Algorithmic Empathy: Toward a Critique of Aesthetic AI (original) (raw)
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A Digital Aesthetics? Artificial Intelligence and the Future of the Art
Artificial intelligence has brought about significant changes in various creative domains, sparking discussions about the nature of art and its authenticity in the era of AI. Some scholars assert that the computer monitor now serves as a canvas, a brush, a musical instrument, and even an art tutor, leading us to explore deeper connections between AI and creativity. However, in this presentation, we wish to emphasize the humanistic dimension of creative processes once more. we acknowledge the role of AI in enhancing creative endeavors, but we firmly believe that human creativity remains paramount in the production of artistic works. The current notion of machines replacing artists is, in our view, more of a media sensation than a reality. Examining the history of electronic arts, our paper argues that claims of AI's artistic superiority are not novel; they echo similar trends from the past. The current enthusiasm mirrors earlier media frenzies. While the sciences have made significant strides in unraveling the mysteries of the human brain, our understanding of the intricacies of our remarkably creative minds, their origins, and their fulfillment in our brains This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY NC), which permits distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Architectural Design, 2022
The current discussions about the adoption of AI (artificial intelligence) in visual arts, design, architecture, cinema, music and other arts often rely on widely accepted ideas about art and creativity. These ideas include the following: “Art is the most creative human domain.” “Art and creativity can’t be measured.” “Artists does not follow rules.” It is also commonly assumed that “computers can only follow rules,” and therefore “computers struggle to generate something novel and original.” Taken together, these ideas lead to a new assumption: “generation of original art is a great test of AI progress.” Where do these popular popular ideas about art and its relationship to creativity come from? Historically, they are quite recent. For thousands of years human creators in all human cultures made artifacts that today we put in museums and worship as great art. But their creators did not have modern concepts of art, artist, and creativity. Th goal of this text is to briefly discuss the historical origins of currently popular ideas about art and creativity, and suggest that these ideas limit our vision of cultural AI. There are a few dominant popular understandings of “art” today. Logically, they contradict each other. Despite this, they may perfectly co-exist in a single publication or conversation. Sometimes one idea dominates and others do not appear. But very often, all three are assumed to be valid in the same time. Because these ideas contradict each other, holding them together can lead to feelings of confusion and unease - and also big fears about “creative AI.”
AM Journal of Art and Media Studies
If aesthetic and teleological judgments are equally reflective, then it can be argued that such judgments can be applied concurrently to digital objects, specifically those that are products of the rapidly developing sophisticated forms of artificial intelligence (AI). Evidence of the aesthetic effects of technological development are observable in more than just experienceable objects; rooted in inscrutable machine learning, AI’s complexity is a problem when it is presented as an aesthetic authority, particularly when it comes to automated curatorial practice or as a progressively determinative aesthetic force originating in an independent agency that is internally self-consistent.Rooted in theories of the post-digital and the New Aesthetic, this paper examines emerging new forms of art and aesthetic experiences that appear to reveal these capabilities of AI. While the most advanced forms of AI barely qualify for a ‘soft’ description at this point, it appears inevitable that a ‘har...
Artificial Aesthetics: A Critical Guide to AI, Media and Design, 2022
What would be the equivalent of the Turing test for an AI system capable of creating new songs, games, music, visual art, design, architecture, films? This looks like a simple question with an easy answer. If a system can automatically create new works in each media or genre and we cannot tell the difference between those works and those created by humans, it passes the Turing test... If we think further, we quickly realize that this is more complex. To even begin to answer it, we may need to consider ideas from several fields such as philosophical aesthetics, experimental psychology of the arts, histories of the arts, media theory, and software studies. Discussions about a Turing test for artistic creativity have not used perspectives from the last two fields much, and yet in my view they are very important for thinking about AI and creativity questions. This chapters explores the challenges of defining a test for artistic AI in our era when human creators routinely rely on digital assets and creative software which already has been offering AI-type support for long time. In other worlds: what would it mean for “genuine artistic AI” to compete with contemporary artists who already implicitly use AI implemented in their standard tools (operating in Photoshop, Premiere, After Effects, Blender, Unreal and so on behind the scene)?
Art, AI and Culture, 2022
This is a low resolution preview of a book. If you find it useful or interesting, please consider buying a copy. Art, AI and Culture interrogates the aesthetic heritage of Modernism as it informs contemporary cultural applications of AI which demonstrate there is no escape from the kaleidoscopic lineage of colonialism where the status of "human" and all the rights that entails were withheld from the colonized in general, and from slaves, labor, and women specifically. This analysis theorizes the social identity threat posed by AI's challenges to existing social, cultural, political, and economic orders. Digital technology is not exempt from this historical lineage that transforms familiar questions of economic displacement caused by machine learning and digital automation into new battles in an on-going conflict over social status and position. This cultural approach to AI reveals the ways that it transforms expressions of identity, leisure and luxury into opportunities for profit extraction. Social phenomena, (including racism, sexism, and nationalism), capture individuals in a web of systemic control where digital automation provides a mechanism preserving the existing hierarchies and social status that it might otherwise challenge. Drawing on a reconception of capitalism as a proxy for social status and position, this study critiques the fantasy that replacing all human labor will create a fully automated luxury utopia without bias, oppression, or social change.
