Responsible Data Science by Design

Responsible data science by design guides IDS. 

We educate the next generation of responsible data scientists.

Through community events and an upcoming Master’s track in responsible data science, we aim to make sure that the next generation of data scientists can implement and evaluate the components of responsibility (transparency, privacy/confidentiality, accountability, and social values) in the relevant scope (across actors, digital objects, data science processes, and social impacts).

We help data-driven communities develop and implement a responsibility agenda that is grounded in data science.

There can’t be a one-size-fits-all responsibility agenda across every domain. Rather, communities should be entrusted with developing and implementing responsibility agendas that align with certain principles while matching their needs, goals, and histories. IDS is well-positioned to help, as we have experience with developing and implementing components of responsibility with multiple communities, and we have deep technical expertise in relevant problems. 

IDS was founded by Distinguished Professor Michel Dumontier, who is a co-founder of the FAIR (Findable, Accessible, Interoperable, Re-usable) principles. Our responsibility agenda is rooted in implementing FAIR workflows and disseminating FAIR practices across many domains. Those experiences have proven to us that the future of innovation lies in weaving a responsibility agenda with a technical agenda (not siloing them), and in creating future data scientists who are equally fluent in both agendas.