societal questions of our time. This comprehensive collection addresses a broad range of subjects, including the meaning of food, moral analyses of vegetarianism and starvation, the safety and environmental risks of genetically modified food, issues of global food politics and the food industry, and the relationships among food, evolution, and human (...) history. (shrink)

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

Everyday memory tasks often require that researchers focus on output-bound measures of memory. As a result, nonmemorial processes (e.g., report option and grain size) may influence recall accuracy. These nonmemorial processes, usually eliminated by laboratory researchers, have the potential to explain some anomalous results and may even be useful to enhance everyday recollection.

How social media and DIY communities have enabled new forms of political participation that emphasize doing and making rather than passive consumption. Today, DIY—do-it-yourself—describes more than self-taught carpentry. Social media enables DIY citizens to organize and protest in new ways and to repurpose corporate content in order to offer political counternarratives. This book examines the usefulness and limits of DIY citizenship, exploring the diverse forms of political participation and “critical making” that have emerged in recent years. The authors and artists (...) in this collection describe DIY citizens whose activities range from activist fan blogging and video production to knitting and the creation of community gardens. Contributors examine DIY activism, describing new modes of civic engagement that include Harry Potter fan activism and the activities of the Yes Men. They consider DIY making in learning, culture, hacking, and the arts, including do-it-yourself media production and collaborative documentary making. They discuss DIY and design and how citizens can unlock the black box of technological infrastructures to engage and innovate open and participatory critical making. And they explore DIY and media, describing activists' efforts to remake and reimagine media and the public sphere. As these chapters make clear, DIY is characterized by its emphasis on “doing” and making rather than passive consumption. DIY citizens assume active roles as interventionists, makers, hackers, modders, and tinkerers, in pursuit of new forms of engaged and participatory democracy. Contributors Mike Ananny, Chris Atton, Alexandra Bal, Megan Boler, Catherine Burwell, Red Chidgey, Andrew Clement, Negin Dahya, Suzanne de Castell, Carl DiSalvo, Kevin Driscoll, Christina Dunbar-Hester, Joseph Ferenbok, Stephanie Fisher, Miki Foster, Stephen Gilbert, Henry Jenkins, Jennifer Jenson, Yasmin B. Kafai, Ann Light, Steve Mann, Joel McKim, Brenda McPhail, Owen McSwiney, Joshua McVeigh-Schultz, Graham Meikle, Emily Rose Michaud, Kate Milberry, Michael Murphy, Jason Nolan, Kate Orton-Johnson, Kylie A. Peppler, David J. Phillips, Karen Pollock, Matt Ratto, Ian Reilly, Rosa Reitsamer, Mandy Rose, Daniela K. Rosner, Yukari Seko, Karen Louise Smith, Lana Swartz, Alex Tichine, Jennette Weber, Elke Zobl. (shrink)

Experiments are presented showing that visual search for Mueller-Lyer (ML) stimuli is based on complete configurations, rather than component segments. Segments easily detected in isolation were difficult to detect when embedded in a configuration, indicating preemption by low-level groups. This preemption—which caused stimulus components to become inaccessible to rapid search—was an all-or-nothing effect, and so could serve as a powerful test of grouping. It is shown that these effects are unlikely to be due to blurring by simple spatial filters at (...) early visual levels. It is proposed instead that they are due to more sophisticated processes that rapidly bind contour fragments into spatially-extended assemblies. These results support the view that rapid visual search cannot access the primitives formed at the earliest stages of visual processing; rather, it can access only higher-level, more ecologically-relevant structures. (shrink)

The past few years have seen a resurgence of interest in the scientific study of magic. Despite being only a few years old, this “new wave” has already resulted in a host of interesting studies, often using methods that are both powerful and original. These developments have largely borne out our earlier hopes (Kuhn et al., 2008) that new opportunities were available for scientific studies based on the use of magic. And it would seem that much more can still be (...) done along these lines. -/- But in addition to this, we also suggested that it might be time to consider developing an outright science of magic—a distinct area of study concerned with the experience of wonder that results from encountering an apparently impossible event1. To this end, we proposed a framework as to how this might be achieved (Rensink and Kuhn, 2015). A science can be viewed as a systematic method of investigation involving three sets of issues: (i) the entities considered relevant, (ii) the kinds of questions that can be asked about them, and (iii) the kinds of answers that are legitimate (Kuhn, 1970). In the case of magic, we suggested that this could be done at three different levels, each focusing on a distinct set of issues concerned with the nature of magic itself: (i) the nature of magical experience, (ii) how individual magic tricks create this experience, and (iii) organizing knowledge of the set of known tricks in a more comprehensive way (Rensink and Kuhn, 2015). Our framework also included a base level focused on how the methods of magic could be used as tools to investigate issues in existing fields of study. -/- Lamont (2010) and Lamont et al. (2010) raised a number of concerns about the possibility of such a science, which we have addressed (Rensink and Kuhn, 2015). More recently, Lamont (2015) raised a new objection, arguing that although base-level work (i.e., applications of magic methods) might be useful, there is too little structure in magic tricks for them to be studied in a systematic way at the other levels, ruling out a science of magic. We argue here, however, that although this concern raises some interesting challenges for this science, it does not negate the possibility that it could exist, and could contribute to the study of the mind. (shrink)

The capacity of visual attention/STM can be determined by change-detection experiments. Detecting the presence of change leads to an estimate of 4 items, while detecting the absence of change leads to an estimate of 1 item. Thus, there are two magical numbers in vision: 4 and 1. The underlying limits, however, are not necessarily those of central STM.

