How AI Uses Your Data to Infer Secrets You Never Shared
You know companies collect your browsing history, purchase records, and location data. But you may not realize they can use that information to infer things you have never explicitly shared — your health status, political leanings, sexual orientation, or even your income bracket — all with increasing accuracy thanks to artificial intelligence.
This isn’t science fiction. It’s happening now, and it raises serious questions about consent, transparency, and the limits of existing privacy laws.
What Is Inferred Data?
Inferred data is any information derived from other data points, rather than directly provided by you. For example, if you visit a pregnancy-related website, a retailer doesn’t have to ask if you are pregnant — it can guess based on your browsing behaviour. That guess is inferred data.
What’s new is the scale and precision of these inferences. Machine learning models can process thousands of small signals — what time you shop, which articles you read, how long you linger on a page — and predict sensitive attributes with unsettling reliability. Research has shown that AI models can infer sexual orientation from Facebook likes, political affiliation from purchase history, and even medical conditions from smartphone keystroke patterns.
Recent Developments That Should Catch Your Attention
Two articles published in early July 2026 highlight growing concern around this issue.
Bloomberg Law News reported on how companies are using AI to infer everything from creditworthiness to health risk, often without consumers’ knowledge or meaningful consent. A companion piece from Dykema, a law firm, stressed that “AI-powered inferred data poses new threats for consumer privacy.” Both pieces point out that existing privacy laws such as GDPR and CCPA were designed for the data you give directly, not for the data computers deduce from it. This regulatory gap leaves consumers with little recourse when companies build detailed profiles using inferences you never authorised.
Why This Matters for Your Privacy
The danger is not abstract. Inferred data can be used to:
- Deny you services. Insurers might infer risky health behaviours from your social media activity and adjust premiums without telling you why. Employers could use inferred personality traits during hiring.
- Manipulate your decisions. Advertisers can infer your emotional state and target ads when you are most vulnerable.
- Create irreversible records. Even if an inference is wrong — say, the model mistakenly tags you as high risk for a disease — you may never know or have a way to correct it.
Because these inferences are protected as “business insights” rather than personal data, you typically have no right to access or delete them. This creates a shadow profile that operates outside your awareness.
What You Can Do Right Now
No single step will completely stop inference — as long as you use digital services, some data will be collected. But you can reduce the risk significantly.
- Limit what you share. Before you fill out a form, ask: does this service really need this information? The less raw data you provide, the less material AI has to work with.
- Use privacy-focused tools. A browser extension like Privacy Badger or uBlock Origin can block trackers that feed inference models. Consider a search engine like DuckDuckGo that doesn’t build profiles.
- Adjust platform settings. On social media, disable ad personalisation and location history. Review app permissions regularly — many apps request data they don’t need.
- Opt out where possible. Under CCPA and similar laws, you can request that companies not sell your data. Some services also let you limit the use of your data for profiling. These opt-outs are often hidden in privacy settings, so you may need to dig.
- Use a VPN. A VPN hides your IP address and makes it harder for companies to connect your online activity to a single identity. It’s not a cure-all, but it adds a layer of separation.
The Bigger Picture
Until laws catch up, tech companies face little penalty for building detailed inferred profiles. Some privacy advocates argue that we need new regulations requiring explicit consent before companies can make high-risk inferences — especially those about health, finances, or protected characteristics. Techniques like differential privacy and data minimisation can limit what models learn from individuals, but adoption remains voluntary.
For now, the best defence is awareness. Understanding that inference is happening — and that it carries real consequences — is the first step toward protecting yourself.
Sources:
- Dykema, “AI-Powered Inferred Data Poses New Threats for Consumer Privacy,” July 2026
- Bloomberg Law News, “AI-Powered Inferred Data Poses New Threats for Consumer Privacy,” July 2026