Why pictures?
Chapter Two: Why Nonhuman Pictures? With Trevor Paglen and Joanna Zylinska
EuroNet

Class: Reichstag

This class was learned from 87 images of Reichstag. The visualizations below show the maximally activated representations of what makes Reichstag look like Reichstag. Each image begins with a randomly-seeded noise image, which leads to a slightly different class representation. Below are 12 activations created from 12 random noise images.

Data Sources

Images used for training: 87 Image sources: Google (57) , Flickr (29) Bounding boxes and URLs: reichstag.json

EuroNet

As artificial intelligence progresses, so-called 'convolutional networks' (ConvNets) now exist that can recognise objects within photographic images. Constant Dullaart has retrained these image recognition networks to include European artefacts, creating an image dataset. He asks, 'How can Europe's diverse cultural output be represented within this dataset, and what is the networks' capacity to recognise what is deemed European?' By illustrating the networks' ability to draw out cultural bias, Dullaart shows mechanised image interpretation's understanding of Europe in 2017.

Constant Dullaart was born in the Netherlands. He reflects on the cultural and social effects of communication and image processing technologies. His work includes websites, performances, fake armies and manipulated found images, presented both offline and in the public space of the Internet.

More information: https://imagenet.xyz/about/index.html

Class: Gołąbki (cabbage rolls)

This class was learned from 93 images of Gołąbki (cabbage rolls). The visualizations below show the maximally activated representations of what makes Gołąbki (cabbage rolls) look like Gołąbki (cabbage rolls). Each image begins with a randomly-seeded noise image, which leads to a slightly different class representation. Below are 12 activations created from 12 random noise images.

Data Sources

Images used for training: 93 Image sources: Google (59) , Flickr (0) Bounding boxes and URLs: golabki.json

Class: Winston Churchill

This class was learned from 90 images of Winston Churchill. The visualizations below show the maximally activated representations of what makes Winston Churchill look like Winston Churchill. Each image begins with a randomly-seeded noise image, which leads to a slightly different class representation. Below are 12 activations created from 12 random noise images.

Data Sources

Images used for training: 90 Image sources: Google (87) , Flickr (0) Bounding boxes and URLs: winston-churchill.json

Errorism: Notes on agency and the creative process
My work investigates the future of labor and creativity, asking questions about how image-making and art-making will change in the future. While Joanna Zylinska and Trevor Paglen are asking questions about the status and the future of images and the bias of technologies used to make images, my works ask questions about the future of the single, individual image author. Today we all become both authors and workers in the global system of AI as we all contribute to the refinement of machine learning algorithms, while simultaneously participating, actively or passively, in the creation of the value of images by circulating them online. AI can be seen as a system of collective intelligence where the entire society is a dispersed factory of data mining, in which everyone participates in the production of value. The crowds became important assets of late capitalism, and they are being mined by corporations and governments.

We are evolving as a species in response to technology and perhaps in the near future the figure of the individual author, which, as we know, is a construction created to extract value from the labor of the multitude, will be replaced by other, more complex, collective forms of cultural production, more apt and useful as evolutionary adaptations in an increasingly networked society. Perhaps current technological changes will lead to the transformations of human creativity where singular authors will become obsolete. In my opinion, it should be connected with a redistribution of capital, which currently flows only towards individual authors and galleries. In my work, I am trying to imagine future scenarios in which profits from the sales of artworks are redistributed among multitudes of people, active and passive workers of the AI planetary machine. In projects such as Aggregated Ghost and Conversions, I am investigating complex, collective forms of authorship, the replacement of a single author by a crowd or collective intelligence, and the redistribution of capital drawn from image-making. Conversions also investigate the unstable status of works that try to allude to ontological classification. In the contemporary world, in which we are surrounded by technical objects that perpetually change, constantly updated by their creators and by their users, there is a necessity for reflecting this mutability in the status and forms of images themselves.

