I think it's a good question. In terms of meaningful collaboration across the sector, I would say that right now we have science policies that I think would support doing that, such as the open science initiative. For instance, if there's a federal goal towards AI innovation, we need robust research data management. We have a policy being rolled out in that respect to get data management plans done at the front end of research so that at the back end of research we can have data to share and to be leveraged and innovated upon. We have the policy and we have the vision, but we don't have the incentives and rewards for researchers to actually do that.
For example, at my institution and others across this country, researchers don't have the skills and the practical knowledge to get consent, to de-identify their data and to prepare it for that mission-driven goal of AI innovation. I think that because we don't have those skills, as researchers we need to upskill. To do that, we need to know that we can focus on getting those skills and getting that training, and that it will be valued. It's not just about producing more; it's pausing and taking time to upskill ourselves so that we can get our data into a position for lending toward collaborations beyond our single use of how we envision that data to be used.