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Screencap "As a part of careful data collection practices, researchers must adopt frameworks such as [13, 52, 86] to describe the uses for which their models are suited and benchmark evaluations for a variety of conditions. This involves providing thorough documentation on the data used in model building, including the motivations underlying data selection and collection processes. This documentation should reflect and indicate researchers’ goals, values, and motivations in assembling data and creating a given model. It should also make note of potential users and stakeholders, particularly those that stand to be negatively impacted by model errors or misuse. We note that just because a model might have many different applications doesn’t mean that its developers don’t need to consider stakeholders. An exploration of stakeholders for likely use cases can still be informative around potential risks, even when there is no way to guarantee that all use cases can be explored." 2nd-4th sentences highlighted in blue.