Computational Photography: AI & Creative Process – Episode 21

In this weeks episode of Modem Futura Andrew Maynard and I take you through the lens to discuss how technology, especially AI, is reshaping not only photography, but the creative and artistic process. From the evolution of cameras to the rise of smartphones and computational photography, the conversation highlights how advancements have democratized the art form, making it accessible to everyone, and raise the question of how we can keep it human-centric as advancements in AI threaten to push everything to the middle.

We ask some tough questions around what is gained and what is lost with new technological advancements? Especially in creative mediums or processes? Is bigger, faster, stronger always better? Join us in this episode as we explore these issues through the “lens” of photography - that has implications and lessons to be learned for nearly all creative human activity.

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Evolution of Camera Technology (a brief truncated version)

In true Sean form, we have to start at the beginning to understand and perhaps better appreciate how photography has evolved remarkably since its inception, transforming from intricate chemical processes to today's seamless integration of AI and computational power. In this episode of Modem Futura, we explore this incredible journey and discuss the fascinating implications for art and authenticity.

Starting with the pioneering efforts of Joseph Nicéphore Niépce in 1826, photography began as an art rooted deeply in science. By 1839, Louis Daguerre’s Daguerreotype significantly reduced exposure times, turning photography into a viable commercial enterprise. George Eastman further democratized photography with his Kodak box camera in 1888, making it accessible to everyday users with the iconic tagline, “You press the button, we do the rest.”

Film photography dominated the 20th century, highlighted by innovations such as Kodak’s Brownie camera, Leica’s compact 35mm system, Polaroid’s revolutionary instant photography, and professional-grade Single-Lens Reflex (SLR) cameras by Nikon and Canon (as well as many others like Olympus which will always have a soft spot in my heart). These developments broadened photography’s reach, allowing individuals and professionals alike to capture the world more vividly.

The digital revolution of the late 20th century marked a critical shift. From Kodak engineer Steven Sasson's rudimentary digital camera in 1975 to consumer-friendly models like Sony's Mavica (this is the one with the 3.5 inch floppy disk) and Canon’s PowerShot, photography swiftly transitioned from film to digital. Canon’s EOS D30, Panasonic and Olympus's mirrorless systems, and Nikon’s groundbreaking D90, with its video capabilities, set new benchmarks in versatility and innovation.

The smartphone era that kicked off in 2007 to today has further revolutionized the field. Advances such as dual lenses, computational photography, and AI-driven enhancements became commonplace, allowing users unprecedented creative possibilities. Smartphones with AI-driven multiple camera systems and Apple's introduction of dual-lens setups marked significant milestones. The simple fact that you can hand hold a smart phone and take night shot s

The Rise of Computational Photography and Future Horizon

Today, it seems that computational photography defines much of our visual culture - and in some instances is hard to work with camera platforms that don’t engage in some levels of automation. AI-driven enhancements, electronic viewfinders offering real-time adjustments, and algorithmic image processing have significantly altered photography. These innovations raise essential questions: Can art remain authentic amid such computational manipulation? When you look into your viewfinder or the display screen - can you trust what you see? Again here we ask what is gained by the advancement of this technology and what is lost?

Are we potentially setting up a new generation of visual artists that will miss out on the knowledge and language of how to control their image - surrendering all aspects of the photograph making to automated machine learning processes? I have taught for years, that we must know the rules of photography visual medium so we can effectively break them to tell a story, or convey expression, or evoke a feeling… to miss out on that is to push everything to the middle… potentially diluting not only the images we see and interact with, but the very message the artist was trying to make.

Ultimately, this evolution prompts critical reflection: Is computational photography enriching or diluting artistic authenticity? This debate continues as photography moves further into an exciting, digitally driven future. And of course photography is not alone, this same question can (and is) being raised at all levels of human creativity and mediums of expression and art.

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