Conversions is a series of ever-morphing liquid crystal paintings, which react to changes in society. The feelings expressed by thousands of people around the globe cause the paintings to evolve, like living organisms or ecosystems. Conversions visually transform according to the data harvested from social media feeds belonging to the members of protest movements. Each piece employs Artificial Intelligence algorithms to analyze the dynamic of emotions (enthusiasm, joy, sadness, fear, anger, and disgust) expressed in thousands of Twitter posts. Then, that information is aggregated and fed to an artificial society model -- a computer simulation of social interactions. That simulation is connected to a custom circuit board that heats layers of liquid crystal pigments on top of a copper plate. The paintings undergo dynamic changes via phase transitions in the liquid-crystal particles present in the pigment, creating forms reminiscent of bacterial colonies, slime molds, galaxies, geological forms, maps, and hyperspectral images from remote sensing. Conversions constantly evolve as digital and physical footprints of emotions and labor of the multitude of people as opposed to a single author. Entire societies cause changes in the appearance of these artworks.
Conversions investigate how energy, a substance in motion, can be converted from social to thermal and electrical energy. A perpetual litmus test of the aggregated social capital and social energies. These works also address the longtime attempts of scientists to design artificial intelligence that can replicate human artistic creativity. An artist is simulated here by the labor of the crowd of people fusing collective intelligence and artificial intelligence. Each time a liquid crystal painting" sells, a portion of the profits is redistributed to several social movements.

To realize Aggregated Ghost I teamed up with the scientists at the Massachusetts Institute of Technology Artificial Intelligence Lab. The work is based on data mining and crowdsourcing. The image is a collective self-portrait of the new online working class. Ten thousand employees of the Amazon Mechanical Turk online crowdsourcing platform were paid to submit selfies. Through this action, one of the many jobs that remote online workers take daily becomes the starting point for reflection on privacy and data sharing. A custom algorithm combined all the self-portraits into a single form. If the work is sold in the art market, the workers who contributed to its creation share in the profits via a bonus system. Symbolically connecting the dispersed worker community, the piece asks questions about agency and the possibility of redistributing capital in surveillance capitalism.

Forms and technologies of image-making and symbolic communication are closely related to societies' evolution, ideologies, and political economy. The history of image-making could be seen from the perspective of leaving traces -- from the first human traces, handprints, and signs in Paleolithic caves, through the carbon footprints of the industrial societies, to the contemporary digital footprints that we all leave with our behaviors online as well as, in aggregate, the geological traces left by the mining of elements used in computers and server farms. For that reason, it was interesting to me to investigate the earliest signs collectively produced by the Paleolithic humans and to consider how particular first signs led us in the long run to the development of fully formed societies and to where we are today. Moreover, I was interested in various biases that are present in the analyses of the images left by early humans by both science and the humanities.

My new series of works, Adjacent Possible (2021) realized for my solo exhibition Crowd Crystal at Castello di Rivoli in Turin, Italy, investigates alternative directions in which human culture could have evolved or is presently evolving, and the role that images play in the transformations of human societies. I collaborated with computational social scientists Prof. LeRon Shults and Dr. Justin Lane to apply machine learning algorithms to an archive of thousands of various iterations of 32 graphic signs -- the earliest known forms of symbolic communication, dating 40,000 BC to 14,000 BC -- documented in the Paleolithic caves in Europe by the paleoanthropologist Genevieve von Petzinger. These first signs were the earliest human attempts to pass information onto larger groups of people and to preserve it. They precede the early forms of writing by tens of thousands of years. Some of the earliest human signs may have even preceded language.

The machine learning algorithm which we deployed produced other potential signs that could have emerged as products of collective subjectivity. I executed these AI-generated signs on fragments of a potential cave wall. The project explores the direction in which we would have evolved as a species if we created and used different signs.

