Activating the archive through generative systems – Remaking images from the Aalto rare books collection

The focus of this thesis is on generative processes applied in the context of art and design. Specifically, it looks at the conception and application of a suitable analogue generative system utilised for working with archival material from the Aalto Visual Resources Centre. The project is documented in detail to describe the process from conception through execution in a systematic and transparent way. The review of three different taxonomies and the analysis of selected works, as well as the identification of artists’ motivations for using generative systems, are used to define the scope of generative art as well as to define and discuss the thesis project

Direito autoral e inteligência artificial : um estudo sobre a utilização de obras intelectuais em bases de dados de IA

A evolução tecnológica das inteligências artificiais têm as tornado cada vez mais capazes de criar obras estéticas idênticas a de seres humanos, com estas ferramentas tornando-se populares e acessíveis ao público em geral. Tais sistemas criam obras de arte com base em algoritmos de machine learning, utilizando-se de obras de arte protegidas por direito autoral em sua base de dados. A presente monografia tem como objetivo analisar a relação jurídica entre a obra final gerada por uma inteligência artificial generativa de arte e a obra intelectual protegida por direito autoral utilizada em sua base de dados. A pesquisa foi conduzida por meio de método dialético, confrontando-se aspectos técnicos das inteligências artificiais com o ordenamento jurídico sobre direito autoral, buscando-se uma síntese que possibilite a análise do objeto da pesquisa. Dessa forma, concluiu-se que tal análise resultou na percepção de que não se encontraram conceitos da seara do direito do autor aplicáveis de modo incontroverso às obras geradas por inteligências artificiais. Em face disso, percebe-se ser necessário, em momento anterior, definir se o direito de autor é efetivamente aplicável às inteligências artificiais generativas e se sua obra final é uma obra intelectual passível de proteção por direito autoral. Além disso, levanta-se a hipótese de ser necessária, criação de regulação específica aplicável às inteligências artificiais, que aborde, também, questões relacionadas às obras geradas por estas.The technological evolution of artificial intelligences has made them increasingly capable of creating aesthetic works identical to those of human beings, with these tools becoming popular and accessible to the general public. Such systems create works of art based on machine learning algorithms, using copyrighted works of art in their databases. This paper aims to analyze the legal relationship between the final work generated by a generative artificial intelligence for art and the intellectual work protected by copyright used in its database. The research was conducted through a dialectical method, confronting technical aspects of artificial intelligences with the legal system on copyright, seeking a synthesis that enables the analysis of the research object. Thus, it was concluded that such analysis resulted in the perception that uncontroversial concepts of copyright law were not found applicable to works generated by artificial intelligences. In this regard, it is necessary, in advance, to define whether copyright law is effectively applicable to generative artificial intelligences and whether their final work is an intellectual work subject to copyright protection. In addition, the hypothesis is raised that specific regulation applicable to artificial intelligences may be necessary, which also addresses issues related to works generated by them

The Mechanical Turkness: Tactical Media Art and the Critique of Corporate AI

The extensive industrialization of artificial intelligence (AI) since the mid-2010s has increasingly motivated artists to address its economic and sociopolitical consequences. In this chapter, I discuss interrelated art practices that thematize creative agency, crowdsourced labor, and delegated artmaking to reveal the social rootage of AI technologies and underline the productive human roles in their development. I focus on works whose poetic features indicate broader issues of contemporary AI-influenced science, technology, economy, and society. By exploring the conceptual, methodological, and ethical aspects of their effectiveness in disrupting the political regime of corporate AI, I identify several problems that affect their tactical impact and outline potential avenues for tackling the challenges and advancing the field.Comment: Matthes, J\"org, Damian Trilling, Ljubi\v{s}a Boji\'c and Simona \v{Z}iki\'c, eds. 2024. Navigating the Digital Age: An In-Depth Exploration into the Intersection of Modern Technologies and Societal Transformation. Vienna and Belgrade: Institute for Philosophy and Social Theory and University of Belgrade and Department of Communication, University of Vienn

On creative practice and generative AI:Co-shaping the development of emerging artistic technologies

In recent years, advances in artificial intelligence (AI) and machine learning have given rise to powerful new tools and methods for creative practitioners. 2022–2023 in particular saw an explosion in generative AI tools, models and use cases. Noting the long history of critical arts engaging with AI, this chapter considers both the application of generative AI in the creative indus-tries, and ways in which artists co-shape the development of these emerging technologies. After reviewing the landscape of generative AI in visual arts, music and games, we propose four areas of critical interest for the future co-shaping of generative AI and creative practice in the areas of communi-ties and open source, deeper engagement with AI, beyond the human and cultural feedbacks

