Put together. Falling apart.

Put together. Falling apart.

A few notes on entropy.

Life is a self-organizing system. It coalesces available resources into sustainability at least to the point of reproduction. Putting together is the process of life. It is an evolutionary necessity. And yet, falling apart is necessary for evolutionary progress. That is the genetic mutations that increase species’ adaptations to the host environment.

What an amazing system of adaptation is Homo sapiens. We can adapt in real time, adjusting our psychological responses to perceived or anticipated experience. Psychology can manifest as a physical force.

When I first began taking pictures, in 1980, using a brother’s Nikkormat 35mm camera, I took them to see what things looked like in a photograph. By the late 1980s, I had switched to slide film. The purity of it. Reality in miniature that could be projected on a screen, larger than life. It said something in the small and the large. Projecting images on a screen nearly 2 meters diagonal made it fun to do with other people. An art event.

A picture operates within the frame of information theory. In 1949, Claude Shannon proposed an information theory that reframed data transmission as a system addressing three problems.

(1) The technical problem of how information is transmitted from a sender to a receiver.

(2) The semantic problem of how precisely a transmission conveys intended meaning.

(3) The effectiveness problem of the transmission bringing about the desired end.

Significant is that Shannon used entropy as a measure of information. A low value for entropy means the information is highly organized. It’s certain in its content. A photograph with low entropy conveys the same thing to every viewer.


My childhood picture has a unique point of view to me. I call it The Prediction because, to me, my present-day brothers and I are already in the picture. Since very few people know all three of us, then or now, most viewers can’t see the image as I do. Its effectiveness is limited. As a photographer, I struggled with all three problems, but the real-time experience of a slide show highlighted the effectiveness problem.

Like the over 1 trillion other pictures taken each year, most of my photos are deliberate records. And a slide show is a similarly deliberate event where the viewer takes on the conscious role of receiving the record. I struggled when viewers saw the same image I did, but we didn’t see eye to eye. Some pictures, as information, weren’t effective. They did not fully “work.”

This is the photographic challenge. How can an image work? How might a photographer address the technical, semantic, and effectiveness problems? It’s here that psychology meets physics. The programmability of human psychology creates as many points of view as there are people. Uncertainty is at the heart of entropy. The uncertainty of a viewer’s psychology is at the heart of the photographic challenge for those trying to say specific things to others through photography.

Portrait photography has to address that challenge. But since people are complicated, it’s hard to break through a viewer’s existing notions of a person. Portraits either confirm beliefs or they are propaganda. Art is a struggle with classification.

Knowing that people classify what they see, and 1 trillion images a year can’t be wrong, I try to have fun by increasing the entropy in the image. I introduce uncertainty into the system of classification. I can more fully engage the muse of entropy because I use color, contrast, and composition in ways that put some things together while letting other things fall apart. Macro photography magnifies the impact of subtle shifts in light, camera position, and camera-to-subject distance. Different lenses have different fingerprints. They render differently. Camera settings for shutter speed and aperture have their impact.

At the extreme, I close my eyes and have the muses play a larger part in the photographic process. I can then be a viewer, too, and see what has fallen apart and what has been put together.

Dean Ritz is a technology strategist with a focus on mechanisms and models for data transparency. He has published on topics of ethics, organizational theory, and data standards as public policy for Oxford University Press, Routledge, and Springer-Verlag. Most recently, he wrote a policy paper for the Data Foundation in the US. His photographic work can be seen at his home and in a couple corners of the internet. He and his prime mate live in the US.

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Ideas for change