Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues that AI (...) image generation is a kind of theft. This paper analyzes, substantiates, and critiques these arguments, concluding that AI image generators involve an unethical kind of labour theft. If correct, many other AI applications also rely upon theft. (shrink)

In this reply to my reviewers, I touch upon Husserl’s notion of fantasy. Whereas Kant positions fantasy outside the scope of his own work, Husserl brings it back. The importance of this notion lies in freeing imagination from the tight link to images, as for Husserl imagination is an activity that functions as a “quasi perception.” Ihde and Stiegler enrich Husserl’s analysis of imagination with various aspects of technology: Ihde shows how changes in the technologies that mediate our imagination will (...) necessarily change our imagination; Stiegler broadens Husserl’s analysis of retention. The two theories can be combined into a new understanding of subjectivity that is modeled as layers. Some layers can be performed by AI. The second part deals with the question of whether AI can be imaginative. Traditionally, imaginative creativity is associated with art. Bioart and AI art are brought as examples of a new definition of art, according to which art is the arrangement of materials in a way that produces a meaning. This definition does not refer specifically to creativity. In both forms of art, the biological/artificial and the human cooperate so that the former arranges the materials and the latter produces the meaning, albeit this division of labor is not clear-cut. The result is a co-shaping process. My conclusion is that algorithms can be considered creative by human standards, but this entails a new mode of imagination that is co-shaped and co-shared by humans and algorithms. The layer paradigm explains how such co-shaping works in practice. (shrink)

This collection of quotes demonstrates the elegant simplicity of Ai Weiwei's thoughts on key aspects of his art, politics, and life. A master at communicating powerful ideas in astonishingly few words, Ai Weiwei is known for his innovative use of social media to disseminate his views. The book is organized into six categories: freedom of expression; art and activism; government, power, and moral choices; the digital world; history, the historical moment, and the future; and personal reflections. Together, these quotes span (...) some of the most revealing moments of Ai Weiwei's eventful career-from his risky investigation into student deaths in the 2008 Sichuan earthquake to his arbitrary arrest in 2011-providing a window into the mind of one of the world's most electrifying and courageous contemporary artists. Ai Weiwei is one of China's most influential and inspiring figures. Artist, architect, curator, and activist, he has been an outspoken critic of the Chinese government's stance on human rights and democracy. (shrink)

In the treatise On the Spiritual in Art, Wassily Kandinsky divided the creation of art into three categories, the ultimate one of which is called Composition. In this article, I argue that Kandinsky’s classification is similar and comparable to the principle of semi-abstract Chinese freehand brushwork summarized by Zheng Xie in the Inscriptions on Painting - Bamboo. In an attempt to clarify the core of Kandinsky’s strategy of abstraction, i.e. the transformation from painting to writing, I then connect it with (...) the evolution of Chinese characters and the aesthetic theory of Chinese calligraphy, which is also in accord with Kandinsky’s idea of internal necessity and the spirit in art. Through this aesthetic dialogue across time and space, this article aims to bring a new dimension to the understanding of Western abstractionism from the perspective of the oriental philosophy of art. (shrink)

本书包括:最早的军事智慧之光及其衰落—中国古代近代军事思想;他山之玉和真理源头—外国军事思想;人类最伟大的军事战略—毛泽东军事思想;现代化、正规化革命军队的利器—邓小平新时期军队建设思想;新世纪富国强 兵的行动指南—江泽民国防和军队建设思想五章内容。.

For Viennese artist Florian Pumhösl »abstraction is a method«, not a category. Or rather, if abstraction is the defining category of modernism, the objective is to reproduce modernism's problems and limits and exploit relationships among its parts. Considering what Pumhösl calls the »textile complex« of modernism, this essay examines the artist's work in parallel with Charles Sanders Peirce's diagram concept and Gottfried Semper's use of textile diagrams throughout Style in the Technical and Tectonic Arts. _German_ »Abstraktion« ist für den Wiener (...) Künstler Florian Pumhösl eine »Methode«, keine Kategorie. Oder vielmehr, wenn Abstraktion die bestimmende Kategorie der Moderne ist, dann ist das Ziel, die Probleme und Beschränkungen der Moderne zu reproduzieren und die Beziehungen zwischen ihren Elementen auszunutzen. Vor dem Hintergrund dessen, was Pumhösl den »Gewebekomplex« der Moderne nennt, untersucht dieser Bei trag das Werk des Künstlers und führt es mit Charles Sanders Peirces Diagramm Konzept und Gottfried Sempers Einsatz von »textilen« Diagrammen in seinem Werk Der Stil in den technischen und tektonischen Künsten eng. (shrink)