Recent developments in vision science have resulted in several major changes in our understanding of human visual perception. For example, attention no longer appears necessary for "visual intelligence"--a large amount of sophisticated processing can be done without it. Scene perception no longer appears to involve static, general-purpose descriptions, but instead may involve dynamic representations whose content depends on the individual and the task. And vision itself no longer appears to be limited to the production of a conscious "picture"--it may also (...) guide processes outside the conscious awareness of the observer. (shrink)

This paper explores the extent to which a scientific framework for visualization might be possible. It presents several potential parts of a framework, illustrated by application to the visualization of correlation in scatterplots. The first is an extended-vision thesis, which posits that a viewer and visualization system can be usefully considered as a single system that perceives structure in a dataset, much like "basic" vision perceives structure in the world. This characterization is then used to suggest approaches to evaluation that (...) take advantage of techniques used in vision science. Next, an optimal-reduction thesis is presented, which posits that an optimal visualization enables the given task to be reduced to the most suitable operations in the extended system. A systematic comparison of alternative designs is then proposed, guided by what is known about perceptual mechanisms. It is shown that these elements can be extended in various ways—some even overlapping with parts of vision science. As such, a science of some kind appears possible for at least some parts of visualization. It would remain distinct from design practice, but could nevertheless assist with the design of visualizations that better engage human perception and cognition. (shrink)

Knill, Kersten, & Mamassian (Chapter 6) provide an interesting discussion of how the Bayesian formulation can be used to help investigate human vision. In their view, computational theories can be based on an ideal observer that uses Bayesian inference to make optimal use of available information. Four factors are important here: the image information used, the output structures estimated, the priors assumed (i.e., knowledge about the structure of the world), and the likelihood function used (i.e., knowledge about the projection of (...) the world onto the sensors). Knill & Kersten argue that such a framework not only helps analyze a perceptual task, but can also help investigators to define it. Two examples are provided (the interpretation of surface contour and the perception of moving shadows) to show how this approach can be used in practice. As the authors admit, most (if not all) perceptual processes are ill-suited to a "strong" Bayesian approach based on a single consistent model of the world. Instead, they argue for a "weak" variant that assumes Bayesian inference to be carried out in modules of more limited scope. But how weak is "weak"? Are such approaches suitable for only a few relatively low-level tasks, or can they be applied more generally? Could a weak Bayesian approach, for example, explain how we would recognize the return of Elvis Presley? The formal modelling of human perception To help get a fix on things, it is useful to examine the fate of an earlier attempt to formalize human perception: the application of information theory. It was once hoped that this theory—a close cousin of the Bayesian formulation—would provide a way to uncover information-handling laws that were largely independent of physical implementation. In this approach, the human nervous system was assumed to have.. (shrink)

Adelson & Pentland (Chapter 11) use an engaging metaphor to illustrate their position on scene analysis: interpretations are produced by a workshop that employs a set of specialists, each concerned with a single aspect of the scene. The authors argue that it is too expensive to have a supervisor co-ordinate the specialists and that it is too expensive to let them operate independently. They then show that a careful sequencing of the specialists leads to solutions of minimum cost, at least (...) for their world of Mondrian panels. (shrink)

One of the more compelling beliefs about vision is that it is based on representations that are coherent and complete, with everything in the visual field described in great detail. However, changes made during a visual disturbance are found to be difficult to see, arguing against the idea that our brains contain a detailed, picture-like representation of the scene. Instead, it is argued here that a more dynamic, "just-in-time" representation is involved, one with deep similarities to the way that users (...) interact with external displays. It is further argued that these similarities can provide a basis for the design of intelligent display systems that can interact with humans in highly effective and novel ways. (shrink)

When looking at a scene, observers feel that they see its entire structure in great detail and can immediately notice any changes in it. However, when brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: identification of changes becomes extremely difficult, even when changes are large and made repeatedly. Identification is much faster when a verbal cue is provided, showing that poor visibility is not the cause of (...) this difficulty. Identification is also faster for objects mentioned in brief verbal descriptions of the scene. These results support the idea that observers never form a complete, detailed representation of their surroundings. In addition, results also indicate that attention is required to perceive change, and that in the absence of localized motion signals it is guided on the basis of high-level interest. (shrink)

Scene Perception is the visual perception of an environment as viewed by an observer at any given time. It includes not only the perception of individual objects, but also such things as their relative locations, and expectations about what other kinds of objects might be encountered. -/- Given that scene perception is so effortless for most observers, it might be thought of as something easy to understand. However, the amount of effort required by a process often bears little relation to (...) its underlying complexity. A closer look shows that scene perception is a highly complex activity, and that any account of it must deal with several difficult issues: What exactly is a scene? What aspects of it do we represent? And what are the processes involved? Finding the answers to these questions has proven to be extraordinarily difficult. (shrink)

This chapter presents an overview of several recent developments in vision science, and outlines some of their implications for the management of visual attention in graphic displays. These include ways of sending attention to the right item at the right time, techniques to improve attentional efficiency, and possibilities for offloading some of the processing typically done by attention onto nonattentional mechanisms. In addition it is argued that such techniques not only allow more effective use to be made of visual attention, (...) but also open up new possibilities for human-machine interaction. (shrink)