The promise of Newtonian science to create a universal precise explanation of all phenomena seems to be out-dated. “Cutting through complexity” may kill potential solutions. The complexity of real phenomena should be accepted and at best tamed by appropriate techniques. Complexity, a recent megatrend in the sciences, may effectuate another scientific revolution.

Scientificity is essentially methodology. The use of information technology as methodological instruments in science has been increasing for decades, this raises the question: Does this transform science? This question is the subject of the Special Issue in Minds and Machines “The epistemological significance of methods in computer simulation and machine learning”. We show that there is a technological change in this area that has three methodological and epistemic consequences: methodological opacity, reproducibility issues, and altered forms of justification.