The concept of the work system is based on the fact that the human operator is its central element. There is no work system without a human as main part of the operating force. The most obvious reason for this absolute necessity is the fact that all work activity is done in order to comply with certain human desires whatsoever. Undoubtedly, as part of all work processes there is a human operator who represents the highest operating authority. The human's prominent role of being the highest authority in the work process would not be conceivable without his capabilities based on what we call cognition. Originally, the term cognition was used in disciplines which address the questions of how human brains work and how human behaviours could be explained, like physiology and psychology. Based on these disciplines, other interdisciplinary approaches evolved like neuroscience and cognitive psychology dealing with cognition as main research subject. Meanwhile, all this research work on human cognition tends to be subsumed collectively under a combined discipline called cognitive science.
Cognitive science has made enormous progress in the course of the last two decades. It should not be overlooked here that there is also other use of the notion of cognition in recent literature like in the context of distributed cognition and joint cognitive systems. These publications take cognition in a broader sense. They emphasise that cognition is not solely located in a single human operator's mind when operating in a work process but that it is distributed over the work system components and environment, whether the pertinent objects are humanmade artefacts or other humans involved. This view can even be extended by adding the organisational dimension of system design and realisation to become operative. Although this is a valid approach we will on purpose stay with the original way of interpretation, building up work systems with emphasis on the individual entities which incorporate cognition. Today, the term and concept of cognition is no longer limited to natural cognition only, like human cognition. Along with the tremendous ongoing technological advances in computer science, concerning computation power and software design, artificial cognition increasingly comes into focus. This leads to the question how the kinds of functions of human cognition can also apply for artificial cognition. It turns out that, in principal, these kinds of functions are valid for both natural and artificial cognition, however the realisation of these functions may be very different, and indeed are. Both, natural and artificial cognition have their particular scientific community with different views on which aspects of cognition are to be studied and for which purpose. There is the world of psychology and neuroscience considering human cognition, and on the other hand, there are the disciplines like computer science and to some extent engineering dealing with artificial cognition.
Both sides, pursuing not exactly the same objectives, though, are making use of the other's research results with great benefit. Since cognitive scientists provide more and more quantifiable results about these characteristics, the technology-related community is making use of these findings. On the other hand, cognitive scientists follow up the achievements in information processing artefacts capable of representing certain cognitive characteristics from which they can learn exactly how these are working in comparison to human information processing, thereby possibly gaining new insights in human cognition. Therefore, the contributions on the analysis and realisation of cognition in both the cognitive scientists' and the engineers' realm will be discussed in this article. Emphasis will be laid on what has to be learned from the cognitive scientists and what are the main lines of thought to actually derive a concept of artificial cognition. From the point of view of the work system designer human cognition is seen as a functional component, implemented on the tissue of the human brain and embedded into some kind of work environment. The human operator provides the most inner environmental layer of the brain, embodying this functional component and making use of it in the context of the work process. In the first place, this inner environmental layer provides sensors (receptors) and effectors without which no work at all can be done. It is not an easy task to separate between the sensing and effecting systems in the human body on the one hand and the human cognition on the other hand. Despite this fact, however, a separation seems adequate and very useful for the purpose of the organisation of this article.
The sensors are represented by the various human sensory modalities (visual, auditory, haptic, vestibular and olfactory) and their physiological properties. Effectors are represented by the muscle system of the human body (e.g. muscles to move arm or/and leg). This includes also the muscles for the articulation of spoken language and gestures. Both, the human sensing and effecting systems represent the interface to the world outside the human operator with two further environmental layers, first the work system layer and finally the external environment layer outside the work system. For the work system layer, all existing work system components are to be considered except the human operator. This layer is optional depending on which components are definitely involved in the work system. Since the work system has already been described in more depth, the focus of this article shall lie on some insight into the subject of human cognition. Many readers may wonder at this point, in particular those who have to design technical equipment, why sound knowledge about human cognition can be of great benefit for the design of technical support systems as part of a work system. However, this insight is in fact of great significance for the work system designer, since the knowledge about human cognition lends itself to more systematic approach for enhancing the effectiveness of work systems. This is subsumed under the discipline of human engineering. Unfortunately, designers often have become used to live with (too) little feedback of the users and what could have been achieved, if one would rigorously apply what is known about human cognition and resulting needs for the effective human-machine interaction in the work process. They are used to intuitively imagine how the human operator will make effective use of what they are designing, not realising that it is about impossible to comprehensively match with the real needs. From our experience we know that taking some effort of studying the findings about human cognition will pay off with great yield. Along these lines, knowledge about human cognition can be of great advantage for the work system designer in at least the following three ways:
1. The design of artificial components supporting the human operator, in particular artificial cognition, can be specified on a more rational basis, because it is better known where the human operator really needs support, when artificial cognition makes sense, and for which function. If we want to come to a decision on how the function allocation between the human operator and artificial cognitive components shall be designed, knowledge about human cognition is crucial.
2. In order to make sure that the artificial cognitive functions are being in compliance with the actual needs of the human operator, the embodiment of knowledge about human cognitive behaviour into artificial systems as part of work system is very useful. Only then effective co-operation on a cognitive level between artificial systems (automation) and the human operator can be made a design characteristic. This can be achieved by quantitative models of human behaviour like those we have in mind ourselves when we are supporting any co-workers in our daily life or are co-operating with somebody.
3. The use of the knowledge about the capabilities and the architecture of human cognition as a reference is a prudent way to achieve better designs. This does not mean that a designer should feel compelled to copy the design of the human brain. He rather can make use of his knowledge to benefit from assessments about on which functional basis the outstanding capabilities of human cognition are founded. This might lead to the conclusion to simply take over design features, if it makes sense, or to be stimulated by the unique realisations in the brain in both physical and functional structuring, like the mechanisms of learning, attention control and consciousness and to try for similar effects features in the artificial system. Moreover, the use of knowledge about human cognition might lead the designer to solutions where artificial cognition may have a chance to do better.
In summary, it is the human cognitive system the designer indeed can learn from, keeping in mind, though, that there are certain basic features which cannot be copied easily and that there are certain new options different from human cognition when starting to design an artificial cognitive system.
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