1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.

What exactly is the human element separating humans from animals and machines? The common answers that immediately come to mind—like art, empathy, or technology—fall apart under close inspection. Dominic Pettman argues that it is a mistake to define such rigid distinctions in the first place, and the most decisive “human error” may be the ingrained impulse to understand ourselves primarily in contrast to our other worldly companions. In _Human Error_, Pettman describes the three sides of the cybernetic triangle—human, animal, (...) and machine—as a rubric for understanding key figures, texts, and sites where our species-being is either reinforced or challenged by our relationship to our own narcissistic technologies. Consequently, species-being has become a matter of _specious_-being, in which the idea of humanity is not only a case of mistaken identity but indeed the mistake of identity. _Human Error_ boldly insists on the necessity of relinquishing our anthropomorphism but also on the extreme difficulty of doing so, given how deeply this attitude is bound with all our other most cherished beliefs about forms of life. (shrink)

Autonomous underwater vehicles are widely used to accomplish various missions in the complex marine environment; the design of a control system for AUVs is particularly difficult due to the high nonlinearity, variations in hydrodynamic coefficients, and external force from ocean currents. In this paper, we propose a controller based on deep reinforcement learning in a simulation environment for studying the control performance of the vectored thruster AUV. RL is an important method of artificial intelligence that can learn behavior through (...) trial-and-error interactions with the environment, so it does not need to provide an accurate AUV control model that is very hard to establish. The proposed RL algorithm only uses the information that can be measured by sensors inside the AUVs as the input parameters, and the outputs of the designed controller are the continuous control actions, which are the commands that are set to the vectored thruster. Moreover, a reward function is developed for deep RL controller considering different factors which actually affect the control accuracy of AUV navigation control. To confirm the algorithm’s effectiveness, a series of simulations are carried out in the designed simulation environment, which is a method to save time and improve efficiency. Simulation results prove the feasibility of the deep RL algorithm applied to the control system for AUV. Furthermore, our work also provides an optional method for robot control problems to deal with improving technology requirements and complicated application environments. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Cognitive Error and Contemplative Practices:The Cultivation of Discernment in Mind and HeartWesley J. WildmanBrains are amazing organs in all creatures with central nervous systems and especially in human beings. But they are not perfect. Without forgetting the larger success story of cognitive evolution, I want to explore the way that cognitive biases sometimes produce errors in both religious and secular social settings and how such errors can be (...) diagnosed and corrected when they occur. This will involve noticing that error diagnosis and correction is a process that certain social groups have a vested interest in resisting or neglecting, in some respects, while the very same social groups may furnish resources that support the detection of cognitive errors, in other respects.This presents a moral quandary for both secular and religious groups. Should we educate children to be fully aware of their cognitive vulnerability to advertising, thereby learning how to resist and eventually become immune to one of the fundamental power sources of modern market economies? Should religious groups explain to young people their cognitive tendencies to posit the action of supernatural beings whether or not any such action exists, even though this may disrupt the power of religious groups to forge bracing social togetherness that supports psychologically useful coping skills? While I do not seek to answer such complex moral questions in this paper, I do argue that knowledge of cognitive biases and the resulting tendencies to cognitive error, self-defeating behaviors, and self-deception should be made available to those individuals and groups who are interested in promoting a high degree of critical self-awareness in the analysis of beliefs and behaviors in both secular and religious contexts.The term "error" is a potentially problematic one in that it misleadingly suggests that there might be a uniquely correct way in which cognition should work. I do not wish to suggest such a binary opposition. After all, biases exist in the human cognitive system either because they have been selected in the evolutionary process for their survival benefits or because they are side effects of other traits selected for their usefulness. My concern is with the wondrous human discovery that we can analyze [End Page 61] our behaviors and beliefs with such precision that we can sometimes detect when our cognitive biases produce mistaken beliefs and self-defeating behaviors. This forms the basis for my contention that cognition can often work better than it does—more accurately, less self-destructively—when tendencies to cognitive error are diagnosed, corrected, and perhaps even systematically resisted.The profound irony here is that the very same social groups (secular and religious) with an obvious vested interest in resisting such enlightenment in some respects can also promote processes of discernment and insight in other respects. Existing literature in the cognitive psychology of religion rarely bothers with such subtleties. It is common to assume that simply to notice the operation of cognitive biases in religion—say, in supporting belief in supernatural entities who providentially interact in human affairs, or in establishing and reinforcing people's willingness to defer to certain kinds of religious authority—is at the same time to establish the presence of rampant cognitive error, massive resistance to diagnosing and correcting it, and thus the infliction of pernicious cruelties on young children who have no way of escaping the resulting irrational indoctrination.This moral reflex to condemn religious groups because of their characteristic reluctance to acknowledge the role of cognitive biases in their beliefs and practices is understandable given the irrationality, ignorance, or denial that such reluctance suggests. I frankly acknowledge that I share this moral concern. But the actual complexities of religious practice demonstrate that the situation demands a subtler evaluation. Resistance to awareness of cognitive biases exists both inside and outside religious groups; economic and political practices in all eras and of all types have every bit as much to gain from neglecting to enlighten people about their cognitive operations as religious groups do—just consider the techniques employed in commercial advertising and political campaigns. Moreover, religious groups also promote methods of discernment and self-awareness that have historically been, and continue to be, the dominant method by which... (shrink)

