Emotional Engineers: Toward Morally Responsible Design

Engineers are normally seen as the archetype of people who make decisions in a rational and quantitative way. However, technological design is not value neutral. The way a technology is designed determines its possibilities, which can, for better or for worse, have consequences for human wellbeing. This leads various scholars to the claim that engineers should explicitly take into account ethical considerations. They are at the cradle of new technological developments and can thereby influence the possible risks and benefits more directly than anybody else. I have argued elsewhere that emotions are an indispensable source of ethical insight into ethical aspects of risk. In this paper I will argue that this means that engineers should also include emotional reflection into their work. This requires a new understanding of the competencies of engineers: they should not be unemotional calculators; quite the opposite, they should work to cultivate their moral emotions and sensitivity, in order to be engaged in morally responsible engineering

The Timing of the Cognitive Cycle

We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary “ignition” of conscious broadcasting. Neuroscientists have independently proposed ideas similar to the cognitive cycle, the fundamental hypothesis of the LIDA model of cognition. High-level cognition, such as deliberation, planning, etc., is typically enabled by multiple cognitive cycles. In this paper we describe a timing model LIDA's cognitive cycle. Based on empirical and simulation data we propose that an initial phase of perception (stimulus recognition) occurs 80–100 ms from stimulus onset under optimal conditions. It is followed by a conscious episode (broadcast) 200–280 ms after stimulus onset, and an action selection phase 60–110 ms from the start of the conscious phase. One cognitive cycle would therefore take 260–390 ms. The LIDA timing model is consistent with brain evidence indicating a fundamental role for a theta-gamma wave, spreading forward from sensory cortices to rostral corticothalamic regions. This posteriofrontal theta-gamma wave may be experienced as a conscious perceptual event starting at 200–280 ms post stimulus. The action selection component of the cycle is proposed to involve frontal, striatal and cerebellar regions. Thus the cycle is inherently recurrent, as the anatomy of the thalamocortical system suggests. The LIDA model fits a large body of cognitive and neuroscientific evidence. Finally, we describe two LIDA-based software agents: the LIDA Reaction Time agent that simulates human performance in a simple reaction time task, and the LIDA Allport agent which models phenomenal simultaneity within timeframes comparable to human subjects. While there are many models of reaction time performance, these results fall naturally out of a biologically and computationally plausible cognitive architecture

From Computer Metaphor to Computational Modeling: The Evolution of Computationalism

In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive (neuro)science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year

Kleptoparasitic prey competition in shoaling fish: effects of familiarity and prey distribution

Familiarity is thought to stabilize dominance hierarchies and reduce aggressive interactions within groups of socially living animals. Though familiarity has been widely studied in shoaling fish, few studies have investigated changes in prey competition as a function of time spent together within groups of initially unfamiliar individuals. In this study, we created shoals of three-spined stickleback (Gasterosteus aculeatus) and monitored changes in foraging rates and related competitive behaviors within shoals over a 4-week period in experimental series where prey was spatially and temporally concentrated or dispersed. Prey share was unequal under both prey distribution modes, and disparity in prey share was not seen to change as trials progressed. Interestingly, the contest rate for prey items fell over time when individuals were competing for dispersed prey but not when prey were concentrated. We found no evidence that fish showed association preferences for either group members that had consumed a greater or lesser proportion of prey during trials. Though the intensity of competition may be reduced by increased group stability in nature, this is likely to be strongly dependent on the way prey resources are distributed through space and time. Copyright 2006.flock; foraging; scrounging behavior; shoal; threespine stickleback