Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. (shrink)

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is (...) a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction 2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis? 2.2The informational benefits of multivariate pattern analysis 3Why the Decoder’s Dictum Is False 3.1We don’t know what information is decoded 3.2The theoretical basis for the dictum 3.3Undermining the theoretical basis 4Objections and Replies 4.1Does anyone really believe the dictum? 4.2Good decoding is not enough 4.3Predicting behaviour is not enough 5Moving beyond the Dictum 6Conclusion. (shrink)

I argue that bounded agents face a systematic accuracy-coherence tradeoff in cognition. Agents must choose whether to structure their cognition in ways likely to promote coherence or accuracy. I illustrate the accuracy-coherence tradeoff by showing how it arises out of at least two component tradeoffs: a coherence-complexity tradeoff between coherence and cognitive complexity, and a coherence-variety tradeoff between coherence and strategic variety. These tradeoffs give rise to an accuracy-coherence tradeoff because privileging coherence over complexity or strategic variety often leads to (...) a corresponding reduction in accuracy. I conclude with a discussion of two normative consequences for the study of bounded rationality: the importance of procedural rationality and the role of coherence in theories of bounded rationality. (shrink)

The paper shows why and how an empirical study of fast-and-frugal heuristics can provide norms of good reasoning, and thus how (and how far) rationality can be naturalized. We explain the heuristics that humans often rely on in solving problems, for example, choosing investment strategies or apartments, placing bets in sports, or making library searches. We then show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, (...) including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route, emphasizing ecological rationality (the relationship between cognitive heuristics and environment), and argue that in uncertain environments, more information and computation are not always better (the “less-can-be-more” doctrine). The resulting naturalism about rationality is thus normative because it not only describes what heuristics people use, but also in which specific environments one should rely on a heuristic in order to make better inferences. While we desist from claiming that the scope of ecological rationality is unlimited, we think it is of wide practical use. (shrink)

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we (...) explore fast and frugal heuristics – simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data – that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program. Key Words: adaptive toolbox; bounded rationality; decision making; elimination models; environment structure; heuristics; ignorance-based reasoning; limited information search; robustness; satisficing; simplicity. (shrink)

A new experimental paradigm involving a computerised quiz was used to examine, on an intra-individual level, the strength of association between four components of the surprise syndrome: cognitive (degree of prospectively estimated unexpectedness), experiential (the feeling of surprise), behavioural (degree of response delay on a parallel task), and expressive (the facial expression of surprise). It is argued that this paradigm, together with associated methods of data analysis, effectively controls for most method factors that could in previous studies have lowered the (...) correlations among the components of emotion syndromes. It was found that (a) the components of the surprise syndrome were all positively correlated; (b) strong association existed only between the cognitive and the experiential component of surprise; (c) the coherence between syndrome components did not increase with increasing intensity of surprise; and (d) there was also only moderate coherence between the components of the facial expression of surprise (eyebrow raising, eye widening, mouth opening), although in this case, coherence tended to increase with intensity. Taken together, the findings support only a weakly probabilistic version of a behavioural syndrome view of surprise. However, the component correlations seem strong enough to support the existence of strong associations among a subset of the mental or central neurophysiological processes engaged in surprise. (shrink)

Epistemic responsibility involves at least two central ideas. (V) To be epistemically responsible is to display the virtue(s) epistemic internalists take to be central to justification (e.g., coherence, having good reasons, fitting the evidence). (C) In normal (non-skeptical)circumstances and in thelong run, epistemic responsibility is strongly positively correlated with reliability. Sections 1 and 2 review evidence showing that for a wide range of real-world problems, the most reliable, tractable reasoning strategies audaciously flout the internalist''s epistemic virtues. In Section 3, I (...) argue that these results force us to give up either (V), our current conception of what it is to be epistemically responsible, or (C) the responsibility-reliability connection. I will argue that we should relinquish (V). This is likely to reshape our epistemic practices. It will force us to alter our epistemic judgments about certain instances of reasoning, to endorse some counterintuitive epistemic prescriptions, and to rethink what it is for cognitive agents to be epistemically responsible. (shrink)

