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Gabrielle Lamb

Gabrielle Lamb Choreographs “Orange” Inspired by Trevor Paglen

Katy Donoghue

25 October 2017

The experimental dance troupe BalletCollective premieres “Translation” in New York at the NYU Skirball Center October 25, 26, and 27. The program includes debuts from choreographers Troy Schumacher and Gabrielle Lamb, danced by members of the New York City Ballet, with scores performed live for the first time.

BalletCollective, founded by Schumacher, pairs choreographers with artists and composers to create a truly collaborative piece. “The collaborative process is everything to us. It pushes us to consider different artistic methods, to bend and stretch our notions of traditional ballet and the world around us,” said Schumacher in a statement. “This year, we began by asking novelist Ken Liu and artist Trevor Paglen to share an original work that deals with various perspectives on translation. Vastly different yet equally poignant, the works inspired new combinations of movement and musical in way that we hope expands the language of dance and resonates with a wide audience.”

Gabrielle Lamb

Photo by Cole Wilson

Lamb looked at Paglen’s recent work where he taught a computer to “see,” resulting in machine-generated images of objects. Focusing on an orange image, a score by composer Caleb Burhans was written, to which Lamb choreographed Orange.

In advance of the debut tonight, Whitewall asked Lamb about creating Orange with composer Burhans and Paglen.

Gabrielle Lamb

Photo by Cole Wilson

WHITEWALL: Can you tell us about your initial reaction to Trevor Paglen’s work?        

GABRIELLE LAMB: In our first conversation, Trevor introduced Caleb Burhans and I to his project on machine vision—a series of images generated by computers he trained to see and, then, to reproduce on command images of objects or subjects they knew. He showed us a few of the image sets he used in training computers to “see” — thousands of thousand pictures of an orange, of a basketball, of a pumpkin, are introduced to a neural network so that the network can begin to “recognize” and differentiate it.  Once trained, the network begins to generate its own images of these objects: hazy, colorful, and abstract to us, but to the network absolutely distinct.

Gabrielle Lamb

Photo by Cole Wilson

I asked Caleb which of the images from the training process attracted him, and he said the orange. So, we started working from that.

WW: How did you translate that into choreography?

Gabrielle Lamb

Photo by Cole Wilson

GL: Caleb took the first steps of translating Trevor’s concepts into music. He described the opening of the piece as a “void horizon” filling with pitches and momentum as the AI learns about the orange. He told me that he intentionally rewrote that section many times in order to give it the feeling of AI recalibrating after every new piece of information.

His insight helped me to imagine ways the dancers could move around the stage, at first as disconnected bits of information, and then later as connected parts of a more sophisticated whole. There’s a melodic climax, which I chose to use for a whole-cast section of large, full-bodied dancing. Then he returns to the chords from the beginning, only this time like a machine grinding to a halt. That was fun to put into movement.

Gabrielle Lamb

Photo by Cole Wilson

Sometimes it felt most important to respond to the melancholy in Caleb’s music. I felt a similar melancholy learning from Trevor about AI and the strange, alarming things it can do; and I wanted to get some of that mood onstage.

The dancers and I also spent some time playing with real oranges in the studio. We made a short arm phrase that involved rolling the oranges on the floor, or along our bodies, switching them from one hand to another. Then I got rid of the oranges and tried to preserve the integrity of the movements in space. I always knew I wouldn’t actually use the fruit onstage, but I liked the idea of a starting point that disappears back into the work and is never seen by the audience, similar to how the image of the orange is used in the AI training process.

Gabrielle Lamb

Photo by Cole Wilson

To be honest, you can only translate so much. It was important to me to make a work that had integrity as a dance piece, that could stand alone without a knowledge of its source.

WW: As a choreographer and dancer, what did you connect with in Trevor’s practice?

GL: Trevor’s practice is fascinating. It’s political and cerebral, and he realizes his work on a large scale.  It’s also quite different from my own practice. For example, Trevor studied geography and many of his projects involve long distances: satellites, undersea cables, or photos taken from far away. I work with the body, and I originate much of the choreographic language in my own body before I take it to a roomful of dancers. He’s working on a very large scale; he’s thinking in miles. I’m working in the kinesphere and thinking in terms of inches and minutes. This difference in our approach was interesting to me. Also, I was attracted to (and intimidated by) Trevor’s practice—it is conceptually rigorous and aesthetically beautiful.

Gabrielle Lamb

Portrait by Ken Kramer

WW: This was your first time working with a commissioned score. How would you describe collaborating with Caleb?

GL: Caleb was definitely the right composer for this collaboration. I was at first intimidated by the cerebral aspect of Trevor’s work. I wondered: how we could ever bring these concepts into music or movement? But Caleb is very grounded, and he seems to know how to zoom in on one thing, without worrying about what else might get left out. And yet he was also able to relate his composition to Trevor’s machine vision series in a way that worked. His descriptions of the musical process and structure helped me to find my way whenever I got lost in my own process.



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