A friendly, non-technical introduction to differential privacy - Ted is writing things

An introduction and table of contents for my beginner-friendly blog post series about differential privacy.

Differential privacy is getting a lot of attention lately. Companies and governments are starting to publish data anonymized with this notion. Universities are offering courses about it. Statisticians are getting acquainted with this new approach to protecting data. Open-source organizations are publishing tooling to make differential privacy easier to use. So, you might be wondering: what's the hype all about? What even is differential privacy? What makes it so special? How does it work in practice? And, perhaps more importantly, can I understand it without having to read a bunch of complicat

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• Shruti Das

related reading

• Why not differential privacy? - Ted is writing thingsdesfontain.es
• Differential Privacy: Issues for Policymakerssimons.berkeley.edu
• Big data may not know your name, but it knows everything elsenews.ycombinator.com
• Yu Weiyuweii.com
• DP-VAE: Human-Readable Text Anonymization for Online Reviews with Differentially Private Variational Autoencodersweb.archive.org
• 1902.06101arxiv.org
• Can a Model Be Differentially Private and Fair?pair.withgoogle.com
• Just know stuff. (Or, how to achieve success in a machine learning PhD.) · Patrick Kidgerkidger.site
• Shredder: Learning Noise Distributions to Protect Inference Privacycseweb.ucsd.edu
• Henry Corrigan-Gibbs Disserationstacks.stanford.edu
• How randomized response can help collect sensitive information responsiblypair.withgoogle.com
• Vitruvia: Advancing Personalized Medicine with a World Model of Human Healthlinkedin.com