Drawing the Sound: Rhythm in the Age of AI and the Human Hand in Art

A Visual Story of Steelpan

When I think of visual representations of steelpan, Jackie Hinkson’s work first comes to mind for the way his hands recreate not just the appearance of pan, but its living essence. Translating rhythm, movement, and atmosphere into marks or brushstrokes, these works do more than record, they embody energy, history, and soul. Honouring the ways we translate our stories of our national instrument, means ensuring that the seen is also the felt—and that works by artists like Jackie Hinkson remain part of how we preserve and develop its spirit visually in the digital age. 

Jackie Hinkson, one of Trinidad and Tobago’s most celebrated visual artists, has spent over six decades honing this in his plein air creations. Hinkson has shaped the development of national art in the post–World War II and post-independence eras, receiving both an Honorary Doctor of Letters from the University of the West Indies and the Chaconia Medal (Gold) for his contribution to the arts. 

Hinkson’s work doesn’t merely depict the steelpan, it records the heartbeat of a steelpan performance and embodies its pulse. In his charcoal and ink renderings the arcs of players’ bodies bend to the rhythm, light dances off the curve of the pans, and the crowd vibrates in a turbulent harmony of individualistic expression. Lines cross in deliberate chaos, and the weight of each mark records the pan’s heartrate. Its movement and its music distilled into ink and memory stored on paper and canvas. 

Now, technology offers extraordinary tools to preserve and extend the reach of stories, freeing an artist’s work from the confines of gallery walls so it can travel, inspire, and educate far beyond physical boundaries. High-resolution imaging, augmented reality, and immersive environments not only preserve the soul of human expression but also create new ways to engage with it. These tools can bring cultural heritage into new dimensions, yet their true value lies in remaining anchored to the depth of human-made observation. Without that grounding, the technology is spectacle; with it, it becomes a bridge to deeper understanding. Imagine the energy of the steelpan yard in Hinkson’s work brought to life through animations or immersive exhibitions—traveling alongside steel orchestras, to visually share and deepen the story of people and place wherever they go.

Art, Science, and the Truths We See

Human artistic perception can anticipate or echo scientific observation in profound ways. Beyond aesthetics, this is about preserving history, memory, and movement in human-made art by documenting what has yet to be observed or measured scientifically. Great artworks depicting fluid flows have inspired some fluid dynamicists to analyze them just as they would real flows in laboratory experiments, field measurements, or numerical simulations — opening the door to quantitative, objective research on artistic representation.

Van Gogh recorded patterns in nature that science would only later quantify, seeing truths that lay beyond the reach of formal measurement at the time. The swirled skies in Vincent van Gogh’s Starry Night (1889), Road with Cypress and Star (1890), and Wheat Field with Crows (1890) remarkably capture the physics of turbulent flow with mathematical precision (Aragón et al., 2008). Through intuitive, expressive brushwork, Van Gogh rexreated complex visual patterns mirrored in the statistical structure of turbulence. Turbulence itself was only formally described decades later by mathematician Andrey Kolmogorov in the mid-20th century.

“This result suggests that van Gogh had a very careful observation of real flows, so that not only the sizes of whirls/eddies in The Starry Night but also their relative distances and intensity follow the physical law that governs turbulent flows.”
— Sherman et al., 2023

The human eye—trained by lived experience rather than computational models—reveals truths that science would later confirm. Whether mapping the rhythm of a steelpan yard or the restless motion of the night sky, handmade records offer a bridge between feeling and fact. They preserve the patterns of our world in forms that can be experienced now and studied for generations to come.

AI and Quantitative Research on Artistic Representation

If art can echo scientific truths with mathematical precision, as Van Gogh’s brushwork captured turbulence decades before it was mathematically defined, then AI offers new ways to analyze, extend, and even test these artistic records. By processing vast amounts of visual and sensory data, AI can detect patterns and structures hidden in paintings, music and performances, turning what was once subjective perception into a quantifiable record.