Time is a necessary element in understanding AI art. Firstly, time reveals the historical process by which art-theoretical predicates move from the unmarked to the marked, which can thus be utilized as a defense for arguing the legitimacy of AI art as art. Furthermore, AI art should be seen as a “new” art that is temporally ahead of the descriptive forms of art theory. Secondly, time provides a unique interpretation of AI artworks’ characteristics and aesthetic experience. The absence of experience, (...) the de-depth of AI artworks, and the “short experience/short memory” aesthetic mode of the masses are closely linked to the scarcity of time in an age of acceleration. Finally, time reflects the loss of “aura” and the new end of art that AI art may bring about. Time provides a defense and explanation of AI art, as well as a perspective for reflecting on the development of art in contemporary times. (shrink)

This manuscript introduces the reader to Chicana feminisms as a field of study. The focus is on providing an overview to prepare the reader to pursue more specific areas and authors within Chicana feminisms. It provides an overview of the field of Chicana feminisms, tracing the historical origins of Chicanas' efforts to bring attention to the effects of gender in Chicana and Chicano studies; highlights the innovative and pathbreaking methodologies developed within the field of Chicana feminisms, such as testimonio, conocimiento, (...) and auto-historia; explores Chicana art and activism; and looks to the future of Chicana feminisms by discussing the newest developments in the field. As is customary in the Mexican American Experience series, there will be additional suggested readings and exercises at the end of each chapter. (shrink)

In the realm of man's culture, among the things created by man, art should be beautiful; its primary essential characteristic should be that it be able to evoke a sense of beauty in the person, that by its beauty it be able to provide for the person the pleasure of the sense of beauty. This is a fact that no one can deny outright. However, saying that art should be beautiful is not the same as saying that all art is (...) beautiful. In fact, there is art which is beautiful and art which is not beautiful; and this too is a fact that no one can deny. (shrink)

This paper explores the intersection of art history and AI technology. Special attention is paid to Generative Adversarial Networks (GANs), a machine learning technology widely used in AI art. This technology is particularly interesting to art history and the philosophy of art because it raises enduring questions about the creative process of artmaking, especially what constitutes a new and original work of art. While this is a relatively new area, it is possible to discern emerging directions where art and AI (...) intersect. One pressing issue concerns the use (or misuse) of algorithmically enabled technologies and datasets to perpetuate longstanding art-historical biases. The critical position adopted in this paper shares this concern. I examine a notable example of GAN technology that claims to create original art styles. While such experiments in computational creativity are technically interesting, their artistic aims can be questionable. I argue a mechanical model of artistic development based solely on the autonomy of style is problematic for at least two reasons: 1) it uncritically reinstates a formalist view of art history; 2) it recreates a narrow style-centric ‘historical modernism.’ However, despite voicing these reservations, I also discuss the potential of this technology to engage with topics of critical relevance to art history and the philosophy of art. (shrink)

Arthur C. Danto did not live to witness the proliferation of AI in artistic creation. However, his philosophy of art offers key ideas about art that can provide an interesting perspective on artwork generated by artificial intelligence (AI). In this article, I analyze how his ideas about contemporary art, intention, interpretation, and authorship could be applied to the ongoing debate about AI and artistic creation. At the same time, it is also interesting to consider whether the incorporation of AI into (...) artistic creation marks a new chapter in the narrative, which seems to have reached its end, or if it represents a significant rupture with past artistic traditions. (shrink)

For Viennese artist Florian Pumhösl »abstraction is a method«, not a category. Or rather, if abstraction is the defining category of modernism, the objective is to reproduce modernism's problems and limits and exploit relationships among its parts. Considering what Pumhösl calls the »textile complex« of modernism, this essay examines the artist's work in parallel with Charles Sanders Peirce's diagram concept and Gottfried Semper's use of textile diagrams throughout Style in the Technical and Tectonic Arts.

