Navigating Data Privacy
Learn key strategies for building privacy-first AI, fostering innovation, resilience, and lasting user trust in the latest Privacy by Design: The AI Podcast, What It Takes To Build A Privacy First AI Product. https://youtu.be/d_sMmUBuSdk Ready...
The old tech adage “move fast and break things” is showing its limits in the age of AI. In data-driven application development, rushing without embedding privacy can create a minefield triggering a pendulum swing between...
Three Paths to AI Privacy – Lockdown, Caution to the Wind, or the Smarter Choice What are your real options when launching AI with sensitive data? Most teams run into three choices: lock privacy down...
Key Takeaways Continuous discovery of PHI/PII data transforms healthcare privacy from chaos into clarity. Automated, purpose-driven controls replace manual processes and reduce risk. Precision in protection (masking, tokenization, encryption, redaction) accelerates safe innovation. Automation enables...
The Blind Spots Haven’t Disappeared PII and PHI rarely sit neatly in columns. They leak into emails, tickets, chat logs, free-text notes, forgotten backups, and shadow exports. Even with policies or masking, gaps remain. And...
Podcast Why Data Masking Isn’t Enough in AI Pipelines Data masking looks good on a checklist. It satisfies the “something was done” mentality. But in today’s AI pipelines, masking isn’t real protection. If we want...
Listen to the Podcast Introduction: Clinical Data, AI, and Patient Trust Few industries handle data as sensitive as healthcare data. Patient records, lab results, insurance claims, and clinical notes reveal deeply personal details. Regulations like...
Listen to the Podcast Responsible AI Starts with Trusted Data AI is moving fast. New models launch every week. But if personally identifiable information (PII) or protected health information (PHI) slips into training data, your...