Research doc.

Forward/Introduction

First let me introduce myself, I’m Sanne Schilder a fourth year photography student. Like a novel, I wanted photography to be an extension of myself. Collecting images of time and space where I was tempted to press the shutter. Throughout my study those thoughts soon disappeared completely.

My urgency lies within the image. Ever since I was little, I was fascinated on how the image was a mediator between the world and myself. It was an entrance to make the world imaginable. It did not take long before I wanted to harvest my own images of the world. So in order to collect and appropriate the image, photography was the medium that I grabbed on to. At the beginning I made snapshots for my own satisfaction. But that seemed to disappear partly over time. I missed the craft and the possibilities to explore the material. I experiment with photosensitive films and papers, chemicals and webcams. But I was looking for a different kind of knowledge. Photography, as we all traditionally known, had undergone a transition. The further I came to realize that, the more I wanted to dissociate myself from its tradition. The deluge of images, the saturation, has prompted me to ask if it still makes sense to photograph in his existing framework. Everyone with a camera these days can make pictures without knowing about the complex processes.

So as an image-maker in the digital age I think about new ways of seeing. When the world changes, the image together with it. Today, in the age of smart phones, Google Earth, satellites and CCTV, image practices become all pervasive. The definition of photography expands. Opening new possibilities. Fred Ritchin once remarked: “Photography, as we have known it, is both ending and enlarging, with an evolving medium hidden inside it as in a Trojan horse, camouflaged, for the moment, as if it were nearly identical: its doppelganger, only better.” Without question, the photographic landscape and image-making devices will change and it will play a fundamental role in many basic elements of our lives. The development makes me very curious and that is why I do not abandon mine practice. I haven’t seen anything yet.

Abstract

Not only humans perceive the world, as an topic I turned my attention to machine vision. This research offers ways of thinking about photography that may enlarge our skill to explore and perhaps even improve image-making. The developments of the medium has always been closely linked with technological capabilities of a culture. Now we have entered the digital age, something unthinkable has happened. Images become disconnected from human acting and human vision. I attempt to see from their perspective; how do machines perceive the world and can they be a legitimate voice in the discourse of photography? No doubt this innovation will affect visual culture and transform society. Through this project I will explore in what way machine perception can expand the field of photography, open our view of external reality and aesthetic integration.

Central Question

In what way can machine perception expand the field of photography?

Relevance of the Topic

The contemporary revolution in photography offers opportunities that exceed wildest expectations. The medium is embedded in our everyday life on many different levels: from automated license plate recognition systems, Google Earth, Instagram, drones media to the advent of infinite image storage. It contains many different kind of technologies, imaging devices and practices. The photographic landscape has ultimately transformed society and affect visual culture. “Photography can therefore be described as a technology of life: it not only represents life but also shapes and regulates it–while also documenting or even envisioning its demise.” (Zylinska) To my mind, photography as it was once understood, has going beyond his existing framework and perception. The definition extends to help us see what photography has become. Photographs are no longer positioned as a discrete object, like the traditional way. Billions of images are added daily and this saturation has prompted me to ask if it still makes sense to photograph in his existing framework. Everyone these days has cameras and image-processing software at his or her fingertips. Knowledge of craftsmanship is no longer necessary to produce an image-quality that was only possible with years of practise and training in equipment. I attempt to find a new perspective through exploring this deluge of images; I had to look critically again. The developments are going so far that over the last decade or so, something radical has happened. In this posthumanist world, the human is no longer automatically the subject who sees. The shift has been barley noticed; an invisible landscape of images produced by machines for other machines to see. Trevor Paglen introduced me to “the idea of photography as seeing machines and explore questions such as: How do we see the world with machines? What happens if we think about photography in terms of imaging systems instead of images? How can we think about images made by machines for other machines? What are the implications of a world in which photography is both ubiquitous and, curiously, largely invisible? Paglen proposed a simple definition that has far-reaching consequences: seeing machines.” (Paglen)

