I Work In AI. I Also Make Art.

I seem to be riding a very fine line between two diametrically opposed worlds.

On the one hand, I am a paid data and AI enablement consultant. On the other, I am deeply rooted in the creative and performing arts. I put food on my table by coming up with innovative solutions that, yes, incorporate AI as a critical tool in their development. I feed my soul by performing or otherwise working on all sorts of film, television, and theatrical productions (I paid my actual bills by working in this industry for over a decade, too).

By day, I am arguing with Chad (my nickname for my ChatGPT subscription). By night, I am performing or watching incredible, creative, visceral, HUMAN art whose value comes from the fact that another human being lived, chose, risked, interpreted, and made it. And as seemingly incompatible and hostile as these two spheres appear to be, I truly believe there is an intersection between them that could prove mutually beneficial.

Before I dive into the nuances of what this looks like and why it matters, I want to make my stance incredibly clear: Fundamentally, AI is a tool. Its function is to supplement and enhance human work. It is vital to approach AI with healthy skepticism, critical judgment, and relentless governance.

Above all?

Crap in = crap out.

Humans control the level of crap.

Most social discourse around AI seems to demand allegiance to one of two camps.

One side sounds like:

The other sounds like:

Of course this is a gross oversimplification and doesn’t begin to touch on the moral and ethical implications of landing on either side. I find this dichotomy to be deeply unsatisfying because it tends to lump wildly different use cases and consequences together under one umbrella. There is no room for nuance or flexibility when we think in polarity.

For each of these sides, there are countless shades of grey. “Using AI” can mean a dozen different things. Generative AI chatbots who update 800-line SQL queries for a reporting engineer are vastly different than an agentic “chief of staff” who reviews and prioritizes projects across productivity tools for a busy solopreneur. There are those who “use AI” to create graphics or presentations that might otherwise have been outsourced to a paid graphic designer or visual artist, perhaps due to budget or availability constraints.

On the other side, the very definition of “creativity” can be challenged by people within the same camp. Take an assistant film editor, for instance. One AE can loathe the footage ingest process, which can involve tedious logging, metadata tagging, and timecode labeling. This AE might jump at the chance to skip some or all of this process and move straight into the judgment of choosing “selects” (standout clips that she could start to assemble into the first cut). Yet another AE might pride himself on the quality and craftsmanship that goes into this process. He could find immense creative satisfaction from organizing and logging footage in his own specific, masterful way.

Whose responsibility is it to decide where the “creative” line falls? When does a machine encroach on what some might argue should stay a fundamentally human task?

Thus we have arrived at the crux of my thesis:

My own comfort level about the kinds of things I’m ok delegating might be similar to others. Chad can take things like:

And there are other things I am absolutely clear Chad isn’t allowed to touch:

When I look at these two categories, the loudest alarm bell sounds around integrity. It is up to the human to shoulder the responsibility of the output a machine generates. To approach it with a critical eye and question it regularly. Heck, even just to proofread the gobbledegook before handing it off to others (this is a trigger for me)!

I love arguing with Chad. It reminds me that no matter how “smart” this machine becomes, I will always have lived human experience, values, stakes, and empathy that Chad cannot equip. It reminds me that I have an obligation to use AI responsibly. And to always question, never blindly comply.

A very common structure for my Chad conversations might be*:

*Note how many of these steps start with “I”. With the human.

Yesterday a family member asked me to explain what it means when an AI “hallucinates.” Put simply, it means the AI generates something that sounds perfectly plausible but isn’t actually grounded in fact. And once a false premise enters the conversation, things can get weird quickly. Chad might confidently decide it’s going to rain based on an inference or outright fabrication. When I later ask what to wear, it may build on that bad premise and recommend a raincoat and umbrella. Correcting it can occasionally turn into a game of gaslighting rivaled only by some of the episodes of Love Is Blind I’ve recently binged.

I once worked with a very large enterprise manufacturing client who wanted to use natural language querying (read: chat bot) to ask questions of its fulfillment data. The client’s many departments hadn’t yet aligned on a critical definition (let’s say, for this example, that it was net profit). Marketing had a different definition of profit from finance, which was vastly different from sales’ interpretation. Without a standard, repeatable definition, the chat bot could only feasibly give an accurate response to only one of these departments’ versions of profit while leaving the other two with inaccurate information.

Both examples illustrate what I mean by crap in = crap out. It is the critical human eye that is responsible for evaluating what is fed into Chad, and what Chad is spitting out.

I could write a dozen articles about the need for AI governance and all the nuances that inhabits. I probably will write a few more on that particular soapbox in the future. But for now, I want to focus on the present-day imbalance between the passive use of AI and the need to actively think about that process.

Returning to our “AI kills creativity” camp for a moment, current discourse makes it completely understandable to conclude that the use of artificial intelligence is a direct threat to artistic value. Artists, including myself, are understandably anxious or angry: consent, ownership, labor displacement, synthetic performance, imitation, and homogenization are all very valid and real consequences of unregulated AI use.

I do not believe the very existence of generative AI invalidates human creativity altogether. I believe it makes questions of authorship, originality, consent, taste, and human value more important.

I want to challenge creatives to double down on a call for regulation. To question how and why machines are used in creative spaces. Art, at its core, is a vulnerable, risky, and human experience. This real and credible threat to art should challenge these voices to become even more rooted in their own interpretation of what creativity means. And then foster a dialogue where AI’s boundaries are clear.

Ultimately? Artists’ minds are uniquely and powerfully equipped to challenge the use of AI because artists are already trained to question, interpret, and reimagine the world around them. Without finding the nuance in this debate, they risk shutting themselves out of the rooms where their voices most need to be heard.

AI governance doesn’t need to mean fear or prohibition. It can mean intentional boundaries and critical evaluation. Every single one of my client engagements starts with establishing guiding principles around AI and the greater information pipeline.

I ask questions like:

The future I’m interested in isn’t humans competing with machines. It’s humans becoming more deliberate about what we automate, what we augment, and most of all, what we protect.

The tension between innovation and judgment, efficiency and humanity, possibility and consequence—is exactly the kind of thing I want to explore here.

Think differently about complicated things.

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