Reinforcement learning relies on the reward prediction error (RPE) signals conveyed by the midbrain dopamine system. Previous studies showed that dopamine plays an important role in both positive and negative reinforcement. However, whether various reinforcement processes will induce distinct learning signals is still unclear. In a probabilistic learning task, we examined RPE signals in different reinforcement types using an electrophysiology index, namely, the feedback-related negativity (FRN). Ninety-four participants were randomly assigned into four groups: base (no (...) money incentive), positive reinforcement (presentation of money rewards), negative reinforcement (removal of money losses), and combined reinforcement (money rewards and removal of money losses) groups. In addition, in order to evaluate the engagement of emotional activity in the different reinforcement processes, Positive and Negative Affect Schedule-Expanded Form (PANAS-X) scales were applied before and after the experiment to detect the emotional changes. The results showed that there was no difference between groups in the dopamine-related learning bias. However, compared to the other three groups, negative reinforcement elicited smaller FRN (the difference-wave measure) during the learning, stronger positive affect and joviality, and less fatigue after the learning, in which the difference between the negative and positive reinforcement groups was smaller. The results indicated that pure avoidance motivation may induce distinct emotional fluctuations, which influence the feedback processing. (shrink)

In the past two decades, reinforcement learning has become a popular framework for understanding brain function. A key component of RL models, prediction error, has been associated with neural signals throughout the brain, including subcortical nuclei, primary sensory cortices, and prefrontal cortex. Depending on the location in which activity is observed, the functional interpretation of prediction error may change: Prediction errors may reflect a discrepancy in the anticipated and actual value of reward, a signal indicating the salience (...) or novelty of a stimulus, and many other interpretations. Anterior cingulate cortex has long been recognized as a region involved in processing behavioral error, and recent computational models of the region have expanded this interpretation to include a more general role for the region in predicting likely events, broadly construed, and signaling deviations between expected and observed events. Ongoing modeling work investigating the interaction between ACC and additional regions involved in cognitive control suggests an even broader role for cingulate in computing a hierarchically structured surprise signal critical for learning models of the environment. The result is a predictive coding model of the frontal lobes, suggesting that predictive coding may be a unifying computational principle across the neocortex. (shrink)

Position papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called trustworthy AI. In such papers, the technical and regulatory strategies are frequently analyzed in detail, but the concept of trustworthy AI is not. As a result, it remains unclear. This paper lays out a variety of possible interpretations of the concept and concludes that none of them is appropriate. The central problem is that, by framing (...) the ethics of AI in terms of trustworthiness, we reinforce unjustified anthropocentric assumptions that stand in the way of clear analysis. Furthermore, even if we insist on a purely epistemic interpretation of the concept, according to which trustworthiness just means measurable reliability, it turns out that the analysis will, nevertheless, suffer from a subtle form of anthropocentrism. The paper goes on to develop the concept of strange error, which serves both to sharpen the initial diagnosis of the inadequacy of trustworthy AI and to articulate the novel epistemological situation created by the use of AI. The paper concludes with a discussion of how strange error puts pressure on standard practices of assessing moral culpability, particularly in the context of medicine. (shrink)

Prefrontal cerebral areas project to Purkinje cells, located in the most lateral part of the cerebellum, via mossy and climbing fibers. The latter olivary error signals reflect the attentional load of the prefrontal cortex. At the cerebral level, LTP-LTD plasticity allows these Purkinje cells to adaptively reinforce the active pyramidal cells involved in the motor sequence.

Reinforcement learning systems usually assume that a value function is defined over all states that can immediately give the value of a particular state or action. These values are used by a selection mechanism to decide which action to take. In contrast, when humans and animals make decisions, they collect evidence for different alternatives over time and take action only when sufficient evidence has been accumulated. We have previously developed a model of memory processing that includes semantic, episodic and (...) working memory in a comprehensive architecture. Here, we describe how this memory mechanism can support decision making when the alternatives cannot be evaluated based on immediate sensory information alone. Instead we first imagine, and then evaluate a possible future that will result from choosing one of the alternatives. Here we present an extended model that can be used as a model for decision making that depends on accumulating evidence over time, whether that information comes from the sequential attention to different sensory properties or from internal simulation of the consequences of making a particular choice. We show how the new model explains both simple immediate choices, choices that depend on multiple sensory factors and complicated selections between alternatives that require forward looking simulations based on episodic and semantic memory structures. In this framework, vicarious trial and error is explained as an internal simulation that accumulates evidence for a particular choice. We argue that a system like this forms the “missing link” between more traditional ideas of semantic and episodic memory, and the associative nature of reinforcement learning. (shrink)

Next SectionThis article proposes that knowledge of cultural expectations concerning ethical responses to unintentional harm can help students and physicians better to understand patients’ distress when physicians fail to disclose, apologise for, and make amends for harmful medical errors. While not universal, the Judeo-Christian traditions of confession, repentance, and forgiveness inform the cultural expectations of many individuals within secular western societies. Physicians’ professional obligations concerning truth telling reflect these expectations and are inclusive of the disclosure of medical error, while (...) physicians may express a need for self-forgiveness after making errors and should be aware that patients may also rely upon forgiveness as a means of dealing with harm. The article recommends that learning how to disclose errors, apologise to injured patients, ensure that these patients’ needs are met, and confront the emotional dimensions of one’s own mistakes should be part of medical education and reinforced by the conduct of senior physicians. (shrink)

This paper suggests an online solution for the optimal tracking control of robotic systems based on a single critic neural network -based reinforcement learning method. To this end, we rewrite the robotic system model as a state-space form, which will facilitate the realization of optimal tracking control synthesis. To maintain the tracking response, a steady-state control is designed, and then an adaptive optimal tracking control is used to ensure that the tracking error can achieve convergence in an optimal (...) sense. To solve the obtained optimal control via the framework of adaptive dynamic programming, the command trajectory to be tracked and the modified tracking Hamilton-Jacobi-Bellman are all formulated. An online RL algorithm is the developed to address the HJB equation using a critic NN with online learning algorithm. Simulation results are given to verify the effectiveness of the proposed method. (shrink)

The large scale, time varying, and diversification of physically coupled networked infrastructures such as power grid and transportation system lead to the complexity of their controller design, implementation, and expansion. For tackling these challenges, we suggest an online distributed reinforcement learning control algorithm with the one-layer neural network for each subsystem or called agents to adapt the variation of the networked infrastructures. Each controller includes a critic network and action network for approximating strategy utility function and desired control law, (...) respectively. For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. The stability of the control system with learning algorithm is analyzed; the upper bound of the tracking error and neural network weights are also estimated. The effectiveness of our proposed controller is illustrated in the simulation; the results indicate the stability under communication delay and disturbances as well. (shrink)

This study examines how a Purkinje cell receives its appropriate olivary error signal during the learning of compound movements. We suggest that the Purkinje cell only reinforces those target pyramidal cells which already participate in the movement, subsequently reducing any repeated error signal, such as its own climbing fiber input, [simpson et al.; smith].