Despite the ubiquity of uncertainty, scientific attention has focused primarily on probabilistic approaches, which predominantly rely on the assumption that uncertainty can be measured and expressed numerically. At the same time, the increasing amount of research from a range of areas including psychology, economics, and sociology testify that in the real world, people’s understanding of risky and uncertain situations cannot be satisfactorily explained in probabilistic and decision-theoretical terms. In this article, we offer a theoretical overview of an alternative approach to (...) uncertainty developed in the framework of the ecological rationality research program. We first trace the origins of the ecological approach to uncertainty in Simon’s bounded rationality and Brunswik’s lens model framework and then proceed by outlining a theoretical view of uncertainty that ensues from the ecological rationality approach. We argue that the ecological concept of uncertainty relies on a systemic view of uncertainty that features it as a property of the organism–environment system. We also show how simple heuristics can deal with unmeasurable uncertainty and in what cases ignoring probabilities emerges as a proper response to uncertainty. (shrink)

This article provides an overview of recent results on lexicographic, linear, and Bayesian models for paired comparison from a cognitive psychology perspective. Within each class, we distinguish subclasses according to the computational complexity required for parameter setting. We identify the optimal model in each class, where optimality is defined with respect to performance when fitting known data. Although not optimal when fitting data, simple models can be astonishingly accurate when generalizing to new data. A simple heuristic belonging to the class (...) of lexicographic models is Take The Best (Gigerenzer & Goldstein (1996) Psychol. Rev. 102: 684). It is more robust than other lexicographic strategies which use complex procedures to establish a cue hierarchy. In fact, it is robust due to its simplicity, not despite it. Similarly, Take The Best looks up only a fraction of the information that linear and Bayesian models require; yet it achieves performance comparable to that of models which integrate information. Due to its simplicity, frugality, and accuracy, Take The Best is a plausible candidate for a psychological model in the tradition of bounded rationality. We review empirical evidence showing the descriptive validity of fast and frugal heuristics. (shrink)

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point (...) estimates, decisions, and probability assessments by human participants. The best fit is obtained for a version that weights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implements speed and frugality in a psychologically plausible way. (shrink)

Our aim in this paper is to bring the woefully neglected literature on predictive modeling to bear on some central questions in the philosophy of science. The lesson of this literature is straightforward: For a very wide range of prediction problems, statistical prediction rules (SPRs), often rules that are very easy to implement, make predictions than are as reliable as, and typically more reliable than, human experts. We will argue that the success of SPRs forces us to reconsider our views (...) about what is involved in understanding, explanation, good reasoning, and about how we ought to do philosophy of science. (shrink)

In some domains experts perform better than novices, and in other domains experts do not generally perform better than novices. According to empirical studies of expert performance, this is because the former but not the latter domains make available to training practitioners a direct form of learning feedback. Several philosophers resource this empirical literature to cast doubt on the quality of philosophical expertise. They claim that philosophy is like the dubious domains in that it does not make available the good, (...) direct kind of learning feedback, and thus there are empirical grounds for doubting the epistemic quality of philosophical expertise. I examine the empirical studies that are purportedly bad news for professional philosophers. On the basis of that examination, I provide three reasons why the empirical study of non-philosophical expertise does not undermine the status of philosophical expertise. First, the non-philosophical task-types from which the critics generalize are unrepresentative of relevant philosophical task-types. Second, empirical critiques of non-philosophical experts are often made relative to the performance of linear models—a comparison that is inapt in a philosophical context. Third, the critics fail to discuss findings from the empirical study of non-philosophical expertise that have more favorable implications for the epistemic status of philosophical expertise. In addition to discussing implications for philosophical expertise, this article makes progress in the philosophical analysis of the science of expertise and expert development. (shrink)

