Authority, Trust & Provenance
Building a verifiable author identity online
Why anonymity now costs you
For years, content could rank on keywords and links alone. That era is closing. AI engines assembling an answer face a question humans have always faced: can I trust this source? Their answer increasingly depends on whether they can establish a real, qualified human behind the words. Content that can't be attributed is content that can't be corroborated — and corroboration is the currency of trust.
The three layers of verifiable identity
1. Machine-readable schema
Add Person schema as JSON-LD to your author and about pages. The fields that matter:
name,jobTitle, andworksForknowsAbout— the topics you have genuine expertise insameAs— an array of URLs to authoritative profiles (LinkedIn, professional bodies, a personal site)
The sameAs links are the load-bearing part: they let an engine cross-reference your
identity against sources it already trusts.
2. Consistent attribution
Every article should name its author and link to a single canonical author page. Mixed or missing bylines fragment your identity and weaken the signal. One person, one canonical profile, linked everywhere.
3. A real footprint
Schema points at reality; reality has to be there. A LinkedIn profile with a genuine
history, membership of a relevant professional body, talks, citations, a company that
exists — these are what the sameAs links resolve to. You can't fake your way to a
verifiable identity; you can only make a real one legible.
A worked example
This site practises exactly this. The about page carries full Person schema
for the author, with credentials and a sameAs link to LinkedIn, and every guide is
attributed to the same canonical profile. View the page source and you can read the
machine-readable identity yourself — which is the whole point.
What to do this week
- Write one canonical author page per real author.
- Add
Personschema withsameAslinks to at least two authoritative profiles. - Ensure every article bylines to that canonical page.
- Fill gaps in the real-world footprint those links point to.
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