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AI image generation represents a logical evolution from early digital media algorithms, starting with basic paint programs in the 1970s and advancing to sophisticated 3D graphics and media creation software by the 1990s. Early algorithms struggled to simulate materials and effects, but advances in the 1970s and 1980s led to realistic simulations of natural phenomena and artistic techniques. Generative AI continues this trend, using neural networks to combine and interpolate visual patterns from extensive datasets. This method of digital media creation underscores the modular and discrete nature of computer-generated imagery, distinguishing it from traditional optical media.

O artigo discute a transição da criação de imagens manual e baseadas em lentes para o procedimento preditivo da IA generativa, em que os computadores geram novas mídias aprendendo com grandes conjuntos de dados e prevendo novos artefatos. Essa mudança da representação para a previsão marca uma uma mudança significativa na forma como as imagens são produzidas, avançando em direção à "mídia preditiva". Os autores também investigam as características comuns entre os processos de criação humana e de IA, em que ambos aprendem com grandes quantidades de dados culturais para produzir novos artefatos. No entanto, a IA atualmente tem dificuldades para gerar "átomos culturais" altamente exclusivos ou raros, que são mais bem compreendidos pelos criadores humanos. O artigo também coloca a IA geradora no contexto da arte moderna e da história da mídia. Os artefatos gerados pela IA dependem de um grande arquivo de outros artefatos de mídia. Esse mecanismo generativo vincula a mídia generativa a gêneros, métodos e movimentos artísticos anteriores, como a colagem de fotos da década de 1920, a pop art da década de 1960 ou a net art da década de 1990.

The moral standing of robots and artificial intelligence (AI) systems has become a widely debated topic by normative research. This discussion, however, has primarily focused on those systems developed for social functions, e.g., social robots. Given the increasing interdependence of society with nonsocial machines, examining how existing normative claims could be extended to specific disrupted sectors, such as the art industry, has become imperative. Inspired by the proposals to ground machines’ moral status on social relations advanced by Gunkel and Coeckelbergh, this research presents online experiments (∑N = 448) that test whether and how interacting with AI-generated art affects the perceived moral standing of its creator, i.e., the AI-generative system. Our results indicate that assessing an AI system’s lack of mind could influence how people subsequently evaluate AI-generated art. We also find that the overvaluation of AI-generated images could negatively affect their creator’s perceived agency. Our experiments, however, did not suggest that interacting with AI-generated art has any significant effect on the perceived moral standing of the machine. These findings reveal that social-relational approaches to AI rights could be intertwined with property-based theses of moral standing. We shed light on how empirical studies can contribute to the AI and robot rights debate by revealing the public perception of this issue.

(1) La crise du médium qui a touché le monde de l’art s’explique par l’efflorescence de pratiques artistiques et par l’irruption des médias dans la sphère de l’art (photographie et cinéma, puis télévision et vidéo). La logique et les techniques de la culture de masse venaient faire effraction dans la logique plus aristocratique de l’art traditionnel. (2) Une autre déferlante devait venir porter l’estocade : les technologies numériques qui révolutionnaient les conditions de production et de réception des biens culturels. L’idée d’une œuvre multimédia, déclinable sur divers supports, usant d’outils d’édition ou de remixage s’imposait. (3) Une esthétique post-média peut donc s’ébaucher, fondée sur de nouvelles catégories, importées des technologies numériques (mais prises au sens large) : l’organisation de données, l’expérience-utilisateur, le design d’informations, le logiciel, l’utilisateur… (4) Cet utilisateur doit s’appréhender d’abord en fonction de son comportement informationnel : i. e. ses tactiques informationnelles du quotidien consistant à organiser, filtrer et interagir avec de l’information (bien au-delà de la seule sphère d’Internet). Notre comportement informationnel a changé, et il nous prédispose à une nouvelle forme de réception esthétique. (5) Depuis cinquante ans, un glissement s’est opéré dans le champ de la critique : l’intérêt est passé de l’auteur vers le lecteur idéal, pour finir sur le lecteur effectif. Pour comprendre ce dernier, à l’ère du post-Internet, il faut prendre en compte un nouvel élément : le logiciel. En intégrant le logiciel au modèle théorique de {l’émetteur, message, récepteur via un canal et un code}, on peut mettre en avant son poids majeur dans les opérations de création et de réception.Ces bases d’une esthétique post-média sont plus en phase avec nos vies et nos technologies actuelles, mais bien sûr elles présentent un biais : elles sont incapables de rendre compte de la dimension affective de la réception esthétique.