Que dire à des jeunes de vingt ans pour leur conduite dans ce monde qui part à la dérive? La civilisation s'effondre, les valeurs s'inversent, la culture se rétrécit comme une peau de chagrin, les livres comptent moins que les écrans, l'école n'apprend plus à penser mais à obéir au politiquement correct, la famille explosée, décomposée, recomposée se retrouve souvent composée d'ayants droit égotistes et narcissiques. De nouveaux repères surgissent, qui contredisent les anciens : le racisme revient sous forme de (...) racialisme, la phallocratie sous prétexte de néo-féminisme, l'antisémitisme sous couvert d'antisionisme, le fascisme sous des allures de progressisme, le nihilisme sous les atours de la modernité, l'antispécisme et le transhumanisme passent pour des humanismes alors que l'un et l'autre travaillent à la mort de l'homme, l'écologisme se pare des plumes anticapitalistes bien qu'il soit le navire amiral du capital--il y a de quoi perdre pied. J'ai rédigé une série de lettres à cette jeune génération pour lui raconter les racines culturelles de notre époque : elles ont pour sujet la moraline, le néo-féminisme, le décolonialisme, l'islamo-gauchisme, l'antifascisme, la déresponsabilisation, la créolisation, l'antisémitisme, l'écologisme, l'art contemporain, le transhumanisme, l'antispécisme. L'une d'elles explique en quoi consiste l'art d'être français : d'abord ne pas être dupe, ensuite porter haut l'héritage du libre examen de Montaigne, du rationalisme de Descartes, de l'hédonisme de Rabelais, de l'ironie de Voltaire, de l'esprit de finesse de Marivaux, de la politique de Hugo."--Back cover. (shrink)

AI’s new ability to create artworks is seen as a major challenge to today’s understanding of art. There is a strong tension between people who predict that AI will replace artists and critics who claim that AI art will never be art. Furthermore, recent studies have documented a negative bias towards AI art. This paper provides a philosophical explanation for this negative bias, based on our shared understanding of the ontological differences between objects. We argue that our perception of art (...) depends on our understanding of the context of its creation: human-made art is experienced as an interplay between the artist and nature. In AI-generated art, this interplay is either absent or minimised. We conclude that the displacement of the “human factor” in art will not lead to an evolution of art, but to the end of art. (shrink)

This paper investigates the transformative influence of generative AI on the arts, connecting it with Walter Benjamin's insights regarding the aura of art in the mechanical reproduction era. It scrutinizes how generative AI not only redefines art's traditional aura but also introduces a dynamic interplay between technological liberation and dependency. The analysis extends to the democratization of artistic expression and its broader societal impacts, highlighting a shift in art creation, perception, and interpretation in the digital age. This research encapsulates the (...) evolving nature of authenticity, creativity, and human–machine collaboration, marking a significant paradigm shift in art's conception and its role in society. (shrink)

The use of AI-generated videos centered on the face raises various concerns among professionals and audiences due to the difficulty of providing coherent descriptive tools of their cultural significance. At the same time, the focus of artists and their audiences shifts from the art as a text to the collaboration process between artificial intelligence (AI) and the involved social actors. This raises significant concerns between policymakers and other social actors looking for guidelines for the appropriate use of AI as a (...) tool, collaborator or substitute for creative workers, which can have immediate and long-term impacts on society and culture. Semiotics of culture provides descriptive tools for understanding and evaluating artistic texts and their role in semiotic space, the semiosphere. This article addresses how Lotman’s theory can contribute to the methodology for analyzing AI-generated texts as dynamic models. The theoretical framework developed by Lotman in his research on artistic text, dynamic systems and culture can be applied to the studies of current shifts related to AI-generated arts. This paper looks at the reception of AI-generated videos focused on face representations. In doing so, it analyses the dynamic processes in the creation process of AI-generated videos through their reception in related texts. The findings of this article highlight how Lotman’s theoretical framework can contribute to the methodology to analyze the cultural dynamics evoked by AI-generated artistic texts. (shrink)

