In the modern age, searching the internet yields millions of answers in milliseconds. We even have Artificial Intelligence assembling words to answer our questions directly. But as astrophysicist and science communicator Neil deGrasse Tyson asks: How do you know what to trust?
Information algorithms and Large Language Models don't inherently "think"—they optimize for engagement or assemble words based on statistical probability. When you search for the truth, you need a personal filtering mechanism. Tyson proposes a system of Flags. Let's build that filter together.
1. The Domain Baseline
When you are looking for objective, verifiable truth, the source matters. Where is the information hosted? The URL itself is your first clue.
Try typing a website domain below to see how the filter reacts to its origin.
.edu or .gov generally have rigorous institutional oversight, peer review, or legal accountability. You are highly likely to find correct, objective information here..com, .net, or .org doesn't mean the site is lying! It simply means there is no guaranteed institutional oversight to publish there. You must evaluate the specific claims yourself.2. Vested Interests
If a source isn't an educational or government institution, you must look at the speaker. Are they independent, or do they have a vested financial interest in the outcome of their claims?
Let's look at a hypothetical scenario. A researcher publishes a paper stating that a new commercial compound is completely harmless.
Claim: "Chemical X is perfectly safe."
3. The Context Trap
The internet runs on engagement, and nothing drives engagement like outrage. A common tactic is to lift a snippet of video or text out of its original source and strip away the surrounding context to completely invert its meaning.
You see a viral post on social media claiming a prominent scientist made a terrible admission. Toggle the context below to see how the meaning changes.
4. Crossing into Red Flags: Conspiracies
Yellow flags mean "caution"—pause and verify. But when does a claim cross the line into a Red Flag? A red flag means the methodology behind the claim is fundamentally, irreparably flawed.
In science, when new data contradicts a hypothesis, the scientist changes the hypothesis. But what happens when someone refuses to let their hypothesis go?
Your Hypothesis: The Earth is flat.
The Data: Satellite imagery, orbital physics, and centuries of navigation prove it is a sphere.
How do you resolve this conflict?
5. The Consensus & Cherry-Picking
The frontier of science is messy. Studies are published all the time, and occasionally, an unverified outlier will suggest something completely new. Eventually, repeated testing by independent researchers builds a scientific consensus.
Below are 50 studies on a topic. 49 of them found no link between a standard medical treatment and a specific illness. 1 early, unverified study claimed it found a link.
Click on the data point you want to use to form your worldview.
Conclusion
The goal of these flags is not to make you a cynic who trusts nothing. The goal is to make you an active, critical consumer of information in a world designed to overwhelm you.
When you encounter a new claim, check the domain. Look for vested interests. Ensure it's not taken out of context. And if the claim requires a global conspiracy or ignores overwhelming consensus, raise the red flag and walk away.