According to previous reports, selfie takers in widely different cultural contexts prefer poses showing the left cheek more than the right cheek. This posing bias may be interpreted as evidence for a right-hemispheric specialization for the expression of facial emotions. However, earlier studies analyzed selfie poses as categorized by human raters, which raises methodological issues in relation to the distinction between frontal and three-quarter poses. Here, we provide converging evidence by analyzing the (extended) selfiecity database which includes automatic assessments of head rotation and of emotional expression. We confirm a culture- and sex-independent left-cheek bias and report stronger expression of negative emotions in selfies showing the left cheek. These results are generally consistent with a psychobiological account of a left cheek bias in self-portraits but reveal possible unexpected facts concerning the relation between side bias and lateralization of emotional expression.

El autor reflexiona sobre la llegada de nuevas categorías de reflexión en el mundo de los estudios de los medios, y cómo el software y los códigos de programación del lenguaje digital se insertan en la cultura de masas para cambiar radicalmente nuestra capacidad de análisis y de comprensión crítica de la evolución de la cultura digital. Plantea la necesidad de pensar en los “actos” de software y su carácter performativo y dinámico, considerándolos un “habla” más que un lenguaje. Y apela a la necesidad de capacitarse para comprender críticamente las dimensiones de poder que este nuevo instrumento comunicativo tiene sobre nuestras vidas.

One of the main questions in the humanities is how cultures and artistic expressions change over time. While a number of researchers have used quantitative computational methods to study historical changes in literature, music, and cinema, our paper offers the first quantitative analysis of historical changes in visual art created by users of a social online network. We propose a number of computational methods for the analysis of temporal development of art images. We then apply these methods to a sample of 270,000 artworks created between 2001 and 2010 by users of the largest social network for art-DeviantArt (www.deviantart.com). We investigate changes in subjects, techniques, sizes, proportions and also selected visual characteristics of images. Because these artworks are classified by their creators into two general categories-Traditional Art and Digital Art-we are also able to investigate if the use of digital tools has had a significant effect on the content and form of artworks. Our analysis reveals a number of gradual and systematic changes over a ten-year period in artworks belonging to both categories.

I developed the concept of cultural analytics in 2005 to refer to "the analysis of massive cultural datasets and flows using computational and visualization techniques." In 2007 we established a research lab (Software Studies Initiative, softwarestudies.com) to start working on practical projects. The following are the examples of theoretical and practical questions that are driving our research: What does it mean to represent "culture" by "data"? What are the unique possibilities offered by computational analysis of large cultural data in contrast to qualitative methods used in humanities and social science? How can we use quantitative techniques to study the key cultural form of our era — interactive media? How can we combine computational analysis and visualization of large cultural data with qualitative methods, including "close reading"? (In other words, how does one combine analysis of larger patterns with the analysis of individual artifacts and their details?) How can computational analysis do justice to variability and diversity of cultural artifacts and processes, rather than focusing on the "typical" and "most popular"? Eight years later, the work of our lab has become only a tiny portion of a very large body of research. Thousands of researchers have already published tens of thousands of papers analyzing patterns in massive cultural datasets. First, there are data describing the activity on the most popular social networks (Flickr, Instagram, YouTube, Twitter, etc.), user-created content shared on these networks (tweets, images, video, etc.), and also users' interactions with this content (likes, favorites, reports, comments). Second, researchers have also started to analyze particular professional cultural areas and historical periods, such as website design, fashion photography, twentieth-century popular music, nineteenth-century literature, etc. This work is carried out in two newly developed fields — social computing and digital humanities.

This article presents the first project in digital humanities which uses digital image analysis and visualization for the study of a massive image collection - one million manga pages. These pages correspond to 883 manga series that were available as “scanlations” (manga digitized and translated by fans) in the fall 2009. Using computational techniques we were able to systematically analyze the visual language of special pages inserted by fans in scanlated versions, and also study visual differences between the pages from original Japanese publications and official English translations. The result is a better understanding of the multiple "mangas" which make up the "manga universe."

