Want to Use AI Safely? A New Government Report Points to Privacy Tech That Helps

Every time you ask a chatbot a question or use an AI image generator, your data goes somewhere. Often it’s processed on a company’s servers, and sometimes it’s stored or used to train the next model. For consumers concerned about where that information ends up, a new report from the U.S. Government Accountability Office (GAO) offers some reassurance—and a roadmap.

The report, published in May 2026, examines how privacy-enhancing technologies (PETs) can make AI adoption safer without slowing innovation. The GAO isn’t a tech company with a product to sell; it’s a nonpartisan federal agency that audits and evaluates programs for Congress. When it weighs in on privacy tech, it’s worth paying attention.

What Happened

The GAO concluded that several privacy technologies are ready for wider use in consumer AI. These include differential privacy (adding noise to data so individuals can’t be identified), federated learning (training models across devices without moving raw data to a central server), on-device processing (keeping computations on your phone or laptop), and synthetic data generation (creating artificial data sets that mimic real patterns but don’t contain personal information).

The report’s key message: these tools already exist and are being adopted, but they aren’t yet standard across all AI services. If used consistently, they could reduce the risks of data breaches, unauthorized surveillance, and unintended exposure of personal details.

Why It Matters for Consumers

Most people using AI tools today don’t know what happens to their inputs. A chat about a health issue, a draft of a work email, or a photo used to generate a new image—all of these become part of the service’s data stream. Without PETs, that data can be stored indefinitely, sold to third parties, or leaked in a breach.

Here’s how each technology helps you:

  • Differential privacy ensures that even if someone gains access to a data set, they can’t tell which records belong to you. Companies like Apple use it in their products.
  • Federated learning means a model can improve by learning from your device’s data without ever sending that data to a cloud server. Your phone learns, but the company doesn’t see your information.
  • On-device processing keeps the entire AI operation local. Google’s on-device AI, for instance, can complete tasks like transcription or photo editing without an internet connection—your data never leaves your device.
  • Synthetic data can be used to train models so the real data never enters the training pipeline.

The GAO acknowledged that no single technology is a complete fix, and some come with trade-offs like reduced accuracy. But the report emphasizes that even partial adoption is far better than none.

What You Can Do Right Now

You don’t have to wait for the industry to catch up. Here are concrete steps you can take today to ensure the AI services you use respect your privacy:

  • Check the privacy policy. Look for mentions of “differential privacy,” “on-device processing,” or “federated learning.” If a company doesn’t explain how it handles your data in plain language, that’s a red flag.
  • Prefer services that process locally. Apple Intelligence and Google’s on-device AI features are good examples. When possible, use apps that work offline for sensitive tasks.
  • Opt out of data training. Many AI services let you disable the use of your conversations for model improvement. Find that setting and switch it off.
  • Ask before you trust. Before signing up for a new AI tool, ask: “Do you use privacy-enhancing technologies?” If the answer is vague or defensive, consider an alternative.
  • Limit what you share. Even with PETs, avoid inputting highly sensitive personal information—like Social Security numbers, medical records, or passwords—into any AI service.

Sources

  • “Privacy Tech Could Be Key to Safer AI Adoption,” MeriTalk, May 20, 2026. (Based on GAO report)
  • U.S. Government Accountability Office (GAO) — nonpartisan congressional watchdog agency. Report on privacy-enhancing technologies released May 2026.