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BEYOND DISCIPLINES: SMART DECISION TOOL

J. Velencei

First published: 2017https://doi.org/10.5593/sgemsocial2017/41/S17.037View metrics

Abstract

Understanding the human–computer interaction has its own pace, it would be equally wrong to rush it or slow it down. To figure out whether to attack a new phenomenon or to stand with it, we need to choose a viewpoint. Building on background knowledge it can say that none of the disciplines deals with reality, each of them tears out a different part of reality, which is then studied using concepts and methods of that discipline and/or borrowing from other disciplines. Terry Winograd realized that the artificial world does not postulate that in reality the wind blows and there are cats, and that this can mess up its cards. This paper demonstrates that disciplines, that study the human–computer interaction, behave like Goliath and fail to see the reality in which there are winds and cats and even slingshots. In this paper a transdisciplinary method is proposed, in other words a view of the human–computer interaction without the disciplinary “cages”. Another method also is proposed, namely the "if...then" logical connections between disciplinary concepts which are made transparent by the Doctus Smart Decision Tool. With this transdisciplinary method, experience and inexperience can be connected, for both the experienced and the inexperienced decision maker uses logic to make decisions. The only difference is, that the inexperienced believe in the plethora of rules, while the experienced know how to make the same decision based on fewer rules. The result is the algorithm to reduce experience and so map a part of tacit knowledge. The conclusion of this paper is that fast thinking, experience mining and rule based behaviour metaphors are good enough to describe the reality of the human–computer interaction.

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Publication details

Title
BEYOND DISCIPLINES: SMART DECISION TOOL
Authors
J. Velencei
Proceedings
4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM 2017
Publisher
STEF92 Technology
Year
2017
Pages
295-302
SWS Citekey
Velencei201717295302
ISSN
2367-5659
ISBN
978-619-7408-23-2
Language
en
Publication type
Proceedings Paper
Keywords
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