privacy

Social media is an ant mill (Internet is a disaster) (Ep. 303)

Internet followed nature. Until it didn't. And became the disaster we know.
 
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About Apple's Privacy (Ep. 302)

Paragon's spyware hacked fully updated iPhones without a single click. Apple just spent $2B on tech that reads your silent speech. And your iCloud? Governments can request it with paperwork. This is what the privacy brand actually buys you.
 
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NEW TO DATA SCIENCE AT HOME?
Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions.
Learn more at https://datascienceathome.com
 
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We love hearing from you!
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Don’t forget to like, subscribe, and hit the 🔔 for updates on the latest in AI and data science!
 

Is neural hash by Apple violating our privacy? (Ep. 173)

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Can I get paid for my data? With Mike Andi from Mytiki (Ep. 150)

Your data is worth thousands a year. Why aren’t you getting your fair share? There is a company that has a mission: they want you to take back control and get paid for your data.
In this episode I speak about knowledge graphs, data confidentiality and privacy with Mike Audi, CEO of MyTiki.
 
 
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You are the product [RB] (Ep. 147)

In this episode I am with George Hosu from Cerebralab
and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not.
 
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This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience
 
If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.
 
Links
https://cerebralab.com
https://www.eugenewei.com/blog/2019/2/19/status-as-a-service

You are the product (Ep. 140)

In this episode I am with George Hosu from Cerebralab
and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not.
 
Our Sponsors
This episode is supported by Chapman’s Schmid College of Science and Technology, where master’s and PhD students join in cutting-edge research as they prepare to take the next big leap in their professional journey.To learn more about the innovative tools and collaborative approach that distinguish the Chapman program in Computational and Data Sciences, visit chapman.edu/datascience
 
If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.
 
Links
https://cerebralab.com
https://www.eugenewei.com/blog/2019/2/19/status-as-a-service

Let's talk about federated learning (Ep. 122)

Let's talk about federated learning. Why is it important? Why large organizations are not ready yet?
 
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This episode is supported by Monday.com
The Monday Apps Challenge is bringing developers around the world together to compete in order to build apps that can improve the way teams work together on monday.com.
 

Why you care about homomorphic encryption (Ep. 116)

After deep learning, a new entry is about ready to go on stage. The usual journalists are warming up their keyboards for blogs, news feeds, tweets, in one word, hype.This time it's all about privacy and data confidentiality. The new words, homomorphic encryption.
 
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This episode is supported by Amethix Technologies.
Amethix works to create and maximize the impact of the world’s leading corporations, startups, and nonprofits, so they can create a better future for everyone they serve. They are a consulting firm focused on data science, machine learning, and artificial intelligence.
 
References
Towards a Homomorphic Machine Learning Big Data Pipeline for the Financial Services Sector
IBM Fully Homomorphic Encryption Toolkit for Linux

Pandemics and the risks of collecting data (Ep. 103)

Codiv-19 is an emergency. True. Let's just not prepare for another emergency about privacy violation when this one is over.
 
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WARNING!! Neural networks can memorize secrets (ep. 100)

One of the best features of neural networks and machine learning models is to memorize patterns from training data and apply those to unseen observations. That's where the magic is. However, there are scenarios in which the same machine learning models learn patterns so well such that they can disclose some of the data they have been trained on. This phenomenon goes under the name of unintended memorization and it is extremely dangerous.
Think about a language generator that discloses the passwords, the credit card numbers and the social security numbers of the records it has been trained on. Or more generally, think about a synthetic data generator that can disclose the training data it is trying to protect. 
In this episode I explain why unintended memorization is a real problem in machine learning. Except for differentially private training there is no other way to mitigate such a problem in realistic conditions.At Pryml we are very aware of this. Which is why we have been developing a synthetic data generation technology that is not affected by such an issue.
 
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References
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networkshttps://www.usenix.org/conference/usenixsecurity19/presentation/carlini