Computation is the medium of contemporary science. To understand the consequences of this gnoseological and epistemological revolution, one has to evaluate the outcome. As sciences become computational, difficulties concerning data processing associated with knowledge acquisition and dissemination are reduced. The focus on data afforded a quantum leap in many domains, including computation itself. The word complexity became part of the modern scientific discourse as a result of our ability to capture more data, and to associate it with interactions characterized quantitatively. In the process, the notion of complexity itself lost its resolution. This study introduces the undecidable as a criterion for characterizing a particular type of complexity. Defined as G-complexity, it allows for the understanding of questions pertinent to knowledge about the world, in particular, the living. With decidability as a well-defined criterion for complexity, we provide a context for understanding how experimental evidence-the hallmark of science in our days-can be accumulated, and what the characteristics of scientific work are at this juncture in the development of science.