In this contribution we analyze how the actions of rational agents feed back on their beliefs. We present two agent-based computer simulations studying complex social interactions in which agents that follow utility maximizing strategies thereby deteriorate their own long-term quality of beliefs. We take these results as a starting point to discuss the complex relationship between rational action couched in terms of maximizing utility and the emergence of informational inequalities.

Two classic learning situations are critically reviewed and interpreted from a synergetic point of view: human learning of complex skills, and animal discrimination learning. Both show typical characteristics of nonlinear phase transitions: instability, fluctuations, critical slowing down and reorganisation. Plateaus in the acquisition curves of complex skills can be viewed as phases of arrested progress in which a reorganisation of simple skills is necessary before their integration into complex units is possible. Fluctuations and critical slowing down are (...) expressed in instances of "vicarious trial-and-error," which describe the oscillating behavior of rats at a choice point that is shown only just before discrimination learning is completed. It is concluded that education might pay more attention to the role of individual learning rhythms. (shrink)

This case study explored how a teacher, Mr. Smith, and his students experienced a mandated performance assessment while simultaneously preparing for an end of the year high-stakes, multiple-choice assessment. We employed qualitative research methods to examine how the teacher enacted a mandated performance assessment during a unit on Byzantium and how students described their learning and classroom experiences from the unit. Drawing on Grant's idea of ambitious teaching and learning of history and Ball's work on policy realization, (...) analysis of these data indicated that Mr. Smith interpreted and enacted a performance assessment in ways that differed from how district and state policy makers intended. Despite an assessment that the district designed to promote historical thinking skills, students learned primarily factual knowledge. (shrink)

Abstract:I examine from a conventionalist perspective the Nash bargaining problem that philosophers use as a tool for analyzing fair division. From this perspective, the solutions to bargaining problems are conventions that can emerge from inductive learning and focal point effects. I contrast the conventionalist approach to analyzing the bargaining problem with the better-known rational choice approach, which I criticize for having overly demanding epistemic presuppositions and for producing disappointing results. I apply a simple model of inductive learning (...) to specific bargaining problems to show that agents can learn from repeated experience to follow a variety of bargaining conventions in a given problem. I conclude that such agents can come to regard two such conventions as focal for the bargaining problem, one that assigns claimants equal shares of a good and another egalitarian solution of equal payoff gains, and that the egalitarian solution tends to prevail when these two solutions differ. I conclude further that the above analysis lends support for admitting interpersonal utility comparisons into the analysis of fair division problems, and also suggests a focal point explanation of the wide acceptance of the Aristotelian proportionality principle of distributive justice. (shrink)

From a theoretical perspective, most discussions of statistical learning have focused on the possible “statistical” properties that are the object of learning. Much less attention has been given to defining what “learning” is in the context of “statistical learning.” One major difficulty is that SL research has been monitoring participants’ performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow (...) a brief visual or auditory familiarization stream. Is that all there is to characterizing SL abilities? Here we adopt a novel perspective for investigating the processing of regularities in the visual modality. By tracking online performance in a self-paced SL paradigm, we focus on the trajectory of learning. In a set of three experiments we show that this paradigm provides a reliable and valid signature of SL performance, and it offers important insights for understanding how statistical regularities are perceived and assimilated in the visual modality. This demonstrates the promise of integrating different operational measures to our theory of SL. (shrink)

‘India’s founding moment’ a moment of breath-taking political imagination and it is one of the great achievements of Madhav Khosla. to unpack important parts of its pre-history and emergence. This article will look at two questions—one about alternatives and the other about contexts. Regarding alternatives, I am interested in the paths not taken and an understanding of possibilities. I try to get a sense of possible alternative futures or modernities that the founding generation pondered, in the best case allowing us (...) to wonder what we can learn from the choices made as well as from the paths rejected. The other question I raise is the question of the intellectual contexts, in which the founding took place. Coming from a non-Indian perspective, I am interested in the entanglements, the contexts and potentially migrating ideas that emerge. (shrink)