AI Aesthetics and the Anthropocentric Myth of Creativity
Nodes, 2022
Suppose human creativity could be potentially replicated by mechanical processes. In that case, we would face a crossroads: either we could give up using the concept of creativity altogether, or if we hold to our common understanding of what creativity is, we could agree to apply this concept to non-human phenomena as well, as world champion Lee Sedol did when judging the performance of AlphaGo. However, the idea that artificial creativity discloses the mechanic nature of human creativity should also be met with a bit of critical detachment, particularly if we consider the specific case of the arts. In fact, artificial reproductions of human artifacts do not follow the same processes with which humans actually produced those artifacts. Nobody thinks that Mondrian followed procedures similar to the algorithm used in 1966 that generated pseudo-Mondrian, even though the public appreciated the artificial images more than the original ones....
Latent Spaces: What AI Art Can Tell Us About Aesthetic Experience
Odradek, 2022
In her book L’art victime de l’estétique, Carole Talon-Hugon criticizes the identification that has been made between art and aesthetics since the Eighteenth century. In this context, what the author calls “aesthetics” or “aesthetic experience” is essentially linked to the sphere of sensitivity, which becomes more and more isolated from that of good and truth. Art – this is the author’s thesis – progressively loses its link to good and truth as it becomes something that must just affect the senses. In this context, the author recalls that a central role was played by the growing importance of colour, in a process that led from Impressionism to abstract art. Throughout this evolution, according to Talon- Hugon, the intention of painting increasingly became an attempt to restitute “the purely visible impression,” isolated from any judgement or identification. In this paper, this thesis will be confronted with a new type of art, the art made through artificial intelligence. In particular, the focus will be on some artworks made through a kind of AI called Latent spaces: what aI art can teLL us about aesthetIc experIence GANs (generative adversarial networks). If one considers these pictures, one may notice that they share with some early Twentieth century paintings the fact that colour becomes somewhat independent from the outlines and drawing. Outlines are very blurred and the identities of the objects are not certain. Nevertheless, this type of colour in GANs pictures doesn’t demonstrate a denial of the task of identifying things. On the contrary, it is precisely concerned with the machine’s very attempt to classify objects. Moreover, even if we recognize in the AI our own attempts to classify and comprehend the world (the Ai as an “uncanny mirror” of ourselves), the AI remains nevertheless something other than ourselves. Therefore, the aesthetic pleasure when faced with these pictures implies the expectation not only of a possible knowledge, but also of a new relationship with an other. This will allow some considerations on the very notion of aesthetics itself.
Artificial Aesthetics. Chapter 1 (Emanuele Arielli): “Even an AI could do that”
Artificial Aesthetics: A Critical Guide to AI, Media and Design, 2021
"Artificial Aesthetics. A Critical Guide to AI, Media and Design" is a book by Lev Manovich and Emanuele Arielli. The book is released one chapter at a time on academia.edu, medium.com, and manovich.net. Each chapter will be added to academia.edu as a separate PDF in "Articles" section. Later all chapters will be combined into a single PDF and it will be added to "Books." Book Preface: Suppose you are a designer, an architect, a photographer, a video maker, a musician, a writer, an artist, or a professional or student in any other creative field. Or perhaps you are a digital creator making content in multiple media. You may be wondering how AI will affect your professional area in general and your work and career. This book does not aim to predict the future or tell you exactly what will happen. Instead, we want to offer you a set of intellectual tools to help you better navigate any changes that may come along. These tools come from several different fields: aesthetics, philosophy of art and psychology of art (Emanuele), and media theory, digital culture studies, and data science (Lev). As far as we know, our book is the first to bring together all these different perspectives in thinking about creative AI. We started the work on the book in summer 2019, exchanging numerous messages, commenting on each other ideas, and sharing drafts of sections. The final book is a result of this process. Although each chapter is written by one author, it reflects the discussions we had over 27 months.
Estudios Artísticos, 2024
In his groundbreaking work, Abstraction and Empathy, Wilhelm Worringer delved into the intricacies of various abstract and figurative artworks, contending that they evoke distinct impulses in the human audience—specifically, the urges towards abstraction and empathy. This article asserts the presence of empirical evidence supporting the extension of Worringer’s concepts beyond the realm of art appreciation to the domain of art-making. Consequently, it posits that abstraction and empathy serve as foundational principles guiding the production of both abstract and figurative art. This holds particular significance in the 21st century, where artificial intelligence (AI) assumes a creative role that was absent during Worringer’s initial formulation of his theory. Thus, this paper postulates that AI inherently harbors a predisposition for the generation of abstract art, owing to its non-living and inorganic origins and functioning.