This paper addresses the question of whether artificial systems can be considered creative in the absence of cognition. It advances a novel perspective by grounding the analysis on a foundational premise: generative AI systems, such as LLMs and GMIs, are non-cognitive. This distinction is established through the application of the Minimal Cognitive Grid (MCG), offering a more precise entry point into the creativity debate. Despite their non-cognitive nature, these systems produce outputs that meet standard criteria for creativity—novelty (...) and usefulness—and reproduce, in functional terms, the stages of human creative processes. A comparative analysis with the Wallas–Jaoui model supports this claim. However, the absence of intentionality and authenticity limits any attribution of genuine creativity. So, how can we define Artificial Creativity? To resolve this, the paper introduces a minimal definition of artificial creativity as a non-cognitive, non-intentional, and non-authentic generative mechanism. This is the first attempt to define the concept directly, rather than by exclusion. The definition clarifies the theoretical boundaries between natural and artificial creativity, avoids anthropocentric bias, and establishes a foundation for future research in computational creativity and philosophy of AI. (shrink)

AI has displayed notable originality across the worlds of art, science and gaming. But is it right to say that such machines are creative? This question is bound up with other challenging questions about the capacities of artificial systems. Human creativity typically involves some conscious experience of the creative project. If consciousness is necessary for creativity, then a case could be made that these (presumably) unconscious machines are not really creative. I argue that there is no compelling (...) case for thinking that consciousness is generally necessary for creativity. However, lessons learned from this discussion suggest that a more localised claim about aesthetic creativity has greater promise. I propose that consciousness is required for creativity in projects with aesthetic goals. If an AI lacks consciousness, then it is incapable of aesthetic experience, and without aesthetic experience, it cannot engage in aesthetic creative projects. (shrink)

Can an artificial intelligence (AI), whose outputs are correlated with humans’ inputs in an extremely opaque way, be thought of as creative? I will answer in the negative, starting with the analysis of the case of Edmond de Belamy, together with further cases. More precisely, I will offer the following three kinds of arguments. First, what results from testing the idea of creative AI against the background of traditional definitions of creativity, especially from a philosophical perspective. Second, what (...) results from testing the idea of creative AI against the background of the notion of meta-sensemaking. Third, what results from testing the idea of creative AI against the background of the epistemology of creativity. After arguing that the possible answer to my starting question is negative, at least in the sense that speaking of creative AI means speaking of something far different from human creativity, I will argue that the reflection upon the idea of creative AI should not make us lose sight of what is most important: what creativity is always for, i.e. making sense of our own existence, from art to anything, not only because it is a kind of existential urgency for us but also because it is pleasant in itself for us. (shrink)

In this paper I take a philosophy of technology approach to so-called “creative AI.” In light of the disruptions promised by generative AI systems, I explore the way AI may give cause to develop a philosophical concept of creativity for the new technological milieu, beyond those often found in AI models, based on human psychology alone. Largely framed by the process thought of Alfred Whitehead, the paper first engages in a critique of human-centric accounts of creativity that are (...) dominant in the AI field, and then explores the way a process philosophy of technology can describe emerging creativity-technology relationships. The conclusion of the paper is twofold: the first is that creative AI systems should embrace a more contingent and complex concept of creativity in order to produce “new, surprising, and valuable” objects in the world. The second is that one of the key roles of contemporary philosophy of technology is to rethink creativity as artificial in light of the potential of AI. (shrink)

Despite the recent upsurge of interest in the investigation of creativity, the question of how to measure creativity is arguably underdiscussed. The aim of this paper is to address this gap, proposing a multidimensional account of creativity which identifies problem-solving, evaluation, and naivety as measurable features that are common among creative processes. The benefits that result from the adoption of this model are twofold: integrating discussions on creativity in various domains and offering the tools to assess (...) creativity across systems of different kinds. By situating creativity within this framework, I aim to contribute to a non-anthropocentric, more comprehensive understanding of the notion, and to debates on natural and artificial creativity. (shrink)

In the current era, robots and artificial agents can do jobs that could only be achieved with human creativity in the past, therefore successfully stepped into the sacred territory that once considered exclusive to human. Given this situation, Mark Amerika made two significant contributions with his new book, “My life as an Artificial Creative Intelligence”. This book added to the emerging literary genre collaborated by human artists and AI, telling the story about the advanced ACI developed in (...) the project FATAL ERROR and its relationship with Amerika as its co-author and creator. Moreover, this book documented an in-depth investigation into the nature of creativity and its processes, asking whether creativity is exclusive to the human mind. (shrink)

This article discusses three dimensions of creativity: metaphorical thinking; social interaction; and going beyond extrapolation in predictions. An overview of applications of neural networks in these three areas is offered. It is argued that the current reliance on the apparatus of statistical regression limits the scope of possibilities for neural networks in general, and in moving towards artificial creativity in particular. Artificial creativity may require revising some foundational principles on which neural networks are currently built.