I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays influence (...) his communication behaviour, and RL agents act in a non-rational way whereas BL agents display a small degree of rationality by using best response dynamics . The complete system simulates an evolutionary process of communication strategies, which agents can learn in a structured spatial society. The significant questions are: what circumstances could lead to an evolutionary process that doesn’t result in the expected DOPL convention; and to what extent is interlocutor rationality necessary for the emergence of a society-wide convention à la DOPL? (shrink)

Behavior in one-shot coordination games with common knowledge labels can be described by theories of salience and focal points. Behavior in repeated games, including coordination games, can be explained by theories of learning. This paper considers games in which both theories apply, repeated coordination games with common knowledge labels. The research question asks how players combine the two sources of information—salience and the history of play—when making their choices. We specifically ask whether salience, normally considered as a one-shot strategy, (...) continues to influence players’ actions beyond the first round, even while the player might learn from the history of play. We explore two possible mechanisms for such a continuing effect of salience: via an influence on prior beliefs, and/or via a bias, given beliefs. Regression analysis of individual-level choices shows that salience, normally considered only in the context of one-shot games, does exert a lasting effect, with the precise mechanism depending on the details of the game. (shrink)

Numerous authors indicate that the influence of academic education extends beyond the growth of specialized knowledge gained by the graduates. Scholars are trying to identify and examine the potential impact of higher learning on students’ attitudes and choices. One of the dimensions considered by the researchers is the effect of university training on students’ moral choices. Our paper attempts to identify differences between the students’ declared moral choices and their majors (fields of studies). Working with a sample of university (...) students of Economics and Sociology (N = 181), and using three variants of the Trolley Problem, the subjects’ responses are used to identify the similarities and differences between their choices. The participants were asked to respond to three hypothetical situations regarding a runaway trolley. Their decision in the first scenario could save a person’s life or let her be run over by the trolley. In the second scenario, their decision could either let one person die and save five lives or save one life and let five people be killed. These two scenarios required pulling a lever to switch the trolley from one track to another. The third scenario requires pushing an obese person in front of the runaway trolley to stop it from killing five persons. As expected, we found a significant difference between the two groups (the economists and the sociologists) in the case of our third scenario, however, we found no evidence supporting the indoctrination hypothesis. We conclude that the existing differences between the choices made by the future economists and sociologists may support the preselection hypothesis. (shrink)

This article reports research in three Nottingham schools, concerned with (1) 'The school as fertile ground: how the ethos of a school enables everyone in it to benefit from the presence of artists in class'; (2) 'Children on the edge: how the arts reach those children who otherwise exclude themselves from class activities, for any reason' and (3) 'Children's voices and choices: how even very young children can learn to express their wishes, and then have them realised through arts projects'. (...) The research methodology was rooted in two modes of inquiry, philosophical investigation and action research. The article draws on this research to argue that arts-based work in school has helped disadvantaged and/or disaffected children to engage in activities (both arts-based and others), and to be able to lay the groundwork for exercising voice and agency as they did so. If social justice is to flourish there is a need for particular kinds of public spaces and a need to create conditions such that children can learn to participate in those spaces, whether or not they are comfortable with the usual settings for 'rational argument' or 'deliberative democracy'. It is suggested that arts-based education, in some forms, is one good way of creating these conditions. (shrink)

By employing binary committee choice problems, this paper investigates how varying or eliminating feedback about payoffs affects: subjects’ learning about the underlying relationship between their nominal voting weights and their expected payoffs in weighted voting games; the transfer of acquired learning from one committee choice problem to a similar but different problem. In the experiment, subjects choose to join one of two committees and obtain a payoff stochastically determined by a voting theory. We found that: subjects (...) learned to choose the committee that generates a higher expected payoff even without feedback about the payoffs they received; there was statistically significant evidence of “meaningful learning” only for the treatment with no payoff-related feedback. This finding calls for re-thinking existing models of learning to incorporate some type of introspection. (shrink)

In an attempt to bridge the vast divide between classical Asian thought and contemporary Western philosophy, Joel J. Kupperman finds that the two traditions do not, by and large, supply different answers to the same questions. Rather, each tradition is searching for answers to their own set of questions--mapping out distinct philosophical investigations. In this groundbreaking book, Kupperman argues that the foundational Indian and Chinese texts include lines of thought that can enrich current philosophical practice, and in some cases provide (...) uniquely sophisticated insights. Special attention is given to the ethical issues of formation and fluidity of self, the nature and possibilities of choice, the compartmentalization of life implicit in some ethical systems, the variations of ethical demands from person to person, and the nature of philosophy itself as a communicative activity. This study will provide a wealth of information for philosophers seeking a closer knowledge of Asian philosophy and general readers with an interest in Eastern thought. (shrink)

