The myth of the moral faculty: Response to Kirkby

David Kirkby argues that I have misrepresented Marc Hauser's conception of a moral faculty, in a way that invalidates my chief arguments against the existence and necessity of such a faculty. The core of Kirkby's challenge is that what Hauser lists as necessary conditions for the moral faculty to do its work are not themselves components of that faculty. I argue that there is no useful way to distinguish necessary conditions of moral judgments from the alleged moral faculty itself, and that even if we could do this, we would be left with an empty non-explanation of the supposed moral faculty that amounts to nothing more than the claim that we have a faculty that generates judgments of right versus wrong.     

The cognitive impenetrability of the content of early vision is a necessary and sufficient condition for purely nonconceptual content

I elaborate on Pylyshyn's definition of the cognitive impenetrability (CI) of early vision, and draw on the role of concepts in perceptual processing, which links the problem of the CI or cognitive penetrability (CP) of early vision with the problem of the nonconceptual content (NCC) of perception. I explain, first, the sense in which the content of early vision is CI and I argue that if some content is CI, it is conceptually encapsulated, that is, it is NCC. Then, I examine the definitions of NCC and argue that they lead to the view that the NCC of perception is retrieved in a stage of visual processing that is CI. Thus, the CI of a state and content is a sufficient and necessary condition for the state and its content to be purely NCC, the CI?≡?NCC thesis. Since early vision is CI, the purely NCC of perception is formed in early vision. I defend the CI?≡?NCC thesis by arguing against objections raised against both the sufficient and the necessary part of the thesis.     

Cognitive load while driving impairs memory of moving but not stationary elements within the environment

The negative impact of cognitive load, such as cell phone conversations, while driving is well established, but understanding the nature of this performance deficit is still being developed. To test the impact of load on awareness of different elements in a driving scene, memory for items within the environment was examined under load and no load conditions. Participants drove through two different scenarios in a driving simulator, were periodically interrupted by a pause in the driving during, and were asked questions regarding moving and stationary objects in the environment. Participants in the load condition drove while concurrently counting backwards by sevens. Results indicate that driving under load conditions led to diminished knowledge of moving, but not stationary, objects in the scene. This result suggests not all types of knowledge are equally impaired. Potential implications for current theories of cell phone use while driving and applied attention theory are discussed.     

The development of causal categorization

Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children's classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).     

Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

Clinicians have long noted that individuals with high psychopathic traits exhibit unique interpersonal style often observable during forensic interviews. Here we develop an automated approach for quantifying head dynamics during video-recorded naturalistic clinical interviews. We expected head dynamics would be related to psychopathic traits. As predicted, dwell times indicate that those with higher levels of psychopathic traits are characterized by more stationary head positions, focused directly towards the camera/interviewer, than were individuals low in psychopathic traits. These associations were primarily driven by developmental/antisocial features of psychopathy, indicating that those with severe and life-course persistent antisocial behavior exhibit more rigid and focused orienting of their head during interpersonal communication. These results encourage more research into the automated quantification of behavioral manifestations of personality to support clinical observations that psychopaths exhibit unique qualities in non-verbal interpersonal communication.     

How did I get here? Individual differences in perceived retrospective personality change

People's beliefs about their own past personality development are associated with current and future self-concepts. Here, we report on 2 studies designed to elucidate the way people think about retrospective changes to their own personality. We found that incremental theories of personality were associated with greater perceived retrospective personality change and that perceived retrospective personality change was associated with the belief that specific volitional and situational causes were involved. In addition, we found that across all Big-5 personality traits and agency, higher current standing (in the socially desirable direction) was positively associated with greater perceived retrospective personality change. This research demonstrates how people vary in their beliefs about retrospective personality change.