Every scientific or intellectual movement rests on central premises and assumptions that shape its philosophy. The purpose of this study is to review a brief account of the main philosophical bases of grey systems theory (GST) and the paradigm governing its principles. So, the recent studies on the philosophical foundations of GST have been reviewed and tried to pay attention to some key ambiguities in the previous studies and give more and clearer explanations in this paper. Also, this paper tries (...) to fill the gap among the previous studies and to provide a purposeful connection between them by expressing two key concepts: complete information and imbalance knowledge. Primarily, the study addresses the theoretical foundations of uncertainty and the concept of greyness. Next, it focuses on the notion of “complete information” and challenges to it. Then, it reviews such processes as perception, cognition, and understanding, as well as their dynamic nature. It explains how knowledge is produced through understanding and interpreting information/data and the dynamics governing the whole process. Also, the study describes any dataset, no matter how large it may be, will remain incomplete, imperfect, and grey, so humans only rely on incomplete datasets to interpret the world. As such, information and knowledge are always grey and uncertain because they are basically contingent on subjective understandings and interpretations and imperfect inputs and data. Finally, as a key development, this study also demonstrates that human grey knowledge remains imbalanced across different disciplines and spheres. In the end, a brief overview of the philosophical paradigm of GST is also provided. GST is depicted as an anti-realistic, anti-positivistic, and non-deterministic approach, which is inherently pluralistic and ideographic. According to GST principles, dynamicity and change are essential parts of human narratives of the world and systems, and human knowledge is constantly reproduced through collecting new information. As a result, knowledge, theories, narratives, and scientific laws dynamically change. Given this premise, one could argue that GST is considerably compatible with the postulates of post-modern thinking. (shrink)

This study seeks to explicate the philosophical foundations and theoretical outlines of grey systems theory by focusing on human perception, cognition, and understanding processes and by considering their functions in the process of producing knowledge. Primarily, the study investigates the processes of perception, cognition, and understanding, as well as their dynamicity. Then, it is explained how knowledge is produced through the interpretation/understanding of information and data and through the dynamicity governing this process. The findings reveal that human perception, cognition, and (...) understanding perpetually remain grey and imperfect, while lost sensatory data mark the very first aspect of greyness in such human capabilities. Furthermore, any piece of data, as a discrete and single entity, represents a determinate fact, symbol or signal from the world, while any set of data, no matter how large, remains incomplete and imperfect, and human beings always interpret inadequate sets of data in the world. Therefore, information and knowledge always remain grey and uncertain because they deeply rely on subjective understandings/interpretations and work with imperfect inputs and sets of data. The impact of knowledge on action and interaction and their effects on the world are some factors adding to the dynamicity of the world. Constant change in world data, outdated knowledge, defects in datasets, and human biases in understanding all confirm the infinitely grey nature of human knowledge of the world. (shrink)

This paper discusses the epistemic status of biology from the standpoint of the systemic approach to living systems based on the notion of biological autonomy. This approach aims to provide an understanding of the distinctive character of biological systems and this paper analyses its theoretical and epistemological dimensions. The paper argues that, considered from this perspective, biological systems are examples of emergent phenomena, that the biological domain exhibits special features with respect to other domains, and that biology as a discipline (...) employs some core concepts, such as teleology, function, regulation among others, that are irreducible to those employed in physics and chemistry. It addresses the claim made by Jacques Monod that biology as a science is marginal. It argues that biology is general insofar as it constitutes a paradigmatic example of complexity science, both in terms of how it defines the theoretical object of study and of the epistemology and heuristics employed. As such, biology may provide lessons that can be applied more widely to develop an epistemology of complex systems. (shrink)