Data scientists often set out to make a positive impact—generating insights upon which organizations can make decisions. A key aspect of that work is ensuring that data is being collected, managed, and analyzed ethically. But as conversations about ethical data science increase, so do questions about how ethics in data science looks in practice: When do you do an ethics check? And what do you do if something seems off?

Join us for this Case Study with DataKind’s Afua Bruce and Rachel Wells to hear what happened when their team faced an ethical challenge during a project that used social media data. While wrapping up the project, the team found out that they didn’t have full information on how the data was obtained. Faced with the decision about whether to deliver the project to the partner when the data trail was incomplete, DataKind reviewed the data source’s use policies, unpacked the trade-offs of different approaches, and carefully communicated with all stakeholders to eventually terminate the project. Afua and Rachel take you through the decision-making process, trade-offs, outcomes, and lessons learned from this project experience; highlight the importance of a data trail and evaluating where all data sources come from; and explain how to walk back a data science solution and project when ethical issues arise.

Recorded on January 25, 2022. See the original event page for resources for further learning or watch recordings of other past events.

O'Reilly Case Studies explore how organizations have overcome common challenges in business and technology through a series of one-hour interactive events. You’ll engage in a live conversation with experts, sharing your questions and challenges while hearing their unique perspectives, insights, and lessons learned.