Serious Privacy
For those who are interested in the hottest field in a technology world. Whether you are a professional who wants to learn more about privacy, data protection, or cybersecurity law or someone who just finds this fascinating, we have topics for you from data management to cybersecurity to social justice and data ethics and AI. In-depth information on serious privacy topics.
This podcast, hosted by Dr. K Royal and Paul Breitbarth, features open, unscripted discussions with global privacy professionals (those kitchen table or back porch conversations) where you hear the opinions and thoughts of those who are on the front lines working on the newest issues in handling personal data. Real information on your schedule - because the world needs serious privacy.
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Serious Privacy
Data Science and Privacy - sugarcoated or straight up? It Depends (with Katharine Jarmul of Cape Privacy)
Privacy and data protection are not just a job for lawyers or professionals who specialize in privacy - not anymore. Technology plays an important role in ensuring personal data can remain private. Ensuring that personal data is secure but useful requires a level of skill found in data scientists.
In this episode of Serious Privacy, Paul Breitbarth and K Royal searched for just such a skilled individual,Katharine Jarmul, the Head of Product at Cape Privacy, and a data scientist. Cape Privacy is a New York-based company assisting others with machine learning, data security and adding value to data. Katharine explains what data science actually is, how to keep data private, useful and valuable at the same time, and how to create synthetic data appropriately. Also a big question when it comes to powerful technology revolves around the ethics and the investment of individual technologists in the ethics of privacy.
Join us as we discuss these topics and more, such as GPT-3, “this person does not exist,” the work of Cynthia Dwork, and differential privacy vs the generative model. As often happens in an episode, certain topics in privacy are revisited, mainly because they are wicked problems with no identified solution. One such topic Katharine discussed is bias in machine learning and approaches to solving bias once identified. Throughout this episode, we reference quite a few resources that we will provide the links - as always.
Resources
- IAPP article on AI and synthetic data: https://iapp.org/news/a/accelerating-ai-with-synthetic-data/
- Federated / Collaborative Learning Introduction: https://federated.withgoogle.com/
- Encrypted Learning with TF-Encrypted (also can be used in a collaborative setting where we are sharing data): https://medium.com/dropoutlabs/encrypted-deep-learning-training-and-predictions-with-tf-encrypted-keras-557193284f44
- Europe - Ethics guidelines for trustworthy AI https://ec.europa.eu/futurium/en/ai-alliance-consultation
Social Media
Twitter: @privacypodcast, @EuroPaulB, @heartofprivacy, @trustarc, @kjam, @capeprivacy
Instagram @seriousprivacy
If you have comments or questions, find us on LinkedIn and IG @seriousprivacy @podcastprivacy @euroPaulB @heartofprivacy and email podcast@seriousprivacy.eu. Rate and Review us!
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