At DataKind, we take an expansive definition of data ethics and responsible data science as broad terms that can be used to describe the appropriate handling of data, use and performance of models, inclusion of stakeholders, staffing of teams, and more. Incorporating ethical review and responsible data science practices has been part of DataKind’s approach from the beginning. Still, DataKind is committed to continuous improvement, and we’ve expanded our data ethics practices over the last decade, as we’ve learned and grown.
Last month, we were excited to host a Lunch + Learn for our volunteer community on ethics in the DataKind Playbook. The DataKind Playbook is a volunteer co-created, globally-accessible, living knowledge base that’s your go-to resource for DataKind projects. With over 100 attendees, our Center for Excellence provided resources from the DataKind Playbook to share best practices for approaching Data Science and AI for Good projects with an ethics lens.
Want to learn more about DataKind’s ethical practices and the DataKind Playbook? Look no further!
Check out the Lunch + Learn recording below.
Looking for more about the DataKind Playbook? Interested in getting involved? The best way is to visit playbook.datakind.org and start exploring! Share any feedback and ideas you have for us directly in the Playbook.
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As always, thank you for your support of this critical work!
- Our Ethics + Responsible Data Science Practices at DataKind
- Introducing DataKind’s Playbook
- Co-Creating to Codifying Processes Across a Global Network of Volunteers: How We Built DataKind’s Playbook
- DataKind UK’s Practitioner’s Guide to Data Ethics Toolkits
- DataKind’s Playbook
- DataKind’s Center of Excellence