MSE enables exploring a wider set of questions than traditional stock assessments and facilitates agreeing on management procedures that are robust to a wider range of uncertainties than previous management regimes, in commercial or industrial fisheries.

MSE approaches necessitate resolution of a variety of scientific disputes, which itself can be a benefit. It can show that some of the uncertainties that have been considered important are in fact unlikely to have impacts on management objectives, thus lessening conflicts and resolving differences in beliefs.

Other philosophical questions remain open. How to decide on the plausibility of operating models is still an active area of research. Should operating models have predictive powers? How should they be validated and how often? When can we say that MPs have been sufficiently tested and who gets to say it?

How can we deal with the barriers to participation presented by the technical nature of the MSE approach? Open source approaches to sharing the code are helpful but do not empower key stakeholders to critically engage with the process. Reproducibility is an issue even for other modellers; results are rarely run by more than one team.

While helpful in resolving some disagreements, MSE rarely addresses questions of equity. Harvest control rules that are evaluated within MSE usually say little or nothing about how the total catch should be allocated among different users of the resource. However, there have been examples where MSE was explicitly designed to tackle these issues.

The socio-economic benefits of MSE are not guaranteed but depend strongly on how the MSE process is set up, especially, on its transparency, inclusiveness, and effort to improve communication.