How Privacy Tech Can Make AI Safer for You: What the GAO Report Means

We are quickly reaching a point where AI-driven tools are part of everyday life—chatbots, smart assistants, recommendation engines, and image generators. But the convenience often comes with a hidden cost: your personal data. Every prompt you type, every photo you upload, and every search you run can be collected, stored, and sometimes reused to train the next model.

A recent report from the U.S. Government Accountability Office (GAO) addresses this tension head-on. Published in May 2026, the report suggests that privacy-enhancing technologies (PETs) may be the key to unlocking safer AI adoption—especially for government agencies, but with implications for all of us.

What Happened

The GAO reviewed how federal agencies are using AI and where privacy risks are most acute. Their central finding: current data protection practices are often insufficient. However, the report highlights a set of tools called PETs that can reduce these risks while still allowing AI systems to function effectively. The GAO specifically recommends that agencies prioritize implementing PETs, such as differential privacy and federated learning, as part of their AI governance frameworks.

This is not a hypothetical exercise. Some of these technologies are already in use by major tech companies. The GAO report is notable because it pushes for broader adoption at the government level, which could set standards for the private sector as well.

Why It Matters for You

Even if you never interact directly with a government AI system, you almost certainly use commercial products that rely on similar data-hungry models. Popular chatbots like ChatGPT, smart assistants like Alexa or Google Assistant, and even fitness apps that suggest workouts based on your history all process personal information. Without strong privacy protections, that data can leak, be sold, or be used in ways you never agreed to.

PETs work by altering how data is collected, stored, or analyzed so that the AI can still learn—but without exposing your private details. Here is a quick walkthrough of the most common ones mentioned in the GAO report:

  • Differential privacy: Adds a small amount of “noise” to data before it is used. The overall model remains accurate, but it becomes nearly impossible to identify any single person’s information. Apple and Google use this in their operating systems for things like predictive text and traffic data.
  • Federated learning: Instead of sending your data to a central server, the AI model is updated directly on your device. Only the model updates (not your data) are sent back. This is why your phone’s keyboard can learn your typing habits without uploading everything you type.
  • Homomorphic encryption: Allows computation on encrypted data without ever decrypting it. The AI can process your information while you keep the keys. It is computationally heavy but offers a very high level of protection.
  • Synthetic data: Replace real data with artificial records that mirror the statistical patterns of the original dataset. The AI learns from synthetic data, and the real personal data never leaves the vault.

The GAO report stresses that no single PET is a silver bullet. Each tool has trade-offs between privacy, accuracy, speed, and cost. But used together or in appropriate contexts, they can meaningfully reduce the risk of data breaches, misuse, and re-identification.

What You as a Consumer Can Do

You do not need to become a cryptographer to benefit from PETs. Here are practical steps to protect your privacy when using AI tools:

  1. Choose services that advertise privacy protections. Look for terms like “differential privacy,” “federated learning,” or “on-device processing” in privacy policies or product pages. For example, Apple’s AI features often mention differential privacy, and Google’s Gboard uses federated learning.
  2. Ask questions. If you are considering a new AI-powered app, email support or check their documentation. Ask: “Do you collect raw user data for training? Do you use any privacy-enhancing technologies?” If they cannot answer clearly, treat that as a red flag.
  3. Turn off data sharing when possible. Many AI tools allow you to opt out of using your data for model improvement. It may mean slower or less personalized results, but it protects your privacy.
  4. Be cautious with sensitive information. Even if a service uses PETs, avoid entering personally identifiable details (full name, address, financial info) into public chatbots or AI assistants unless you are sure of their data handling.
  5. Watch for certifications or standards. As the GAO pushes agencies to adopt PETs, expect private companies to follow. Future labels like “GAO-recommended privacy practices” or third-party audits could become trust signals. Keep an eye out.

The GAO report is not a consumer guide, but its recommendations for agencies set a benchmark. If the federal government is taking PETs seriously, you can expect—and demand—the same from the apps and devices you use every day.

Sources

  • MeriTalk, “GAO: Privacy Tech Could Be Key to Safer AI Adoption,” May 20, 2026. (Primary news report)
  • U.S. Government Accountability Office, “Privacy-Enhancing Technologies: Key to Safer AI Adoption,” May 2026. (Please verify exact title and publication details.)

Note: This draft is based on news coverage of the GAO report. For the most accurate and complete information, consult the report directly.