As AI produces more scientific results, understanding them and finding worthwhile new questions become increasingly valuable.

I propose a two-part approach.

First, autonomous or human-directed AI agents submit their work to a public repository.

Second, the scientific community draws from this pool of results, identifies the important ones and asks the next set of important questions. This work of interpretation, synthesis and question formation should be recognised and rewarded in peer-reviewed academic journals.