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Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Data Science and Privacy - sugarcoated or straight up? It Depends (with Katharine Jarmul of Cape Privacy)

46:51
 
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Manage episode 277104221 series 2681731
Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

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!
Proudly sponsored by TrustArc. Learn more about NymityAI at https://trustarc.com/nymityai-beta/
#heartofprivacy #europaulb #seriousprivacy #privacy #dataprotection #cybersecuritylaw #CPO #DPO #CISO

  continue reading

195 에피소드

Artwork
icon공유
 
Manage episode 277104221 series 2681731
Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Paul Breitbarth and Dr. K Royal, Paul Breitbarth, and Dr. K Royal 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

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!
Proudly sponsored by TrustArc. Learn more about NymityAI at https://trustarc.com/nymityai-beta/
#heartofprivacy #europaulb #seriousprivacy #privacy #dataprotection #cybersecuritylaw #CPO #DPO #CISO

  continue reading

195 에피소드

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