Donna LaLonde

In the April 2023 issue of CHANCE, we issued a generative art challenge. “A person paints with their brains and not with their hands.” This quote, attributed to Michelangelo (and modified by us), captures the spirit of our art challenge—”Pixel by Pixel: The Art of CHANCE.” For this challenge, we wanted our readers to use their brains and computational skills to create generative art. We introduced this challenge as a next step in meeting CHANCE‘s mission to use data to advance science, education, and society. Our goal for “Pixel by Pixel: The Art of CHANCE” was to encourage and showcase the skills and knowledge of data science while highlighting the creative applications of the discipline.

The theme for this challenge was creativity, so we purposefully established few rules or constraints. We required that an artist serve as a muse for the generative art. The artists Vincent van Gogh, Pablo Picasso, Jackson Pollock, Edvard Munch, Salvador Dalí, and Corita Kent were the group from which a muse was to be selected. The second requirement used the art historian Jason Bailey’s description of generative art in “Why Love Generative Art?” He described generative art as, “art programmed using a computer that intentionally introduces randomness as part of its creation process.” Submissions required the image created, the code, and a description of how the image was created. In this article, we are delighted to share the winning submissions.

Winning Submissions

The winning entry in the student category was submitted by Lexie Hassien. Her submission is an interpretation of Vincent van Gogh’s “The Olive Trees,” which was painted in Saint Rémy, June–July 1889. The reference art can be seen on the Museum of Modern Art in New York City’s website.

The winning entry in the professional category was submitted by Giulio Stancari. The piece is titled “Dynamic Rubies.” It is inspired by Van Gogh’s use of primary colors and complex patterns, as in “Starry Night.” In this work, randomness enters two different ways: as pseudo-random numbers for the initial conditions and for the system parameters and as regions of apparent random motion interleaved with regular patterns.

Hassien’s Process

In late 2021, I visited the Dallas Museum of Art’s exhibition “Van Gogh and the Olive Groves,” where I could see the painting in person. My fond memories of this exhibition motivated me to create my interpretation of “The Olive Trees” through generative art.

I used flow fields to create dynamic curves that emulate the style of not only Van Gogh’s “Olive Trees” but also his other works such as “Starry Night.” In my artwork, the soothing color palettes for the sky, mountains, trees, and grass were based on true colors from the painting.

The R code I wrote uses some internal functions from the aRtsy package as well as ggplot2. I used the cubic noise generator in the aRtsy package to initialize the angles of the flow field. I also used custom sine waves with random jitters to smooth out the transitions between the horizontal color palettes.

The current version of the code takes approximately 25 minutes to run, but a simplified version of the image can be produced by reducing the number in the “lines” variable.

Stancari’s Process

The piece is titled “Dynamic Rubies,” as patterns and colors were chosen to resemble a collection of jewels, obtained with the computational techniques of dynamical systems. (“Dynamic Quilt” was also an option.) The contest specified a list of artists to serve as creative muses. This work was inspired by Van Gogh’s use of primary colors and complex patterns, as in the famous “Starry Night” series.

The image was generated using the equations of nonlinear dynamics. Nonlinear dynamical systems have a wide range of applications, including physical sciences, ecology, and social sciences. These models also describe the motion of particles in accelerators, where accurate and robust predictions are needed for the design and optimization of complex experiments. In each panel of the image, the horizontal and vertical coordinates represent the positions and momenta—recorded at regular intervals—of particles subject to nonlinear forces for different values of the oscillation period. Colors mark different initial conditions.

The work of Henri Poincaré at the end of the 19th century intimately combined dynamics and geometry, for example, in the investigation of the stability of the solar system. It was shown that even simple laws describing time evolution, expressed as nonlinear differential equations or as discrete transformations, can create a wealth of phenomena with direct geometrical interpretations: stationary points; periodic orbits; chaos. It became clear that knowing the laws governing a system can differ greatly from being able to make long-term predictions.

From the experimental point of view, the statistical analysis of a system’s observable properties plays an important role in the determination of its governing laws and in estimating the magnitude of stochastic effects. In this piece, randomness enters two different ways. First, pseudo-random numbers are used as initial conditions and as parameters in the equations. Second, deterministic chaos arises in the system’s behavior—regions with points apparently scattered at random are interleaved with regular patterns.

The “Pixel by Pixel: The Art of CHANCE” challenge provided an opportunity to illuminate the intersection of data science and creativity. Our winners demonstrate the potential of generative art to inspire, provoke thought, and evoke emotion. The diversity of approaches highlights the versatility of data science as a tool for fostering innovation across disciplines. Our goal for this challenge was to provide an opportunity to focus on the mission of CHANCE—to use data to advance science, education, and society. Reflecting on the outcomes, it is clear we were successful. The submissions represent more than just a technical achievement—they engage with the creative process.

We will work to create new challenges that reaffirm the profound impact of statistics and data science on advancing science, education, and society. The possibilities are boundless, and we invite you to help us by contributing ideas for future challenges! Code to create the artworks can be found in the supplementary materials.

About the Author

Donna LaLonde is associate executive director of the American Statistical Association, where she works with colleagues to advance the ASA’s vision and mission and supports activities associated with presidential initiatives, professional development, and accreditation. Before joining the ASA, LaLonde was a faculty member at Washburn University and served in various administrative positions, including interim chair of the education department and associate vice president for academic affairs.

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