I argue that there is an underappreciated threat posed by the emergence of generative artificial intelligence (AI). I call this the threat of creative obsolescence. The threat is that, given the capabilities of generative AI, humans may gradually abandon our creative pursuits, and in doing so, lose something of significant value. To show why the threat is a realistic possibility, I consider three kinds of value philosophers have attributed to creativity: aesthetic value, epistemic value, and practical value. I (...) then offer examples in which contemporary AI models appear to furnish value of each kind. I argue that the fact that AI appears capable of generating products with the same kinds of value for which human creativity has long been prized raises a question: Should humans continue to strive for creativity in the age of AI? I argue for three reasons to think we should. Each reason identifies a value of creativity that AI appears unable to replicate: imagination, originality, and connectedness. If I am right about any of these reasons, AI cannot fully replace the value of human creativity. But if we fail to recognize this and outsource our creative pursuits to AI, we risk a future in which the distinctive value of human creativity is lost. (shrink)

There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. My central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they (...) must disclose the creative agent’s inquisitive self. It is through self-disclosure, including the disclosure of the inquisitive self, that we put ourselves in a position to be seen by and connect with others through our creative pursuits. Because relying on AI for certain generative tasks is less self-disclosive than the creative work such technologies supplant, this reliance threatens to weaken our connections to one another. (shrink)

The question of whether machines can be creative has been at the centre of debates among scholars and practitioners well before the inception of artificial intelligence (AI) as a recognised field of research. This paper reviews how some of the key thinkers in the fields of creativity and AI have approached this question, contextualising their views within the ebbs and flows of AI technological developments, from the 1950s until now. The thread of this overview is Margaret Boden's identification (...) of novelty, surprisingness and value, as the three cardinal features of creativity. This review will retrace the steps of the quest of artificial intelligence researchers as they strive to replicate each of these three properties within human-made machines. The paper closes with a reflection on how the third of these properties, value, prompts us to consider societal challenges raised by the widespread adoption of AI for creativity that transcend the question: ‘Can AI be creative?’. (shrink)

This chapter considers the potential of artificial intelligence (AI) to exhibit creativity and imagination, in light of recent advances in generative AI and the use of deep neural networks (DNNs). Reasons for doubting that AI exhibits genuine creativity or imagination are considered, including the claim that the creativity of an algorithm lies in its developer, that generative AI merely reproduces patterns in its training data, and that AI is lacking in a necessary feature for creativity (...) or imagination, such as consciousness, agency, metacognitive awareness, or the use of mental imagery. In each case, a counterargument is provided that AI already has or soon will overcome the apparent barrier. In some instances, this is because the critical features deemed lacking in AI may not be necessary for human creativity and imagination either. In others, it is because important developmental and structural similarities between humans and generative AI have been insufficiently appreciated. (shrink)

1. In the last decade, technological systems based on Artificial Intelligence (AI) architectures entered our lives at an increasingly fast pace. Virtual assistants facilitate our daily tasks, recom...

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical consciousness to understand (...) itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

ABSTRACT Generative artificial intelligence is transforming the way we make, and think about, art. With prompting from human users, these generative systems now produce aesthetically compelling and seemingly creative works in a variety of artistic domains. In doing so, they challenge the ways we think about artistic credit, about creativity, and about the mechanism of legal copyright, which is meant to protect and promote creativity in a capitalist art market. All of this is currently at play in (...) the courtroom, as artists contest the ways in which their artworks can be rightfully fed into these artificial systems (“the problem of the inputs”), and other artists are challenged over whether they might be credited for the visual images these systems generate (“the problem of the outputs”). Here, we explore these problems as they arise in visual art. We argue that the contested legal landscape surrounding these artificial systems reflects the ways they challenge our received notions of artistic credit and creativity. And we suggest that clarifying or changing the application of copyright in light of their generative capacities will ultimately involve revising our conception of art. (shrink)