“Now objects perceive me,” the painter Paul Klee wrote in his notebook, according to Paul Virilio in The Vision Machine. The French theorist explains that we are on the verge of synthetic vision, the automation of perception – “ a machine that would be capable not only of recognising the contours of shapes, but also of completely interpreting the visual field.” – (Virilio 1994* 1988) Historically, the performances of machines go beyond expectations. In the field of perception, the process in order to sensory information and turn it into concepts, the understanding became a reality. Trough deep learning or A.I., computers and devices are able to do some of the things that brains do. Inspired by natural evolution, Artificial Neural Networks use a process that is called evolutionary algorithms to generate a variation of patterns – composed in several layers, unrecognizable to humans. This set of patterns might look absurd to humans but for machine vision they are the most realistic representation of a certain thing. They single out the best “performing” ones: the image that the system classifies with a high percentage of probability. But what came completely unexpectedly is that machine perception has a connected with machine creativity. Can machines turn a concept into something out there in the world? Blaise Agüera y Arcas a software engineer, software architect and designer explains this connection: “I think Michelangelo had a penetrating insight into to this dual relationship between perception and creativity. This is a famous quote of his: "Every block of stone has a statue inside of it, and the job of the sculptor is to discover it." So I think that what Michelangelo was getting at is that we create by perceiving, and that perception itself is an act of imagination and is the stuff of creativity.”(Arcas) If your think from this point of view, that perception and creativity are intimately connected, than any creature is able to create and are by no means uniquely human.

In closing, I think that there is a new frontier and it will challenge the established ways of seeing. The embracing of machine perception will introduce us to a “New Vision”. This double point of view will expand our understanding, just like the invention of photography. I wonder, if photography became this life-shaping medium what will his nearly identical replica achieve? The development of photography has been from his origin a process of increasing awareness of the concept of knowledge and supported our visual capacities if there where inadequate. “Embracing nonhuman vision as both a concept and a mode of being in the world will allow humans to see beyond the humanist limitations of their current philosophies and worldviews, to unsee themselves in their godlike positioning of both everywhere and nowhere, and to become reanchored and reattached again.” (Zylinska 15) As an artist I think it’s very exited to adopt this “New Vision”. As machine intelligence develops, can it be a legitimate voice in the discourse of my practice? In which aspect will it engaging with external reality and aesthetic integration? In ways, it’s hard to imagine from today’s point of view, but I think this can be a new entrance to make the world imaginable.

Hypothesis

Approaching ‘seeing machines’ will introduce me to a new field of algorithms. Appealing is that they rely on photographic technologies, so in the end I still work with images. Focussing on the aspects of machine-to-machine communication I hope to find life in photography again, stimulating new approaches. In the ideal scenario, seeing machines become a tool, which expand our minds about how we vision the world: escaping my personal point of view to give new insights. This understanding of ‘seeing machines’ has to take into account that it is an extension of the photographic medium: The consequences are that I have to inquire myself with the history of machine image production. Through the artistic-based research I submit myself with the questions that calls for reflection and debate. By adopting this “New Vision” I wanted to make my work only perceivable for machines: photographs that are not optimized to be seen by human. The world they’ve shaped looks nothing like the world we thought we lived in.

Research Approach

‘Seeing Machines’ was the working title of my artistic-based research. I came across this concept a year ago in an interview with Ola Lanko. This understanding is much more all-encompassing, comparing to ‘photography’ leaving little to the imagination. Although I could not exactly explain what it would contain and of this should be accepted as photography. So, to reinvent the medium for myself I searched for literature and projects within this domain.

Paglen introduced me to the idea of ‘Seeing Machines’ and from this question based text I was confident enough to submit myself with the question if machine perception can expand the field of photography. To make the content visible of machine image algorithms lead actually back to Paglen, a recently exhibition ‘A Study of Invisible Images’. It reveals the hidden spectrum of machine-to-machine communication and provides photographs in answer to the questions he makes. The study takes reality as a starting point and makes a slice of the process visible. But his research approach, to collaborate with software developers and computer scientist and as artist-in-residence at Stanford University, will not be the same as mine.

