Daniel Temkin uses code and other devices to manipulate how we understand photography and visual perception.

I first came across Daniel Temkin's Straightened Trees series in late 2016 when I was curating "Future isms," Humble's exhibition that used utopian/dystopian images as a metaphor for the dark times and uncertainty surrounding the United States presidential election. Buildings and power lines twist and contort around artificially "corrected" trees, calling into question what is real, what's human-made, and how we conjure a landscape-ideal. Temkin's trees, which he makes by using an algorithm and code injection to alter the digital structure of a straight, large-format photograph respond to a need to control a messy world. A critique of perfectionism. A landscaping rhinoplasty with disastrous consequences.

Like Straightened Trees, Temkin's larger practice is all about the conflict between human thought and logic. It reflects the two worlds he straddles: photography and computer programming. In a recent exhibition at New York City's Higher Pictures Gallery, he paired his trees against his new series Dither Studies.

For those, like myself, who are likely unaware of what "dithering" is, it's one of the most fundamental algorithms of contemporary photography, dating back to the 1970s when it was used to translate color or grayscale images to black and white pixels. The process allows a limited color palette to take on the look of a gradient image. Kind of like a highly pixelated ombre sky. Temkin hand renders these images in acrylic on panel, turning each pixel into a square of color, with highly psychedelic results. While visually dissimilar, Dither Studies relates to Straightened Trees in its push to pull apart the image-making process, confronting the strange and illogical structures of human and machine-based perfectionism.

A presidential term (and a much more frightening world) deep into my admiration for his work, Temkin and I spoke to bring it together.

Jon Feinstein in conversation with Daniel Temkin