Are lessons being learnt from the replication crisis or will the revolution devour its children? Open Q science from the editor's perspective

The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system's inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice, while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.