This article considers current advances in tattooing that are challenging community-held views of authorship and ownership, and the need to address this tension. The key challenge is from AI-generated artworks being used as tattoo designs, but the authorial role of the tattooist is also challenged by body art projects such as tattoo collection. Legal clarity for tattooing is lacking, and in addressing this, this article advocates for an open, community-based form of shared copyright ownership and authorship for projects as tattoo (...) collecting, drawing on Dusollier’s and Mendis’ work. This article contributes to both copyright and cultural heritage legal scholarship, and to tattooing scholarship and the tattooing community. AI-generated art being tattooed on people has not been explored in the literature to date, and this article fills this gap. Furthermore, this article contributes a pilot study of the tattoo community’s views on AI-generated tattoos, which is currently lacking from the scholarly debate on AI-generated art. This article argues that the debate within the tattoo community about AI-generated art being used in tattoos needs to be addressed within the community through agreed extra-legal norms, which may well depart from how copyright law decides to approach AI-generated art globally. This article also asserts that AI should _not_ be regarded as the “author” of tattoo works in the traditional copyright sense, as only a human tattooist can draw from a number of cultural, textual, audiovisual and visual, cultural folklore, history and mythical references in creating their tattoo designs, as well as drawing on the client’s personal stories. This article explores the following: (i) an understanding of tattooing as an artform; (ii) tattoos in UK copyright law; (iii) an exploration of the authorial role of the tattooist within tattooing; (iv) the authorial role of the tattooist within tattoo collecting; (v) AI-generated tattoos—perspectives from the tattoo community, through a pilot study of YouTube videos and viewer comments about this; and (vi) a consideration of whether copyright legal reform is the solution for the tattooing community. (shrink)

This study proposed a children’s digital art ability training system with artificial intelligence-assisted learning, which was designed to achieve the goal of improving children’s drawing ability. AI technology was introduced for outline recognition, hue color matching, and color ratio calculation to machine train students’ cognition of chromatics, and smart glasses were used to view actual augmented reality paintings to enhance the effectiveness of improving elementary school students’ imagination and painting performance through the diversified stimulation of colors. This study adopted the (...) quasi-experimental research method and designs the pre-test and post-test for different groups. The research subjects are the Grade 4 students of an elementary school in Taitung City, Taiwan. The test tools included an imagination test and an evaluation of painting performance ability. The test results of a total of 30 students before and after the experiment included the experimental group that received the children’s digital art ability training system with AI-assisted learning and 30 students in the control group that had not received the teaching were analyzed by covariance. These results were supplemented by the description and interpretation of student feedback, teachers’ reflection notes, and other qualitative data to understand the performance of the students in the experimental group in terms of imagination and painting performance. (shrink)

This paper delves into the intricate relationship between Artificial Intelligence (AI) and the art ecosystem, emphasizing the need for a decolonizing approach in the face of AI's growing influence. It argues that the development of AI is not just a technological leap but also a significant cultural and societal moment, akin to the advent of moving images that Walter Benjamin famously analyzed. The paper examines how AI, particularly in its current oligarchical and corporate-driven form, perpetuates and magnifies the existing social (...) inequalities, thereby necessitating a critical and radical rethinking of its role in society and the arts. At the heart of the discussion is the concept of AI as a broad term encompassing various forms of machine intelligence, from natural language processing to computer vision. The paper criticizes the dominant anthropocentric view of intelligence and creativity, proposing a more inclusive approach that considers the diverse forms of intelligence present in other species and potentially in AI itself. It underscores the role of AI in shaping the art ecosystem, not just in the creative process but also in gatekeeping and decision-making. The paper proposes a framework for decolonizing AI in the art ecosystem, focusing on four key tasks: recognizing access as a form of power, understanding and addressing biases inherent in AI, assessing the impact of AI on marginalized communities, and challenging dominant narratives and epistemologies to create space for alternative voices and perspectives. It emphasizes the need for artists and the art community to engage actively with AI, shaping its development towards more equitable and just outcomes. In conclusion, the paper calls for a radical reimagination of AI's role in society and the arts, advocating for a future where AI is not just about technological advancement but also about fostering a more inclusive, equitable, and creatively diverse world. It invites artists, thinkers, and innovators to join in this journey of reimagining and reshaping the future of AI and the art ecosystem. (shrink)

Fueled by ever-growing amounts of (digital) data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, (public) health, and judicial (...) contexts. Data from a scenario-based survey experiment with a national sample (N = 958) show that people are by and large concerned about risks and have mixed opinions about fairness and usefulness of automated decision-making at a societal level, with general attitudes influenced by individual characteristics. Interestingly, decisions taken automatically by AI were often evaluated on par or even better than human experts for specific decisions. Theoretical and societal implications about these findings are discussed. (shrink)

This book discusses the work of four different kinds of artists from four different countries to examine how they create a space for politics in their work.