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals result (...) in different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem property such as computational difficulty of the rules biased the search process and so affected learning. Experiment 2 examined the impact of examples (...) as instructional tools and found that their effectiveness was determined by whether they uniquely pointed to the correct rule. Experiment 3 compared verbal directions with examples and found that both could guide search. The final experiment tried to improve learning by using more explicit verbal directions or by adding scaffolding to the example. While both manipulations improved learning, learning still took the form of a search through a hypothesis space of possible rules. We describe a model that embodies two assumptions: the instruction can bias the rules participants hypothesize rather than directly be encoded into a rule; participants do not have memory for past wrong hypotheses and are likely to retry them. These assumptions are realized in a Markov model that fits all the data by estimating two sets of probabilities. First, the learning condition induced one set of Start probabilities of trying various rules. Second, should this first hypothesis prove wrong, the learning condition induced a second set of Choice probabilities of considering various rules. These findings broaden our understanding of effective instruction and provide implications for instructional design. (shrink)

In our daily lives, we continuously evaluate feedback information, update our knowledge, and adapt our behavior in order to reach desired goals. This ability to learn from feedback information, however, declines with age. Previous research has indicated that certain higher-level learning processes, such as feedback evaluation, integration of feedback information, and updating of knowledge, seem to be affected by age, and recent studies have shown how the adaption of choice behavior following feedback can differ with age. The neural (...) mechanisms underlying this age-related change in choice behavior during learning, however, remain unclear. The aim of this study is therefore to investigate the relation between learning-related neural processes and choice behavior during feedback learning in two age groups. Behavioral and fMRI data were collected, while a group of young and older adults performed a probabilistic learning task consisting of 10 blocks of 20 trials each. On each trial, the participants chose between a house and a face, after which they received visual feedback. In each block, either the house or the face image had a higher probability of yielding a reward. Participants were instructed to try to maximize their gains. Our results showed that less successful learning in older adults, as indicated by a lower learning rate, corresponded with a higher tendency to switch to the other stimulus option, and with a reduced adaptation of this switch choice behavior following positive feedback. At the neural level, activation following positive and negative feedback was found to be less distinctive in the older adults, due to a smaller feedback-evaluation response to positive feedback in this group. Furthermore, whereas young adults displayed increased levels of knowledge updating prior to adapting choice behavior, we did not find this effect in older adults. Together, our results suggest that diminished learning performance with age corresponds with diminished evaluation of positive feedback and reduced knowledge updating related to changes in choice behavior, indicating how such differences in feedback processing at the trial level in older adults might lead to reduced learning performance across trials. (shrink)

We consider two players each of whom attempts to predict the behavior of the other, using no more than the history of earlier predictions. Behaviors are limited to a pair of options, conventionally denoted by 0, 1. Such players face the problem of learning to coordinate choices. The present paper formulates their situation recursion theoretically, and investigates the prospects for success. A pair of players build up a matrix with two rows and infinitely many columns, and are said to (...) “learn” each other if cofinitely many of the columns show the same number in both rows (either 0 or 1). Among other results we prove that there are two collections of players that force all other players to choose their camp. Each collection is composed of players that learn everyone else in the same collection, but no player that learns all members of one collection learns any member of the other. (shrink)

We routinely observe others’ choices and use them to guide our own. Whose choices influence us more, and why? Prior work has focused on the effect of perceived similarity between two individuals, such as the degree of overlap in past choices or explicitly recognizable group affiliations. In the real world, however, any dyadic relationship is part of a more complex social structure involving multiple social groups that are not directly observable. Here we suggest that human learners go beyond dyadic similarities (...) in choice behaviors or explicit group memberships; they infer the structure of social influence by grouping individuals based on choices, and they use these groups to decide whose choices to follow. We propose a computational model that formalizes this idea, and we test the model predictions in a series of behavioral experiments. In Experiment 1, we reproduce a well-established finding that people's choices are more likely to be influenced by someone whose past choices are more similar to their own past choices, as predicted by our model as well as dyadic similarity models. In Experiments 2–5, we test a set of unique predictions of our model by looking at cases where the degree of choice overlap between individuals is equated, but their choices indicate a latent group structure. We then apply our model to prior empirical results on infants’ understanding of others’ preferences, presenting an alternative account of developmental changes. Finally, we discuss how our model relates to classical findings in the social influence literature and the theoretical implications of our model. Taken together, our findings demonstrate that structure learning is a powerful framework for explaining the influence of social information on decision making in a variety of contexts. (shrink)

