Democratizing Methods

The past few decades have seen an explosion in the development of freely available software to implement statistical methods and algorithms to help explore and analyze data. However, researchers tend to assume that releasing software packages implementing specific methods is sufficient for ensuring that the tools are adopted and used correctly. Typically, very little attention is paid to the user experience. This in turn means that the tools do not get used, are used incorrectly, or the results are misinterpreted.

This talk will present a case study for how software development could be different by describing a causal analysis tool that scaffolds the user experience. I will discuss lessons learned through user studies and experimental evidence. I conclude with calls to action for those that develop methods and software.