With the advent of the era of artificial intelligence, deep reinforcement learning has achieved unprecedented success in high-dimensional and large-scale artificial intelligence tasks. However, the insecurity and instability of the DRL algorithm have an important impact on its performance. The Soft Actor-Critic algorithm uses advanced functions to update the policy and value network to alleviate some of these problems. However, SAC still has some problems. In order to reduce the error caused by the overestimation of SAC, we propose (...) a new SAC algorithm called Averaged-SAC. By averaging the previously learned action-state estimates, it reduces the overestimation problem of soft Q-learning, thereby contributing to a more stable training process and improving performance. We evaluate the performance of Averaged-SAC through some games in the MuJoCo environment. The experimental results show that the Averaged-SAC algorithm effectively improves the performance of the SAC algorithm and the stability of the training process. (shrink)

The generation of the pitch control signal in a wind turbine (WT) is not straightforward due to the nonlinear dynamics of the system and the coupling of its internal variables; in addition, they are subjected to the uncertainty that comes from the random nature of the wind. Fuzzy logic has proved useful in applications with changing system parameters or where uncertainty is relevant as in this one, but the tuning of the fuzzy logic controller (FLC) parameters is neither straightforward nor (...) an easy task. On the other hand, reinforcement learning (RL) allows systems to automatically learn, and this capability can be exploited to tune the FLC. In this work, a WT pitch control architecture that uses RL to tune the membership functions and scale the output of a fuzzy controller is proposed. The RL strategy calculates the fuzzy controller gains in order to reduce the output power error of the WT according to the wind speed. Different reward mechanisms based on the output power error have been considered. Simulation results with different wind profiles show that this architecture performs better (123.7 W) in terms of power errors than an FLC without RL (133.2 W) or a simpler PID (208.8 W). Even more, it provides a smooth response and outperforms other hybrid controllers such as RL-PID and radial basis function neural network control. (shrink)

In this essay, at the epistemological level I focus on groups, and not merely individuals, when examining medical errors on behalf of both the medical industry and patients who engage in medical conspiracy theories. Specifically, I use the work in virtue and vice epistemology by Quassim Cassam and Miranda Fricker to diagnose some of the problems that arise with medical conspiracism. Cassam identifies the vice conspiracist mentality to help explain the preponderance of conspiracy theorizing. Fricker provides a framework for thinking (...) about group errors by identifying the vices of testimonial and hermeneutic injustice. I argue that medical conspiracists present a warped version of Fricker’s vices by acting as if they are the victims of these injustices instead of the purveyors of them. In addition, I argue that errors on behalf of various medical groups, such as hospitals and health organizations, reinforce many conspiracy theories. (shrink)

Reinforcement Learning (RL) handles policy search problems: searching a mapping from state space to action space. However RL is based on gradient methods and as such, cannot deal with problems with multimodal landscape. In contrast, though Genetic Algorithm (GA) is promising to deal with them, it seems to be unsuitable for policy search problems from the viewpoint of the cost of evaluation. Minimal Generation Gap (MGG), used as a generation-alternation model in GA, generates many offspring from two or more (...) parents selected from a population. Therefore, evaluating policies of generated offspring requires much trial and error (i.e. interaction between an agent and an environment). In this paper, we incorporate importance sampling into the framework of MGG in order to reduce the cost of evaluation on policy search. The proposed techniques are applied to Markov Decision Process (MDP) with multimodal landscape. The experimental results show that these techniques can reduce the number of interaction between an agent and an environment, and also mean that MGG and importance sampling are good for each other. (shrink)

Reinforcement Learning is a promising technique for creating agents that can be applied to real world problems. The most important features of RL are trial-and-error search and delayed reward. Thus, agents randomly act in the early learning stage. However, such random actions are impractical for real world problems. This paper presents a novel model of RL agents. A feature of our learning agent model is to integrate the Analytic Hierarchy Process into the standard RL agent model, which consists (...) of three modules: state recognition, learning, and action selecting modules. In our model, the AHP module is designed with {\\it primary knowledge} that humans intrinsically have in a process until a goal state is attained. This integration aims at increasing promising actions instead of completely random actions in the standard RL algorithms. Profit Sharing is adopted as a RL method for our model, since PS is known to be useful even in multi-agent environments. To evaluate our approach in a multi-agent environment, we test a PS RL method with our agent model on a pursuit problem in a grid world. Computational results show that our approach outperforms the standard PS in terms of learning speed in the earlier stages of learning. We also show that the learning performance of our approach is superior at least competitive to that of the standard one in the final stages of learning. (shrink)

Curiosity is evident in humans of all sorts from early infancy, and it has also been said to appear in a wide range of other animals, including monkeys, birds, rats, and octopuses. The classical definition of curiosity as an intrinsic desire for knowledge may seem inapplicable to animal curiosity: one might wonder how and indeed whether a rat could have such a fancy desire. Even if rats must learn many things to survive, one might expect their learning must be driven (...) by simpler incentives, such as hunger. One might also wonder what proximal signals could guide animals towards knowledge itself, or how something as abstract as knowledge could ever be a motivational target for an unreflective animal. Taking a cue from recent work in reinforcement learning, I argue that surprise functions as a reward signal for the curious animal, and then show how this amounts to a desire for knowledge gain, where knowledge is conceived of as a cognitive adaptation to reality. This adaptation results in a mental state whose existence depends essentially on the truth of its contents, a factive mental state. Curious creatures benefit from an interaction between the prediction-error correction processes of basic learning and the active surprise-seeking force of their curiosity. This internally adversarial interaction accelerates knowledge gain in ways that are very helpful for agents with the restrictions of biological creatures, in environments with the complexity of our natural world. (shrink)

