There is a growing streak of public condescension on LinkedIn directed at marketing and communications professionals who use AI in their work. It is a mob mentality dressed up as some sort of virtue-signaling professional standard.
It shows up in comment sections. It shows up in the performative sighing over em dashes and structured paragraphs. It shows up in the pile-ons when someone’s post is deemed too clean, too organized, too suspiciously coherent, or too nice, even, to have come from a human being who was also managing a conference, a membership renewal cycle, and a board meeting in the same week.
It’s the implicit message baked into a hundred posts a week: if you used an AI tool at any point in your process, your work doesn’t count.
“This Feels Very AI”
It’s the comment that says “this feels very AI” left on a colleague’s post with no further context — meant to land as an indictment, not a question. It’s the LinkedIn thread where professionals compete to demonstrate the most disgust at AI-assisted content while the person who wrote it watches their credibility get picked apart publicly. It’s the implicit message baked into a hundred posts a week: if you used an AI tool at any point in your process, the work doesn’t count.
This is not thoughtful critique of lazy AI use. This is something different — a mean-spirited policing of how peers produce work, performed in public, for social capital.
Researcher Advait Sarkar named it in a peer-reviewed paper presented at the 2025 CHI Conference on Human Factors in Computing Systems. He called it AI shaming — and he argued it has less to do with quality concerns than most people want to admit. His finding: AI shaming functions as boundary work, a way for middle-class knowledge workers to protect professional identity and class standing by making AI use a mark of shame. The criticism isn’t really about the work. It’s about who gets to be considered a serious professional.
In associations, where credibility and peer relationships are the currency, that dynamic is particularly corrosive.
The Transparency Trap
Here is the contradiction that nobody pushing the “demand transparency” position wants to sit with.
The same professionals loudest about wanting honest disclosure of AI use are actively constructing the environment where disclosure is professionally dangerous. Those two things cannot coexist. You do not get to demand transparency while simultaneously making transparency a liability and then wonder why nobody is being honest with you.
The research is unambiguous on this.
A Duke University study published in the Proceedings of the National Academy of Sciences ran four experiments with over 4,400 participants and found a consistent social evaluation penalty for people who disclosed AI use at work — rated as less competent, less diligent, and less trustworthy than peers who said nothing, even when the actual work quality was identical. Workers reduce their reliance on AI when that usage is visible to evaluators, not because the tool stopped working, but because the social cost of being seen using it outweighs the productivity gain.
That’s not a hypothetical. That is what is happening right now in association offices, marketing departments, and communications teams across the sector. People are making calculations. They are looking at what happened to the colleague who mentioned ChatGPT in a staff meeting and weighing whether honesty is worth it.
What the Shaming Culture Is Actually Producing
Here is what the mean-spirited crowd is actually accomplishing, because it is not what they think.
They are not stopping AI use. And, for Association professionals, we are operating in an environment of expanding demand — more content, faster turnaround, leaner teams, higher member expectations, tighter budgets. The job does not pause for a philosophical debate about authenticity. Work gets done. Newsletters go out. Social calendars get executed. Conference promotional pushes happen on time.
The shaming culture does not eliminate AI from the workflow. It drives it underground. And underground is worse — for the organization that loses visibility into how its communications are being produced, for the profession that loses the honest practitioner knowledge that comes from people sharing what actually works, and for the trust the associations sector keeps insisting it values above everything else.
A staff member who quietly uses AI to hit a deadline and tells no one is not a problem the condescending LinkedIn comment solved. It is a problem that comment created. The environment that makes honesty professionally risky is the environment that produces silence, and silence is not the same as compliance.
What Transparency Actually Requires
If the associations community genuinely wants honest conversations about how AI is being used — and it should, because those conversations would make the whole sector better — it has to intentionally decide what kind of culture it is actually building. A community where practitioners can share what works, name what doesn’t, and develop real collective knowledge about tools that are not going away. Or, a LinkedIn environment where the loudest voices perform their skepticism at the expense of their peers and call it a standard.
Mean-spirited is not a professional standard. It is a chilling effect. And chilling effects in a community built on shared knowledge have consequences that outlast any individual comment thread.
The associations sector is more than capable of having a serious conversation regarding AI, and the when/where/how/why around it. I just hope the loud, naive minority isn’t allowed to shout it out.
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