PROBABLY PRIVATE

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Past Issues

  • Common AI Product Privacy Mistakes, Masterclasses and Trainings
    In this newsletter, you'll look at some common privacy mistakes organizations make when building AI products or agent workflows. I also announce upcoming masterclasses and trainings that are available for organizations building AI products and talk about why talking about privacy is hard right now.
  • Video Course launch, studying memorization via security and privacy and personalizing your recommendations
    In this issue, you'll learn about how privacy and security research exposed AI memorization before it was a common topic in AI conferences. I also announce my new O'Reilly video course and an open-source library for content curation and personalized recommendations.
  • How does memorization in AI systems happen? What should we do about it?
    In this issue, you'll explore exactly how memorization in AI systems happens, by investigating training data repetition, novel training examples and model overparameterization. You'll also explore some ways that this testing could move into regular AI system development or regulation.
  • Building Private and Personal AI systems, Exploring ML Memorization
    In this issue, you'll explore how today's AI systems parallel early computing and what this could mean for building out more private, more personal AI. In addition, the ML memorization exploration continues by investigating datasets and distributions and encoding and embeddings.
  • Memorization in Machine Learning and Multidisciplinary Practices
    Does memorization in machine learning happen, and if so, how? In this issue, I reveal the initial thoughts on an article series on how, why, when and exactly what happens when deep learning models memorize their training data. In addition, I share some thoughts post-sabbatical on next steps and observations on multidisciplinary settings for privacy work.
  • AI Act, Biden's Executive Order on AI, Data Privacy in der Praxis
    This newsletter covers recent legislation changes, including the EU's AI Act, Data Governance Act, Data Act and Biden's Executive Order on AI. In addition, Practical Data Privacy is being released in German with updated sections on recommended risk analysis for LLMs and how LLMs and other large models memorize their training data.
  • Meta's Mega-GDPR-Fine and Data Sovereignty, Ethical E-Commerce and Empowerment
    This issue covers the 1.2B€/$1.3B fine handed down by European authorities to Meta, as well as why this fine could change the way data flows in our world. I also share my recent experience attending the ethical e-commerce summit, which provided inspiration on how to empower small- and medium-sized businesses to approach sustainability, ethical data use and built-in privacy.
  • ChatGPT & GDPR Showdown, AINow Report and Privacy, Privilege & Fraud
    In this issue, you'll learn about the latest updates between GDPR authorities and ChatGPT — including my own experience sending a deletion request. I'll share some highlights from AINow's newest report on power & Big Tech. Following the UK's pension authority's Tweet featuring non-consensual videos of people being taken into custody for alleged "fraud", I'll present the links between privacy, privilege and fraud detection.
  • All your text are belong to ChatGPT
    In this issue, I dive into known privacy and security problems with ChatGPT, including a recent privacy and security incident, an analysis of potential security problems with ChatGPT plugins and musings on how closed training datasets hide unknown risks and ethical implications.
  • Upcoming O'Reilly Book and Building a Privacy-First Newsletter
    This issue announces my upcoming O'Reilly book Practical Data Privacy and explains how I migrated the newsletter to more privacy-first services with much effort and learnings along the way.
  • Justice, Anti-Discrimination Law and AI
    This issue is about racial justice, policing, profiling, machine learning and anti-discrimination law. Rest in Power George Floyd.
  • Election Disinformation and Privacy
    This issue covers fundamental theories of misinformation and how they intersect with privacy in light of the US 2020 election.
  • GDPR, SurveillanceTech, Browser Tracking
    This issue explores the impact of GDPR two years later, how OSINT and US Startups are intersecting as well as a round-up of good research and reads on browser tracking. Enjoy!
  • Welcome: Privacy Shield, Contact Tracing & Adversarial ML
    Welcome to Probably Private! In this issue, we cover the recent privacy shield ruling, debates on contract tracing and its benefits and weaknesses as well as the legality of adversarial machine learning research.