Speculations about the role of consciousness in physical systems are frequently observed in the literature concerned with the interpretation of quantum mechanics. While only three experimental investigations can be found on this topic in physics journals, more than 800 relevant experiments have been reported in the literature of parapsychology. A well-defined body of empirical evidence from this domain was reviewed using meta-analytic techniques to assess methodological quality and overall effect size. Results showed effects conforming to chance expectation in control conditions (...) and unequivocal non-chance effects in experimental conditions. This quantitative literature review agrees with the findings of two earlier reviews, suggesting the existence of some form of consciousness-related anomaly in random physical systems. (shrink)

Cognitive scientists have revealed systematic errors in human reasoning. There is disagreement about what these errors indicate about human rationality, but one upshot seems clear: human reasoning does not seem to fit traditional views of human rationality. This concern about rationality has made its way through various fields and has recently caught the attention of philosophers. The concern is that if philosophers are prone to systematic errors in reasoning, then the integrity of philosophy would be threatened. In this paper, I (...) present some of the more famous work in cognitive science that has marshaled this concern. Then I present reasons to think that those with training in philosophy will be less prone to certain systematic errors in reasoning. The suggestion is that if philosophers could be shown to be less prone to such errors, then the worries about the integrity of philosophy could be constrained. Then I present evidence that, according to performance on the CRT (Frederick 2005), those who have benefited from training and selection in philosophy are indeed less prone to one kind of systematic error: irrationally arbitrating between intuitive and reflective responses. Nonetheless, philosophers are not entirely immune to this systematic error, and their proclivity for this error is statistically related to their responses to a variety of philosophical questions. So, while the evidence herein puts constraints on the worries about the integrity of philosophy, it by no means eliminates these worries. The conclusion, then, is that the present evidence offers prima facie reasons to ascribe a mitigated privilege to philosophers' ability to rationally arbitrate between intuitive and reflective responses. (shrink)

In the course of legal reasoning—whether for purposes of deciding an issue, justifying a decision, predicting how an issue will be decided, or arguing for how it should be decided—one often is required to reach conclusions based on a balance of reasons that is not straightforwardly reducible to the application of rules. Recent AI and Law work has modeled reason-balancing, both within and across cases, with set-theoretic and rule- or value-ordering approaches. This article explores a way to model balancing in (...) quantitative terms that may yield new questions, insights, and tools. (shrink)

Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is (...) a residual role for logic in understanding reasoning; and others put forward alternative formalisms for uncertain reasoning, or raise specific technical, methodological, or empirical challenges. In responding to these points, we aim to clarify the scope and limits of probability and logic in cognitive science; explore the meaning of the explanation of cognition; and re-evaluate the empirical case for Bayesian rationality. (shrink)

Why would decision makers adopt heuristics, priors, or in short “habits” that prevent them from optimally using pertinent information—even when such information is freely-available? One answer, Herbert Simon’s “procedural rationality” regards the question invalid: DMs do not, and in fact cannot, process information in an optimal fashion. For Simon, habits are the primitives, where humans are ready to replace them only when they no longer sustain a pregiven “satisficing” goal. An alternative answer, Daniel Kahneman’s “mental economy” regards the question valid: (...) DMs make decisions based on optimization. Kahneman understands optimization not differently from the standard economist’s “bounded rationality.” This might surprise some researchers given that the early Kahneman, along with Tversky, have uncovered biases that appear to suggest that choices depart greatly from rational choices. However, once we consider cognitive cost as part of the constraints, such biases turn out to be occasional failures of habits that are otherwise optimal on average. They are optimal as they save us the cognitive cost of case-by-case deliberation. While Kahneman’s bounded rationality situates him in the neoclassical economics camp, Simon’s procedural rationality echoes Bourdieu’s “habitus” camp. To abridge the fault line of the two camps, this paper proposes a “two problem areas hypothesis.” Along the neoclassical camp, habits satisfy wellbeing, what this paper calls “substantive satisfaction.” Along the Bourdieu camp, habits satisfy belonging, love, and bonding with one’s environment, what this paper calls “transcendental satisfaction.”. (shrink)