Current explanatory frameworks for social norms pay little attention to why and how brains might carry out computational functions that generate norm compliance behavior. This paper expands on existing literature by laying out the beginnings of a neurocomputational framework for social norms and social cognition, which can be the basis for advancing our understanding of the nature and mechanisms of social norms. Two neurocomputational building blocks are identified that might constitute the core of the mechanism of norm compliance. They consist (...) of Bayesian and reinforcement learning systems. It is sketched why and how the concerted activity of these systems can generate norm compliance by minimization of three specific kinds of prediction-errors. (shrink)

In this chapter, we consider the plausibility and consequences of the use of the term “honest errors” to describe the accidental killings of civilians resulting from the US military’s drone campaigns in Iraq, Syria, Afghanistan, and elsewhere. We argue that the narrative of “honest errors” unjustifiably excuses those involved in these killings from moral culpability, and reinforces long-standing, pernicious assumptions about the moral superiority of the US military and the inevitability of civilian deaths in combat. Furthermore, we maintain that, given (...) the knowledge-distorting practices within the US military’s organizational structure, few if any civilian deaths from drone strikes meet the criteria of a genuinely morally excusing “honest mistake”. Instead, these accidental killings often reflect objectionable attitudes of relative disregard for the safety of civilians. These attitudes are, we argue, sufficient to warrant the attribution of blame and moral responsibility, both with respect to certain individual actions and with respect to the US military as an institution. In light of this, we propose incorporating a Principle of the Moral Equality of Non-combatants into military assessments of what counts as “acceptable risk” to civilians. This would go some way, we argue, to redressing the ongoing injustice inflicted on the victims of civilian killings by the failure of the US military and US political leadership to take moral responsibility for unjustified civilian deaths. (shrink)

A theoretical framework for the reinforcement learning of aesthetic biases was recently proposed based on brain circuitries revealed by neuroimaging. A model grounded on that framework accounted for interesting features of human aesthetic biases. These features included individuality, cultural predispositions, stochastic dynamics of learning and aesthetic biases, and the peak-shift effect. However, despite the success in explaining these features, a potential weakness was the linearity of the value function used to predict reward. This linearity meant that the learning process (...) employed a value function that assumed a linear relationship between reward and sensory stimuli. Linearity is common in reinforcement learning in neuroscience. However, linearity can be problematic because neural mechanisms and the dependence of reward on sensory stimuli were typically nonlinear. Here, we analyze the learning performance with models including optimal nonlinear value functions. We also compare updating the free parameters of the value functions with the delta rule, which neuroscience models use frequently, vs. updating with a new Phi rule that considers the structure of the nonlinearities. Our computer simulations showed that optimal nonlinear value functions resulted in improvements of learning errors when the reward models were nonlinear. Similarly, the new Phi rule led to improvements in these errors. These improvements were accompanied by the straightening of the trajectories of the vector of free parameters in its phase space. This straightening meant that the process became more efficient in learning the prediction of reward. Surprisingly, however, this improved efficiency had a complex relationship with the rate of learning. Finally, the stochasticity arising from the probabilistic sampling of sensory stimuli, rewards, and motivations helped the learning process narrow the range of free parameters to nearly optimal outcomes. Therefore, we suggest that value functions and update rules optimized for social and ecological constraints are ideal for learning aesthetic biases. (shrink)

Cognitive psychologists have uncovered a number of natural tendencies to systematic errors in thinking. This paper proposes some ways that intellectual character virtues might help correct these sources of epistemic unreliability. We begin with an overview of some insights from recent work in dual-process cognitive psychology regarding ‘biases and heuristics’, and argue that the dozens of hazards the psychologists catalogue arise from combinations and specifications of a small handful of more basic patterns of thinking. We expound four of these, and (...) sketch how they conspire to produce the myriad biases, heuristics, and illusions. We then offer accounts of two character virtues—self-vigilance and intellectual vitality—and explain how these virtues could help correct our error-prone thinking. The self-vigilant person appreciates her vulnerability to natural epistemic defects, is on the watch for cues to the working of these possible error-makers, and intelligently acts to correct for them. The intellectually vital person is naturally or has learned to be energetic, active, alert, attentive, and inquisitive, contrary to the natural tendency to cognitive laziness. We suggest that these intellectual virtues, like the moral virtues, will cluster in the personality, and will tend to be mutually reinforcing and mutually recruiting, even as each has its own corrective function. (shrink)

Nihilism, Nietzsche and the Doppelganger Problem Was Nietzsche a nihilist? Yes, because, like J. L. Mackie, he was an error-theorist about morality, including the elitist morality to which he himself subscribed. But he was variously a diagnostician, an opponent and a survivor of certain other kinds of nihilism. Schacht argues that Nietzsche cannot have been an error theorist, since meta-ethical nihilism is inconsistent with the moral commitment that Nietzsche displayed. Schacht’s exegetical argument parallels the substantive argument (advocated in (...) recent years by Wright and Blackburn) that Mackie’s error theory can’t be true because if it were, we would have to give up morality or give up moralizing. I answer this argument with a little bit of help from Nietzsche. I then pose a problem, the Doppelganger Problem, for the meta-ethical nihilism that I attribute to Mackie and Nietzsche. (If A is a moral proposition then not-A is a moral proposition: hence not all moral propositions can be false.) I solve the problem by reformulating the error theory and also deal with a variant of the problem, the Reinforced Doppelganger, glancing at a famous paper of Ronald Dworkin’s. Thus, whatever its demerits, the error theory, is not self-refuting, nor does it require us to give up morality. (shrink)

