How AI Is Secretly Inferring Your Personal Data — and What You Can Do About It
You probably know that companies collect data about you: what you search for, where you shop, which videos you watch. But a less obvious threat is growing. With advances in artificial intelligence, companies no longer need you to tell them your political views, health status, or income. They can infer it — from seemingly harmless scraps of information.
A recent legal analysis from Dykema, covered by Bloomberg Law News, highlights how AI-powered inferred data is becoming a significant privacy concern. Understanding what inferred data is, how it works, and how to limit its reach is increasingly important for anyone who uses digital services.
What happened?
In July 2026, the law firm Dykema published an article titled “AI-Powered Inferred Data Poses New Threats for Consumer Privacy.” The piece, reported on by Bloomberg Law News, explains that artificial intelligence can now piece together highly sensitive personal details from data points that alone seem trivial.
For example, a social media platform might use your “Likes,” check‑in locations, and the time you spend on certain posts to predict your political affiliation, religious beliefs, or health conditions — even if you never share that information directly. This isn’t science fiction. It is already happening.
The term “inferred data” refers to conclusions drawn about a person based on data analysis, rather than information the person voluntarily provides. As AI models become more powerful and widely deployed, the accuracy and scope of these inferences have grown dramatically.
Why it matters
For consumers, the consequences of AI‑powered inference can be subtle at first but accumulate into real risks.
- Price discrimination. An airline or hotel website might infer that you are a business traveler with a higher willingness to pay and show you different prices than a casual tourist.
- Insurance and credit decisions. Insurers could use inferred health or lifestyle data to adjust premiums, even if you have never disclosed a medical condition. Credit scoring models already incorporate inferred behavioral patterns.
- Targeted scams and manipulation. Malicious actors can infer vulnerabilities — such as financial stress, recent life changes, or political leanings — and craft highly personalized phishing messages or misinformation campaigns.
- Erosion of privacy. Even if you carefully guard your own information, you may not control what others or algorithms deduce about you. The FTC and privacy advocates have raised concerns that inferred data often falls outside existing legal protections like GDPR or CCPA, leaving consumers with limited recourse.
The Dykema analysis points out that current privacy laws generally focus on data that consumers knowingly provide. Inferred data, however, is created by the company, which complicates questions of consent and ownership. Until regulators catch up, the burden largely falls on individuals to protect themselves.
What readers can do
You cannot stop all inference, but you can reduce the raw material AI uses to build a profile of you.
Limit what you share publicly. On social media, review your privacy settings and consider making your friends list, likes, and comments visible only to trusted connections. Even a public “like” on a post can feed an inference model.
Audit app permissions. Many mobile apps request access to location, contacts, and microphone. Deny permissions that are not strictly necessary for the app’s core function. For example, a flashlight app does not need your geolocation.
Use privacy‑focused tools. Browser extensions such as uBlock Origin, Privacy Badger, or Ghostery block trackers that collect behavioral data. Search engines like DuckDuckGo do not build profiles of your searches. Consider using a VPN to mask your IP address, though be aware that VPNs are not a silver bullet.
Opt out where possible. Under the California Consumer Privacy Act (CCPA) and similar state laws, you can request that companies delete your data and opt out of the sale or sharing of your personal information. Many companies also offer “do not sell my personal information” links. Use them.
Be skeptical of “free” services. If a service does not charge money, it likely monetizes your data — including inferences drawn from it. Weigh the benefits against the privacy cost.
Check your digital footprint occasionally. Services like Google’s My Activity, Facebook’s Off‑Facebook Activity, or privacy audit tools (e.g., PrivacyCheck) can show you what data these platforms have collected about you.
No single step will make you invisible, but layering these habits makes it harder for AI models to assemble a reliable picture of your private life.
Sources
- Dykema, “AI-Powered Inferred Data Poses New Threats for Consumer Privacy,” July 2026.
- Bloomberg Law News, coverage of the same topic, July 2026.
This article is for informational purposes and does not constitute legal advice. Privacy laws vary by jurisdiction, and the effectiveness of the steps above depends on the specific platforms and services you use.