Data Privacy
Explore the key risks associated with data privacy in machine learning pipelines including data breaches, reidentification, and predatory advertising. Learn why protecting personal data is crucial, understand legal frameworks like GDPR, and discover how vulnerabilities in data collection can lead to targeted attacks and privacy loss. This lesson equips you to identify and mitigate data privacy issues that threaten ML pipeline reliability and user security.
Data is very revealing when it’s collected on a mass scale, as it is today. Many will be familiar with data breaches or leaks where personally identifiable information (PII) is hacked, leaked, or stolen from databases and either kept for a ransom or published on the internet. The gravity of situations like this is why global governments charge such a high fee for violation of data privacy laws. In Europe, the General Data Protection Regulation (GDPR) is of the utmost importance for any company handling potentially sensitive data. Clearly, data privacy is important, but why should we be concerned with it?
Motivation
There are many risks to holding private data. Let’s discuss some of these risks and the consequences that may result from them.