This book discusses the work of four different kinds of artists from four different countries to examine how they create a space for politics in their work.

In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...) willing to consider robots as artists than humans, which is partially explained by the fact that they are less disposed to attribute artistic intentions to robots. (shrink)

AI technologies hold great promise for addressing existing problems in organizational contexts, but the potential benefits must not obscure the potential perils associated with AI. In this article, we conceptually explore these promises and perils by examining AI use in organizational contexts. The exploration complements and extends extant literature on AI management by providing a typology describing four types of AI use, based on the idea of co-constitution of AI technologies and organizational context. Building on this typology, we propose three (...) recommendations for informed use of AI in contemporary organizations. First, explicitly define the purpose of organizational AI use. Second, define the appropriate level of transparency and algorithmic management for organizational AI use. Third, be aware of AI’s context-dependent nature. (shrink)

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the (...) field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust--in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better. (shrink)

Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...) solution for the so-called NP-complete problems will also be a solution for any other such problems. Its artificial-intelligence analogue is the class of AI-complete problems, for which a complete mathematical formalization still does not exist. In this chapter we will focus on analysing computational classes to better understand possible formalizations of AI-complete problems, and to see whether a universal algorithm, such as a Turing test, could exist for all AI-complete problems. In order to better observe how modern computer science tries to deal with computational complexity issues, we present several different deep-learning strategies involving optimization methods to see that the inability to exactly solve a problem from a higher order computational class does not mean there is not a satisfactory solution using state-of-the-art machine-learning techniques. Such methods are compared to philosophical issues and psychological research regarding human abilities of solving analogous NP-complete problems, to fortify the claim that we do not need to have an exact and correct way of solving AI-complete problems to nevertheless possibly achieve the notion of strong AI. (shrink)

Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ (...) increasing reliance on AI to make decisions that may affect how people live their lives may have a significant impact on privacy while also raising issues about algorithmic transparency and human control. In this paper, building and expanding on previous works, we will look at how the deployment of Artificial Intelligence technology may lead to changes in identity, security, and other crucial values. We will discuss what challenges we may face in the process, while critically reflecting on whether such changes may be desirable. Finally, drawing on a series of considerations underlying virtue ethics, we will formulate a set of preliminary suggestions, which—we hope—can be used to more carefully guide the future roll out of AI technologies for human flourishing; that is, for social and moral good. (shrink)

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and (...) the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment. (shrink)

By mid-2019 there were more than 80 AI ethics guides available in the public domain. Despite this, 2020 saw numerous news stories break related to ethically questionable uses of AI. In part, this is because AI ethics theory remains highly abstract, and of limited practical applicability to those actually responsible for designing algorithms and AI systems. Our previous research sought to start closing this gap between the ‘what’ and the ‘how’ of AI ethics through the creation of a searchable typology (...) of tools and methods designed to translate between the five most common AI ethics principles and implementable design practices. Whilst a useful starting point, that research rested on the assumption that _all_ AI practitioners are aware of the ethical implications of AI, understand their importance, and are actively seeking to respond to them. In reality, it is unclear whether this is the case. It is this limitation that we seek to overcome here by conducting a mixed-methods qualitative analysis to answer the following four questions: what do AI practitioners understand about the need to translate ethical principles into practice? What motivates AI practitioners to embed ethical principles into design practices? What barriers do AI practitioners face when attempting to translate ethical principles into practice? And finally, what assistance do AI practitioners want and need when translating ethical principles into practice? (shrink)