Key References

Trevor Paglen, A Study of Invisible Images, Megalith, pigment print, 821/2x72 inch. (2017) [1]

Sterling Crispin, Data-Masks, Stages of evolution for Chronos (Greco)(2013-2015) [2]

Memo Akten, Learning to see: Hello, World! (2017) [3]

Literature

My perception on photography isn’t the same as it once was. Naturally, I didn’t saw the complexity of the image. Literature opened my eyes. A book that still dominates the way of thinking about photography is from Susan Sontag, on photography. The image is rich in many different ways. Also Vilém Flusser confronted me with the inevitable that the image is no longer accepted as an automatically depicted world. All the layers that adhere the image are unavoidable. This is the basic knowledge I received from my practice. The current time asks to consider new perspectives and trough Fred Ritchin, Trevor Paglen and Joanna Zylinska I became aware of this. What photography have become turns out to appear as alien to us.

“What photography evolves into is, to a significant degree, up to those interested in abetting its transformation the possibilities for change are freshly palpable. The stakes are momentous: our outlooks on life, both perceptual and conceptual, are sure to be deeply affected. What looms before us finally is not simply a question of media but one that, when answered, will help determine, to a degree greater than we now thing, our own uncertain fates.” (Ritchin 185)

What comes after photography is not predestined. I attempt to reflect on the past to move forward. Paul Virilio, the best known for his written about technology introduced me to the vision machine. A ‘synthetic vision’, this understanding will be seen as a “competition” in the visual field. What will be the effects, the theoretical and practical consequences for our own ‘vision of the world.’

“Vision” is the process of interpreting the optically derived impressions or data. In such an understanding of vision, the term refers to both the physiologically based process in living beings and the technically based process in electronic and digital apparatuses which process visual information." (Broeckmann 126)

I move to the outline of what images made by machines could suggest.

Experiments

Insights from Experimentation

Realised work

(what did you actually make)

Bibliography

Ritchin, Fred. After Photography. Norton, 2010.

Zylinska, Joanna. nonhuman photography. Londen: The MIT press, 2017.

Flusser, Vilém. Een filosofie van de fotografie. Trans. Marc Geerards. Utrecht: Uitgeverij IJzer, 2007.

Sontag, Susan. Over fotografie. Trans. Henny Scheepmaker. Amsterdam: De bezige bij, 2015.

Broeckmann, Andreas. Machine Art in the Twentieth Century. Londen: The MIT press, 2016.

Virilio, Paul. The vision machine. Trans. Julie Rose. Londen: British Film Institute, 1994.

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Trevor Paglen. ‘Is photography over?’ Foto museum Winterthur. (2014): Online. Internet. 03.03.2014. Available [4]

Trevor Paglen. 'seeing machines' Foto museum Winterthur. (2014): Online. Internet. 13.03.2014. Available [5]

Trevor Paglen. 'Scripts' Foto museum Winterthur. (2014): Online Internet. 24.03.2014. Available [6]

Trevor Paglen. 'invisible Images (Your Pictures Are Looking at You)' The new inquiry. (2016): Online. Internet. 08.12.2016. Available [7]

http://www.metropictures.com/exhibitions/trevor-paglen4/press-release

Blaise Agüera y Arcas. ‘Art in the age of machine intelligence’ Medium. (2006): Online. Internet. 23 February 2016. Available [8]

Blaise Agüera y Arcas. 'How computers learning to be creative' TED@BCG Paris: Online. Internet. Available [9]

Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson. 'Understanding Neural Networks Through Deep Visualization' (2015): Online. Internet. 8.06.2015. Available

[10]

Adit Deshpande. 'A Beginner's Guide To Understanding Convolutional Neural Networks' (2016): Online. Internet. 20.07.2016. Available. [11]

http://www.memo.tv/learning-to-see/