The hologram Errorism presents a simulation of several artworks of which I am not the author but which were generated by artificial intelligence algorithms based on my works created to date. The piece employs AI algorithms GPT3 and GPT2 --- models for natural language processing that create new texts based on existing publications by the same author and the entire corpus of English language online. In this case, the algorithms were trained on a set of descriptions of all my works and the essays I wrote. The algorithms generated a set of descriptions of conceptual works, which I never authored but could potentially create. Thinking broadly, the author of these descriptions is a collective intelligence: millions of people contributing to the corpus of human language. These descriptions were visualized by me as holographic animations. Perhaps the algorithms revealed ideas for artworks rejected by my unconscious but reflect what is possible: the margin of error, an alternative configuration, or future forms of my artistic work. Using the example of my art, I analyze the role of error in the creative process and undermine the idea of creativity as an individual endeavor.
Future of the Image: Why disappearing pictures?
OPEN

I am writing this essay in response to Why nonhuman pictures? by Trevor Paglen and Joanna Zylinska. I particularly want to elaborate on the points made about the future of the image, but from a different angle.

When I was eight years old I created my first website. The year was 1999 and my dad helped me develop a website with a topic of my choosing. I chose to create a web page called Esther's Studio, to which I would upload my "artwork": quirky drawings my father would scan for me. Little did I know that my interest in creating turned into a life path. More importantly, I did not grasp the digital realm I was sending my drawings into. I still don't.

We refer to the internet as a place (as I referred to my website as a studio). We talk about the cloud, cookies, (fire)walls, surfing, masters, servers and branches. For a lack of understanding, we re-use everyday words to familiarize ourselves with the abstract digital realm. It helps to refer to the internet as a landscape, because we have only just started to understand what is happening to our personal data.

The drawings for my first-ever website would cover topics within the horizon of my world, not extending far beyond the borders of our garden. I drew family members and chickens, but in essence -- I laid the foundation for my art today. The website became my inspiration, not the drawings. "Technology and place" have become the key interests in my artistic practice.

As I got older I was embarrassed to find my website easily pulled-up, even though it had been taken down years prior. It was not the kind of thing to be proud of as an insecure teenager. Now, the website makes me chuckle and marvel at the fact that I had such a determination to pursue art at such a young age. It does make me wonder: Does the internet ever forget?

This is when I learned about The Right To Be Forgotten. I was immediately struck by its poetic title, but this is the official term of a European Union law. As the name suggests, it deals with a person's right to have their data removed from online searches. Mind you -- removed from searches -- not from the internet as such, full stop.

In my work, I look at how humans relate to technology. I am specifically interested in the unseen. How does a person that knows nothing about technology relate to it? I aim to provoke a feeling through my work, rather than give didactic explanations. Inspired by these notions, I created work on The Right To Be Forgotten. I now finished a first chapter on portraiture.

I am reproducing a Google-found portrait of the first man to successfully claim his "Right To Be Forgotten" in the European Court of Justice. His successful lawsuit made his quest to be forgotten very memorable. I look for reproduction techniques that simultaneously show and alter his portrait. The internet does not forget and so we are faced with ever-growing personal archives. For this body of work, I use photographic reproduction as a means of reflecting on endless circulation: the resilience of the image.

The man in question is part of this project but the work is not about him. I am not interested in sharing the details of his story. He has rather become a symbol of the ambivalent tension between wanting to be remembered and wanting to be forgotten.

Individuals have very little understanding or control over their online image. However, there are two sides to every coin; namely the right to information. How do we remember and how does the internet remember?

The Austrian professor of internet governance and regulations Viktor Mayer-Schönberger has very interesting thoughts on this matter 1 . He compared the human brain to a large attic, full of memories and old belongings. Everything is there. Old information slowly moves to the bottom of each pile. Not completely forgotten, but not at the forefront of our memory either. This is at odds with the way the internet functions. On the internet old information remains forever swimming at the surface.

I mockingly titled this essay "Why disappearing pictures?", because we slowly come to realize that they won't disappear.

