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This volume presents a variety of perspectives from within and outside moral psychology. Recently there has been an explosion of research in moral psychology, but it is one of the subfields most in need of bridge-building, both within and across areas. Interests in moral phenomena have spawned several separate lines of research that appear to address similar concerns from a variety of perspectives. The contributions to this volume examine key theoretical and empirical issues these perspectives share that connect these issues with the broader base of theory and research in social and cognitive psychology. The first two chapters discuss the role of mental representation in moral judgment and reasoning. Sloman, Fernbach, and Ewing argue that causal models are the canonical representational medium underlying moral reasoning, and Mikhail offers an account that makes use of linguistic structures and implicates legal concepts. Bilz and Nadler follow with a discussion of the ways in which laws, which are typically construed in terms of affecting behavior, exert an influence on moral attitudes, cognition, and emotions. Baron and Ritov follow with a discussion of how people’s moral cognition is often driven by law-like rules that forbid actions and suggest that value-driven judgment is relatively less concerned by the consequences of those actions than some normative standards would prescribe. Iliev et al. argue that moral cognition makes use of both rules and consequences, and review a number of laboratory studies that suggest that values influence what captures our attention, and that attention is a powerful determinant of judgment and preference. Ginges follows with a discussion of how these value-related processes influence cognition and behavior outside the laboratory, in high-stakes, real-world conflicts. Two subsequent chapters discuss further building blocks of moral cognition. Lapsley and Narvaez discuss the development of moral characters in children, and Reyna and Casillas offer a memory-based account of moral reasoning, backed up by developmental evidence. Their theoretical framework is also very relevant to the phenomena discussed in the Sloman et al., Baron and Ritov, and Iliev et al. chapters. The final three chapters are centrally focused on the interplay of hot and cold cognition. They examine the relationship between recent empirical findings in moral psychology and accounts that rely on concepts and distinctions borrowed from normative ethics and decision theory. Connolly and Hardman focus on bridge-building between contemporary discussions in the judgment and decision making and moral judgment literatures, offering several useful methodological and theoretical critiques. Ditto, Pizarro, and Tannenbaum argue that some forms of moral judgment that appear objective and absolute on the surface are, at bottom, more about motivated reasoning in service of some desired conclusion. Finally, Bauman and Skitka argue that moral relevance is in the eye of the perceiver and emphasize an empirical approach to identifying whether people perceive a given judgment as moral or non-moral. They describe a number of behavioral implications of people’s reported perception that a judgment or choice is a moral one, and in doing so, they suggest that the way in which researchers carve out the moral domain a priori might be dubious.
Defending Life is arguably the most comprehensive defense of the prolife position on abortion – morally, legally, and politically – that has ever been published in an academic monograph. It offers a detailed and critical analysis of Roe v. Wade and Planned Parenthood v. Casey as well as arguments by those who defend a Rawlsian case for abortion-choice, such as J. J. Thomson. The author defends the substance view of persons as the view with the most explanatory power. The substance view entails that the unborn is a subject of moral rights from conception. While defending this view, the author responds to the arguments of thinkers such as Boonin, Dworkin, Stretton, Ford, and Brody. He also critiques Thomson’s famous violinist argument and its revisions by Boonin and McDonagh. Defending Life includes chapters critiquing arguments found in popular politics and the controversy over cloning and stem cell research.
Computer science and artificial intelligence in particular have no curriculum in research methods, as other sciences do. This book presents empirical methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesis-testing tools to help data speak convincingly, and modeling tools to help explain data. Although many of these techniques are statistical, the book discusses statistics in the context of the broader empirical enterprise. The first three chapters introduce empirical questions, exploratory data analysis, and experiment design. The blunt interrogation of statistical hypothesis testing is postponed until chapters 4 and 5, which present classical parametric methods and computer-intensive (Monte Carlo) resampling methods, respectively. This is one of few books to present these new, flexible resampling techniques in an accurate, accessible manner.Much of the book is devoted to research strategies and tactics, introducing new methods in the context of case studies. Chapter 6 covers performance assessment, chapter 7 shows how to identify interactions and dependencies among several factors that explain performance, and chapter 8 discusses predictive models of programs, including causal models. The final chapter asks what counts as a theory in AI, and how empirical methods—which deal with specific systems—can foster general theories.Mathematical details are confined to appendixes and no prior knowledge of statistics or probability theory is assumed. All of the examples can be analyzed by hand or with commercially available statistics packages.The Common Lisp Analytical Statistics Package (CLASP), developed in the author’s laboratory for Unix and Macintosh computers, is available from The MIT Press.A Bradford Book
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