Online Anti-AI Backlash Against Professionals and Creators

Where's the real accountability?

One of my connections is on an OpenAI brand trip, and her comments section is an absolute mess. She’s being called “evil,” a “f*cking loser sellout,” “out of touch”… But she develops workplace training programs, and workplaces are overwhelmingly adopting AI. Her work requires AI literacy and an understanding of how these tools are used, as well as how to help workforces adapt to them. She is looking at organizations, identifying the skills required to navigate them, and positioning herself as an expert to help people get into and progress in their careers at a time where doing so is challenging. As she generates most of her business through social media visibility, being visibly involved with companies that build tools her corporate clients are adopting makes sense.

But the backlash is personal, and that’s a common trend on social media (notably, less so in real-world conversations, from my experience). Anti-AI backlash is often directed at individuals using it or engaging with AI companies rather than at the companies and systemic forces responsible for the tech. Anything AI is often hated indiscriminately, regardless of context or application, and critics call others out without necessarily applying discernment first. Generating slop for clicks and running a business that requires AI literacy are different things.

I find this dynamic interesting and concerning from a crisis management perspective because it highlights a lot about how we process systemic anxiety. Much of the backlash is driven by fear that comes from uncertainty about what AI will do to our work lives and the planet (not unreasonable fears, I must add). There’s a lot of public anger around it that needs an outlet, and writing a critical comment on the socials is easier than confronting a multi‑trillion‑dollar tech conglomerate.

In crisis management, we spend a lot of time comparing where accountability is assigned with where it actually belongs, usually in the context of a corporation or an individual trying to shift blame onto someone else or external factors. In online AI discourse, the public, rather than the AI companies, is often voluntarily engaging in this accountability-shifting themselves, focusing the outrage on the end-users. This is common in crisis scenarios where the primary antagonist isn’t reachable (every iteration of the mask discourse during the pandemic, for example). When the system fails us, we attack its visible representatives, regardless of their power or culpability.

We use sentiment analysis to understand why online commenters are saying what they’re saying, more so than what it is they’re actually saying. I’m not encouraging ‘blame the commenters’ as a crisis comms approach (just like blaming the media, it doesn’t come across well), but we do need to look at the reasons behind the negativity because those help us understand what the anger is about and where it is emotionally directed (which might not be where it’s actively being directed). Analyzing public discourse means identifying the underlying emotions driving the conversation; in this case, the sentiment is characterized by anxiety, betrayal, and helplessness from the integration of AI into our lives. And those feelings are valid. It’s not wrong to be worried about job displacement, copyright infringement, environmental damage, data centers, water usage etc. But criticizing a woman in a TikTok comment section for doing her job doesn’t stop any of that. Sam Altman isn’t reading online comments and feeling bad about himself.

The actual source of the threat is too large and abstract to directly confront. Human labor and creativity are being devalued, and stopping that will require organized political and economic action that will take a lot more than righteous indignation online… unfortunately, finding someone who is visible and adjacent to the issue and directing the product of that anxiety feels like confronting something.

But strategically, attacking the end-user is the least effective way to advocate for ethical AI or protect human labor because it fragments the opposition and sidelines regulatory and transparency issues. The AI companies aren’t thinking about how to address those issues while watching creatives and professionals tearing each other apart over who is the ‘most human’ (us doing that benefits them, because if we’re busy policing each other’s use of AI, we’re not organizing against them). Divide-and-conquer…

The tech industry itself is promoting this and capitalizing on it, profiting from ‘catching people out’ with AI detectors. They’re creating the tools, integrating them into our workflows, and then building more tools for us to use to police their use. It’s a bit of a trap. Theoretically, it’s risk displacement, in which the reputational risk associated with AI use has been successfully shifted from developers to users.

Someone going on an OpenAI brand trip when they have a business that requires AI literacy and online visibility is acting in alignment with reality, because refusing to become AI-literate in that context would mean losing their competitive edge and clients. But the internet loves a binary. Using AI makes you evil; boycotting it makes you good… as if we actually have a choice about whether to use it in all circumstances involving it. Choosing to use AI to write text messages after bad dates (unnecessary) or generate marketing flyers (inadvisable; you lose brand identity as your material looks like everyone else’s) is an active choice; learning about how AI is used in and is changing the real-world environment you work in and, consequently, effectively adapting to its use is not a choice. We can’t deny reality and expect it to go away. We can hate AI and try to avoid it as much as we want, but we can’t escape it because we can’t even use the internet without (even indirectly) supporting AI.

Adopting AI is a survival tactic for many professionals because clients are insisting on it and competitors are using it, so you can be objectively against AI and AI companies for the negative effects they’re having while also having to engage to maintain an income. Refusing to engage when your professional activities require it amounts to nothing more than a symbolic gesture that AI companies will literally never notice. But engaging visibly online now comes with additional risk.

What do you do when you’re caught in the crossfire?

First, know you can’t control the narrative underlying online backlash driven by systemic anxiety that you did not create. The narrative in this case stems from fear and a loss of control that existed before you ever mentioned AI. Logical arguments and nuanced explanations don’t touch that narrative; also, defensiveness can validate the criticism. For example, explaining your business model and the need for AI literacy in your field may be interpreted as further evidence of ‘working with evil AI companies’.

Second, remind yourself of your own values and the realities of your industry. You know the value the product you’re using, or the company you’re engaging with, brings to your business and the need to understand the tools your clients are adopting. Being secure in your strategic decisions and discernment helps keep the noise of misdirected online outrage out of your subsequent decision-making (and thus reduces the chance of reactionary comments you’ll later wish you’d kept to yourself).

Third, know the difference between a true PR crisis and a localized controversy. A comments section filled with angry comments is not necessarily a PR crisis if those comments are not from your target audience or paying clients. If the people hiring you are not the people complaining, the issue is contained to the platform. A reputational annoyance, yes, but not a threat to your business continuity. There’s a difference between loud criticism and material damage, and ‘the internet’ is exceptionally good at generating loud criticism that has absolutely no impact whatsoever on a person’s livelihood. Remember this to keep your perspective. “Are the people yelling at me the people who pay my bills?” If no, the volume of the outrage =/= the severity of the business risk.

Be mindful of the psychological aspect as well, because it’s hard to process the scale of the hostility that can come with mass negative commenting. Even if you intellectually know the anger is displaced and that the commenters aren’t your clients, having numerous people calling you evil can trip your threat response and make you feel unsafe or act reactively. So work on those psychological ‘firewalls’ separating your professional strategy from your personal worth. Remember that the reactions you’re getting are reactions to what AI represents to people and not to you yourself as a person. You’re being used as a human shield for a much larger societal failure to regulate and manage disruptive tech. And if you have some cognitive dissonance around the whole thing (like maybe you’re strongly against data centers but have to use AI in your work), name that and acknowledge it. We don’t like how it makes us feel, but more often than not, two things can be true at once.

Broader implications

If we continue to ‘address’ the ethical complexities of new tech by shaming its users, we won’t get the regulatory and social frameworks needed to manage that tech more effectively. The ethical burden of transformative tech should fall on the entities that created and profit from it, not on the individuals who now have to adapt to it.

Let’s stop doing the tech industry’s PR spin for them by misdirecting online hate toward the wrong people.