Robust Knowledge: The Bastness Of Knowledge And Scientific Knowledge

For a network of interacting academics and experts, it is important that we are able to reach certain conclusions based on our common judgement, and constantly refine the existing knowledge in the light of new evidence and research. Ultimately, we should end up with knowledge that can be considered to be robust. Robust knowledge can be defined in terms of the validity, consistency and applicability of particular kind of knowledge. Therefore, robust knowledge often includes the conventions and methodologies that underline the basic foundation of a field. For different areas of knowledge, we seem to have certain qualifications or requirements for knowledge to be considered as “robust”. The word “requires” means that it is absolutely necessary

Robust scientific knowledge is universally accepted by the majority of the people and should withstand the test of falsification. Karl Popper believed that the best way to test whether a theory is valid, is by attempting to find evidence that falsifies or refutes it. In the natural sciences, the scientific method is often regarded as the most effective way to investigate the natural world. Karl Popper claimed that the scientific method is based on the assumption that we can observe our world without any preconceived notions. On the contrary, in the arts, robust knowledge may exist in the form of conventions related to texture, composition, palette and technique, but it is sometimes difficult to interpret whether the art is robust due to the subjective nature and approach of the

Without agreement in the first place, we would not be able refer to the common foundation and basic facts that should be established before any further discussion of justification. Natural science includes models that may contradict with real life, and may not be applicable to our world. However, models are important in the natural sciences, even though those models may not necessarily be the most accurate representation of the specific physical phenomena. These models are continuously refined when more is discovered about the current phenomena, and these models are then updated in the light of new evidence. This then raises the question of whether models that we know may be inaccurate are considered as a part of robust knowledge. Models are simplified versions of our common reality in order to understand fundamental ideas on the most basic level and to make better sense of the world surrounds us. Models are nonetheless useful for us, because it allows us to picture complicated physical phenomena and use a much simpler model to depict our observation through sense perception. For example, the Newton´s first law states that an object will stay in motion unless there is an opposing force acting upon it. We know that this theory, only work when there is not friction or air resistance. However, when using models we sacrifice accuracy for the sake of simplicity. In