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AI’s Trust And Ouroboros Issues

I took part in a discussion this week hosted by the legendary Needham analyst Laura Martin around AI and its future in this industry and others. 

And given the breathless nature of my post-CES LinkedIn feed, I wanted to return to two key points I shared with the audience. 

Both of which have been identified and named by people far more experienced with all this than I am.

The first, and more important, is the Trust Gap.

Which is exactly what it sounds like. 

People have bad experiences with the more popular consumer-facing LLM (Large Language Model) apps and then think “there is absolutely no way I am going to let this thing independently make decisions on $10MM worth of ad buys. Or even $10K.”

The second is the “Ouroboros Effect” where AI engines pull data from the open internet on sites that have pulled data from other GPTs, so that Chat is using data created by Gemini and vice versa, and they’re both passing it on as fact, only that data is often a hallucination or a false flag.

So there’s that and it’s a big honking problem.

Why It Matters

Let’s start with the Trust Gap.

As much as you hear how “agentic AI” is going to change everyone’s lives, especially everyone buying programmatically sold media, people have to actually, you know, start using it in order for it to have any sort of effect.

And if they don’t trust it, then they are not using it. 

Or they’re using it with an elaborate system of human checks and balances. Which are likely to reveal that they’re not really saving much time and money. If they are indeed saving any time and money.

That the industry will eventually get over the Trust Gap is not an issue.

It will.

The question is when.

People get—at some level anyway—that the small confined data sets that the agentic platforms are trained on are very different than the vast ones used by the LLMs and thus more reliable.

And then they remember that last week, ChatGPT sent them to a restaurant that closed two years ago and they flinch.

Because no matter how many times they hear that the task-focused agentic models are not the same as the consumer-focused large language models, they don’t fully believe it. 

Or, at the very least, they don’t want to be the test case.

Which means that like all of the other changes in the media industry (“we’re going to shift more of our ad dollars to CTV”) the shift to agentic buying systems is going to be a long and slow one, with lots of years of “experimental budget only.”

That delay will be compounded by the Ouroboros Effect. Because the data they will be using to place the ads will not be accurate because it was created by one AI, published on the open web, and then scooped up as fact by another AI.

That’s one piece and the other is that the LLMs all rely way too heavily on easily gamed sites like Wikipedia and Reddit.

As I’ve mentioned previously, there’s a journalist named Ashley Rindsberg who’s done a stellar job of exposing how a group of Bad State Actors have hijacked Wikipedia. Which, to its credit, has done its own internal investigation as a result, and gotten rid of some of the rogue editors.

Only the expectation is that this is just the tip of the iceberg, that there is far more of this going on at both Wikipedia and Reddit than we are currently aware of and that we can expect a lot more to come, given that the trick is as simple as hiring a group of people to spend all their time editing Wikipedia entries to reflect a certain POV in the belief that at some time the other side, which is not being paid to do this, will give up.

And since LLMs do most of their learnings on the open web, specifically via Wikipedia and Reddit, this becomes a huge problem and raises the Trust Gap yet again, which when combined with the amount of general AI-created MFA (made for advertising) slop out there, makes the data the GPTs are relying on all that much less trustworthy.

What You Need To Do About It

If you are reading this, do not take away that “AI is just a fad.”

It is not, it will change many things and it is not going away—history does not move backwards.

Do take away that you should temper your enthusiasm for the degree to which “agentic AI” can change media buying, content discovery or just about anything else related to the business.

But understand that there will likely be a tipping point when people start to trust them with larger and larger dollar amounts and the data issues will start to get cleaned up too. 

And that when this point comes, whether that is in three years or five years or 10, that you will need to be ready for it and act.

Or get left on the dustheap of history.

(That said, also bear in mind that it is entirely possible that it all just collapses in on itself in a web 1.0 manner, only to be reborn in a different and less fallible formulation a few years hence.)

Fandom Can Be Dangerous

When I wrote the chapter on Fandom for my book 10 years ago, I focused on the mid-00s Showtime series Queer As Folk. Mostly because I knew two of the lead actors in the show and thus just how crazy their fan base was.

And that rather than gay men, the fans were by and large middle-aged heterosexual women.

Who, to give but one actual example, would look up the names of high school classmates of the siblings of the actors. Set up fake Facebook accounts to try to befriend said siblings. All in the hope that the sibling might have previously unseen photos of the actor in their feeds.

Mostly though, they’d react furiously on social media when the actors were revealed to be actual people separate from the characters they played. 

And swarm and make demands on the producers and the networks on everything from plot changes to reboots, vastly overwhelming their social media resources.

So I was not shocked to learn that something nearly identical was happening to the actors from the surprise new HBO smash Heated Rivalry, a Canadian series about the love affair between two gay hockey players, which also has many steamy sex scenes.

And I bring this up not to bash obsessive middle-aged women who refuse to distinguish between actors and the characters they play, but rather, to point out that given the importance of fandoms in the age of feudal media, they can be a wild and unpredictable lot regardless of whether they are fans of a lusty new TV drama or a popular brand of yoga pants.

Why It Matters

There is a theory, widely accepted among scholars who study this sort of thing, that for a certain type of obsessive, there is far more value in being a fan of a relatively unknown actor like Connor Storrie (one of the stars of Heated Rivalry) than in being a fan of an established star like Brad Pitt.

Pitt will have millions of fans and multiple feudal media bubbles will have been created around him, and thus the odds of being Brad Pitt’s number one fan, or even getting some sort of social media reaction from him—or any A-list star for that matter—are pretty slim. Ditto “accidentally” running into him at the supermarket or on his way out the door.

The odds of being the number one fan of a relatively unknown actor like Storrie, however, are much higher. As are the odds of him actually liking one of your posts.

“Big fish in a small pond” is, I believe, the technical term for it.

And the reason I bring this up is that in the age of feudal media, it is highly likely that niche brands as well as any type of TV, video, music or movie brand will develop some sort of cult following.

Take Tesla, for instance. 

Whose fans would be excoriated by their more obsessive peers for saying something even remotely positive about another car brand. And whose fan base splintered into a series of warring camps around politics and Elon and Cybertrucks, each representing way more than just a consumer opinion, each new split posing new dangers for the brand.

And that keeping fans happy even when they are fighting amongst themselves or making unreasonable demands on the brand is a skill that marketers will need to learn to survive the dark ages of media.

Where the media landscape is often a series of self-contained bubbles built around the brand or the category.

What You Need To Do About It

No matter what you are selling—food, clothing, cars, a TV series, your own creator content—you need to be very aware of your fan base.

For most brands this is a relatively easy ask. 

Your fans are supportive, they’re into you but not in an obsessive way, and so showing them a modicum of love and respect will serve you well.

But for brands with potentially Toxic Fandoms, you will need to handle them with kid gloves. To understand when to engage, when to disengage and how to protect your actors, designers, product teams.

You will need to understand that the noise within certain bubbles may become deafening. Even as the wider world has no idea any of this is going down. 

And that the reaction in those bubbles will decide whether your brand will live and die.

Meaning  you will need to deal with it. 

Thoroughly and carefully. As if you were performing surgery.

One false move and it can all blow up.

You will need to understand that your fan base will not be uniform. That there may be fan bases in other countries. In other cultures with different mores and norms than the United States.

You will need to understand that there is no one set way to deal with any of this—every Toxic Fandom is unique. 

And that you must do your best to deal with them, to neutralize the more extreme segments without alienating them and that sometimes that is not possible, at which point you just brush yourself off and move on.

Podcast: Is 2026 Media’s Dark Ages?

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