This is a philosophical question, not a scientific one. There are many examples of AI systems whose products appear to be creative and whose processing fits the criteria of combination, exploration, or transformation. (Arguably, that’s strictly true of transformation only if the system is linked to contingencies external to the program.) But could any of them or any conceivable computer-based system “really” be creative? That raises queries about whether “real” creativity must involve autonomy, intentionality, valuation, emotion, and consciousness. The (...) answer, in each case, is yes (sometimes with qualifications). However, these concepts are hugely controversial in themselves, quite apart from their relation to creativity—and/or to AI. It follows that no clear answer can be given to the title question. It remains open, until we have clear—and credible—accounts of all these matters. (shrink)

In an era of technological ubiquity, artificial intelligence (AI) is reshaping not only industries but also fundamental human experiences, including artistic creativity. Rooted in a Posthumanist theoretical framework, this research scrutinizes the intricate ethical and aesthetic challenges that artists confront in AI-enabled art creation, with a particular focus on a novel phenomenon we term 'aesthetic loss of control.’ This phenomenon bears significant implications for notions of authorship, copyright, and business ethics in the art industry. Utilizing a mixed-methods approach, (...) our study involves a six-month-long collaboration with 34 artists from diverse artistic and cultural milieus, facilitated by AI algorithms versed in an array of artistic styles. Through iterative cycles of human input and AI output, coupled with in-depth interviews, observational studies, and diary analyses, we meticulously document the artists’ experiences and their emerging doubts over authorship and creative control. Our findings illuminate the nuanced complexities surrounding this 'aesthetic loss of control,’ extending current discussions in business ethics by offering empirically grounded insights and recommendations for navigating these ethical dilemmas. The study not only contributes new theoretical perspectives to the discourse but also provides actionable ethical guidelines for stakeholders in the art industry's commercial ecosystem. (shrink)

Creativity is one of the least understood aspects of intelligence and is often seen as intuitive' and not susceptible to rational enquiry. Recently, however, there has been a resurgence of interest in the area, principally in artificial intelligence and cognitive science, but also in psychology, philosophy, computer science, logic, mathematics, sociology, and architecture and design. This volume brings this work together and provides an overview of this rapidly developing field. It addresses a range of issues. Can computers be (...) creative? Can they help us to understand human creativity? How can artificial intelligence (AI) enhance human creativity? How, in particular, can it contribute to the sciences of the artificial', such as design? Does the new wave of AI (connectionism, geneticism and artificial life) offer more promise in these areas than classical, symbol-handling AI? What would the implications be for AI and cognitive science if computers could not be creative? These issues are explored in five interrelated parts, each of which is introducted and explained by a leading figure in the field. - Prologue (Margaret Boden) - Part I: Foundational Issues (Terry Dartnall) - Part II: Creativity and Cognition (Graeme S. Halford and Robert Levinson) - Part III: Creativity and Connectionism (Chris Thornton) - Part IV: Creativity and Design (John Gero) - Part V: Human Creativity Enhancement (Ernest Edmonds) - Epilogue (Douglas Hofstadter) For researchers in AI, cognitive science, computer science, philosophy, psychology, mathematics, logic, sociology, and architecture and design; and anyone interested in the rapidly growing field of artificial intelligence and creativity. (shrink)

This article offers a theological account of creativity in light of recent developments in artificial intelligence (AI), especially large language models. Drawing on scripture and the philosophical work of Margaret Boden, it argues that creativity—whether divine, human, or computational—is best understood as a moral category. After introducing theologically appropriate forms of analogy, the essay distinguishes between two kinds of divine creativity: creativity ex nihilo (creating from nothing) and creativity in imago (creating in the image (...) of God). These serve as interpretive lenses for assessing human and computational creativity. While AI systems like ChatGPT can produce outputs that are novel, surprising, and valuable, they cannot create ex nihilo or bear the divine image. Their creativity is real but limited, acquiring moral significance only when guided by human agents acting in imago. The final section explores how morally responsible creativity involves accountability, self-formation, and questioning—traits exemplified (in varying degrees of success) in scripture by figures such as Adam, Eve, and Mary, the mother of Jesus. The article concludes that divine creativity is not only the origin but also the ethical standard by which all creativity, including our engagement with AI, should be measured. (shrink)

With the rapid development of artificial intelligence, its application in art education is becoming increasingly widespread, providing students with new ways to enhance creativity and critical thinking. This paper analyses the specific application of artificial intelligence in art education and explores how it fosters students' creativity through innovative teaching methods, personalized learning, and thinking guidance in artistic creation. At the same time, the study also reveals the positive role of artificial intelligence in helping students to (...) screen and criticize information, analyze and evaluate art works, and encourage innovative thinking and critical thinking. The research demonstrates that artificial intelligence significantly enhances students' independent thinking and critical appreciation of art, improving their artistic literacy and innovation while supporting the modernization of art education. (shrink)

