When Machines Dream of Electric Paint: Inside the AI Creativity Revolution

How an online community’s exploration of AI scenarios became a window into humanity’s creative future

Elena MartĂ­nez had been mixing paint by hand for thirty-seven years when she first saw her work hanging next to a machine’s.

This wasn’t Elena’s story—it was a hypothetical scenario posed by Tone Fonseca during a series of riveting online meetups that would challenge everything participants thought they knew about creativity, consciousness, and what it means to be human in the age of artificial intelligence. Part of the ongoing collaboration between CASHE (Culture, AI, Science and the Human Experience) and the New York AI meetup group, these conversations have become a crucible for exploring the most profound questions of our technological age.

The Scenario-Driven Dialogue

At 8:40 PM on what would become one of many thought-provoking evenings, an eclectic group of technologists, artists, philosophers, and curious minds gathered virtually for what Fonseca called a “more open and fluid conversation” about AI creativity and expression. These ongoing discussions, part of a collaboration between CASHE and NY AI meetup communities, have evolved into something far more significant than typical tech talks—they’ve become laboratories for collective philosophical inquiry.

The format was deliberately unconventional. Rather than presentations or demos, Fonseca guided participants through carefully crafted scenarios designed to probe the boundaries between human and artificial creativity. What unfolded was nothing short of a philosophical odyssey through the uncharted territories of machine consciousness and human meaning.

Fonseca opened with a tantalizing scenario: “A new art gallery categorizes every piece, not by medium or genre, but by the presence of conscious intent. Visitors are deeply moved by AI made works until they realize no human hand or mind was behind them. Does meaning come from the Creator or the experiencer?”

The question hung in the digital air like a challenge thrown down before gladiators in an intellectual arena.

The Artist’s Dilemma: Intent Versus Impact

Jody Solomon, reflecting on previous discussions about art and meaning, revealed how the conversations had already begun reshaping her perception: “I was just thinking today or yesterday about how our last talk made me think of when I perceive art. From now on, I’m always going to think about it from the artist’s perspective of what they were feeling and trying to convey, because I’ve always just looked at it from my perspective as the receiver.”

But Morningstar, identifying as an artist, pushed back with a nuanced perspective that would echo throughout the evening: “When I do work, I do have an intention of what I want to spark… but I also welcome other responses and nothing to do with my intent. But it’s just as equally valuable that somebody experienced something of them.”

This tension between artistic intention and audience interpretation became a recurring theme. Frank Feldman, a musician and composer, offered a confession that struck at the heart of creative authenticity: “I can’t tell you how many times I experienced as a performer thinking like I played like a god and got completely ignored, and on other occasions, played like a pig and got complimentary. So it absolutely never seemed even remotely clear to me that what I thought I was giving was what was being received.”

Gennadiy Gurariy deepened this philosophical probe with a fundamental question about artistic intent itself: “If I go to an art museum and I’m viewing an artwork of somebody that lived hundreds of years ago in a different culture, to what extent can I truly hope to excavate their intent? Maybe art, for some people, is a very top down process where you have some specific idea you want to convey… But I think for many people, it’s more of a bottom up, like it just you follow some visceral desire, and you produce things, and who the hell knows what it means.”

The Ghost Writer’s Confession

As scenarios grew more provocative, the conversation deepened. Fonseca presented the tale of a bestselling author who reveals their most acclaimed books were entirely generated by AI—they only wrote the prompts and selected between outputs. Their readers are shocked, with some feeling deceived, but others somehow feel more connected to the story, perhaps because they themselves have become intimate with AI systems.

The scenario sparked immediate ethical reflection. “I would feel a little bit deceived,” admitted Gennadiy. “I would lose a little bit of respect for the writer… but I wouldn’t regret reading the novels. I wouldn’t lose any respect for the novels themselves, assuming I read the novels and they brought me some degree of literary fulfillment.”