Social norms are commonly understood as rules that dictate which behaviors are appropriate, permissible, or obligatory in different situations for members of a given community. Many researchers have sought to explain the ubiquity of social norms in human life in terms of the psychological mechanisms underlying their acquisition, conformity, and enforcement. Existing theories of the psychology of social norms appeal to a variety of constructs, from prediction-error minimization, to reinforcement learning, to shared intentionality, to domain-specific adaptations for norm (...) acquisition. In this paper, we propose a novel methodological and conceptual framework for the cognitive science of social norms that we call normative pluralism. We begin with an analysis of the explanatory aims of the cognitive science of social norms. From this analysis, we derive a recommendation for a reformed conception of its explanandum: a minimally psychological construct that we call normative regularities. Our central empirical proposal is that the psychological underpinnings of social norms are most likely realized by a heterogeneous set of cognitive, motivational, and ecological mechanisms that vary between norms and between individuals, rather than by a single type of process or distinctive norm system. This pluralistic approach, we suggest, offers a methodologically sound point of departure for a fruitful and rigorous science of social norms. (shrink)

The compliance-based approach and the integrity approach have been the mainstream responses to corporate scandals. This paper proposes that, despite each approach comprising necessary elements, neither offers a comprehensive solution. Compliance and integrity, far from being mutually exclusive, reinforce each other. Working together, in a correct relationship, they build a harmonized system that yields positive synergies and which also advocates prudence. It enables the generation of a culture of compliance that tends to minimize the technical and ethical errors in decision (...) making. In order to explore an applied harmonized approach, we analyze the audit committee, a specific and broadly accepted regulatory instrument. Formed by non-executive members, regulation requires these members to be dedicated, qualified, and independent as a guarantee of efficiency. We show how the compound of those elements produces positive effects in a context of solid governance. We conclude that it is the strong relationship between efficiency and prudence, in the creation of a culture of compliance, which enables the minimization of errors. (shrink)

In this paper we explore in what sense we can claim that affordances, the objects of perception for ecological psychology, are related to normativity. First, we offer an account of normativity and provide some examples of how it is understood in the specialized literature. Affordances, we claim, lack correctness criteria and, hence, the possibility of error is not among their necessary conditions. For this reason we will oppose Chemero’s normative theory of affordances. Finally, we will show that there is (...) a way in which taking advantage of affordances could be considered as possessing a normative character, but only when they are evaluated within the framework of social normative standards in particular situations. This reinforces our claim that affordances, per se, lack normativity and can only be taken to be rule-governed in relation to established normative practices. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:“A Child Has Been Born unto Us”Arendt on BirthAdriana CavareroTranslated by Silvia Guslandi and Cosette BruhnsIn The Human Condition, at the end of the dense chapter on action, Hannah Arendt reiterates that action, that is, the political faculty for excellence, “is ontologically rooted” in the fact of natality, “like an ever-present reminder that men, though they must die, are not born in order to die but in order to (...) begin” (Arendt 1998, 246).1 To reinforce this argument, Arendt compares action to miracles, and makes an interesting and, as we will see, somewhat perplexing reference to the Bible:[The miracle] is, in other words, the birth of new men and the new beginning, the action they are capable of by virtue of being born. Only the full experience of this capacity can bestow upon human affairs faith and hope, those two essential characteristics of human existence which Greek antiquity ignored altogether.…It is this faith in and hope for the world that found perhaps its most glorious and most succinct expression in the few words with which the Gospels announced their “glad tidings”: “A child has been born unto us.”(HC, 247)The citation is suggestive, but incorrect. In the Gospels, which do announce with true joy the birth of the child, the phrase as it is quoted here does not exist. It appears instead in Isaiah (9:6), translated into English both as “For to us a child is borne,” and, in the version of the King James Bible from which Arendt is plausibly drawing, as “For unto us a child is born.” The error, if indeed it is an error, is thus twofold (see Young-Ah Gottlieb 2003, 136ff.), since [End Page 12] both the passage referenced and the words cited are incorrect. That Arendt frequently cites from memory, and that the citations tend to be bibliographically incorrect, is known to her interpreters, but in this case the error ends up being quite significant. As is well known, the prophetic text carries a strong Messianic burden, and such a burden would trouble significantly the thesis that Arendt is here illustrating; the Gospels’ message creates instead fewer obstacles to her strategy of framing the meaning of birth within the mundane horizon that in her vocabulary takes the names of “world” or “worldliness.” Since “‘to live’ and to ‘be among men’” mean the same thing (HC, 7), the child, every newborn, that is, every human being that makes its entrance in the world, is not, according to the Arendtian vision, born to us, coming from elsewhere, but appears among us here. The scenario of birth, like that of action, whatever be the holy text that mentions or exemplarily validates them, is, for Arendt, a radically mundane scenario that does not call into question any transcendence or religious instance of salvation.Jewish, secular, and classically trained in Greek and Latin, Arendt, who had little familiarity with the Jewish language and tradition, met Christian thought primarily through Saint Augustine, to whom she dedicated her doctoral thesis (Der Liebesbegriff bei Augustin, published in Berlin in 1929 and then in English in 1996 as Love and Saint Augustine), and who remained a constant point of reference throughout her work. A phrase from Augustine—initium ut esset homo creatus est—present in the thesis, appears, in fact, in Arendt’s later texts, including The Human Condition, indeed with obsessive repetitiveness in reference to the category of birth.2 In her monumental work The Origins of Totalitarianism, published in 1951, a full seven years prior to The Human Condition, Arendt already writes: “Beginning, before it becomes a historical event, is the supreme capacity of man; politically, it is identical with man’s freedom. Initium ut esset homo creatus est, ‘that a beginning be made, man was created’, said Augustine. This beginning is guaranteed by each new birth; it is indeed every man” (Arendt 1973, 479). On the philosophically anomalous theme of birth, the contributions of the Christian tradition that Arendt does appreciate are predominantly two: the “glad tidings” that herald the coming of the child, and Augustine’s comments on the narrative of Creation.Natality, Birth, and the Human Condition of... (shrink)

