The Death of "Spot the Deepfake" (And Why Community Trust Is the Only Way Forward)

By Burt Brooks, CEO & Co-Founder of PathAble AI · February 20, 2026

Here's my hot take on AI vetting, safety, and awareness training: It's already outdated.

Being able to distinguish between real and fake sources will become nearly impossible. Teaching people to look for "extra fingers" or "unreadable text" to identify what is real and what is fake? That advice is already becoming obsolete. As the technology evolves, the distinction will become nearly impossible—if not entirely impossible.

Eventually, everything will be, can be, and should be questioned. Trying to learn what "is AI and what is not AI" will become a fool's errand. And when it comes to educating vulnerable populations, it becomes even more vital AND more difficult.

Trust in images, video, and written publications is at an all-time low and will almost entirely disappear. Yet AI's influence will still be ever-present.

This Isn't Only a Media Literacy Problem. It's an Infrastructure Problem.

For disability employment services, it's an existential threat.

People with disabilities are already systematically excluded from many trust networks—employment verification systems, digital identity platforms, professional credentialing processes. As AI erodes institutional trust, those without strong community ties become even more vulnerable to exploitation and isolation.

The stakes aren't abstract. They're about whether someone gets a job, keeps housing, maintains benefits, or can prove their qualifications to a skeptical employer. When a job coach can't verify a participant's documented skills because "everything looks AI-generated," we're not just dealing with technology confusion—we're dealing with barriers to economic survival.

This is why the next generation of support systems must be built on verified human relationships, not just better algorithms.

Community Vetting: The New Standard

However, it's not all doom and gloom. The trust being lost in institutions is being replaced by something potentially more resilient: Community Vetting.

Human-to-human verification is becoming the benchmark for what is "real" and what is "fake." We need to build strong communities that collectively agree on shared facts. Quibbling over what image or writing is "AI or not" will become a waste of time and energy because there will eventually be no reliable way to tell.

We need to stop asking "what" we can trust and start asking "who" we can trust.

Human trust is rising in value while institutional trust is in decline. Being able to distinguish between someone's motives and incentives to blur the lines between fact and fiction is going to be critical.

What This Looks Like in Practice

At PathAble AI, we're building with this reality in mind. We're not creating a surveillance system or a replacement for human judgment. We're building infrastructure that helps job coaches and participants create documented, verified, shared understanding.

When our platform enables a coach and participant to collaboratively track goals, document progress, and maintain transparent communication, we're building the trust substrate that AI-skeptical communities will desperately need. The AI assists—it doesn't replace. It augments the human relationship—it doesn't become the source of truth.

This is what "augment, don't replace" means in an age of universal AI skepticism. The human relationship is the anchor. The technology is the tool that makes that relationship more effective, more scalable, more sustainable.

Establishing Trust Criteria

As we discuss "community inclusion" as a key tenet of disability services, this needs to be part of that discussion. I challenge us all to establish criteria on what makes a person or group of people trustworthy. Here's a starting framework:

These criteria aren't about perfect judgment—they're about building systems where trust can be earned, maintained, and repaired.

The Call to Action

For disability employment agencies, funders, and policymakers, the implications are clear:

Stop investing in "AI detection" training. Start investing in community trust infrastructure.

Prioritize platforms and practices that document shared understanding between staff and participants, not just compliance checkboxes.

Measure trust as a metric. Not just job placements or program completion rates, but: Do participants trust their coaches? Do coaches have transparent relationships with participants? Can both parties verify shared history and goals?

Hire for trust-building, not just credentials. The next generation of employment specialists will need to be community connectors who can establish and maintain human trust networks in an AI-saturated world.

The Opportunity

The erosion of institutional trust is devastating for many. But for communities that have always been excluded from those institutions—including people with disabilities—this moment offers something unexpected:

A chance to build something better from the ground up.

We can create employment support systems where trust flows from relationships, not from the authority of a letterhead or a certification. Where documentation serves the human connection rather than replacing it. Where technology amplifies dignity rather than surveilling for compliance.

This is the infrastructure challenge of the next decade. Not "how do we detect AI," but "how do we build human trust systems that can function in a world where everything can be faked except the relationship itself."

At PathAble AI, we're committed to building that infrastructure. We invite employment agencies, advocacy organizations, researchers, and funders to join us in asking not just "what technology should we build," but "who are we building it with, and who will trust us when it's done?"

What damages trust? How do we constructively challenge ideas and media so we can benefit as a community, not only as individuals?

The conversation starts now. Let's build the trust networks that will matter when the institutions fail.