Barbara Levine and Paige Ramey:<\/strong><\/p>\n\n\n\n
Vernacular photography \u2013 the use of photographs in ordinary life \u2013 is a powerful medium for understanding the complex interplay between images, individuals, and emotions. From its origins in the 19th century, the photograph quickly became a ubiquitous tool for recording, sharing, and interpreting personal and collective experiences. This democratization of image-making has had profound cultural and social implications, shaping the way we document and engage with the world around us. Today, vernacular photography has evolved into an even more pervasive element of our daily lives. With the advent of smartphones, social media platforms and AI, every moment can be captured, revised, curated, invented and shared instantaneously. By taking a slower, more curious and critical approach to looking at everyday images from the past and the present, we can start to understand the complexities of how we present ourselves and others and how photography (and our interpretations) embraces both reality and fiction.<\/p>\n\n\n\n
Lev Manovich:<\/strong><\/p>\n\n\n\n The sheer volume of images\u2014from Instagram stories to AI-generated photography\u2014has created a paradox where photography is simultaneously everywhere and nowhere, abundant yet devalued. <\/p>\n\n\n\n A contemporary approach must acknowledge photography's fundamental contradictions: it claims to capture truth while inevitably constructing reality, promises permanence while existing in increasingly ephemeral formats, and democratizes image-making while conditioning users to create similar algorithmically successful content. Rather than resolving these tensions, we should sit with their discomfort. This insight emerges from what I call cultural analytics\u2014using computational methods to analyze patterns across millions of images. Cultural analytics reveals that our challenge isn't too many images, but too few aesthetic strategies. When I computationally analyzed and visualized 16 million Instagram photos from 17 global cities, I could systematically compare aesthetic trends across locations and measure the actual degree of visual homogeneity. This macro-level analysis becomes essential for understanding contemporary photography's complexity\u2014revealing both global standardization and local variations that individual viewing cannot detect<\/p>\n\n\n\n AI image generation, as I discuss in \"Artificial Aesthetics\" (2024), also operates through a form of massive-scale cultural analytics\u2014analyzing billions of web images and reproducing their most statistically dominant patterns when generating new images. Rather than creating mere \"pseudo-photographs,\" AI generation exposes how all images are built from recurring visual patterns. What appears as AI's artificial construction actually reveals photography's longstanding reliance on reproducible conventions - the repeated patterns that AI now makes explicit.<\/p>\n\n\n\n Marcel Top:<\/strong><\/p>\n\n\n\n In an era where imagery is more accessible than ever and saturates our digital spaces, the ability to critically read and interpret images has become increasingly important. The sheer volume of images we encounter daily\u2014whether captured by mobile devices or generated by artificial intelligence\u2014demands a more contemplative approach to viewing and understanding photography as a phenomenon full of contradictions. This involves not only deciphering what an image explicitly presents but also recognizing what it omits. Images are not neutral; they are shaped by subjective choices, technological processes, and power structures that determine their visibility and influence.<\/p>\n\n\n\n The democratization of image creation has shifted the dynamics of visual culture. While photographers continue to play a crucial role in shaping the meaning of images, the power of selection and distribution now often lies in the hands of corporations and algorithms. These systems dictate which images gain prominence and which are lost in the vast sea of digital content. As a result, understanding an image requires more than just analyzing its composition or subject matter\u2014it requires an awareness of the mechanisms that control its circulation and impact. AI-generated imagery is an extension of these processes, further reflecting the power structures embedded in visual representation.<\/p>\n\n\n\n Engaging with everyday photography can help us navigate these complexities. Unlike carefully curated or commercially driven images, everyday photographs often emerge without the explicit intention of contributing to the artistic or journalistic sphere. They document the ordinary, offering a raw and unfiltered perspective on life. By examining these images, we can gain insights into the evolving role of photography, its function within different social and cultural contexts, and the ways in which it shapes our perceptions of reality. This practice encourages a more active engagement with images, allowing us to question their origins, purposes, and effects.