The rapid development of artificial intelligence has brought many opportunities and challenges to organization. Some studies have shown that AI can improve organizational creativity. However, the existing research lacks an effective transformation path. This paper makes an innovative approach from the perspective of knowledge sharing, establishes an integration model of artificial intelligence capability, knowledge sharing and organizational creativity. Based on 189 questionnaire data, we use multi-level regression analysis and bootstrap method to analyze the influence mechanism. The (...) results show that artificial intelligence has a positive effect on knowledge sharing, knowledge sharing has a positive effect on organizational creativity, knowledge sharing mediates the relationship between artificial intelligence and organizational creativity, and organizational cohesion has a positive moderating effect on the relationship between artificial intelligence and knowledge sharing. The results supplement the existing research on the relationship between artificial intelligence capability and organizational creativity, expand the theoretical boundary and application space from the perspective of knowledge sharing at the organizational level, and provide reference for organizations to improve creativity. (shrink)

The combination of creativity and innovation is something that has always seemed to be stamped exclusively for humans — until recently, with the advances in Artificial General Intelligence (AGI). In this paper, a novel hybrid AI model involving combining Generative Adversarial Networks (GANs) and Efficient- NetB3 for increasing machine-driven creativity is presented. The model generates diverse artistic samples using GAN-based data augmentation, and can still per- form accurate classification of artistic styles using EfficientNetB3. The approach was trained (...) on the WikiArt dataset of 80,020 painted digitizations over 27 artistic styles. The performance of the hybrid model is experimentally shown to achieve a classification accuracy of 92.85% and exceeds the performance of existing AI- driven creative systems. The work presented in this research suggests that AI may be used to generate original artistic ideas, and it is joined by the larger discursive project surrounding AGI and creativity. Future work includes applying machine-generated creativity to other domains such as music, literature, and design, as well as assessing the novelty of machine-generated creativity. (shrink)

We explore the complex relationship between generative artificial intelligence (G-AI) and the ethical aspects of creative activities. Based on the dual concepts of attribution theory and entrepreneurs’ self-regulation, we examine how G-AI impacts entrepreneurs’ creativity, including unethical creativity, and those displaying traits linked to the ‘dark side’ of the human personality. Using data from India and Bangladesh, we test the core hypothesis that G-AI increases creativity within an entrepreneurial context. Contrary to prevailing narratives about G-AI’s ability (...) to enhance human creativity, our findings show that G-AI’s direct influence on creativity is statistically insignificant. More importantly, our results highlight that G-AI use is positively related to unethical creativity—a form of innovation that breaches normative standards—especially among entrepreneurs with high levels of narcissistic and Machiavellian traits. Our study advances attribution theory and self-regulation by revealing how entrepreneurs’ internal conflicts, such as the tension between aspirational creativity and opportunistic self-interest, interact with their self-control to produce unethical creativity. We offer important insights into how G-AI can be employed responsibly and ethically in entrepreneurial venturing. (shrink)

Digitalization and AI are bringing about the automation of many aspects of our market economies. We shall argue, however, that there is one market phenomenon which AI will never be in a position to automate, namely the phenomenon of entrepreneurship. Entrepreneurship is in several respects uniquely human. It involves on the one hand creativity, which is the ability to produce something that is novel but at the same time salient to outsiders. And on the other hand it involves the (...) feature of alertness, that is the ability to detect unpredictable features of the surroundings of the entrepreneur. Humans are uniquely aware of their surroundings because they are able to draw on ways of gaining knowledge about such surroundings in virtue of their existence as living human organisms. These ways of gaining knowledge are often unconscious, and the knowledge itself provides immediate links to avenues of future response. AI systems, on the other hand, can only handle mathematical algorithms created on the basis of historical training data. We will make the claim that humans can deal with novel situations in creative ways because, unlike AI systems, they can develop the necessary practical know-how through lived experience of the relevant market phenomena. We will then show that even the most powerful generative AI models that we can foresee cannot harness practical knowledge and therefore will fail to emulate human alertness. Our argument has implications not only for the understanding of entrepreneurship but also for the so-called calculation debate. If we are right, then digitalization and AI will never change the fact that human entrepreneurs situated in market contexts are irreplaceable components of the market economy. The argument thereby implies a critique of attempts to replace individual human entrepreneurs with collectives. Neither AI models nor social organizations can achieve anything like 'cooperative entrepreneurship' or 'intrapreneurship' in a way that would diminish the essential market role of the individual human entrepreneur. (shrink)