Researchers are already showing how this works. At Rutgers University, algorithms have been trained to analyze over 80,000 brushstrokes from Picasso and Matisse, identifying forgeries with striking accuracy. Mathematician Dan Rockmore has similarly extracted the “fingerprint” of Rembrandt’s brushwork to authenticate paintings. These examples demonstrate that AI can translate artistic gestures into measurable data. The analysis process includes digitizing paintings, breaking them into grayscale squares, extracting stroke characteristics (like slant and thickness), and plotting them in multidimensional data space to identify stylistic clusters. The question becomes: can AI move beyond questions of authenticity and style to translate artistic vision into models that connect with physics, biology, and cultural life?

Imagine scanning Van Gogh’s Starry Night to generate mathematical descriptions of turbulence in the painted sky, descriptions that build on Kolmogorov’s later equations. Could artworks become raw data for rediscovery, with AI bridging human perception and scientific measurement? In this way, the human body, through art, becomes a recording instrument, capturing rhythm, atmosphere, and movement all at once.

This potential becomes even more compelling when considered in the Caribbean context because of the syncretisation of cultures and ideologies. The steelpan, forged from iron once used for shackles, was transformed into an instrument of freedom and collective joy. Iron also courses through the body in blood, and is a material used in communication technologies to  concentrate magnetic fields for antenna cores. and enable new spintronic devices capable of ultrafast, high-frequency signal processing. 

Jackie Hinkson’s plein air drawings of panyards capture these resonances to embody the physics of sound, the vibration of iron, the rhythm of crowds, and the atmosphere of shared energy. With AI’s capacity to process large datasets, can such artistic records be analyzed quantitatively, translating embodied observation into scientific insight with potential applications in medicine, acoustics, and communication systems?

AI’s potential here is not limited to reproducing an artist’s style or detecting forgeries. It can treat art as a dataset and an archive of human perception. By analyzing brushstrokes, colours, and compositional rhythms, AI can uncover truths about environment, climate, sound, and culture. What might Hinkson’s panyard sketches reveal about how Caribbean space and sound interact with bodies? Could AI read these visual archives as both cultural memory and scientific record, bridging the intimate and the measurable?

Co-imagining with AI for Scientific Discovery through Art

Yet the challenge remains: AI organizes patterns from what already exists, while human creativity disrupts patterns, breaks through expectation, and invents the new. To co-imagine with AI, we must remain attentive to how technology shapes our responses. Used responsibly, AI can become a partner in extending the human hand, eye, and ear into new terrains of knowledge.

Artists and researchers worldwide are already experimenting with such co-imagination. Sougwen Chung collaborates with robotic arms trained on her gestures, transforming drawing into a dialogue between human and machine. Refik Anadol transforms museum archives into immersive data-driven environments, while the French collective Obvious is exploring how brain scans might be translated into visual forms. These experiments point toward AI not as a replacement for creativity but as a collaborator, extending human imagination into new domains of discovery. Art is not only about what we see, but about what we feel, measure, and carry forward as knowledge.

Co-imagining our Visual Landscape 

In an age of AI-generated images, I’m heartened when companies invest in artists who bring colour, texture, and human touch to our digital and shared spaces. I hope the curation of our visual landscape continues to prioritise human expression alongside the efficiency of digital creation. Just as we value diversity when building teams, we should value diversity in our visual language—utilizing algorithmic perfection and digital design to complement human representation, gesture, and soul.

As we move forward, cultural institutions, policymakers, and brands have a responsibility to weave cultural preservation into their visual strategies. This means safeguarding and promoting existing artworks that embody our collective memory. The rhythm of the steelpan deserves to be seen, studied and celebrated in the images that will tell its story to generations yet to come.

References

• Aragón, José & Naumis, Gerardo & Bai, M. & Tôrres, Márcio & Maini, Philip. (2006). Turbulent Luminance in Impassioned van Gogh Paintings. Journal of Mathematical Imaging and Vision. 30. 10.1007/s10851-007-0055-0. 

• Sherman, Aleksandra & Anderson, Derek. (2023). How art contributes to scientific knowledge. Philosophical Psychology. 38. 1-21. 10.1080/09515089.2023.2241499.