The growing uses of algorithm-based decision-making in human resources management have drawn considerable attention from different stakeholders. While prior literature mainly focused on stakeholders directly related to HR decisions (e.g., employees), this paper pertained to a third-party observer perspective and investigated how consumers would respond to companies’ adoption of algorithm-based HR decision-making. Through five experimental studies, we showed that the adoption of algorithm-based (vs. human-based) HR decision-making could induce consumers’ unfavorable ethicality inferences of the company (study 1); because implementing a (...) calculative and data-driven approach (i.e. algorithm-based) to make employee-related decisions violates the deontological principles of respectful employee treatment (study 2). However, this effect was attenuated when consumers had high (vs. low) power distance beliefs (study 3); the algorithm served as assistance (vs. replacement) for human decisions (study 4); or the adoption was framed as employee-oriented (vs. company-oriented) motivated (study 5). Our findings suggested that consumers are aversive to algorithm-based HR decision-making because it is deontologically problematic regardless of its decision quality (i.e. accuracy). This paper contributes to the extant understanding of stakeholders’ responses to algorithm-based HR decision-making and consumers’ attitudes toward algorithm users. (shrink)

It is commonly thought that moral rules and principles, such as ‘Keep your promises,’ ‘Respect autonomy,’ and ‘Distribute goods according to need ,’ should play an essential role in our moral deliberation. Particularists have challenged this view by arguing that principled guidance leads us to engage in worse decision making because principled guidance is too rigid and it leads individuals to neglect or distort relevant details. However, when we examine empirical literature on the use of rules and principles in other (...) domains, we find that people can learn to use rules discriminately and that rule-based models tend to outperform even expert judgment. I argue that this evidence poses a problem for the moral particularist. If the particularist claims that we should not rely on decision-making rules when making practical decisions and it turns out that these rules help us make better decisions, then the particularists’ prescriptive account is deficient. However, if the particularist claims that we should rely on practical decision-making rules but not on moral rules, she needs to explain how practical rules are different from moral rules and why we should rely on the former but not the latter. (shrink)

The effectiveness of decision rules depends on characteristics of both rules and environments. A theoretical analysis of environments specifies the relative predictive accuracies of the “take-the-best” heuristic (TTB) and other simple strategies for choices between two outcomes based on binary cues. We identify three factors: how cues are weighted; characteristics of choice sets; and error. In the absence of error and for cases involving from three to five binary cues, TTB is effective across many environments. However, hybrids of equal weights (...) (EW) and TTB models are more effective as environments become more compensatory. As error in the environment increases, the predictive ability of all models is systematically degraded. Indeed, using the datasets of Gigerenzer et al. (1999, Simple Heuristics That Make Us Smart, New York: Oxford University Press), TTB and similar models do not predict much better than a naïve model that exploits dominance. Finally, we emphasize that the results reported here are conditional on binary cues. (shrink)

In this paper we propose the multiple complex systems approach for assessing domain-general complex problem-solving skills and its processes knowledge acquisition and knowledge application. After defining the construct and the formal frameworks for describing complex problems, we emphasise some of the measurement issues inherent in assessing CPS skills with single tasks. With examples of the MicroDYN test and the MicroFIN test, we show how to adequately score problem-solving skills by using multiple tasks. We discuss implications for problem-solving research and the (...) assessment of CPS skills in general. (shrink)