A scientifically proven method to overcome obstacles and make choices that lead us closer to our goals. WITH A FOREWORD BY MARTINA NAVRATILOVA What do weight gain, poor employee engagement, and climate change all have in common? All three are persistent problems for which solutions are known and readily available. Yet, on an individual and collective level, we continually make choices that lead us not closer to but further away from our stated objectives. Whether we choose the burger and fries (...) over the salad, top-down management over collaboration, or leniency over rigor in combatting climate change, it all comes down to the same thing. The Choice Point. The moment at which we each choose to take an action that we know will undermine our success, but we do it anyway. The Choice Point explains how we experience thousands of thoughts every day: 80 percent are negative, while only 5 percent are new thoughts. We make most of our decisions within two seconds, using mental autopilot systems that we've built through years of experiences, and some of our thoughts (like quitting during a challenge) can compromise our goals. But there's a strategy to change this: Functional Imagery Training (FIT). FIT teaches us how to pick the thoughts that deserve our attention, and how to stop the other, negative thoughts from impacting our actions. Through FIT, we can pause decisions that would typically conflict with our goals, lengthen our Choice Point, and go from passenger to driver of our own minds. Initially developed in 2005 by academics in the UK and Australia, with formal principles emerging through research in 2018, FIT blends motivational interviewing with imagery into a user-friendly model so we can learn, adapt, and adjust our behavior to go beyond what we think is possible. (shrink)

A report of a problem-based learning project on the ethics of terminal care, offered as one of the options available to first year MB ChB students in Edinburgh University Medical School. The project formed part of the 'clinical correlation course' in the new curriculum. Six students took part under the supervision of two clinical tutors and a moral philosopher. The course was case-based and practical with students being given the opportunity over a period of eight weeks to meet patients, (...) relatives and hospital staff at a local geriatrics hospital and terminal care home. The main issue studied was the degree of choice available to patients electing to be treated at home, in hospital or in a hospice. Other issues included: pre-death, disposal of the dead, certification of death, communication with relatives and follow-up bereavement services. (shrink)

Benacerraf’s Problem about mathematical truth displays a tension, indeed a seemingly unbridgeable gap, between Platonist foundations for mathematics on the one hand and Hilbert’s ‘finitary standpoint’ on the other. While that standpoint evinces an admirable philosophical unity, it is ultimately an effete rival to Platonism: It leaves mathematical practice untouched, even the highly non-constructive axiom of choice. Brouwer’s intuitionism is a more potent finitist rival, for it engenders significant deviation from standard (classical) mathematics. The essay illustrates three sorts of (...) intuitionistic deviations (weakening, refinement and outright contradiction), and goes on to sketch the technical tools and arguments that engender those clashes with classical mathematics and the philosophical principles underlying those arguments. Those philosophical principles coalesce into a “standpoint” no less unified and no less finitary that Hilbert’s. This intuitionistic standpoint is sufficiently detailed that it itself provides a benchmark for comparing all the rival positions; and it is sufficiently robust that it dissolves the Benacerrafian dichotomy. However, the intuitionistic refutation of the axiom of choice reveals two distinct sub-streams within that intuitionistic standpoint. Distinguishing these streams suggests perhaps that in spite of that robustness, intuitionism has an internal dichotomy parallel to the Benacerrafian split. The Benacerrafian split is a crack in the foundations of mathematics. But I shall argue that this internal intuitionistic dichotomy is not at all a foundational gap; it is rather a special insight about the nature of mathematical thought. (shrink)

