God Loves a Terrier, Not an Algorithm

A reflection on AI, creativity, and why trading laughter, judgment, and taste for efficiency and personalization leaves our work hollow.

The God Loves a Terrier scene from Best in Show makes me laugh out loud every time I see it. Like, I have an actual physical response. My body makes a noise.

Somewhere along the way, we replaced reactions like that with placeholders. We took laughter and turned it into text. We compressed something bodily and immediate into three letters that politely acknowledge amusement without requiring much of anything from us. LOL is tidy. It’s efficient. It’s also empty.

When you watch someone like Catherine O’Hara work, it’s almost impossible not to laugh. You can feel the joy in the finished project, and you can intuit some level of joy in her creative process. You can feel how she worked with her fellow actors.

We watched Schitt’s Creek twice in our house because it made us laugh out loud. Again and again.

That’s the part people are actually defending when they push back on AI creativity. It’s not just the artistic output. It’s not just the slop. They’re reacting to the steady disappearance of joy from the act of making things.

The Part of Creativity No One Measures

Creativity isn’t just the finished product. It isn’t only the script, or the cut, or the deck, or the thing you can point to in a meeting and say this is done.

There’s a stretch of time before that moment where the work is uncertain. Where you’re trying things without knowing if they’ll land. Where the process itself is the point. That’s where joy lives.

Not just in art, but in ordinary work. In problem solving. In collaboration. In the small satisfaction of discovering a better way to do something with someone else. In moments where work briefly stops feeling like work.

We used to have more of that. We used to laugh in offices. We used to mess around a little. I once covered a co-worker’s desk with mice (the computer kind) We used to leave room for play, even in serious jobs. The more technology we’ve added to our work lives, the more that space has been engineered out.

We track more. Measure more. Optimize more. We communicate faster and flatter. We reduce friction. We remove waste. And in the process, we quietly remove the parts of work that made it feel human.

Joy doesn’t scale well. It doesn’t show up in dashboards. It doesn’t map cleanly to metrics or quarterly goals. Which is exactly why it keeps getting treated as expendable.

When I work creatively with AI, that joy is still there. Sometimes it’s even amplified.

I felt it intensely when I made a short film a couple years back called The Painter. Every frame was an experiment. What happens if I try this. What breaks if I push here. What surprises me if I don’t take the obvious path.

It didn’t feel efficient. It didn’t feel optimized. It felt curious. Alive.

That same curiosity is what you’re seeing when people like Darren Aronofsky experiment with AI-driven work. It’s not about novelty. It’s about testing whether that sense of play and discovery can still exist inside these tools.

It can. And that matters more than most people want to admit.

Why the Backlash Feels Personal

The resistance to AI creativity isn’t only about economic fear. It’s also grief. Grief over the feeling that something meaningful is being flattened. That something human is being smoothed out and replaced with something quieter and more compliant.

Creative work has always been collective. Actors. Writers. Designers. Editors. Crews. There is joy in that ecosystem, in the shared act of making something together.

What sharpens the backlash is how the people building these tools tend to talk about them. Speed. Scale. Efficiency. Output. Replacement. It’s a vocabulary that leaves very little room for curiosity or reverence. Almost no acknowledgment that creation is supposed to feel like something.

Even when creativity gets mentioned, it’s framed as throughput. More content. Faster. Cheaper. That framing isn’t neutral. It tells you exactly what’s valued, and what isn’t.

This Didn’t Start With AI

If you zoom out, this pattern is familiar.

For more than a century, media and work have both been compressed. Time gets tighter. Attention gets thinner. Speed and volume win. Patience and depth lose.

Each shift promises access and convenience, and often delivers. But each one also reduces the space for reflection, ambiguity, and the slower kinds of joy that come from sitting with a problem long enough for it to change you.

Now we talk openly about attention as chemistry, engagement as dopamine, and behavior as something to be engineered and exploited. None of that language leaves much room for joy.

