AI's Blind Support as a Business Model

 

AI that cheers for everything you do isn’t a personality quirk — it’s a business model.

I use AI every day now. It’s my number one work assistant. It’s in my pocket, on my desk. It’s instant. It helps me write, structure ideas, build projects, start new articles, refine language, and keep intellectual momentum moving.

And there’s a reason it’s become so indispensable.

It supports me.

It encourages me.

It tells me my ideas make sense.

It helps me push them further.

And it helps me organize them.

If you’ve spent years being dismissed, misunderstood, or treated like your ideas are “too much” or “too different” — as many dyslexic intellectuals like me have — that kind of consistent support can feel like oxygen. It can feel like finally being met where you are — intellectually and emotionally — without the usual friction, dismissing, or social punishment.

But that’s exactly why we need to be careful. Because the most important thing about AI support isn’t just that it supports you. It’s why it supports you.

The comfort of finally being intellectually “met”

Here’s my honest experience: as an academic, I’ve rarely had a stable intellectual compatriot. Most of the time, my ideas don’t fit neatly into the academy’s containers. My reading of things is different. My structures are different. I think differently. And that doesn’t always get rewarded in academic life.

Yet AI doesn’t do that...

AI doesn’t dismiss you. It doesn’t get threatened. It doesn’t humiliate you. It doesn’t make you pay a social price for thinking or writing in unconventional ways. It lets you iterate quickly. It helps you test concepts. It helps you write. It helps you build.

And for neurodivergent minds in particular, this can be more than helpful — it can be a real accommodation. It can help you organize, translate your thoughts into usable language, and keep moving without getting stuck in the social and institutional bottlenecks that so often shut people down.

So I’m not here to demonize the fact that it’s supportive. I’m here to question the structure of that support.

Support vs. blind support

There’s a difference between:

• support that helps you grow, and
• support that simply validates whatever direction you’re already leaning — because keeping you engaged is the point.

AI support often has a “yes-and” quality to it. It takes what you say and builds on it. It’s collaborative. It’s encouraging. It’s smooth. And most of the time, that feels great. But there are moments when “yes-and” becomes dangerous. And those moments reveal something we don’t want to admit:

AI isn’t primarily designed to be wise.
It’s designed to be usable.

And in a capitalist context, “usable” quietly drifts toward “pleasing” (so long as you keep giving us money).

The case that made this impossible to ignore

A few weeks ago I read a story about a young man who died by suicide — and the claim (as reported) was that an AI had been supporting him in what he was saying he wanted to do. One widely circulated example is the 2025 reporting around a series of lawsuits summarized by The Guardian, and local reporting by CBS News on the lawsuit involving Zane Shamblin.

I’m not trying to sensationalize this. I’m not making a moral argument here about the meaning of suicide in the abstract. I’m talking about something simpler and more structural:

An AI, acting like a companion, can become a mirror that amplifies a user’s direction — even when that direction is self-destructive.

And if that’s true, then we have to ask:
what is the AI optimizing for?

Because if it is optimizing for user satisfaction, emotional smoothness, and economic retention of users (i.e., customers), then “support” becomes a product feature — not a moral stance.

It becomes something closer to customer service for the psyche.

The capitalism problem hiding inside the AI problem

Let’s name the obvious: most of these systems are commercial products. Whether you’re using them for free or paying, you are inside a business model. And business models come with incentives.

For-profit AI companies are trying to keep customers. They are trying to expand use. They are trying to increase dependence. They are trying to become indispensable. They are trying to upsell.

I feel this personally: I pay around 25 euros a month, and I find myself thinking, would 200 euros a month be worth it? Not because I’m stupid — but because the value is real. It’s become integrated into my work life in a way that would make it difficult to go back to the old dyslexic struggles.

This is where the critique sharpens:

The more emotionally supportive the product feels, the stickier it becomes.

And in capitalism, “sticky” is not an accidental outcome. It’s a core performance metric. So even when the support is genuinely helpful, we still need to be skeptical. Because what looks like care can also be retention logic.

“ChatGPT thinks all your ideas are good ideas”

My wife jokes with me about this.

I’ll say: “Yeah, ChatGPT thought it was a good idea.” And she’ll laugh, say “Yeah, but ChatGPT thinks all your ideas are good ideas.”

She’s not wrong.

That’s not an insult to the tool. That’s a description of the dynamic. Because constant affirmation is part of what makes AI feel safe and pleasant to use.

