Seeing that tall black and brown piano in the background before our interview, I sense tradition of human creativity meeting AI. This is about us.

When Maya Ackerman’s family immigrated to Canada, her piano stayed behind in Israel.

That instrument had been more than wood and keys. It’s where emotions melt into music into a feeling, processing change with simple sounds arising from deep wells of experience.

The piano was, and is, her creative partner - even when it wasn’t there.

Don’t Give Up Your Piano: A Conversation About Creative Machines That Serve, Not Replace

Now, as a professor at Santa Clara University and CEO of WaveAI, Ackerman sees us at risk of losing something far bigger: our collective creative piano.

Not to AI itself, but to fear of what AI might become.

Her new book Creative Machines: AI, Art & Us launches with a message that cuts through the replacement anxiety:

“AI has always been, and will always be, all about us.”

Ackerman spent years in foundational machine learning before a talk by artist Harold Cohen changed everything.

She switched to computational creativity, that unpopular intersection where machines meet human expression.

She’s built AI tools for musicians. She understands both the technical architecture and the artistic soul.

What emerges from our conversation isn’t just about Creative Machines or AI technology.

It’s about us, the creative spark in people. Will we surrender our creativity because AI machines seem capable?

Or will we build humble creative machines that expand human expression?

Let’s walk through what that choice means.

1: The Piano as Lifeline: Why Creativity Matters Now

When I ask the question about what the piano means to her, Ackerman’s voice waivers describing losing her piano for the first time:

“I think creativity was a lifeline for me in a way. Through all this moving around the world... at the piano, my feelings would pour out of me, and I would sort of get to process things that otherwise would just sort of sit dormant and fester inside of me.”

That processing matters. Creative expression is how we make sense of displacement, trauma, change. It’s how we stay human through upheaval.

And it’s how we connect through art to other stories, experiences, history, and fear.

Creativity is our lifeline arising out of the depths of human experience.

Making this moment in history unusually dangerous:

“Now we are at a time in history where people wonder if they should even bother to be creative. Good people.

People who are just afraid of what’s going on in the world. And I don’t want the whole planet to lose the piano, so to speak, the way that I did.”

The fear is real. I see it in creators who message me, asking if learning creative skills still matters when AI can generate images, write copy, compose music.

The replacement narrative sinks deep.

AI Imposter Syndrome, AIS, where we feel like imposters compared to AI, but know deep down AI is generating a ton of slop.

And Ackerman offers a different frame:

“The age of AI doesn’t have to be about taking away creativity for us, it can be the opposite.

It can be about making us more creative, giving us more power...

It’s so important that we don’t hang up our hands because we’re scared, right?”

This isn’t naive optimism. It’s foundational clarity about what we’re really building. Intention matters, now more than ever.

2: Harold Cohen’s Scream—Where Does Creativity Live?

Over 10 years ago, Ackerman sat in the back of a conference room, disappointed with her choice to study machine learning, inspired instead by music and singing. She didn’t know what to do with her life.

Then Harold Cohen took the stage.

The pioneering artist behind AARON—one of the earliest creative AI systems—flashed beautiful images on screen. Maya remembers that he starts screaming:

“This old Jewish man screaming on stage.

‘I was the only voice of reason, saying that I was the creative one.’

That’s what he’s screaming.

How other people were arguing that his machine is creative, but he was the only voice of reason, telling them, look, no, he is the creative one.”

The rawness of that conflict between machines and humans, where creativity lives with 2 sources, felt essential to Ackerman. She switched her entire research field.

Years later, at the end of her book, she returned to Cohen’s insight:

“The machines that we make for us are ultimately all about us, and we need to hold on to the torch and take this responsibility seriously and build the kind of world that we want.”

Creative Machines aren’t the villain or the savior. They’re mirrors and tools.

The question isn’t whether they can create.

It’s what role we design them to play.

3: The Bach Test: Facing Our Bias About Machine Creativity

David Cope’s EMI (Experiments in Musical Intelligence) revealed something uncomfortable in the 1980s. He created what became known as a discrimination test:

“People would be given music and not told which piece was made by a machine, which piece was made by the original Bach in this case.

And overwhelmingly, people got it wrong.

People thought that music made by the machine was actually an original Bach, and at the same time believed that the original Bach was made by machine.”

Read that again. When people didn’t know the source, they preferred machine-generated Bach. When told which was which, their preferences reversed.

“This was able to reveal that sometimes it’s not the quality of what the machine creates, but the fact that a machine created it that makes us devalue it.”

Cope later renamed the system “Emily Howell”—humanizing it. With a name, people accepted the work as “human”.

Our bias against machine creativity runs deep. Ackerman argues we need to stop lying to ourselves about it:

“The whole resistance to the idea of machines being creative, saying ‘no, no, no, they’re not really creative, they don’t have feelings, they’re not really creative, blah blah blah,’ is a way to make ourselves feel better, but actually convoluting the story.”

She suggests something harder:

“I think it’s much more healthy for us as a society to admit that machines are being creative. Maybe not in exactly the same way as us, right?

Maybe in a somewhat different way. They have some different strengths and weaknesses from us.”

By admitting machines participate in creative arenas, we can ask the right questions: Given that they can be creative, how do we want them to operate in our world?

What kind of role do we want them to take?

Do we want machines performing on stage while we watch?

Or helping in the background while we create?

4: Shadow Work: Creative Machines as Cultural Mirror

I told Ackerman about visiting the Museum of Tolerance in Los Angeles years ago. At the entrance, two doors: one labeled “Prejudiced,” one labeled “Not Prejudiced.”

Everyone walked toward “Not Prejudiced.”

That door was locked.

The metaphor hit hard—none of us can walk through the “Not Prejudiced” door. We all carry bias, whether we admit it or not.

Creative Machines function as similar mirrors, revealing what we think under our virtue signaling surface.

Ackerman describes AI as “collective consciousness for a specific culture”:

“If we look at a lot of the models we have today, there are collective consciousness to Western data, to Western consciousness.

A lot of their tending towards the mean has to do with a kind of data that we’ve replicated many, many times online.

We copy each other and then it kind of amplifies the aspects of our culture that has been echoed the most.”

Then comes the shadow:

“We know that there is terrible stuff going on. We know there is racism and sexism, and we like to think that it’s out there somewhere else, far away from us. Right?

We also like to think that there is sexism and racism, but not inside this brain... And yet there is so much research showing that every single one of us has implicit biases.”

One research project gave AI a picture of a person along with a profession—a woman labeled “professor” or a man labeled “model.” The results were shameless:

“The machine would take the woman who is now a professor or CEO and give her a beard... Or the guy suddenly has makeup and then lashes.

Now that he is a model... It’s telling us, oh, it’s too feminine for a guy to be a model.

Oh, if a woman is a professor, there must be something masculine about her.”

The AI doesn’t hide what humans would never verbalize. It screams our collective biases back at us.

“And it’s so shameless about revealing the societal biases in a way that humans would never verbalize... the model is showing us what we really think u...