Humanity faces two fundamental problems of learning: learning about the universe, and learning to become civilized. We have solved the first problem, but not the second one, and that puts us in a situation of great danger. Almost all of our global problems have arisen as a result. It has become a matter of extreme urgency to solve the second problem. The key to this is to learn from our solution to the first problem how to solve the second one. (...) This was the basic idea of the 18th century Enlightenment, but in implementing this idea, the Enlightenment blundered. Their mistakes are still built into academia today. In order to le arn how to create a civilized, enlightened world, the key thing we need to do is to cure academia of the structural blunders we have inherited from the Enlightenment. We need to bring about a revolution in science, and in academia more broadly so that the basic aim becomes wisdom, and not just knowledge. (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 Constant change in world data, outdated knowledge, defects in datasets, and human biases in understanding all confirm the infinitely grey nature of human knowledge of the world.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)

Positivism has had a tremendous impact on the development of the social sciences over the past two centuries. It has deeply influenced method and theory, and has seeped deeply into our broader understandings of the nature of the social sciences. Postmodernism has attempted to loosen the grip of positivism on our thinking, and while it has not been without its successes, postmodernism has worked more to deconstruct positivism than to construct something new in its place. Psychologists today perennially wrestle to (...) find and retain their intellectual balance within the methodological, theoretical, and epistemological struggles between positivism and postmodernism. In the process, pre-postmodern criticisms of positivism have been largely forgotten. Although they remain deeply buried at the core of psychology, these early alternatives to positivism are rarely given explicit hearing today. The current piece explores some of the early critiques of positivism, particularly of its scientism, as well as early suggestions to tip the scales in favor ofsapientia. This third option, largely overlooked within mainstream psychology, is of tremendous value today as it is both deconstructive and constructive relative to the shortcomings of positivism. It avoids the overly reductionistic “trivial order” of positivism, as well as the deeply unsatisfying and disorienting “barbaric vagueness” of postmodernism, while simultaneously embracing important core elements of both currents of thought. (shrink)