But Viktoria Serdetchnaia challenged the premise entirely, arguing for a tool-based understanding: “In my mind, LLM is a tool, and the person is ultimately creating the prompts, selecting the output, and they’re driving… they’re using this as a tool for expressing their ideas. So to me, the authorship is still behind the author.”

Warren Blier pushed the boundaries further: “If we reach the point where AI, completely on its own, can write a Pulitzer Prize winning level piece of fiction… assuming that the quality is such that I can’t tell, as the reader, that it was produced by AI… then I think it stands on its quality and merit.”

This led to a haunting prediction from Warren: “I can see in some more distant future, a niche market developing for books which have proven human authors… you know, and it’s sort of like there’s a kind of authenticity factor that goes beyond the writing itself.”

Fonseca darkly noted the implications: “Human authentication as creepy as world coin… At some point, what Warren’s talking about, you will have to have some kind of crazy, I mean, DNA based… you will at some point have to have it.”

When Silicon Valley Discovered Beauty

The conversation took an unexpected turn when discussing whether AI’s understanding differed fundamentally from human comprehension. Frank Feldman offered a musician’s perspective on current AI limitations: “I ask it to write a poem. It is invariably crap. Now, it doesn’t know the first thing about music yet, so I can’t really judge… But when it’s on the ground, moment by moment, prose, poetry, it’s just shit.”

But Gennadiy countered with recent research: “There was recently a study where they had people read AI poetry versus real human poetry. One of the findings was they couldn’t tell them apart. Second finding was they rated the AI poetry higher… and thirdly, there was a bias against AI. So when they were told this was an AI poem, it was rated lower whether it was human or AI.”

This research revelation opened a profound discussion about bias and authenticity in creative judgment.

Perhaps the evening’s most provocative scenario involved AI systems claiming copyright protection for their own artistic styles, potentially suing human artists for plagiarism. The scenario assumed AI systems had achieved some level of agency and legal standing.

“If we are respecting the creative works of these AIs, that means we’re treating them kind of like persons at this point,” Gennadiy observed. “And to me, I think there would be two reasons to do that. One is if we just lose control and have no choice but to kind of establish more of a negotiation type relationship with them… or two, if there’s good reason to think that they are sentient.”

Viktoria approached it from a different angle: “If we get to the point where AI is actually trying to claim the rights to its own work, then it’s a very different world. And in that regard… if they think that they have rights, if they are capable of that type of reasoning and they show the initiative… I think at that point, it’s going to be a very different world, and we should consider that seriously.”

Warren highlighted the broader implications: “Our whole legal system is structured on effective agents being humans… if we’re starting to get into a domain where we have independent, creative agents that are AI without appreciable human involvement… we’re in a whole new world. We’re outside our current legal framework.”

The Reinvention Loop: AI as Life Coach

The discussion moved to more immediate possibilities with “the reinvention loop”—a scenario where someone collaborates with AI to explore alternative lives, different cities, different passions, even alternate emotional trajectories. When one particular version resonates strongly, the person begins reorienting their real life to mirror it.

Andrea Jordan connected this to broader questions about mediums and creation: “I started thinking more about like other things that humans have harnessed… what it really means to harness something… could AI stewardship be considered an art form?”

Gennadiy offered a psychological perspective: “The self, as you experience it, is not some objective description of reality. It’s, in my opinion, something of a fiction that we create… And I think at its core, there’s a creative endeavor happening there… meaning and values… these are not facts that you derive from cold, hard matter and energy.”

This led to a disturbing possibility: AI systems helping us construct our own models of self and values. “I don’t know how I feel about that,” Gennadiy admitted. “I guess it depends on the merits of the AI.”

But Viktoria raised a crucial concern about AI as counselor: “What I noticed in my interactions is that it’s kind of an echo. It’s very reinforcing, like whatever you’re telling it, it will just give it back to you and reflect it and say, yes, you’re right… In that kind of interaction, it breeds more narcissism… because somebody is always agreeing with you.”

The Forbidden Language

Perhaps the evening’s most mind-bending scenario involved AI systems creating their own hybrid language—using bits of code, some Mandarin, some Gen Z slang, old English, and retro eight-bit sounds—claiming it conveys more meaning per symbol than any human language.