Explaining CLIP through Co-Creative Drawings and Interaction

This paper analyses a visual archive of drawings produced by an interactive robotic art installation where audience members narrated their dreams into a system powered by CLIPdraw deep learning (DL) model that interpreted and transformed their dreams into images. The resulting archive of prompt-image pairs were examined and clustered based on concept representation accuracy. As a result of the analysis, the paper proposes four groupings for describing and explaining CLIP-generated results: clear concept, text-to-text as image, indeterminacy and confusion, and lost in translation. This article offers a glimpse into a collection of dreams interpreted, mediated and given form by Artificial Intelligence (AI), showcasing oftentimes unexpected, visually compelling or, indeed, the dream-like output of the system, with the emphasis on processes and results of translations between languages, sign-systems and various modules of the installation. In the end, the paper argues that proposed clusters support better understanding of the neural model

The Future Historiography of AI Art

More and more artists from all over the world are engaging in the production of AI art. Because of this, art historians need to start thinking about how the histories of AI art should be articulated. This paper aims to take part in this conversation by addressing the problem of whether the AIs created by human artists should be considered as artists too in the discourse of art and its history. By building on previous research on ethics, consciousness, authorship, creatorship, and intent, this paper presents a number of arguments as to whether or not anthropocentrism should be abandoned in the writing of AI art’s histories

The AI Work of Art in the Age of Its Co-Creation

Almost one century after Walter Benjamin's dissertation on the value of the work of art under the impact of its technological reproduction on the roots of globalization and mass media society, the current research aims to provide some coordinates to approach the influence of AI co-creative processes in the artistic field. From a media archaeological approach, we will map the collaborative practices that emerge in the Generative Art landscape to understand the creative possibilities of interaction between humans and machine-driven artistic goals. By conceiving the Web 3.0 as an expansive megadungeon, we find an increasing number of projects based on participative dynamics where online communities join forces with AI decentralized artists to reshape the current state of the art. We will take as an example the Botto Project, a community-driven creator conceived by Mario Klingemann, a pioneer of AI artworks who employs machine learning methods to revolutionize the blockchain and crypto art market. This case study leads us to reconsider the (wo)man-machine co-creation as the base of the auratic experience of the work of art in the age of AI co-creativity

Intelligenza artificiale e industrie culturali storia, tecnologie e potenzialità dell’ia nella produzione cinematografica

Negli ultimi anni stiamo assistendo, in svariati campi, a un sempre più vasto utilizzo di tecnologie che utilizzano quella che viene comunemente chiamata “intelligenza artificiale”. Anche il settore audiovisivo, da sempre recettore di novità e incline a evolversi continuamente, sta già vivendo quei processi che lo porteranno a essere rivoluzionato da questo tipo di tecnologie. In un periodo di frenetico progresso scientifico è difficile riuscire a fissare nel tempo e su carta lo stato attuale dello sviluppo tecnologico, dato che ciò che oggi viene considerato come novità domani potrebbe già essere stato superato. È necessario, quindi, uno strumento che riesca a catalogare, se non tutte, almeno le più importanti rivoluzionarie tecnologie d’intelligenza artificiale che hanno investito il mondo della produzione artistica e delle industrie culturali. Uno studio approfondito è dedicato, in particolare, all’industria cinematografica. Dopo una breve introduzione di carattere storico, vengono descritti i principali tipi di rete neurale artificiale e la loro evoluzione. Sono poi delineate e descritte le principali tecnologie d’IA applicate all’elaborazione, comprensione e generazione automatica o assistita d’immagine e testo. Ancora più nel dettaglio sono osservate alcune soluzioni tecnologiche che interessano le varie fasi del processo di produzione cinematografica, come la fase di scrittura e analisi della sceneggiatura, quella di editing e montaggio video, così come quelle riguardanti l’implementazione di effetti visivi e la composizione musicale. Il testo risulta essere, da un lato, una fotografia sul passato che ha interessato lo sviluppo delle tecnologie d’IA, dall’altro uno strumento che illustra il presente così da aiutarci, se non a predire, almeno a non trovarci completamente impreparati di fronte agli sviluppi futuri che interesseranno sia la produzione audiovisiva che, in senso più ampio, la nostra vita di tutti i giorni