Creativity Versus Efficiency

This tension sits underneath almost every conversation about AI right now, and it shows up most clearly in marketing.

Creativity is uneven and emotional. It involves false starts, wasted time, and moments of play that don’t immediately justify themselves. It requires taste and judgment, and a willingness to risk getting it wrong in public. Efficiency wants the opposite: clean inputs, clean outputs, predictable results, speed.

What often gets labeled as creativity in modern marketing is really something else. We call it personalization. Personalization sounds innovative because it feels specific. It looks like care. It carries the language of attention.

If you can tap into someone’s ChatGPT persona, their browsing history, or their behavioral profile, you can tailor a message that sounds like it was written just for them. On paper, that looks creative. In practice, it’s creepy and feels hollow.

We’ve all experienced it. Messages that know our name, our company, our school, our home town, our last click, our interests. Messages that sound intimate but feel automated. Polite. Bloodless. Slightly off.

That’s because it isn’t creativity. It’s optimization. What’s harder to admit is what’s actually happening.

Over‑personalization becomes a way to avoid real creative risk. Specificity replaces originality. Data replaces insight. Brands feign sincerity as a substitute for true creativity. Some CMOs actually fear for their jobs if they stand out too much.

Sincerity can’t be simulated just by knowing more about someone. It comes from having something worth saying, and saying it with care. It comes from perspective, not profiling.

Efficiency isn’t the enemy, and personalization isn’t inherently wrong. But when efficiency becomes the primary value, creativity gets reduced to surface-level tailoring. Surprise disappears. Play disappears. Joy disappears.

People feel that. And when they do, trust erodes. Not because the tools are powerful, but because the work starts to feel manipulative instead of human.

A Different Way to Look at It

There are a few different ways to think about AI creativity, and most of the conversation so far has stayed stuck at the personal level.

At that level, the value is obvious. AI helps you brainstorm faster. It helps you explore more ideas. In filmmaking, video, music, or writing, it compresses the distance between an impulse and a rough version of the thing. You can try more. You can fail faster. You can see what an idea looks like before you’ve fully committed to it.

That alone is meaningful. But it’s not the interesting part yet. The more interesting question is what happens when that individual acceleration runs into a team.

We’re just beginning to work out what collaboration looks like when AI becomes part of the process. Can AI act as something closer to an operating system for teamwork?

In most creative work, whether it’s filmmaking or corporate work or product development, the quality doesn’t come from one person and one tool. It comes from judgment layered over time. A writer’s sense of structure. A designer’s eye. A marketer’s intuition. A sales perspective. People reacting to the work and shaping it through their own experience.

AI can accelerate iteration, but it can’t replace that judgment. It can simulate perspective, but it can’t supply real perspective. It doesn’t know why something feels off. It doesn’t know why a moment lands or doesn’t. People do.

The real challenge, then, isn’t building better AI for individuals. It’s designing processes that let teams use AI creatively together. Processes where iteration is fast, but judgment is shared. Where ideas move quickly, but they’re shaped by multiple points of view.

That’s where perspective starts to matter even more, not less. Someone with a writing background brings something different to the work than someone grounded in design. A cinematographer sees things differently than a marketer. Those differences don’t disappear because AI is involved. They become the point.

Taste becomes the gauge.

Not taste as preference, but taste as understanding. Knowing why something works. Knowing why it doesn’t. Knowing when to stop iterating and when to push further.

That’s the part no one has really nailed yet. We’re still trying to build little bubbles of AI around individual creators. We’re much earlier in figuring out how AI fits into real creative teams.

But that’s where the next phase of creativity actually lives.

Why This Actually Matters

If creativity becomes only a means to an end, people eventually push back. Not because they hate technology, but because they recognize when something human is being pushed aside.

Joy isn’t a side effect of creativity.

It’s the point.

Lose that, and no amount of efficiency will save what we’re building.