Between 1966 and 1974, the US Bureau of Sport Fisheries and Wildlife carried out research on the possibilities of using waste materials for constructing artificial reefs. One of the main outcomes was the recommendation to construct reefs from waste tires. With the encouragement of the findings, more than 700 reefs containing tens of millions of tires were built along the US Atlantic seaboard. This article investigates the artificial reef study at Sandy Hook Marine Laboratory and analyses environmental claims (...) built on its results. The results show that fisheries scientists involved in artificial reef research framed tire artificial reefs as a solution to two problems: recreational fishing enhancement and waste disposal. Their claims about the appropriateness of tire reefs became a driving force of their construction in the US. (shrink)

The modern world is confronted with a series of global problems, exacerbated by technological advancements. In this context, concerns arise in the public consciousness regarding the potential of artificial intelligence (AI) to surpass humans in intellectual and creative activities. The topic of AI creativity becomes pertinent and sparks debates within the scientific community regarding its creative potential. In response to these challenges, members of the Club of Rome in 2018 propose the concept of a new Enlightenment and the (...) principle of balance as a response to the demands of technological development. These ideas underscore the need for a balanced approach to technical progress, taking into account global values and ethical principles. I explore the definitions of creativity and AI, formulate criteria for assessing creativity, and analyse recent achievements in modelling creative processes in AI. I also focus on the utilisation of various algorithms for implementing diverse forms of creative activities, including text, image and music generation. Additionally, I present diverse opinions of researchers regarding creativity in AI. To systematise these perspectives, I propose a classification which allows their ranking. The conclusion emphasises that currently the issue of evaluating the creative potential of AI lacks a definitive solution, underscoring the relevance of further research. The future outlook may alter this situation, prompting the necessity to focus on predicting potential consequences of technological developments and developing mechanisms for controlling AI activities; humans, after all, bear responsibility for AI actions. Such an approach aligns with the concept of a new Enlightenment which seeks a balance between technological advancements and the preservation of global harmony. (shrink)

The aim of this chapter is to show how the technological research activity called “artificial life” is shedding new light on human creativity. Artificial life aims to understanding the fundamental behavior of life-like systems by synthesizing that behavior in artificial systems (more on artificial life below). One of the most interesting behaviors of living systems is their creativity. Biological creativity can be found in both individual living organisms and in the whole biosphere—the entire (...) interconnected system comprised of all forms of life—but I will focus in this chapter on the biological creativity exhibited by the evolutionary process. This is the creativity that enabled the earliest simple life forms to spontaneously evolve into the incredibly rich and beautiful diversity of life that now surrounds us. This diversity of life includes the most complex adaptive and intelligent systems in the known universe. This is an amazingly powerful spontaneous creation process, indeed. I will refer to it as hyper-creativity to call attention to the way in which it produces qualitatively new and more complex kinds of adaptations. There is a similar quality in human creativity. I am thinking of the aesthetic and cultural creativity of artists, but also the intellectual creativity of scientists and scholars, as well as the commercial and practical creativity of craftsmen, businessmen, and entrepreneurs. And I want to focus especially on the hyper- creative aspects of human creativity—the way in which human activity can yield qualitatively new and more complex creations. (shrink)

Recent advances in generative artificial intelligence (GenAI) have led to their use in a wide range of professions and tasks requiring creativity. Yet, there is no literature on how to optimally elicit creative output from GenAI chatbots. We systematically evaluated nine GenAI chatbots using a divergent thinking task (i.e., Alternate Uses Task) to explore whether the originality of GenAI ideas differs within a single response and across repeated prompts for more ideas. We analyzed the 1250 responses for each (...) chatbot using repeated-measures ANOVA, which showed no significant effect of response order on idea originality for all GenAI models (p > 0.05). Similarly, repeated prompting for more ideas generally did not affect the originality of the ‘average’ or ‘best’ ideas. The sole exception was DeepSeek-V3, which exhibited meaningfully higher originality scores after being prompted twice for more ideas (p = 0.01). These findings suggest that, in contrast to humans, GenAI models maintain highly stable ideational patterns, which is useful for informing best practices for interpreting GenAI outputs in creative workflows. We also discuss the implications of human-AI co-creativity and avenues for future research. (shrink)