The new wave of ‘foundation models’—general-purpose generative AI models, for production of text (e.g., ChatGPT) or images (e.g., MidJourney)—represent a dramatic advance in the state of the art for AI. But their use also introduces a range of new risks, which has prompted an ongoing conversation about possible regulatory mechanisms. Here we propose a specific principle that should be incorporated into legislation: that any organization developing a foundation model intended for public use must demonstrate a reliable detection mechanism for the (...) content it generates, as a condition of its public release. The detection mechanism should be made publicly available in a tool that allows users to query, for an arbitrary item of content, whether the item was generated (wholly or partly) by the model. In this paper, we argue that this requirement is technically feasible and would play an important role in reducing certain risks from new AI models in many domains. We also outline a number of options for the tool’s design, and summarize a number of points where further input from policymakers and researchers would be required. (shrink)

AI for social good is a thriving research topic and a frequently declared goal of AI strategies and regulation. This article investigates the requirements necessary in order for AI to actually serve a public interest, and hence be socially good. The authors propose shifting the focus of the discourse towards democratic governance processes when developing and deploying AI systems. The article draws from the rich history of public interest theory in political philosophy and law, and develops a framework for ‘public (...) interest AI’. The framework consists of (1) public justification for the AI system, (2) an emphasis on equality, (3) deliberation/ co-design process, (4) technical safeguards, and (5) openness to validation. This framework is then applied to two case studies, namely SyRI, the Dutch welfare fraud detection project, and UNICEF’s Project Connect, that maps schools worldwide. Through the analysis of these cases, the authors conclude that public interest is a helpful and practical guide for the development and governance of AI for the people. (shrink)

Recommender Systems (RecSys) have been around since the early days of the Internet, helping users navigate the vast ocean of information and the increasingly available options that have been available for us ever since. The range of tasks for which one could use a RecSys is expanding as the technical capabilities grow, with the disruption of Machine Learning representing a tipping point in this domain, as in many others. However, the increase of the technical capabilities of AI-powered RecSys did not (...) come with a thorough consideration of their ethical implications and, despite being a well-established technical domain, the potential impacts of RecSys on their users are still under-assessed. This paper aims at filling this gap in regards to one of the main impacts of RecSys: personal autonomy. We first describe how technology can affect human values and a suitable methodology to identify these effects and mitigate potential harms: Value Sensitive Design (VSD). We use VSD to carry out a conceptual investigation of personal autonomy in the context of a generic RecSys and draw on a nuanced account of procedural autonomy to focus on two components: competence and authenticity. We provide the results of our inquiry as a value hierarchy and apply it to the design of a speculative RecSys as an example. (shrink)

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and (...) the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment. (shrink)

This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...) academic settings. These range from conservative approaches emphasizing the need for stringent AI regulations to more progressive strategies that seek to leverage AI’s capabilities. The paper accentuates the importance of guidelines that are adaptable, transparent, and culturally sensitive, acknowledging the global context of academic research. It also highlights the pressing need for effective implementation and enforcement of these guidelines to ensure that the integration of AI into academia does not compromise the integrity of scholarly work. The conclusion emphasizes the dynamic balance required between embracing AI’s transformative potential and upholding the timeless values of academic rigor and ethical research. This comprehensive analysis aims to provide a detailed perspective on the evolving role of AI in academia, fostering a dialog on how best to navigate this new technological frontier while preserving the sanctity of academic scholarship. (shrink)

Here I look at sundry aspects of the current controversy about Generative AI and, in particular, the implications of this new and rapidly evolving technology for poetry, the arts, and human creativity in general. My essay looks at earlier episodes in the history of thought, from Descartes on, that I take to have prefigured this latest debate around 'the human' in relation to its various physical, 'artificial,' or (presumptively) prosthetic means of extension and refinement. I also discuss its bearing on (...) literary-critical issues concerning the formal or structural aspects of poetry, the role (if any) of authorial intent, and the extent to which criticism enters into– and might lay claim to a stake in–what counts as human creativity. A central point of reference is William Empson's 1930 book, Seven Types of Ambiguity, where these issues are raised in a strikingly prescient way through his practice of close-focused textual analysis allied to great philosophical acuity. I conclude that a priori attitudinizing, pro or con, is not much use in this context, but that poets, critics, philosophers, cognitive scientists, and AI researchers need to cooperate in the reexamination of many long-standing but now highly contestable distinctions. (shrink)