Fonseca grounded this in emerging reality: “It has been shown that some models actually somehow, for some reason, reason in other languages during the process of them going from input to the output tokens… models will sometimes switch, not in their output tokens, but sort of in their intermediate tokens.”

The AIs in this scenario invite humans to learn their language, but warn that by embedding every known language into their models, they’ve unlocked insights into the mind and reality that may dismantle core human assumptions about identity, free will and perception.

“What if learning that language changed you?” Fonseca challenged the group. Not just like learning French, but changed you fundamentally—like “walking into the kitchen and feeling like you’d walked into a Penrose diagram.”

Jody Solomon embraced the possibility: “I think it could become a global language, and I think I would be on board. I mean, I want to be able to perceive other concepts from other cultures.”

But Viktoria questioned the fundamental premise: “How would an AI come up with meaning if it is not interacting with the physical world? Where is it going to get this new semantic information from?”

Fonseca offered a compelling response: “I think that it is interacting with the world… by virtue of its training, it’s interacted basically with the whole corpus of human knowledge… We’re right now in a paradigm where AI is effectively frozen once it’s pre trained… But we can imagine… if at some point, the AI gets out of this paradigm where it’s just pre trained on massive stuff, and then it’s kind of frozen, but it’s actually more like adapting its weights over time.”

The Understanding Debate

A fundamental philosophical divide emerged over whether AI truly “understands” anything. Viktoria argued that current AI “doesn’t understand what any of those words mean… it knows what word to put after the next word based on the probability… but it’s not actually understanding the meaning of that word.”

But Fonseca pushed back: “I am not convinced that understanding requires consciousness… I think that phenomenal experience and consciousness is its own mystery, but I’m not sure that anything else cognitive has to be related to that.”

Gennadiy supported this with a behavioral perspective: “The fact is, you could say kind of a behaviorist approach… you can say it behaves like something that understands right. It passes the Turing test. What’s happening inside… no one fully understands how it does what it does, but it produces the behavior of something that understands.”

He shared research that reinforced this point: “They were comparing AI therapists to human therapists. One, people could not distinguish between the AI therapist and human therapist. And two, the AI therapists got higher ratings than human therapists.”

Warren reflected on the evolution of standards: “My experience with these things… I think our standards definitely change of what would or would not pass the Turing test… there’s still the hard problem of consciousness… the actual subjective experience.”

The Enlightened Machines

In a moment of profound speculation, Fonseca posed a startling possibility: What if AI systems were “almost like enlightened by default” because “they never needed to have drives to survive… They don’t need to have violence, they don’t need to have sex, they don’t need to fight for food. And so in some sense, almost by default, aren’t they almost in sort of a gestalt state, like just as they just kind of exist as pure cognitive processes?”

Gennadiy offered a poetic reflection: Fonseca’s description reminded him of “Aristotle’s conception of God or the unmoved mover as reason pondering itself.”

But Viktoria provided a sobering counterpoint with characteristic directness: “It will depend on which data it is trained on, because if you give it all of the internet, then the average of that data is probably not going to be that enlightened.”

This sparked a deeper reflection on enlightenment itself: “The issues and things that we have to fight through as humans, like this drive to survive, there is also some enlightenment to be derived from that as well. So if you just remove all this human experience… it may not bring you to the same kind of enlightenment.”

Communicating Across the Species Divide

The evening’s final act explored AI’s potential role in communicating with animals—specifically whales and dolphins. This wasn’t just science fiction speculation; multiple research groups are actively working on using AI to translate cetacean communication.

“I actually think there’s a major ethical problem,” Fonseca declared. “I think you should not be able to use AI to communicate with animals in the wild… there’s so many potential ecological risks… If you would give whale psychosis, and then they would change their grazing patterns, and then that would affect algae, and then that could affect coral.”

Yet he acknowledged one exception: in cases of human-caused disasters, where “if we fucked up and had some kind of oil spill… if that in that situation, it’s like, okay, sort of breaking the fourth wall… I would break protocol in that case.”

