It is highly likely that, to achieve full human–machine symbiosis, truly intelligent cognitive systems—human-like —may have to be developed first. Such systems should not only be capable of performing human-like thinking, reasoning, and problem solving, but also be capable of displaying human-like motivation, emotion, and personality. In this opinion article, I will argue that such systems are indeed possible and needed to achieve true and full symbiosis with humans. A computational cognitive architecture is used in this article to illustrate, in (...) a preliminary way, what can be achieved in this regard. It is shown that Clarion involves complex structures, representations, and mechanisms, and is capable of capturing human cognitive performance as well as human motivation, emotion, personality, and other relevant aspects. It is further argued that the cognitive architecture can enable and facilitate true human–machine symbiosis. (shrink)

The necessity of epistemological theorisation for management science is questionable. However, epistemology can be useful if the following distinction between three kinds of epistemology, usually overlooked, is taken into account: epistemology as a structured academic discipline, epistemology as an intellectual exercise produced outside academic epistemology, and finally the epistemology specific to each researcher. When this distinction is not made, epistemology can become counterproductive and impede scientific work.

Math anxiety results in a drop in performance on various math-related tasks, including the symbolic number ordering task in which participants decide whether a triplet of digits is presented in order (e.g. 3-5-7) or not (e.g. 3-7-5). We investigated whether the strategy repertoire and reaction times during a symbolic ordering task were affected by math anxiety. In study 1, participants performed an untimed symbolic number ordering task and indicated the strategy they used on a trial-by-trial basis. The use of the (...) memory retrieval strategy, based on the immediate recognition of the triplet, decreased with high math anxiety, but disappeared when controlling for general anxiety. In the study 2, participants completed a timed version of the number order task. High math-anxious participants used the decomposition strategy (e.g. 5 is larger than 3 and 7 is larger than 5 to decide whether 3-5-7 is in the correct order) more often, and were slower in responding when both memory- and other decomposition strategies were used. Altogether, both studies demonstrate that high-math anxious participants are not only slower to decide whether a number triplet is in the correct order, but also rely more on procedural strategies. (shrink)

The current status of Beilock and Carr's "execution focus" theory of choking under pressure in performance of a sensorimotor skill is reviewed and assessed, mainly from the perspective of cognitive psychology, and put into the context of a wider range of issues, attempting to take philosophical analysis into account. These issues include other kinds of skills, pre-performance practice, post-performance evaluation and repair, and integrating new and creative achievements into repertoires of heavily practiced routines. The focus is on variation in the (...) demand for reflection versus automaticity across the full gamut of learning and experience, not just game-time performance. Though automaticity remains important and there are many circumstances in which being "in the zone" is good whereas “execution focus” can do harm, it appears that reflective action deserves just as much a place at the performance table as does unreflective action. (shrink)

This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various situations. These motivational (...) representations help to make cognitive architectural models more comprehensive and provide deeper explanations of psychological processes. This work represents a step forward in making computational cognitive architectures better reflections of the human mind and all its motivational complexity and intricacy. (shrink)