Differential Privacy in AI: What it is and Why it Matters?
Reading Time: 6 minutes When working with data, there are three approaches to handling privacy. The first is traditional data, which is raw and unaltered, consisting of personally identifiable information that is highly valuable for analysis but extremely vulnerable to breaches. The second one is anonymization, which reduces risk by removing or masking identifiers such as names or IDs; …