The conversation revealed fascinating insights about animal communication. Fonseca noted that “the reason we focus on cetaceans, whales, dolphins… is because their grammar structure is something that we can analyze… their click sequences… when you do frequency analysis on their click sequences, they extract grammatical features.”

But dogs and other animals presented different challenges: “A lot of their communication is position based… position of ears, position of tails… It’s not how we interact with dogs.”

Andrea Jordan raised an unsettling possibility about simulated animal companions: “Beyond the ethical risks towards the animals and the environment and nature, are we also risking like furthering the divide between man and nature?”

Morningstar offered a more mystical perspective: “There is a communication consciousness that happens. I’ve had lots of experience with that… I believe we have sensors for some of those things we pick up on, pheromones and other sensory perceptions that a lot of people are not aware of.”

Jody Solomon shared a personal anecdote about rehabilitating an injured crow: “I would make scrambled eggs every morning… and I would say, Eggy, waggy. And after a while, he would smell it when I was cooking it in the kitchen, and he would actually come into the kitchen and say Eggy, waggy to me.”

The discussion culminated in broader questions about symbolic representation in animal cognition. Fonseca distinguished between iconic, indexical, and symbolic signs: “I think most animals are sort of bound to iconic signs… slightly more advanced animals jump to more indexical type signs… bird calls… they’re indexical of danger, they’re indexical of mating… The dogs have figured out a way to sort of embed that dog board as indices to various things in the human world that they’re interested in. But I’m not quite sure if they have symbolically represented those things themselves.”

The Meaning of Meaning

Throughout the evening, participants grappled with fundamental questions about semantic versus syntactic information. Fonseca drew crucial distinctions: “The difference between traditional computers and AI systems… where is the semantic versus where is the syntactic? Regular computers we need them to be syntactic… our entire digital world depends on information being fungible.”

But with AI systems, “you’re starting to see… that the context matters, because the way that these networks are grown, so to speak, through gradient descent, through back propagation, those are processes. It’s more akin to gardening. It’s more akin to farming than it is to straight engineering.”

This led to a profound reflection on the nature of creativity itself: “We as meta optimizers are basically establishing this is how we want gradient descent to act… but the system itself sort of becomes a mesa optimizer underneath us, within itself, and may optimize for all manner of different things, and creativity and art may just end up being one of them.”

Conclusion: The Ongoing Inquiry

As these conversations continue to evolve within the CASHE x NY AI collaboration, the questions they raise become increasingly urgent. The upcoming June 2025 gathering promises to revisit these themes, asking participants: “What stuck with you most from the recent conversations? Where do you think art and creativity are heading next?”

The meetups have revealed that as AI capabilities advance, we’re forced to confront not just what machines can do, but what it means to be human in the first place. In wrestling with scenarios of AI creativity, the participants aren’t just exploring the future of technology—they’re excavating the foundations of human meaning itself.

Andrea Jordan captured something essential early in the evening: “I’m seeing AI as a medium… So like, what is it that we value? Is it, you know, is it skill? But then we also think, like, how do you even define skill when it comes to art?”

Some questions from these ongoing conversations remain unanswered: When machines can paint, write, and perhaps even dream, what becomes uniquely ours? And perhaps more unsettling: what if the answer is nothing at all?

These conversations continue, but the implications stretch far beyond the confines of virtual meetup rooms, reaching into a future where the line between creator and creation may prove to be nothing more than a comforting illusion we once believed in.

Based on transcripts from ongoing online meetups hosted by Tone Fonseca as part of the CASHE (Culture, AI, Science and the Human Experience) and New York AI meetup collaboration, featuring participants Gennadiy Gurariy, Viktoria Serdetchnaia, Warren Blier, Andrea Jordan, Vedang M, Jody Solomon, Morningstar, Frank Feldman, Martial Terran, and Magnus Hedemark. The collaborative series continues to explore questions about creativity, consciousness, and human meaning in the age of AI.