Unsupervised learning algorithms are widely used for many important statistical tasks with numerous applications in science and industry. Yet despite their prevalence, they have attracted remarkably little philosophical scrutiny to date. This stands in stark contrast to supervised and reinforcement learning algorithms, which have been widely studied and critically evaluated, often with an emphasis on ethical concerns. In this article, I analyze three canonical unsupervised learning problems: clustering, abstraction, and generative modeling. I argue that these methods raise unique epistemological (...) and ontological questions, providing data-driven tools for discovering natural kinds and distinguishing essence from contingency. This analysis goes some way toward filling the lacuna in contemporary philosophical discourse on unsupervised learning, as well as bringing conceptual unity to a heterogeneous field more often described by what it isnot(i.e., supervised or reinforcement learning) than by what itis. I submit that unsupervised learning is not just a legitimate subject of philosophical inquiry but perhaps the most fundamental branch of all AI. However, an uncritical overreliance on unsupervised methods poses major epistemic and ethical risks. I conclude by advocating for a pragmatic, error-statistical approach that embraces the opportunities and mitigates the challenges posed by this powerful class of algorithms. (shrink)

As is well known, Wittgenstein pointed out an asymmetry between first- and third-person psychological statements: the first, unlike the latter, involve observation or a claim to knowledge and are constitutionally open to uncertainty. In this paper, I challenge this asymmetry and Wittgenstein's own affirmation of the constitutional uncertainty of third-person psychological statements, and argue that Wittgenstein ultimately did too. I first show that, on his view, most of our third-person psychological statements are noncognitive; they stem from a subjective certainty: a (...) certainty which, though not the result of an epistemic process, is not invulnerable to error in that it is a kind of assumption. I then trace Wittgenstein's realization that some third-person psychological certainties are not merely subjective but 'objective' (which means, as he uses the word, that they are logically indubitable): in some cases, we can be as logically certain that someone else is in pain than we are about ourselves being in pain. This positively reinforces Wittgenstein's rebuttal of other mind scepticism. I conclude with a response to objections about the legitimacy of calling an assurance that is logical (i.e., that does not have uncertainty or doubt on its flipside) a 'certainty', by suggesting that the flipside is to be found in pathological cases, and most pertinently here, in cases of dyssemia: a rare disorder affecting the ability to properly express or recognize basic physical expressions of feeling. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Adjudicating the Debate Over Two Models of Nature AppreciationSheila Lintott (bio)It seems commonplace to point out that we aesthetically appreciate a wide variety of objects: that is, art objects are not the only good candidates for aesthetic appreciation.1 We know from experience that one can aesthetically appreciate not only Georgia O'Keefe's White Trumpet Flower, but also a white trumpet flower. Similarly, we can aesthetically appreciate both a pictorial representation (...) of the human form and that form instantiated in certain prime specimens. We do so, moreover, without classifying either flowers or human beings as art objects. Yet, the paradigm of aesthetic appreciation today, in both everyday life and in educative contexts, is the appreciation of art, which explains why we tend to try to understand what makes aesthetic appreciation appropriate in terms of what makes art appreciation appropriate. This approach may not be entirely mistaken, for beginning with the familiar is always a good plan. However, it must be done with care, otherwise important differences between our relationships with the art we appreciate and with the nature we appreciate may be overlooked, thereby obscuring salient differences in the appreciation of each.In this essay, I focus on the issue of the appropriate aesthetic appreciation of nature and offer an overview of a contemporary debate on the topic. I begin with a general discussion of art and nature appreciation. I then summarize Kendall Walton's theory of appropriate art appreciation and explain his skepticism regarding the possibility of appropriate and inappropriate nature appreciation. Next, I discuss two models according to which Walton is mistaken, as the philosophers who present these models, Allen Carlson and Noël Carroll, do so to illustrate how nature appreciation can be properly considered appropriate or inappropriate. It may seem that given the recent proliferation of models of nature appreciation, the last thing we should seek is yet another model. However, in the end, I shall argue the need for a new and different kind of model, one that is a revisionist and extensionist model of nature appreciation. [End Page 52]Art and Nature AppreciationConcerning the perceptual activity of the audience, how we ought to appreciate artworks is largely uncontroversial. Perhaps this is why Carlson opens his attempt to understand the aesthetic appreciation of nature with a presentation of the aesthetic appreciation of art, explaining that "with art objects there is a straightforward sense in which we know both what and how to aesthetically appreciate."2 Although not all artworks offer "straightforward" examples of aesthetic appreciation, Carlson's general point is reasonably motivated. As Kendall Walton succinctly explains: "Paintings and sculptures are to be looked at; sonatas and songs are to be heard. What is important about these works of art, as works of art, is what can be seen or heard in them."3 That we ought to look at paintings and listen to sonatas seems obvious for at least two reasons. First, via formal education and informal interactions, we have grown familiar with the conventions of art appreciation; second, such conventions find experiential reinforcement when, for example, our auditory sense is tickled by a Mozart concerto.4Underlying our relative lack of confidence when it comes to nature appreciation is the obvious fact that nature, unlike art, is not an artifact. Nature was not made by beings like us; it was made neither for our use, nor for our entertainment, nor for our appreciation.5 As Carlson puts it, "art objects are our own creations; it is for this reason that we know what is and what is not part of a work, which of its aspects are of aesthetic significance, and how to appreciate them" (ANE, 41). We need, therefore, a model of nature appreciation that will serve as a source of education regarding how best to appreciate nature and will offer the confidence we lack and the guidance we seek.It might seem that we should simply apply our knowledge of art to nature appreciation — that is, appreciate nature as if it were art. However, as numerous philosophers have noticed, this approach is mistaken.6 The mistake is both theoretical and practical. Theoretically, it is a category error... (shrink)