The past four decades of research in the social sciences have shed light on two important phenomena. One is that human decision-making is full of predicable errors and biases that often lead individuals to make choices that defeat their own ends (i.e., the bad choice phenomenon), and the other is that individuals’ decisions and behaviors are powerfully shaped by their environment (i.e., the influence phenomenon). Some have argued that it is ethically defensible that the influence phenomenon be utilized to (...) address the bad choice phenomenon. They propose that “choice architects” learn about the various ways in which choices can be influenced and directed by the environment, and then work to design environments, broadly construed, that influence individuals towards choices that make them better off. Those who advocate intentionally creating choice environments that lead people to better choices believe that doing so is ethically permissible because (1) it makes people better off, and (2) it does so in a way that is entirely compatible with individual liberty. The evaluation of these two claims is the main focus of this paper. (shrink)

In the past few years, machine learning (ML) tools have been implemented with success in the medical context. However, several practitioners have raised concerns about the lack of transparency—at the algorithmic level—of many of these tools; and solutions from the field of explainable AI (XAI) have been seen as a way to open the ‘black box’ and make the tools more trustworthy. Recently, Alex London has argued that in the medical context we do not need machine learning tools (...) to be interpretable at the algorithmic level to make them trustworthy, as long as they meet some strict empirical desiderata. In this paper, we analyse and develop London’s position. In particular, we make two claims. First, we claim that London’s solution to the problem of trust can potentially address another problem, which is how to evaluate the reliability of ML tools in medicine for regulatory purposes. Second, we claim that to deal with this problem, we need to develop London’s views by shifting the focus from the opacity of algorithmic details to the opacity of the way in which ML tools are trained and built. We claim that to regulate AI tools and evaluate their reliability, agencies need an explanation of how ML tools have been built, which requires documenting and justifying the technical choices that practitioners have made in designing such tools. This is because different algorithmic designs may lead to different outcomes, and to the realization of different purposes. However, given that technical choices underlying algorithmic design are shaped by value-laden considerations, opening the black box of the design process means also making transparent and motivating (technical and ethical) values and preferences behind such choices. Using tools from philosophy of technology and philosophy of science, we elaborate a framework showing how an explanation of the training processes of ML tools in medicine should look like. (shrink)

The COVID-19 pandemic created a situation for the implementation of emergency remote learning. This meant that as a lecturer at a traditionalist University of contact sessions, the pandemic forced us to teach remotely through online methods of communication, using online lectures, narrated powerpoints, voice clips, podcasts, interviews and interactive videos. The assessments were conducted online from assignments to multiple choice questions, which forced the lecturers to think differently about the way the assessments were presented, in order to avoid (...) easy access to answers found in a textbook and online. This meant that more application questions of theory to practice were assessed in a more challenging way to prevent cheating and collaboration with peers. Formal assessments completed during emergency remote learning, have become the past practice, as innovative methods have been adopted for learning and for assessment purposes in order to preserve the integrity and attainment of the degree through online modes of learning. The aim of the paper investigates and explores the methods of teaching, together with the results obtained from the students of 2019 and 2020 in their final year relating to two final year modules against the literature relating to learning processes and methodologies. (shrink)

The Monty Hall Dilemma (MHD) is a two-step decision problem involving counterintuitive conditional probabilities. The first choice is made among three equally probable options, whereas the second choice takes place after the elimination of one of the non-selected options which does not hide the prize. Differing from most Bayesian problems, statistical information in the MHD has to be inferred, either by learning outcome probabilities or by reasoning from the presented sequence of events. This often leads to suboptimal (...) decisions and erroneous probability judgments. Specifically, decision makers commonly develop a wrong intuition that final probabilities are equally distributed, together with a preference for their first choice. Several studies have shown that repeated practice enhances sensitivity to the different reward probabilities, but does not facilitate correct Bayesian reasoning. However, modest improvements in probability judgments have been observed after guided explanations. To explain these dissociations, the present review focuses on two types of causes producing the observed biases: Emotional-based choice biases and cognitive limitations in understanding probabilistic information. Among the latter, we identify a crucial cause for the universal difficulty in overcoming the equiprobability illusion: Incomplete representation of prior and conditional probabilities. We conclude that repeated practice and/or high incentives can be effective for overcoming choice biases, but promoting an adequate partitioning of possibilities seems to be necessary for overcoming cognitive illusions and improving Bayesian reasoning. (shrink)