  • 1: Viktor Mayer-Schönberger, Delete: The Virtue of Forgetting in the Digital Age (Princeton University Press, 2011
  • Imaging and Imagining the Real

    Five Provisional Statements

    This short essay attempts to put in place some key points that aim to analyze and dissect practices and approaches to documentary photography in relation to an increasingly complex, interconnected and over-visualized world. It takes as a starting point how new positions and trends in documentary photography make use of what I would like to call expanded narratives to define their impact in the construction of mediated realities and their consumption.
    In the following statements I draw on the input given by Joanna Zylinska and Trevor Paglen and argue that we ought to see photography as a catalyst for the construction of different ways of looking at the world. The focus is on contemporary documentary practices, analyzed in terms of the new forms of production and dissemination they use to dismantle established ideas about the linear relationship between reality and representation. I invite you to take a closer look at some of the options that are available to documentary practices to build a visual language that has the potential to lend legitimacy to our relationship with the world. Paradoxically, in a post-truth age, such a visual language allows for what can perhaps still be called an ‘authentic’ imagining practice.

    We need to make a cognitive effort towards machine-mediated pictures of the real. Humans are no longer central to the act of taking a photograph. As a result of technical advances, various devices are now able to create images of ‘the real world’. But it is important to stress that humans remain at the center of the complex relationship between vision and representation. Machines are able to produce, read and distribute images autonomously. However, they are not yet able to form autonomous narratives regarding their own observations. What machines provide is an expansion of the possibilities of vision. Expanded vision in turn provides a different way to mediate social, economic, cultural and psychological processes. By making use of satellite imaging or medical body scans, for instance, humans can document both past and present; they are able to collect evidence of a ‘reality’ which is not yet empirical. As a consequence, our attention needs to shift from the medium to a critical reading of the possibilities and limitations of generating meaning. We need to analyze how technical apparatuses can contribute to the process of documentation while continuing with the critical debate about the way this kind of imagery intersects with non-fictional narratives.

    We need to take advantage of what the internet has to offer. If we are to make sense of documentary approaches in the context of today’s networked image, we need to acknowledge the challenges of complex networks. In our universally connected world, with its non-linear access to information and its plurality of voices and sources, polarization and cyber-balkanization are ubiquitous phenomena. It becomes ever more important to analyze the way in which the visual is created, modified, post-produced, re-contextualized and distributed. The practices of editing, transforming and mixing offer possibilities for new narratives that – while allowing for factual documentation – shift the focus to a process of reproduction rather than production, where available content becomes the core of visual representation strategies. Emphasis will have to be on the process of narration. Through the use of different types of image – from vernacular photography to computer-generated imagery, memes and emojis, news footage, data visualizations and user-generated content – complex narratives can be created to present a comprehensive and aesthetically coherent process of documentation, as suggested, for example, by the internet-based investigative work of the Bellingcat collective .

    We need to embrace interactivity. Navigating and experiencing the complexity of the visual in the context of networks is becoming an increasingly difficult cognitive, philosophical and psychological challenge. We are all fully immersed in a non-linear narrative as we simultaneously experience both the physical and the virtual worlds. Virtual reality, augmented reality, augmented photography, gamification and mixed reality offer different sensorial experiences and help to blur the boundaries between medium and content. These new paradigms enable new strategies for documentary engagement and awareness building. They also encourage the creation of complex narratives within the mix of visual languages and media. The way we consume narratives has shifted from a passive to a more and more active position: we select, we interact, we construct sense and meaning. The context of the networked image fully embraces the new relationship that occurs between the visual and the audience by fostering the creation of immersive experiences across different platforms. Take as an example sensorial forms of media immersion where audience members are actually able to play a part in the story. The choices of the audience will trigger narrative turns. We live in a world where we experience a multitude of identities and acts of positioning. Accordingly, documentary narration needs to be designed from a user-driven perspective and modelled on the example of social activism, which is able to produce new social frameworks and to challenge existing narratives by using a specific hashtag or meme.

