CONCEPT MODELS
The Problem Model.
The differentiation crisis.
Creators produce work—written, visual, musical. That work passes through a creative process (increasingly involving AI tools) before reaching platforms and distributors. The audience receives it and asks one critical question: "Who made this?"
The problem? Most platforms and content controllers don't care.
They'll distribute whatever performs, regardless of authorship. Meanwhile, audiences fall into categories:
Utilitarian: "I don't care who made it."
Casual: "I kinda care, sometimes..."
Conscientious: "I care a lot. I don't want to be misled or confused about the source."
The question marks between the work and the audience represent the confusion. Without a clear standard, there's no way to know if something is human-made, AI-assisted, or entirely AI-generated.
This is the gap VerifiedHuman fills.
We're not the first to see this problem. But the existing solutions don't work.
1. LEGISLATIVE (Laws & copyrights)
Laws are complex, cumbersome, and widely ignored. They're slow to adapt and ineffective at changing behavior. Copyright exists, but it doesn't dictate human behavior—values do. Legislation can support an ethic, but it can't create one.
2. TECHNOLOGICAL (Encryption & detection)
Encryption only protects existing content. AI continuously generates and iterates on novel content. AI detection tools are not solid and easy to beat. Worse, AI is chasing its own tail—like the movie War Games, it's an endless arms race no one can win.
3. VALUES-BASED (This is us.)
No widely agreed standard existed. Societal value for authenticity was diminishing. Enforcement seemed impossible. Until now.
VerifiedHuman provides the standard, restores the value, and builds enforcement through trust and accountability.
The VerifiedHuman Primary Model. How the standard actually works.
OFFER OF AUTHENTICITY:
Creators (writers, visual artists, musicians) agree to a field-specific standard. They say, "Trust me. I made this."
ACCEPTANCE WITH CONFIDENCE:
The audience sees the VerifiedHuman mark. They know what it means. They can choose to trust the creator based on that commitment. The standard creates a space of trust where creator and audience meet with mutual understanding and appreciation.
WHEN TRUST BREAKS:
If someone thinks a creator violated the standard ("I think they're cheating"), there's a mechanism to address it:
Passive verification:
Via email, phone, Zoom. "We may call you." Trust, but verify.
Active verification (for education and organizations):
Third-party auditors randomly evaluate work samples to verify compliance.
The result: Accountability without surveillance. Trust with integrity. A shared standard that means something because people choose to honor it.
CONCEPT VIDEOS
You really can't tell the difference
0:28 | Micah describes the problem of differentiation between human vs. AI work in media creation.
Establishing essential authorship, creation, and composition
2:13 | Micah discusses why technological encryption and detection (the second common "solutions") fall short.
Trust in the classroom
1:05 | Micah argues for creating a clear space between students and educators, where trust can be established and, if breached, revisited.
Legislation fails
1:33 | Micah discusses why legislation and copyrights (the first common "solutions") are insufficient.
The missing piece–trust
1:28 | Micah talks about the leveraging human trust as the key to addressing the problem.
Leadership Lessons from a Dancing Guy
This is a viral video by Derek Sivers. "Let's watch a movement happen, start to finish, in under 3 minutes..."
We love it because we feel like the dancing guy. VerifiedHuman started because the problem was real and no one else was solving it.
We hope you'll join us, because as Derek says, "When you find a lone nut doing something great, have the guts to be the first one to stand up and join in."
Technology falls short
2:01 | Micah discusses why technological encryption and detection (the second common "solutions") fall short.
Space between creator & audience
0:49 | Micah explains how an agreed standard creates a space of trust between creators and their audience to point back to if trust is broken.