Despite strong evidence that autonomy enhances motivation and achievement, few interventions for promoting student autonomy in higher education have been developed and empirically tested. Here, we demonstrate how two autonomy-supportive policies effectively increase classroom attendance and subject mastery. First, in a randomized controlled field study, we explored the effect of allowing students to choose whether to make their attendance mandatory (i.e., a component of their course grades). We found that nearly all students used the opportunity as a pre-commitment device and (...) were subsequently more likely to attend class than were students whose attendance had been mandated. Second, in a multi-year cohort study, we explored the effect of allowing students to opt out of a challenging, high-effort assessment stream, finding that students given greater autonomy invested more effort into their assignments and attained greater proficiency with the material. We discuss other opportunities for applying choice architecture to improve learning, motivation, and well-being in higher education. (shrink)

The uncertainty associated with paradigmatic families has been shown to correlate with their phonetic characteristics in speech, suggesting that representations of complex sublexical relations between words are part of speaker knowledge. To better understand this, recent studies have used two-layer neural network models to examine the way paradigmatic uncertainty emerges in learning. However, to date this work has largely ignored the way choices about the representation of inflectional and grammatical functions (IFS) in models strongly influence what they subsequently learn. (...) To explore the consequences of this, we investigate how representations of IFS in the input-output structures of learning models affect the capacity of uncertainty estimates derived from them to account for phonetic variability in speech. Specifically, we examine whether IFS are best represented as outputs to neural networks (as in previous studies) or as inputs by building models that embody both choices and examining their capacity to account for uncertainty effects in the formant trajectories of word final [ɐ], which in German discriminates around sixty different IFS. Overall, we find that formants are enhanced as the uncertainty associated with IFS decreases. This result dovetails with a growing number of studies of morphological and inflectional families that have shown that enhancement is associated with lower uncertainty in context. Importantly, we also find that in models where IFS serve as inputs—as our theoretical analysis suggests they ought to—its uncertainty measures provide better fits to the empirical variance observed in [ɐ] formants than models where IFS serve as outputs. This supports our suggestion that IFS serve as cognitive cues during speech production, and should be treated as such in modeling. It is also consistent with the idea that when IFS serve as inputs to a learning network. This maintains the distinction between those parts of the network that represent message and those that represent signal. We conclude by describing how maintaining a “signal-message-uncertainty distinction” can allow us to reconcile a range of apparently contradictory findings about the relationship between articulation and uncertainty in context. (shrink)

This paper examines whether adults can adapt to novel accents of their native language that contain unfamiliar context-dependent phonological alternations. In two experiments, French participants listen to short stories read in accented speech. Their knowledge of the accents is then tested in a forced-choice identification task. In Experiment 1, two groups of listeners are exposed to newly created French accents in which certain vowels harmonize or disharmonize, respectively, to the rounding of the preceding vowel. Despite the cross-linguistic predominance of (...) vowel harmony over disharmony, the two groups adapt equally well to both accents, suggesting that this typological difference is not reflected in perceptual learning. Experiment 2 further explores the mechanism underlying this type of phonological learning. Participants are exposed to an accent in which some vowels harmonize and others disharmonize, yielding an increased featural complexity. They adapt less well to this regularity, showing that adaptation to novel accents involves feature-based inferences. (shrink)

Decision making often takes place in social environments where other actors influence individuals' decisions. The present article examines how advice affects individual learning. Five social learning models combining advice and individual learning‐four based on reinforcement learning and one on Bayesian learning‐and one individual learning model are tested against each other. In two experiments, some participants received good or bad advice prior to a repeated multioption choice task. Receivers of advice adhered to the advice, (...) so that good advice improved performance. The social learning models described the observed learning processes better than the individual learning model. Of the models tested, the best social learning model assumes that outcomes from recommended options are more positively evaluated than outcomes from nonrecommended options. This model correctly predicted that receivers first adhere to advice, then explore other options, and finally return to the recommended option. The model also predicted accurately that good advice has a stronger impact on learning than bad advice. One‐time advice can have a long‐lasting influence on learning by changing the subjective evaluation of outcomes of recommended options. (shrink)

