Data Science Ethics - What Could Go Wrong and How to Avoid It 

Data science models are all around you.
They could impact your admission to a school, whether you get hired (or fired), your work schedule, whom you date, whether you get a loan, what ads are shown to you, what social media posts you see, and so on.
In this video, Kylie Ying talks to us about ethics in Data Science. She talks us through what exactly makes something 'ethical', and applies that to some great cases from Facebook, OKCupid and others. We will also cover ethics around data collection, data manipulation and ownership of the data around you, as well as ethics surrounding algorithms. Some topics discussed include informed consent, privacy, and FAT* (Fairness, Accountability, Transparency).
This content is adapted from OpenDS4All. OpenDS4All is a project created to accelerate the creation of data science curricula at academic institutions: github.com/odpi/OpenDS4All/tr...
Some resources for further discussion:
- www.quantamagazine.org/making...
- www.nature.com/articles/sdata...
Presenter: Kylie Ying
Thank you to @KylieYYing for creating this video for the freeCodeCamp Community!
Subscribe to @KylieYYing channel here: / ycubed

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