We look for a train schedule, a remedy for an allergy, information about a business assistance device. The reflex is the same: type a few words into a search engine and click on the first result. The problem begins when that first result displays a summary generated by artificial intelligence, without the original source being clearly identifiable.
Finding reliable information online today requires specific reflexes, and sharing it without verification only amplifies the noise.
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AI Summaries from Search Engines: What We Read Is Not Always What the Source Says
Google and Microsoft now place AI-generated summaries above traditional results. Many internet users read this summary and never click on the original link. We get a quick answer, but we lose context, nuances, and sometimes the publication date.
The concrete risk: an AI summary can merge two contradictory sources into a single smooth sentence. On a health or regulatory topic, this is enough to mislead. Systematically tracing back to the source cited under the summary is the only way to verify what we are actually reading.
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In practice, we click on the link, look for the exact passage cited, and check the date. If the summary does not link to any identifiable source, we move on to the next result. This habit takes a few seconds and changes the reliability of everything we share afterward.
Checking the Reliability of an Online Source: Operational Criteria
Rather than a long theoretical grid, we focus on three checks that filter out the majority of dubious content. When we come across an article, a post, or an online document, here’s what we look at first:
- Is the author or organization identified and traceable outside of this page? An article without a signature or accessible legal mention is a warning sign. We check if the author has published elsewhere or if the organization has its own website.
- Is the publication date visible and consistent with the topic being discussed? Information presented as current but dating back several years skews reasoning, especially on regulatory or scientific subjects.
- Are the facts presented verifiable against at least one other independent source? If a figure or claim cannot be found anywhere else, caution is warranted before considering it established.
These three filters do not guarantee absolute truth, but they eliminate a large portion of approximate or misleading content. We save time by applying them in this order, as the first filter (identifying the author) often suffices to rule out the least credible pages.
To go further on this type of approach, the information provided by Passez l’info details an approach focused on verification and responsible sharing of online content.
Verification Labels on Social Media: What They Signal and What They Don’t Say
Facebook and Instagram place labels such as “false info” or “partially false” on certain posts, relying on partnerships with fact-checking organizations like AFP. TikTok has implemented a similar program, redirecting users to verified resources during health crises or election periods.
These tools are useful, but they have concrete limitations. The absence of a label does not mean the information is reliable. Automated verification only covers a fraction of posts, often the most viral ones. A post shared in a small private group almost always escapes this filtering.
The other blind spot concerns speed. False content can circulate for hours before a label appears. During this time, it has already been shared, captured in images, and republished on other platforms without the original label.
How We Manage This Daily
We do not rely on the absence of a label to decide whether to share. We apply the same checks as on a traditional website: identified author, visible date, verifiable fact. On social media, we add an additional reflex: check if a recognized media outlet has picked up the info. If the answer is no after two minutes of searching, we do not share.
Sharing Information Online Without Spreading Errors
Verification is one thing. Sharing is another, and this is often where the problem arises. We may have verified content but share it with a comment that distorts its meaning or takes it out of its original context.
A common example: we share a news article by adding a truncated excerpt as a caption. The chosen passage, isolated from the rest, gives a different impression than what the full article says. Sharing the full link rather than a cropped screenshot significantly reduces this risk.
- Before sharing, read the entire article or document, not just the title or the lead. Titles are designed to grab attention, not to faithfully summarize the content.
- If we add a personal comment, clearly distinguish what is a reported fact and what is our interpretation.
- Check that the shared link works and points to the original page. Broken URLs or those redirected to modified pages circulate frequently.
The Case of Old Content Resurfacing
Social media do not always display the publication date visibly. An article from several years ago can reappear in a news feed as if it had just been published. Sharing outdated content on a regulatory or health topic means spreading potentially obsolete information. Checking the date before each share remains the simplest and most effective reflex.
The reliability of online information does not solely depend on platforms or algorithms. It relies on the actions of each person who reads, verifies, and decides to relay content. Three filters, a few seconds of verification, and the choice not to share when in doubt are enough to break the chain of misinformation at the most accessible link: ours.