    We need a plurality of voices, but we also need to contextualize them. Visual representations are direct, fast, easy to produce and accessible to large audiences in the networked world. Many people welcomed the move towards democratization that this process seemed to entail. However, the ability to generate narratives, on the internet and in traditional media, is a double-edged sword. It potentially subverts the process of generating meaning. In our post-truth era we have witnessed the emergence of ‘alternative’ realities based on rumors, misinformation, disinformation and propaganda. While a plurality of narratives is a major asset of our democratized world, we also need to provide tools for reading, contextualizing and critically reflecting on the visual. We need to avoid falling into the trap of an all-too-easy remixing of visual narratives. As I write this text, Photoshop has just announced the release of a beta version of its new Neural Filters. These filters are based on machine learning and allow users to perform a multitude of image manipulations, from ‘skin smoothing’ to ‘smart portraits’ that perform GAN-based processing on various facial elements. Apps and software that allow this type of editing have been available for a while, and Photoshop’s new filters are far from perfect. But the fact that the market leader in photo-manipulation is now offering everyone – even my little sister! – the ability to produce realistic alterations to any type of image represents a major shift. It is becoming increasingly difficult to clearly identify the differences between human and non-human agency. This means we need to place more emphasis on how images are used and less on how they are created.

    We need to take the time to process information. The way in which images are distributed via networks implies different approaches to their production, just as the time taken to react to and critically analyze social events, news stories and happenings differs. In an era of speed and acceleration, documentary approaches call for a counter-trend that favors complexity and long-termism. At the same time, the documentary photographer’s narrative needs to enter into a direct relationship with the multiplicity of visions that constitute it and with visual coherence at the level of language. Speed goes hand in hand with accessibility: the concepts of virality, real-time, live streaming and performativity permeate the way the world is narrated and, at the same time, are subordinated to technological mediation. Whether confronted with a trending hashtag on Twitter or fully immersed in what Hito Steyerl called “bubble vision” in a 2018 lecture at the University of Michigan, it is essential to acknowledge the implications of the speed with which these cultural objects permeate society. Production times for visual materials have changed; our reaction times need to change too.

    This text been edited for the publication in Why Pictures?, and firstly published in: Salvatore Vitale, “Imaging and Imagining the Real. Five Provisional Statements”, in: Post-Photography (= Nummer 10), eds Wolfgang Brückle and Salvatore Vitale, Luzern 2021.

    The Node
    OPEN
    The work was created using photogrammetry techniques and visual filters constructed on the basis of Gan neural networks. It depicts a conversation between two bots against the backdrop of a journey through the city. The bots are an allegory of the Gan network – one is an image maker (Generator), the other recognizes falsehood and truth (Discriminator). The conversation revolves around the structure of the film itself as well as the role of poetry, the city and the infrastructure of the network. The film directly addresses the idea of the multidimensionality of cinematic experience in the city – simultaneous textual, audio, and visual messages originating both in nature and electronic devices. All these layers overlap and intermingle, creating a new form of image.
    Chapter One: Why social pictures? With Nathan Jurgenson
    Thank You for Watching My Art Online
    Algorithms Without Vision

    The change in the social functioning of photography is a fact, but the underlying image-distribution networks are not neutral. If we agree that software is part of the apparatus responsible for the production and circulation of images, we cannot forget that it serves more than improving communication with our relatives and friends. It is also a part of an extractivist logic that is crucial for the functioning of contemporary communication networks, extracting information about our behavior and emotions from the content we create – images included – but also the digital traces we unknowingly leave behind.

    Of course, the alliance between photography and surveillance systems, and even more so the classification practices used by various centers of power, are nothing new. And yet it would be a cliché to suggest that the algorithms monitoring the global circulation of images remind us of less noble uses of photography than communication. The point is rather that it is impossible to look at them that way, as they remain, to a large extent, black boxes. And yet we know that how algorithms see us matters, because they watch us more often than humans do. They are part of a more complex cascade of gazes, influencing, in turn, what we are shown.

