“People are afraid to engage with uncertainty. They don’t know how to engage with uncertainty. And they worry about the politicization of uncertainty. But we’re hitting a tipping point. By not engaging with uncertainty, statistical imaginaries are increasingly disconnected from statistical practice, which is increasingly undermining statistical practice. And that threatens the ability to do statistical work in the first place. If we want data to matter, the science community must help push past the politicization of data and uncertainty to create a statistical imaginary that can engage the limitations of data.
The statistical imaginary of precise, perfect, and neutral data has been ruptured. There is no way to put the proverbial genie back in the bottle. Nothing good will come from attempting to find a new way to ignore uncertainty, noise, and error. The answer to responsible data use is not to repair an illusion. It’s to constructively envision and project a new statistical imaginary with eyes wide open. And this means that all who care about the future of data need to help ground our statistical imaginary in practice, in tools, and in knowledge. Responsible data science isn’t just about what you do, it’s about what you ensure all who work with data do.”