<\/p>\n\n\n\n Nathan Jurgenson: <\/strong><\/p>\n\n\n\n There\u2019s so many ways to answer this question, so a few that come to mind within the space constraints: I look at everyday images as\u2026<\/p>\n\n\n\n As always a part of a grid, a roll, a stream. As ephemeral either literally or de facto in how they often get buried by their multiplicity. <\/p>\n\n\n\n As a photographer. I always view images as one who also produces them. When we screenshot, link, and circulate, we are photographers of the internet. I make images often to be responded with more images, and thus view them with how to make more in mind. Would I have taken that shot this way? How would I respond to this image when messaged to me? These thoughts change what we see in the images.<\/p>\n\n\n\n As the product of survivors bias. We do not see the vast, vast majority of everyday images being taken. The hundreds of selfies that are for the viewer to (mis)understand their own face but are not shared are as important to understand as the ones posted publicly on the big platforms that are more easy for the researcher to research. <\/p>\n\n\n\n As embodied. The camera and eyes, the photo and lips, and grid and memory, the flesh is media. Analyzing the media as detached, virtual, and as technical and anti-human will mislead.<\/p>\n\n\n\n As gestural and discursive, often as more like talking than journalistic documentation or artistic practice. Everyday photographs and some AI generated photographic images share this quality, not about depicting literal fact but conveying other truths.<\/p>\n\n\n\n As one perspective of many. Despite claims to the otherwise, everyday photography can be more factual, as well. News events are often photographed by many people from many angles, and as such are trusted journalistically more: how could everyone fake it in the same way? The everyday photograph continues to have factual, journalistic importance today, and that is because viewers have their multiplicity implicitly in mind. <\/p>\n\n\n\n As deeply gamified objects. Social media are thoroughly infested with game-like scores and metrics, from likes and hearts and reposts and followers. Social media asks us to create and circulate images according to their attention algorithms, and images are thus made and viewed with this game intuitively in mind. So, I am not just viewing any image, I am viewing the gamified algorithm that made it. And by paying attention to an image, I am now a part of this algorithmic attention game. <\/p>\n\n\n\n As a crisis. Those making and looking at images are part of a larger conversation about what is healthy, dehumanizing, and less real and authentic. Was this too many selfies? Does photographing make my experience less real and true? When can you take or look, how much, how often, how much screen is too much screen? Such concerns about digital toxicity are part of how that image was made, thus part of what I see in it. <\/p>\n\n\n\n R\u00f3za Tekla Szil\u00e1gyi:<\/strong><\/p>\n\n\n\n In today\u2019s democratised image-making landscape, where entry-level equipment is widely accessible and easily mastered, photography has become a truly universal language. At the same time, our relationship to it has grown more complex: questioning reality itself has become central to how we engage with photographs.<\/p>\n\n\n\n The way we look has also shifted. A scanning mode of attention \u2013 fast and selective \u2013 has become our default. This is a condition we have to acknowledge \u2013\u00a0perhaps not without critique, but with the awareness that some forms of everyday photographic practice actively thrive on this accelerated way of looking. Algorithms and corporations play a decisive role here, shaping our acquired tastes and subtly influencing the realities we construct through digital platforms \u2013\u00a0realities that are no longer parallel to lived experience but have become fully integrated into it.<\/p>\n\n\n\n Against this backdrop, the act of consciously engaging with everyday photography takes on new importance.\u00a0By pausing to look more deliberately at images in all their formats, we can begin to chart a blueprint for a renewed relationship with photography \u2013 one that acknowledges its contradictions while opening up space for critical understanding<\/p>\n\n\n\n Get to know our jury here<\/a> and read more about the application process for the Eidolon Grant in 2025 here<\/a>.<\/strong><\/p>\n\n\n With the Eidolon Grant deadline approaching, we posed a question to our jury that our team has been returning to again and again, curious to hear their perspectives. Read their inspiring answers and do not forget: the deadline is 31 August midnight! Eidolon: In the age of mass mobile photography and AI-generated pseudo-photographs, how can […]<\/p>\n","protected":false},"author":2,"featured_media":3508,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[39],"tags":[26,49,25],"class_list":["post-3500","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-grant","tag-digital-imageries-mass-images-the-networked-image","tag-eidolon-grant-2025","tag-theories-of-the-vernacular"],"yoast_head":"\n
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This also means questioning our most accepted assumptions about contemporary photography.\u00a0For example, the premise that we live in an age of 'visual saturation' deserves scrutiny. My research analyzing millions of Instagram images reveals that despite the massive volume, we actually see remarkable visual homogeneity\u2014converging around specific poses, lighting styles, and compositional formats creating what I call \u201cInstagram aesthetics.\u201d Rather than saturation, we face standardization.<\/p>\n\n\n\n
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