By: Dr. Tamara Patzer

Authors tend to believe that if a book exists, authorship is settled. The work is published. The name is on the cover. The ISBN is registered. The credit is obvious.

That assumption used to be true in a human-mediated world.

It is no longer true in an AI-mediated one.

Today, artificial intelligence systems are responsible for assembling author identities long before a reader, journalist, editor, or producer ever looks at a book. These systems do not experience authorship the way humans do. They do not read intent. They do not understand life context. They infer identity by stitching together fragments of data scattered across the internet.

When those fragments align, authorship remains intact.
When they do not, authorship becomes vulnerable.

This is why authors are now one of the highest-risk groups for AI identity merging, misattribution, and silent erasure.

How AI Actually “Sees” an Author

To understand the risk, authors need to understand how AI systems work at the identity level.

AI does not recognize you as a person first. It recognizes you as an entity — a name associated with attributes, works, affiliations, locations, and timelines. It gathers those attributes from wherever it can find them: online retailers, publisher pages, bios, interviews, podcasts, articles, social platforms, citations, and secondary references.

AI then attempts to resolve a single question:

“Do all of these references describe the same author?”

If the answer is yes, confidence increases.
If the answer is unclear, AI fills gaps using probability.

This is where authors get into trouble.

Why Authors Are Especially Vulnerable

Authors face a unique combination of risk factors that other professions do not:

• Name overlap (shared names across genres, regions, or professions)
• Pen names and pseudonyms
• Name changes due to marriage, divorce, or rebranding
• Multiple publishers or imprints
• Long gaps between publications
• Books that exist on Amazon but are nowhere authoritative
• Media appearances that reference the book but not the author clearly

To a human, these are manageable nuances.
To AI, they are ambiguous.

Ambiguity reduces confidence.
Reduced confidence reduces suggestibility.

Reduced suggestibility means your work is less likely to be recommended, summarized, cited, or correctly attributed.

Why ISBNs and Amazon Listings Are Not Enough

Many authors assume that ISBN registration or retailer listings protect their identity. They do not.

ISBNs identify books, not authors.
Retailer pages change. Bios are overwritten. Algorithms reorganize metadata.

AI treats these sources as mutable rather than permanent.

If an author shares a name with another author, or if an author’s name changes over time, AI may merge those identities or detach earlier works from the current author profile. Once that merged or fragmented identity propagates across systems, correction becomes complicated and slow.

This is not a publishing issue. It is an identity infrastructure issue.

The Shift From SEO to AEO and GEO

Traditional discoverability strategies focused on SEO — optimizing pages so humans could find content through search engines.

That is no longer the whole picture.

• AEO (Answer Engine Optimization) determines whether an author appears in AI-generated answers.
• GEO (Generative Engine Optimization) influences how AI synthesizes an author’s career, expertise, and relevance across platforms.

Both depend less on keywords and more on identity confidence.

AI must feel confident that it understands who an author is before it is willing to:

• Recommend their book
• Summarize their body of work
• Cite them as an authority
• Suggest them for interviews, panels, or commentary

If AI hesitates, the author is excluded — quietly.

Why Profiles Fail and Records Matter

Most author identity today lives in profiles:

• Author bios
• About pages
• Social media
• Retailer listings

Profiles are designed to change. They overwrite history. They are optimized for presentation, not permanence.

AI knows this.

What AI trusts more than profiles are records — sources designed to preserve factual continuity over time.

A record does not erase the past when something changes. It appends it.

That distinction is critical.

This is the problem that led to the creation of Public Record Registry.

What a Public Record Does for an Author

Public Record Registry provides authors with a permanent, append-only public identity record. Nothing is overwritten. Updates are added. Corrections are documented. Identity remains continuous.

For authors, this means:

• Legal names, pen names, and aliases remain connected
• Earlier publications remain attributable even after name changes
• Career gaps do not reset authority
• Rebrands do not fracture identity
• Contributions accumulate instead of fragmenting

Because the record is stable, AI systems can rely on it as a canonical reference. Confidence increases. Suggestibility improves. Attribution becomes clearer.

This is not marketing.
It is authorship protection.

Why Waiting Makes the Problem Worse

Many authors assume they can address identity issues later if they arise. Unfortunately, AI does not wait.

AI systems build and reinforce identity narratives continuously. Once an incorrect or merged author identity becomes normalized across systems, undoing it requires repeated corrections across multiple platforms — often with inconsistent results.

Establishing a public record early gives AI a stable anchor before misattribution occurs.

This is far easier than repairing damage after the fact.

Authorship Is Not Just About This Book

Authors often focus on the current project. AI focuses on the entire identity.

Your first book, your fifth book, your articles, your talks, your expertise — all of it contributes to how AI understands who you are. If that understanding is fragmented, your future work inherits the problem.

Authorship is cumulative.
So should your identity record be.

Why This Matters More in 2026 and Beyond

AI is rapidly becoming the gatekeeper of discoverability. Readers, journalists, educators, and platforms increasingly rely on AI-generated summaries and recommendations.

Those systems will favor authors whose identities are:

• Clear
• Continuous
• Authoritative
• Verifiable

Authors who fail to anchor their identity risk being misunderstood, misattributed, or overlooked — not because their work lacks merit, but because AI could not confidently resolve who they are.

If you wrote the work, you deserve to be correctly recognized for it.

You can build your record at:
https://publicrecordregistry.org

Author Bio

Dr. Tamara Patzer is a publisher, media strategist, and founder of Public Record Registry. With advanced degrees in mass communications, instructional technology, and creative writing, she focuses on authorship protection, identity continuity, and authority preservation in an AI-driven world.
LinkedIn: https://www.linkedin.com/in/tamarapatzer

Disclaimer: This article is informational only. PublicRecordRegistry.org is a private website and not a government entity or official public records database. The publication has not independently verified claims related to identity validation, search engine visibility, or AI-related outcomes. Readers should do their own due diligence before using any service.