    Since image-recognition systems are non-transparent, what remains are reverse-engineering experiments. As a simple exercise, I uploaded Marta Ziółek’s opening images for this series to several web services. Google Cloud, which “derives insights from your images,” doesn’t know how to deal with these images at all. The braids turn out to be earrings. But that’s not the only problem, because the algorithms recognize not only people, items of clothing, and objects, but they also classify emotions. The standard set used by the algorithm (joy, sorrow, anger, surprise) is insufficient – the listed emotions turn out to be “unlikely” or “very unlikely,” and only “surprise” from the top photo is “possible.” The algorithm is confused, unable to cope with the classification. And yet, given the growing importance of such automatic emotion-recognition systems, such confusion, not to mention possible errors, can have real consequences. By the way, it is this problem that was ridiculed by the researchers at Dovetail Labs, who created emojify.info , a website that allows you to have a “face duel” with the algorithm. It’s worth checking out, to see how clumsy the models can be when they assume that the deviation of the corner of the mouth or the position of the eyebrows can precisely define our mental state.

    Such mistakes probably have a greater impact on our imagination than the helplessness of Google Cloud – especially since all sorts of biases are revealed. This is well illustrated by the experiment with PimEyes , an algorithm-based service that reportedly does a record-breaking job in finding similarities between uploaded images and photos on the web. Its business model is based on an image-control service – the idea is to search for images that resemble our own, and possibly allow us to intervene when they are used without our consent. The problem is that once Martha’s photos are posted to PimEyes, the screen is flooded with porn. Algorithms don’t understand context, and they associate a woman with parted lips and an outstretched hand with pornography – perhaps the only form of transgression known to software (we can spare ourselves jokes about the sexism of the IT industry). Unlike in Rob Wasiewicz’s work, there is no room for humor or irony here – no casseroles or giant women devouring subway cars. Moreover, in an attempt to better understand the logic behind such choices, I took a selfie while emulating Martha’s gesture – lips parted, hand outstretched. Less than a second after submitting it to PimEyes, the screen was covered with aptly chosen photos of myself. The only mistakes depicted guys similar to me, in public speaking situations. So much for biases. You know: a guy with a beard and glasses usually opens his mouth in order to say something into a microphone; a woman – to subordinate herself to male satisfaction.

    Why does this matter? First of all, because just as (let's have it, let's try to include a bit of the humor that machines lack in this gloomy argument) subway cars run on rails, the images circulating among us are, to a large extent, directed by similarly automated software. The limits of its imagination become our horizon. Secondly, as Vladan Joler and Matteo Pasquinelli write, such an algorithmic “undetection of the new” condemns us to look in everything for what already was. Always finding well-recognized patterns, and thus repeating old mistakes. Not very useful in times of crises that may have had no precedents in history (and not to mention sustaining “good old” sexism).

    In her latest, excellent book Atlas of AI, Kate Crawford presents her journey through the places that reveal the backstory – usually invisible to us – of the functioning of new, “smart” technologies. The author visits lithium mining sites, but also the archives of the government agencies that make mugshots of arrested individuals available to the cybercorporations that use these images to train facial-recognition algorithms. In a poignant account, reviewing photos of people at difficult moments in their lives, Crawford shows the effects of the lack of broader discussion of the issue, denouncing “the unswerving belief [of the tech sector] that everything is data and is there for the taking. It doesn’t matter where a photograph was taken or whether it reflects a moment of vulnerability or pain or if it represents a form of shaming the subject. It has become so normalized across the industry to take and use whatever is available that few stop to question the underlying politics.”