Abstract This article is the second part of the series devoted to the analysis of the new hybrid visual language of moving images that emerged during the period 1993–1998 and which today dominates our visual culture. In the first part the author suggested that the new language can be understood with the help of the concept of remixability if we use this concept in a new way. We can call this “deep remixability”, for what gets remixed is not only the content of different media but their fundamental techniques, working methods, and ways of representation and expression. In the earlier article discussion was started of how the new software-based methods of production – specifically software such as After Effects – made this language possible. In this part the author continues to explore different effects of software-based moving image production, and then uses this discussion to refine his analysis of how deep remixability functions. He discusses how today the design of moving image sequences takes place within three-dimensional space, with 3D compositing gradually replacing 2D compositing. He also looks at the shift from the concept “moving image” to a new concept of “media composition”. Finally, he analyzes how the typical production workflow in a contemporary digital studio the ways in which a project moves from one software application to another – affects contemporary visual aesthetics of not only moving but also still images. The article shows that this workflow has two fundamental effects. On the one hand, never before have we witnessed such a variety of forms as today. On the other hand, exactly the same techniques, compositions, and iconography can now appear in any media

Abstract This article is a first part of the series devoted to the analysis of the new hybrid visual language of moving images that emerged during the period 1993–1998. Today this language dominates our visual culture. It can be seen in commercials, music videos, motion graphics, TV graphics, and other types of short non-narrative films and moving image sequences being produced around the world by the media professionals including companies, individual designers and artists, and students. This article analyzes a particular software application which played the key role in the emergence of this language: After Effects. Introduced in 1993, After Effects was the first software designed to do animation, compositing, and special effects on the personal computer. Its broad effect on moving image production can be compared to the effects of Photoshop and Illustrator on photography, illustration, and graphic design. This analysis is used to support the author’s theory that the logic of the new visual language is that of remixability. Normally remixing involves combining content – for example, different music tracks. In this case what gets remixed is not only the content of different media or simply their aesthetics, but their fundamental techniques, working methods, languages, and assumptions. United within the common software environment, cinematography, animation, computer animation, special effects, graphic design, and typography have come to form a new metamedium. A work produced in this new metamedium can use all techniques that were previously unique to these different media, or any subset of these techniques.

O artigo discute características das duas principais abordagens de pesquisa relacionadas com o estudo de amplas bases de dados: a Computação Social (Social Computing) e as Humanidades Digitais (Digital Humanities). Mostra como estas perspectivas desenvolveram-se até o momento, apontando as oportunidades e as ideias ainda não exploradas, que indicam outras dimensões a respeito do modo como essas abordagens podem ser válidas para a análise cultural e para a elaboração de uma ciência da cultura

O Banco de Dados é a primeira parte do quinto capítulo da obra A Linguagem da Nova Mídia (2001), de Lev Manovich. Esse trecho explica o conceito de banco de dados como fundamental para a compreensão da nova mídia, argumenta sobre a relação entre dados e algoritmo, estabelece a distinção entre banco de dados e narrativa e propõe uma análise do cinema de Peter Greenaway e Dziga Vertov sob a lógica do banco de dados.

Abstract Since 1996, artist Miltos Manetas has done paintings that systematically portray the new essential objects of contemporary life: joysticks, computers, computer game consoles, and computer cables (lots of them). Manetas also paints people who are usually intensely engaged in the activities made possible by consumer electronics devices, such as playing a computer game. But he never shows what games they are playing or what images they are looking at. Instead, he focuses on the humancomputer interface: hands clutching a joystick, a body stretched across the floor in the intense concentration or, alternatively, relaxing besides a laptop, a computer console, or a TV.

O artigo propõe uma reflexão sobre o nascimento de uma “estética de ferramentas da informação”. Como os dispositivos – celular, laptop, PDAs, media layer, câmara digital, jogos portatéis – passaram a ser usados como objetos de consumo em todas as áreas da vida das pessoas, sua estética foi alterada em conformidade.