"The pursuit of science by professional scientists every day bears less and less resemblance to the perception of science by the general public. It is not the rule-based, methodical system for accumulating facts that dominates the public view. Rather it is the idiosyncratic, often bumbling search for understanding in mostly uncharted places. It is full of wrong turns, cul-de-sacs, mistaken identities, false findings, errors of fact and judgment-and the occasional remarkable success. The widespread but distorted view of science as infallible (...) originates in an education system that teaches nothing but facts using very large, very frightening textbooks, and is spread by media that report on discoveries but almost never on process. It is further reinforced by politicians who pay for it and want to use it to determine policy and therefore want it right and, worst of all, sometimes by scientists who learn early on that talking too much about failures and not enough about successes can harm their careers. Failure, then, is a book that seeks to make science more appealing by exposing its faults. In this sequel to Ignorance, Stuart Firestein shows us that scientific enterprise is riddled with failures, and that this is not only necessary but good. Failure reveals how science got its start, when humans began to use a process-trial and error-as a kind of recipe that includes a hefty dose of failure. It gives the non-scientifically trained public an insider's view of how science is actually done, with the aim of making it accessible, comprehensible, and entertaining."--Publisher description. (shrink)

In a 2007 paper, we argued that speakers with Autism Spectrum Disorders exhibit pragmatic abilities which are surprising given the usual understanding of communication in that group. That is, it is commonly reported that people diagnosed with an ASD have trouble with metaphor, irony, conversational implicature and other non-literal language. This is not a matter of trouble with knowledge and application of rules of grammar. The difficulties lie, rather, in successful communicative interaction. Though we did find pragmatic errors within literal (...) talk, the transcribed conversations we studied showed many, many successes. A second paper reinforced our finding of a general level of success. It considered differences within the class of pragmatically-inflected yet literal speech acts. The present paper carries our project forward. It overcomes some of the methodological limitations of the second paper, by increasing sample size, and looking at frequency of use rather than just seeming errors. It also includes a control sample. The emerging results are two-fold. On the one hand, there was a slight, statistically significant difference in frequency of use between our participants and the controls in four sub-categories: indexicals, possessives, polysemy and degree on a scale. In all four, the participants diagnosed with ASDs had fewer occurrences overall, relative to controls. On the other hand, there was no significant difference in error rates between ASDs and controls — not in any of the eight categories of pragmatic determinants of literal content that we coded for. The upshot is that, though there were less-preferred forms for participants with ASDs, they do very well indeed with pragmatic determinants of literal content. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Adjudicating the Debate Over Two Models of Nature AppreciationSheila Lintott (bio)It seems commonplace to point out that we aesthetically appreciate a wide variety of objects: that is, art objects are not the only good candidates for aesthetic appreciation.1 We know from experience that one can aesthetically appreciate not only Georgia O'Keefe's White Trumpet Flower, but also a white trumpet flower. Similarly, we can aesthetically appreciate both a pictorial representation (...) of the human form and that form instantiated in certain prime specimens. We do so, moreover, without classifying either flowers or human beings as art objects. Yet, the paradigm of aesthetic appreciation today, in both everyday life and in educative contexts, is the appreciation of art, which explains why we tend to try to understand what makes aesthetic appreciation appropriate in terms of what makes art appreciation appropriate. This approach may not be entirely mistaken, for beginning with the familiar is always a good plan. However, it must be done with care, otherwise important differences between our relationships with the art we appreciate and with the nature we appreciate may be overlooked, thereby obscuring salient differences in the appreciation of each.In this essay, I focus on the issue of the appropriate aesthetic appreciation of nature and offer an overview of a contemporary debate on the topic. I begin with a general discussion of art and nature appreciation. I then summarize Kendall Walton's theory of appropriate art appreciation and explain his skepticism regarding the possibility of appropriate and inappropriate nature appreciation. Next, I discuss two models according to which Walton is mistaken, as the philosophers who present these models, Allen Carlson and Noël Carroll, do so to illustrate how nature appreciation can be properly considered appropriate or inappropriate. It may seem that given the recent proliferation of models of nature appreciation, the last thing we should seek is yet another model. However, in the end, I shall argue the need for a new and different kind of model, one that is a revisionist and extensionist model of nature appreciation. [End Page 52]Art and Nature AppreciationConcerning the perceptual activity of the audience, how we ought to appreciate artworks is largely uncontroversial. Perhaps this is why Carlson opens his attempt to understand the aesthetic appreciation of nature with a presentation of the aesthetic appreciation of art, explaining that "with art objects there is a straightforward sense in which we know both what and how to aesthetically appreciate."2 Although not all artworks offer "straightforward" examples of aesthetic appreciation, Carlson's general point is reasonably motivated. As Kendall Walton succinctly explains: "Paintings and sculptures are to be looked at; sonatas and songs are to be heard. What is important about these works of art, as works of art, is what can be seen or heard in them."3 That we ought to look at paintings and listen to sonatas seems obvious for at least two reasons. First, via formal education and informal interactions, we have grown familiar with the conventions of art appreciation; second, such conventions find experiential reinforcement when, for example, our auditory sense is tickled by a Mozart concerto.4Underlying our relative lack of confidence when it comes to nature appreciation is the obvious fact that nature, unlike art, is not an artifact. Nature was not made by beings like us; it was made neither for our use, nor for our entertainment, nor for our appreciation.5 As Carlson puts it, "art objects are our own creations; it is for this reason that we know what is and what is not part of a work, which of its aspects are of aesthetic significance, and how to appreciate them" (ANE, 41). We need, therefore, a model of nature appreciation that will serve as a source of education regarding how best to appreciate nature and will offer the confidence we lack and the guidance we seek.It might seem that we should simply apply our knowledge of art to nature appreciation — that is, appreciate nature as if it were art. However, as numerous philosophers have noticed, this approach is mistaken.6 The mistake is both theoretical and practical. Theoretically, it is a category error... (shrink)

