Data lies at the heart of almost all of our digital experiences. It's also a key area where things can start to go wrong. Data about people can cause harm in many ways, with outcomes ranging from biased machine-learning algorithms to breaches of privacy.
How might we prioritise fairness, transparency and privacy when working with data? One key tool is Data Sheets, a way of documenting datasets that encourages careful reflection on the process of creating, distributing, and maintaining a dataset. We will also explore other documentation tools that have been inspired by Data Sheets, including System Cards (used to document a wider machine learning service).
In this video, we're going to cover:
These resources were shared during the video lesson.
Upgrade your newsfeeds! Follow some of the people who inspired this chapter:
These tools can help you apply this lesson in real-world projects.
Private notes
A place for you to post notes about anything on this page. Only you can view your notes.