Charles Taber and Milton Lodge provide compelling evidence that people's minds may be closed to information that is inconsistent with their prior beliefs. This type of inconsistency has often been termed ?irrational.? However, recent research suggests that being open or closed minded is not an unchanging variable but depends on one's goals, including one's need for closure, which vary from person to person and situation to situation. In this vein, as Taber and Lodge suggest, those who have more political information (...) may, after having been open minded enough to acquire the information, become closed minded by virtue of having acquired it. At the same time, being more open minded to inaccurate information might lead one in the wrong direction; hence, open mindedness does not necessarily enhance the accuracy of one's judgments or the quality of one's decisions. We may need to rethink the concept of an enlightened, well-informed electorate, to the extent that it assumes the unqualified benefits of open mindedness. (shrink)

Methodological dualism in linguistics occurs when its theories are subjected to standards that are inappropriate for them qua scientific theories. Despite much opposition, methodological dualism abounds in contemporary thinking. In this paper, I treat linguistics as a scientific activity and explore some instances of dualism. By extracting some ubiquitous aspects of scientific methodology from its typically quantitative expression, I show that two recent instances of methodologically dualistic critiques of linguistics are ill-founded. I then show that there are nonetheless some divergences (...) between linguistic and other ordinary scientific methods, reflecting yet a third instance of methodological dualism. (shrink)

Statistical procedures can be applied to episodes in the history of science in order to weight attributes to predict short-term survival of theories; an asymptotic method is used to show that short-term survival is a valid proxy for ultimate survival; and a theoretical argument is made that ultimate survival is a valid proxy for objective truth. While realists will appreciate this last step, instrumentalists do not need it to benefit from the actuarial procedures of cliometric metatheory. Introduction A plausible proxy (...) for Peircean consensus Assessing the validity of theory attributes as predictors of theory survival 3.1 Linear discriminant function 3.2 Factor analysis 3.3 Taxometric analysis Verisimilitude index Satisfying both instrumentalists and realists Recapitulation Implementation of cliometric metatheory * Correspondence about this article may be addressed to Leslie Yonce at pemeehle{at}umn.edu' + u + '@' + d + ''//--> This article had been completed by Paul Meehl at the time of his death on 14 February 2003. His wife, Leslie J. Yonce, is grateful to Keith Gunderson (University of Minnesota, Center for Philosophy of Science) and Niels G. Waller (Psychology Department, Vanderbilt University) for advice with some final editing details. (shrink)

Assuming it rational to treat other persons' probabilities as epistemically significant, how shall their judgements be weighted (Barnes [1998])? Several plausible methods exist, but theorems in classical psychometrics greatly reduce the importance of the problem. If scientists' judgements tend to be positively correlated, the difference between two randomly weighted composites shrinks as the number of judges rises. Since, for reasons such as representative coverage, minimizing bias, and avoiding elitism, we would rarely employ small numbers of judges (e.g. less than 10), (...) the difference between two weighting systems becomes negligible. Suggestions are made for quantifying verisimilitude, identifying 'types' of scientists or theories (taxometrics), inferring latent factors, and estimating reliability of pooled judgements. (shrink)

This paper tests a novel implication of the original version of prospect theory (Kahneman and Tversky, 1979): that choices may systematically violate transitivity. Some have interpreted this implication as a weakness, viewing it as an anomaly generated by the ‘editing phase’ of prospect theory which can be rendered redundant by an appropriate re-specification of the preference function. Although there is some existing evidence that transitivity fails descriptively, the particular form of non-transitivity implied by prospect theory is quite distinctive and hence (...) presents an ideal opportunity to expose that theory to test. An experiment is reported which reveals strong evidence of the predicted intransitivity. It is argued that the existence of this new form of non-transitive behaviour presents a fresh theoretical challenge to those seeking descriptively adequate theories of choice behaviour, and a particular challenge to those who seek explanations within the conventional economic paradigm of utility maximisation. (shrink)

