Privacy in the Age of AI: What Tech Experts Recommend Buying Intro If you’ve felt a creeping unease about how often your phone seems to listen, or how eerily accurate the ads are after a casual conversation, you’re not alone. AI-powered tools are now woven into everything from photo management to customer service, and with that convenience comes a steady erosion of privacy. ...
New MIT Technique Lets You Train AI on Your Phone Without Sharing Your Data Most people who use a smartphone have interacted with some form of AI — photo editing tools that recognize faces, keyboards that predict your next word, or fitness apps that learn your habits. These features usually work by sending your data to servers in the cloud, where the AI model is trained and improved. That convenience comes with a trade-off: your personal messages, photos, and usage patterns leave your device and end up on someone else’s computer. ...
What the Latest Federated AI Research Means for Your Privacy If you use a smartphone with predictive text, voice typing, or a fitness tracker that learns your habits, you are already relying on a type of artificial intelligence called federated learning. The big selling point has always been privacy: your data stays on your device, and only anonymous model updates are sent to the cloud. But recent research has shown that those updates can sometimes be reverse-engineered, leaking parts of your personal information. New work from Oak Ridge National Laboratory (ORNL) aims to close that gap. ...
Your AI Assistant Is Watching: How to Protect Your Privacy Now Open up ChatGPT, ask Google Assistant about the weather, or let an email app draft a reply for you. These tools feel harmless, even helpful. But behind the convenience, a growing amount of your personal information is being collected, stored, and used in ways you may not have agreed to. ...
Why You Need a Records Retention Plan Before Building Anything with AI Introduction Every week brings news of another organization rushing to deploy AI tools—feeding customer data, internal emails, or years of transaction logs into large language models. The promise is real, but so is the risk. Among the many pieces of advice circulating in privacy circles, one principle is quietly gaining traction: get your records retention practices right before you touch AI. The International Association of Privacy Professionals (IAPP) recently published guidance framing retention policies as a prerequisite for responsible AI use, and it’s a message worth taking seriously. ...
Before You Let AI Loose on Your Data, Get Your Records Retention in Order Adopting AI tools that process personal data is rarely a simple plug-and-play decision. Many organizations focus on model accuracy, training data, or integration challenges. But a foundational step often gets overlooked: updating records retention policies. Without a solid retention framework, AI deployments can lead to compliance failures, privacy violations, and regulatory penalties. Recent guidance from the International Association of Privacy Professionals (IAPP) underscores this point—records retention should be a prerequisite, not an afterthought. ...
Title: Here’s How to Organize Your Digital Records Before Using AI Intro: If you’re about to start using a new AI tool—whether it’s a chatbot, document summarizer, or image generator—you might want to pause and do some housekeeping first. AI tools often process data you feed them, and that data can include sensitive or outdated information you’d rather not expose. The practice of managing what you keep and what you delete, known as records retention, is becoming more relevant for everyday users, not just corporate compliance teams. ...
Clean Up Your Digital Files Before Using AI: A Privacy Guide for Everyday Users Over the past year, AI tools like ChatGPT, Microsoft Copilot, and Google Gemini have become part of daily life for many people. They help with writing, brainstorming, and even organizing schedules. But there’s a catch that often gets overlooked: these tools can ingest whatever you feed them, including old emails, personal documents, and chat logs that you no longer need. A recent article from the International Association of Privacy Professionals (IAPP) highlights why records retention—deciding what to keep and what to delete—is a critical first step before adopting AI. The same logic applies to individuals, not just organizations. If you’re planning to use AI more seriously for work or personal tasks, now is a good time to clean house. ...
What Records Should You Keep Before Using AI? A Privacy Guide If you’ve used a chatbot to draft an email, an AI assistant to summarize a document, or a generative tool to generate an image, you’ve left a data trail. Every prompt you type, every output you save, and every setting you adjust can be stored by the service—and sometimes used for training or shared with third parties. Most people are not aware of how much of their personal information accumulates inside these tools, or what they can do to manage it. ...
Don’t Tell Your AI Chatbot These 5 Things to Keep Your Money Safe AI chatbots like ChatGPT, Google Gemini, and Microsoft Copilot have become part of daily life for millions of people. They help draft emails, summarize articles, and answer questions. But their convenience hides a real financial risk: every piece of information you type into a chatbot could be stored, shared, or used against you. A recent column in The Washington Post highlighted five specific things you should never share with an AI chatbot if you want to keep your money safe. Here’s what you need to know. ...