Adaptation by means of natural selection depends on the ability of populations to maintain variation in heritable traits. According to the Modern Synthesis this variation is sustained by mutations and genetic drift. Epigenetics, evodevo, niche construction and cultural factors have more recently been shown to contribute to heritable variation, however, leading an increasing number of biologists to call for an extended view of speciation and evolution. An additional common feature across the animal kingdom is learning, defined as the ability (...) to change behavior according to novel experiences or skills. Learning constitutes an additional source for phenotypic variation, and change in behavior may induce long lasting shifts in fitness, and hence favor evolutionary novelties. Based on published studies, I demonstrate how learning about food, mate choice and habitats has contributed substantially to speciation in the canonical story of Darwin’s finches on the Galapagos Islands. Learning cannot be reduced to genetics, because it demands decisions, which requires a subject. Evolutionary novelties may hence emerge both from shifts in allelic frequencies and from shifts in learned, subject driven behavior. The existence of two principally different sources of variation also prevents the Modern Synthesis from self-referring explanations. (shrink)

In their daily practices, many ethical vegans choose what to eat, wear, and buy among a range that is limited to the exclusion of animal products. Rather than considering and then rejecting the idea of using such products, doing so often does not occur to them as a possibility at all. In other cases, when confronted with the possibility of consuming animal products, vegans have claimed to reject it by saying that it would be impossible for them to do so. (...) I refer to this phenomenon as ‘moral impossibility’. An analysis of moral impossibility in animal ethics shows that it arises when one’s conception of ‘what animals are’ shifts—say through encounter with other animals. It also arises when individuals learn more about animals and what happens to them in production facilities. This establishes a link between increased knowledge, understanding, and imaginative exploration on the one hand, and the exclusion of the possibility of using animals as resources on the other. Taking moral impossibility in veganism seriously has two important consequences: one is that the debate around veganism needs to shift from choice and decision, to a prior analysis of concepts and moral framing; the other is that moral psychology is no longer seen as empirical psychology plus ethical analysis, but the contents of psychological findings are understood as being influenced and framed by moral reflection. (shrink)

In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, (...) post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methods _too, because of specific identifiable characteristics,_ can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices. (shrink)

There is an extensive body of work that has previously examined the teaching of ethics in business schools whereby it is hoped that the values and behaviours of students might be provoked to show positive and enduring change. Rather than dealing with the content issues of particular business ethics courses per se, this article explores the philosophical foundations and the structural conditions for developing ethical training programs in business schools. It is informed by historical analysis, specifically, an examination of Platonic (...) and Aristotelian philosophies that inspires virtue ethics, and together provides four conditions for consideration: respect for law, dialectics, imitation and deliberation. We outline the necessary structural conditions for implementing these requirements as well as suggesting the necessary pedagogical protocol applicable to all courses. It is argued that reference to our two ancient Greek philosophers provide many valuable and insightful lessons for the implementation of ethical training today including choice of theoretical content and the approach towards learning. Further, the enactment of a pedagogical protocol requires a policy of recruiting and managing business school teachers-instructors that takes into account, and consciously encourages, intellectual, relational and spiritual pedagogical qualities. (shrink)

This chapter places the exodus of Russian scholars in the context of the country's turbulent twentieth-century experience of ‘three revolutions, two world wars, civil strife, and several changes of political regime’. It presents an account of the plight of Russian academics in German occupied territories who were caught ‘in the dead space between two tyrannies’. For some the price of survival in the 1940s involved temporary collaboration with the Nazi invaders, which is illustrated in the morally ambiguous wartime experiences of (...) Nikolas Poppe, Professor of Oriental Studies in Leningrad University, a leading expert of the languages and literatures of northern inner Asia; and of Ivan Malinin, professor and head of the department of pathology in the Krasnodar Medical Institute. Both found a way of resisting the communist state through temporary ‘collaboration’, and thus, reaffirmed ‘the right of the individual to make choices’. The chapter concludes by noting the change in Soviet policy towards the emigration of scientists after perestroika and its double-edged effect: ‘On the one hand, emigration impoverishes home institutions, but, on the other, the free migration of scientists has become one of the most effective mechanisms for integrating the country into the global scientific community’. (shrink)