Research on adaptive rationality has focused principally on inference, judgment, and decision-making that lead to behaviors and actions. These processes typically require cognitive representations as input, and these representations must presumably be acquired via learning. Nonetheless, there has been little work on the nature of, and justification for, adaptively rational learning processes. In this paper, we argue that there are strong reasons to believe that some learning is adaptively rational in the same way as judgment and decision-making. Indeed, overall adaptive (...) rationality can only properly be assessed for pairs of learning and decision processes. We thus present a formal framework for modeling such pairs of cognitive processes, and thereby assessing their adaptive rationality relative to the environment and the agent’s goals. We then use this high-level formal framework on specific cases by demonstrating how natural formal constraints on decision-making can lead to substantive predictions about adaptively rational learning and representation; and characterizing adaptively rational learning for fast-and-frugal one-reason decision-making. (shrink)

A number of important decision domains, including decisions about hiring, global warming, and weather hazards, are characterized by a global–local incompatibility. These domains involve variables that cannot be observed by a single decision maker (DM) and require the integration of observations from locally available information cues. This paper presents a new bifocal lens model that describes how the structure of the environment can lead to a unique form of overconfidence when generalizing the reliability of the local environment to a global (...) scale. When the local environment does not reliably reflect the global environment, they are incompatible. While local perspectives vary across DMs, global–local incompatibility can be understood using the structure of classical test theory as the difference between (a) perceived estimates of the reliability derived from the local environment and (b) the true reliability of the local environment. I model global–local incompatibility as the difference between the true and estimated reliability when the assumptions of classical test theory are violated. Using a series of case studies and an empirical study, I demonstrate the widespread utility of this framework, and I conclude by discussing implications for cognitive–ecological theory, risk communication, and overconfidence. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not ameliorate more (...) general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

In this article we describe research methods that are used for the study of individual multiattribute evaluation processes. First we explain that a multiattribute evaluation problem involves the evaluation of a set of alternatives, described by their values on a number of alternatives. We discuss a number of evaluation strategies that may be applied to arrive at a conclusion about the attractiveness or suitability of the alternatives, and next introduce two main research paradigms in this area, structural modelling and process (...) tracing. We argue that the techniques developed within these paradigms all have their advantages and disadvantages, and conclude that the most promising technique to detect the true nature of the evaluation strategy used by a judge seems to be the analysis of verbal protocols. At the same time we think it is wise not to rely on just one technique, but to use a multimethod approach to the study of multiattribute evaluation processes whenever that is possible. (shrink)

One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a program that assesses the (...) relative evil of two courses of action. We compare this program to other attempts to simulate ethical decision-making, assess possibilities for overcoming the trade-off between input simplification and output reliability, and discuss the responsibilities of users and designers in implementing such programs. We conclude by discussing the implications that this project highlights for the successes and challenges of developing automated mechanisms for ethical decision making. (shrink)

Research on “improper” linear models has shown that predetermined weighting schemes for the linear model, such as equally weighting all predictors, can be surprisingly accurate on cross-validation. We review recent advances that can characterize the optimal choice of an improper linear model. We extend this research to the understanding of fast and frugal heuristics, particularly to the ecologically rational goal of understanding in which task environments given heuristics are optimal. We demonstrate how to test this model using the Recognition Heuristic (...) and Take the Best heuristic, show how the model reconciles with the ecological rationality program, and discuss how our prescriptive, computational approach could be approximated by simpler mental rules that might be more descriptive. Echoing the arguments of van Rooij et al., we stress the virtue of having a computationally tractable model of strategy selection, even if one proposes that cognizers use a simpler heuristic process to approximate it. (shrink)

My favorite opponent in this debate once made a remarkable concession, not that it interfered with business as usual:No sensible social scientist believes any particular specification, coefficient estimate, or standard error. Social science theories ... imply that specifications and parameters constant over situations do not exist ... One searches for qualitative theory ... not for quantitative specifications Achen (1987, p.149). . With Hooke's law and the like, we are estimating parameters in specifications that are constant across time—at least to a (...) very good degree of approximation But see Cartwright (1983). . What are the social scientists doing when they estimate non-existent parameters, and put standard errors on the output? How can that help them search for qualitative theory? Those are among the first of my questions, and I never get answers. (shrink)