In this paper we explore in what sense we can claim that affordances, the objects of perception for ecological psychology, are related to normativity. First, we offer an account of normativity and provide some examples of how it is understood in the specialized literature. Affordances, we claim, lack correctness criteria and, hence, the possibility of error is not among their necessary conditions. For this reason we will oppose Chemero’s normative theory of affordances. Finally, we will show that there is (...) a way in which taking advantage of affordances could be considered as possessing a normative character, but only when they are evaluated within the framework of social normative standards in particular situations. This reinforces our claim that affordances, per se, lack normativity and can only be taken to be rule-governed in relation to established normative practices. (shrink)

Lately, a number of referee decisions appear to have reignited the debate over the need to bring more in-game officiating technology into soccer. The fallacies behind the arguments for the inclusion of technology to aid game officials can be narrowed down to those behind current arguments for or against goal-line technology. Both the proponents and opponents of these arguments appear to overemphasise the role of referees to the point of claiming that if refereeing errors could be eliminated in goal-line situations, (...) then the most deserving team would most of the time be expected to win the contest. While we firmly believe that the game of soccer would benefit immensely from infallible officiating, we intend to show that these arguments are founded upon a number of inconspicuous assumptions. First, they assume that goal-line situations can be shown to affect the outcomes of games more than all other game situations. This can easily be shown to be a myth, since goals can be scored from all areas of the playing field. In addition, winning a soccer game, obviously, involves more than just scoring goals. Second, these arguments seem to support the view that referee decisions affect the outcomes of games more than decisions made by players, coaches and managers. This is merely a myth, since one can show that, in light of Cesar Torres's insights, referee involvement in game is limited to regulating situations that demand that the game be restored to its constitutive actualisation. Third, most arguments for goal-line technology tend to support the erroneous view that technology can actually eliminate most ?crucial? human mistakes from sport and, thus, ensure fairness of game outcomes. Such a myth can easily be refuted by reference to numerous cases of inconclusive slow-motion video replays in soccer. Therefore, this paper aims at arguing that, instead of reinforcing the scapegoating of referees and overemphasising the importance of isolated referee decisions to the point of attributing victory or defeat to these ?crucial? decisions, both sides of the goal-line technology debate need to put forth compelling arguments which go beyond the current misguided search for referee infallibility. (shrink)

In a 2007 paper, we argued that speakers with Autism Spectrum Disorders exhibit pragmatic abilities which are surprising given the usual understanding of communication in that group. That is, it is commonly reported that people diagnosed with an ASD have trouble with metaphor, irony, conversational implicature and other non-literal language. This is not a matter of trouble with knowledge and application of rules of grammar. The difficulties lie, rather, in successful communicative interaction. Though we did find pragmatic errors within literal (...) talk, the transcribed conversations we studied showed many, many successes. A second paper reinforced our finding of a general level of success. It considered differences within the class of pragmatically-inflected yet literal speech acts. The present paper carries our project forward. It overcomes some of the methodological limitations of the second paper, by increasing sample size, and looking at frequency of use rather than just seeming errors. It also includes a control sample. The emerging results are two-fold. On the one hand, there was a slight, statistically significant difference in frequency of use between our participants and the controls in four sub-categories: indexicals, possessives, polysemy and degree on a scale. In all four, the participants diagnosed with ASDs had fewer occurrences overall, relative to controls. On the other hand, there was no significant difference in error rates between ASDs and controls — not in any of the eight categories of pragmatic determinants of literal content that we coded for. The upshot is that, though there were less-preferred forms for participants with ASDs, they do very well indeed with pragmatic determinants of literal content. (shrink)

This study investigates the ability of individuals with psychopathy to perform passive avoidance learning and whether this ability is modulated by level of reinforcement/punishment. Nineteen psychopathic and 21 comparison individuals, as defined by the Hare Psychopathy Checklist Revised (Hare, 1991), were given a passive avoidance task with a graded reinforcement schedule. Response to each rewarding number gained a point reward specific to that number (i.e., 1, 700, 1400 or 2000 points). Response to each punishing number lost a point (...) punishment specific to that number (i.e., the loss of 1, 700, 1400 or 2000 points). In line with predictions, individuals with psychopathy made more passive avoidance errors than the comparison individuals. In addition, while the performance of both groups was modulated by level of reward, only the performance of the comparison population was modulated by level of punishment. The results are interpreted with reference to a computational account of the emotional learning impairment in individuals with psychopathy. (shrink)

Background:The acquisition of experience is a major concern for nurses in intensive care units. Although the emotional component of the clinical practice of these nurses has been widely studied, greater examination is required to determine how this component influences their learning and practical experience.Objective:To discover the relationships between emotion, memory and learning and the impacts on nursing clinical practice.Research design:This is a qualitative phenomenological study. The data were collected from open, in-depth interviews. A total of 22 intensive care unit nurses (...) participated in this research between January 2012 and December 2014.Ethical considerations:The School of Nursing Ethics Committee approved the study, which complied with ethical principles and required informed consent.Findings:We found a clear relationship between emotion, memory and the acquisition of experience. This relationship grouped three dimensions: (1) satisfaction, to relieve the patient’s pain or discomfort, give confidence and a sense of security to the patient, enable the presence of family members into the intensive care unit and provide family members with a realistic view of the patient’s situation; (2) error experience, which nurses feel when a patient dies, when they fail to accompany a patient in his or her decision to abandon the struggle to live or when they fail to lend support to the patient’s family; and (3) the feel bad–feel good paradox, which occurs when a mistake in the patient’s care or handling of his or her family is repaired.Conclusion:Emotion is a capacity that impacts on nurses’ experience and influences improvements in clinical practice. Recalling stories of satisfaction helps to reinforce good practice, while recalling stories of errors helps to identify difficulties in the profession and recognise new forms of action. The articulation of emotional competencies may support the development of nursing ethics in the intensive care unit to protect and defend their patients and improve their relationships with families in order to maximise the potential for patient care. (shrink)