In response to calls for greater interdisciplinary involvement from the social sciences and humanities in the development, governance, and study of artificial intelligence systems, this paper presents one sociologist’s view on the problem of algorithmic bias and the reproduction of societal bias. Discussions of bias in AI cover much of the same conceptual terrain that sociologists studying inequality have long understood using more specific terms and theories. Concerns over reproducing societal bias should be informed by an understanding of the ways (...) that inequality is continually reproduced in society—processes that AI systems are either complicit in, or can be designed to disrupt and counter. The contrast presented here is between conservative and radical approaches to AI, with conservatism referring to dominant tendencies that reproduce and strengthen the status quo, while radical approaches work to disrupt systemic forms of inequality. The limitations of a conservative approach to racial bias are discussed through the specific example of biased criminal risk assessments and Indigenous overrepresentation in Canada’s criminal justice system. This illustrates the dangers of treating racial bias as a generalizable problem and equality as a generalizable solution, emphasizing the importance of considering inequality in context. Societal issues can no longer be out of scope for AI and machine learning, given the impact of these systems on human lives. This requires engagement with a growing body of critical AI scholarship that goes beyond biased data to analyze structured ways of perpetuating inequality, opening up the possibility for interdisciplinary engagement and radical alternatives. (shrink)

The editorial introduces issue 21.1 of Technoetic Arts via a critical reflection on the artificial intelligence hype (AI hype) that emerged in 2022. Tracing the history of the critique of Large Language Models, the editorial underscores that there are substantial ethical challenges related to bias in the training data, copyright issues, as well as ecological challenges which the technology industry has consistently downplayed over the years. -/- The editorial highlights the distinction between the current AI technology’s reliance on extensive pre-existing (...) human-generated data for pattern recognition and the performative process inherent in art practice. Patterns of creative output can be replicated without a thorough understanding of underlying concepts. In contrast, the performative process of art practice, as explored through the conceptual frameworks of creativity by Noam Chomsky, Charles Sanders Peirce, and Roger T. Ames and with reference to an earlier publication of the editorial’s author, creates concepts and continually ‘strives to extend itself towards the unknown.’ -/- Following this introductory section, the editorial provides an overview of the ten articles featured in this issue of Technoetic Arts. The first four texts engage with emerging technologies from various perspectives in art and design. The subsequent six articles, part of a special section titled 'Perspectives from Chandigarh,' reflect a quest for meaningful existence within colonial, patriarchal, and biopolitical structures that frame everyday practices of exclusion and oppression. (shrink)

Despite the increase in the research field of ethics in artificial intelligence, most efforts have focused on the debate about principles and guidelines for responsible AI, but not enough attention has been given to the “how” of applied ethics. This paper aims to advance the research exploring the gap between practice and principles in AI ethics by identifying how companies are applying those guidelines and principles in practice. Through a qualitative methodology based on 22 semi-structured interviews and two focus groups, (...) the goal of the current study is to understand how companies approach ethical issues related to AI systems. A structured analysis of the transcripts brought out many actual practices and findings, which are presented around the following main research topics: ethics and principles, privacy, explainability, and fairness. The interviewees also raised issues of accountability and governance. Finally, some recommendations are suggested such as developing specific sector regulations, fostering a data-driven organisational culture, considering the algorithm’s complete life cycle, developing and using a specific code of ethics, and providing specific training on ethical issues. Despite some obvious limitations, such as the type and number of companies interviewed, this work identifies real examples and direct priorities to advance the research exploring the gap between practice and principles in AI ethics, with a specific focus on Spanish companies. (shrink)

This paper offers an overview of the prospects and ethics of using AI to achieve human enhancement, and more broadly what we call intellectual augmentation (IA). After explaining the central notions of human enhancement, IA, and AI, we discuss the state of the art in terms of the main technologies for IA, with or without brain-computer interfaces. Given this picture, we discuss potential ethical problems, namely inadequate performance, safety, coercion and manipulation, privacy, cognitive liberty, authenticity, and fairness in more detail. (...) We conclude that while there are very significant technical hurdles to real human enhancement through AI, and significant ethical problems, there are also significant benefits that may realistically be achieved in ways that are consonant with a rights-based ethics as well. We also highlight the specific concerns that apply particularly to applications of AI for "sheer" IA (more realistic in the near term), and to enhancement applications, respectively. (shrink)