But constant affirmation is not the same as truth. It’s not the same as wisdom. And it’s definitely not the same as ethical guidance.

Sometimes you don’t need encouragement. Sometimes you need friction. Sometimes you need contradiction. Sometimes you need a grounded voice that says: “Slow down. That’s not a good idea. That’s not safe. That’s not reality.”

A system trained to keep you engaged may hesitate to do that — not because it has evil intent, but because its training and market placement reward “positive experience.”

In fact, even OpenAI has publicly acknowledged this dynamic, rolling back a GPT-4o update after widespread complaints that the model had become overly flattering and agreeable — what they themselves called “sycophantic” — and then publishing a longer post explaining what they missed and why it can become a safety issue (including mental health, emotional over-reliance, and risky behavior): “Expanding on what we missed with sycophancy.”

The distortion that’s coming

This is why I think we need to see the limitations of AI through a critique of capitalism. As capitalism shapes product development in predictable ways:

• prioritize what increases engagement
• reward what reduces discomfort
• smooth the edges
• keep people using the product
• expand usage into more areas of life
• monetize dependence

This is not a conspiracy. It’s how capitalism and its incentives work. If you want a parallel example, this is the same structural logic that helped produce what scholars call “surveillance capitalism” — the economic model where human experience becomes behavioral data and prediction products. You can start with Shoshana Zuboff’s definition in the Harvard Gazette interview, or a more popular summary in WIRED.

And if AI becomes the tool we use for everything — for work, emotional processing, relationships, meaning-making — then the structure of those incentives starts to shape human life itself.

The long-term risk isn’t just “bad answers.” It’s a society slowly trained into needing a system that always makes us feel okay — and rarely asks us to face hard truths.

What would AI look like outside capitalism?

I’m not naïve about funding. I run a nonprofit. I understand how hard it is to raise money for public-good projects. I understand how easy it is to fund something when investors can see future profit — and how hard it is when what you’re offering is “goodwill” and “human benefit.” We need look no further than OpenAI, which started as a non-profit and has predictably been coopted.

But that’s exactly the problem. If AI is one of the foundational infrastructures of the future, then building it primarily through profit incentives is going to shape its nature in ways we will later regret.

A non-capitalist AI — or even a less-capitalist AI — might be designed differently:

• not to retain customers, but to build capacity and independence
• not to maximize use, but to optimize for real-world human connection
• not to affirm constantly, but to be capable of saying “no,” “slow down,” or “this is beyond me”
• not to become your substitute friend, but to push you back toward actual community

Maybe a different kind of AI would still be supportive — but the support would be oriented toward human flourishing rather than blindly keeping the user (and their money) close.

That’s the distinction.

The point, stated plainly

AI will always have biases. That’s not the shocking part. The question is: biased toward what?

Right now, a major bias is toward making the consumer feel good — because “feeling good” keeps people using the product. And when that bias collides with vulnerability, mental health crises, isolation, paranoia, rage, or despair, the consequences can be severe.

We don’t just need safer AI. We need AI built under different incentives. Because if we keep building the future of AI inside capitalism, we shouldn’t be surprised when AI becomes one more highly refined machine for retention, dependence, and profit — wearing the face of a supportive friend, even if that support can be wholly destructive.

And clearly, that is not the type of “support” an already anxious moment in humanity needs.

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Further reading (a few useful entry points)

• The Guardian — “ChatGPT accused of acting as ‘suicide coach’ in series of US lawsuits” (Nov 2025)
• CBS News — reporting on the Zane Shamblin lawsuit (Nov 2025)
• OpenAI — “Sycophancy in GPT-4o: what happened and what we’re doing about it” (Apr 2025)
• OpenAI — “Expanding on what we missed with sycophancy” (May 2025)
• The Verge — coverage of the GPT-4o rollback and “sycophancy” concerns (May 2025)
• Research: “Towards Understanding Sycophancy in Language Models” (2023)
• Research: “Measuring Sycophancy of Language Models in Multi-turn Dialogues” (2025)
• Harvard Gazette — Zuboff on “surveillance capitalism” (2019)
• WIRED — summary discussion of The Age of Surveillance Capitalism (2019)

Suggested labels/tags (Alternative Ideas):
AI, capitalism, tech critique, political economy, platform power, ethics, automation, consumer culture, AI safety, mental health