    Crawford – probably known to photography enthusiasts from her collaboration with Trevor Paglen, whose projects touch upon, among other things, automated vision systems – writes about a paradigm shift different to that described by Nathan Jurgenson. It is the shift from image to infrastructure, where context once again ceases to matter – the stripped-down images are thrown into an immaterial machine which squeezes out the data that allows the system to function. It is the grim reverse of the process of socialization. From this perspective, it seems important for creators to regain control over their images. Without that it is difficult to speak of the true democratization of photography and of the growth of its social dimension. Even if, for most of us, these disturbing processes remain invisible – or, as I mentioned, precisely because of it.

    Can You See What I am Sharing?
    So What?
    Can you see me now?
    A romance between aesthetics and physiology
    Hello! Can you hear me?
    I open my mouth

    I open my mouth. I let my lower lip relax and drop. I relax my jaw, my cheeks. I close my eyes. I turn my eyeballs toward the back of my skull. I feel ripples all the way from my tailbone to the back of my head. My body is all in motion. I feel it from the base of my feet to the root of my tongue. My tongue droops, my hands reach out, opening my body, zooming in and negotiating space. I allow my eyelids to open. I see and feel through my skin. By way of my tongue, it emerges from my mouth. I feel a vibration down my body.

    Today, our epidermis, the mask we wear, and the air we breathe, have become the new established boundaries. By revisiting the basic choreography of the mouth and the physiology of the female body, I mediate historical gestures, questioning the violation of bodily boundaries, the kinetic and the tangible in the image. My body is frozen in gesture, between one bodily movement and another.

    Credits 1

  • 1: Costume: Joanna Hawrot in collaboration with Rafał Domink, Photo: Karolina Zajączkowska
  • Series Curated by: Krzysztof Pijarski & Witek Orski
    About

    Although from its inception photography promised to be a democratic medium, circumventing the hierarchies of skill, style, or culture, this potential, like that of a latent image, remained unrealised. The necessary knowledge of chemistry and optics, the prohibitive cost of equipment, the laboriousness of the process, and, finally, the skill required to operate the entire apparatus were the initial stumbling blocks. Over time, such obstacles became less of a hindrance, while the photographic gesture became more and more commonplace. One could argue that it was only after 2007, with the invention of the smartphone—a miniaturised, pocket-sized computer equipped with a phone and camera module—that photography became truly ubiquitous. The parallel development of photo-processing software, including advances in machine learning, colloquially known as artificial intelligence (AI), led to the fact that today everyone is not only capable of taking technically correct pictures, but actually does so on a daily basis.

    If photography really does have democratic potential, that potential does not necessarily lie in the photographic gesture itself, in its universality or ease. It should rather be sought in contemporary image-distribution networks. It has never been easier to reach thousands or even millions of other people with your message. This ecstasy of communication, however, is accompanied by ever-increasing anxiety, triggered by the awareness that this ease of participation in the global circulation of images is concomitant with ever more draconian attempts at controlling, curtailing, and censoring it. And, what’s more, with the knowledge that an increasing number of images are not only not made for people, but also not made by people. Images, in their multitude, are establishing apace an autonomous, global republic of their own.

    In Why Pictures?, we aim to, in concert with contemporary theorists and practitioners, explore this global republic of images in search of the democratic potential of photography. In the sphere of social media, where and how is a common cause established, and a community formed around it, through the sharing of images? When is a collective good felt to be at stake? Is the autonomous character of the republic of images analogous to that of the current modalities of capitalism? If so, could such autonomy, paradoxically, empower the agency of images? And, to take this further, can photography play the role of a universal language in a contemporary world increasingly dominated by particularisms? Can it be a common space for dispute, iconoclash? These, among others, are the questions we would like to ask.

    The Why Pictures? platform was designed by Kaja Kusztra .

    Programming by Stanisław Rojek.

    The series is co-organised by the Krakow Photomonth Festival ; View. Foundation for Visual Culture ; Jasna 10. The Warsaw Cultural Centre of Political Critique as a part of ‘Centrum Jasna,’ financed by the Municipality of Warsaw ; and the Visual Narratives Laboratory at the Film School in Łódź .