The greatest rhetorical challenge to developers of creative artificial intelligence systems is convincingly arguing that their software is more than just an extension of their own creativity. This paper suggests that “creative autonomy,” which exists when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary condition for making this argument. Rather than requiring that the system be hermetically sealed to avoid perceptions of human influence, developing creative autonomy (...) is argued to be more plausible if the system is intimately embedded in a broader society of other creators and critics. Ideas are presented for constructing systems that might be able to achieve creative autonomy. (shrink)

Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic process that transcends the substrate in which it occurs, evolution’s creativity is not limited to nature. Indeed, many researchers in the field of digital evolution have observed their evolving algorithms and organisms subverting their intentions, exposing unrecognized bugs in their code, producing unexpected adaptations, or exhibiting outcomes uncannily convergent with ones in nature. Such stories routinely (...) reveal creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This paper is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems. (shrink)

The article is devoted to defining the contents of the notions « natural», « artificial» as characteristics of creative objects; finding out the peculiarities of creating natural and artificial objects and their interaction; to perspective of the development of a person in the aspect of strengthening of his creativeness. Key words: natural, artificial, creative.

Research on attitudes toward artificial intelligence (AI) painting tools lacks an examination of gender differences among creative workers from the perspective of creative labor. This study used a mixed-methods explanatory sequential design to survey general attitudes toward AI painting tools among creative workers in the fields of animation and gaming, with a focus on gender differences and the underlying reasons for their viewpoints. Quantitative analysis (N = 376) showed no significant gender differences in general attitudes when controlling for computer (...) self-efficacy; however, female participants reported more negative general attitudes under comparable AI anxiety levels. Qualitative interviews (N = 10) confirmed that anxiety about being replaced by AI painting tools drives resistance. Despite equitable knowledge access and the absence of gender segregation in labor division, male interviewees received more technical support, experimental opportunities, and positive social feedback, leading to more positive general attitudes toward AI painting tools. Such disparities might exacerbate general attitude polarization and contribute to broader gender segregation in creative fields. The findings underscore the need for equal support and resources for male and female creative workers, which is crucial for promoting gender equality and ensuring the fair, inclusive use of AI technologies in creative labor. (shrink)

This article explores how the emergence of creative AI technologies transforms creative workers’ self-apprehension in the context of critical theory and labor studies. The distinguishing contribution of this study resides in its focus on how CI laborers’ creativity perception and reception are affected by AI technologies’ intrusion into the creative domain. Creative AI technologies are expected to present new expressive capacities to creative workers and cost-cutting advantages for CIs’ production that put a lot of creative jobs at risk. Findings (...) show that creatives perceive the adaptation of AI technologies as both an opportunity for their creative process and a requirement of their active presence in the market survival as a matter of technocratic rule. We critically analyze creative labor’s novel mods engaged with updated technology and present reflections on the favorable co-creation conditions to flourish an understanding of socially intelligible technology and thereby a creative livelihood against technocracy. (shrink)

As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various (...) forms of AI. (shrink)

Artificial creativity is presented as a counter to Benjamin’s conception of an “aura” in art. Where Benjamin sees authenticity as art’s critical element, generative artificial intelligence operates as pure inauthenticity. Two elements of purely inauthentic art are described: elusiveness and reflection. Elusiveness is the inability to find an origin-story for the created artwork, and reflection is the ability for perceivers to impose any origin that serves their own purposes. The paper subsequently argues that these elements widen the (...) scope of artistic and creative potential. To illustrate, an example is developed around musical improvisation with an artificial intelligence partner. Finally, a question is raised about whether the inauthentic creativity of AI in art can be extended to human experience and our sense of our identities. (shrink)

“Nature-inspired” approaches, with their potential to generate innovative ideas through technology, are expected to surpass current architectural requirements and significantly influence future-oriented designs. A new agenda within the discipline of architecture involves production with artificial intelligence. Within this context, the question, “Can a design product be created by combining the principles of biomimicry and futuristic architecture?” is explored through AI’s capability to autonomously generate multiple architectural form alternatives. The objective is to develop a novel methodology. In the context of (...) futurism, which emphasizes the concept of speed in artistic approaches, this study aims to conceptually discuss the role of AI—collective digital environments that transform traditional design processes—in architectural design. The research findings highlight the importance of experimental design exercises in aiding students to understand AI, stressing the need for this comprehension to go beyond merely mastering the technical aspects of AI. (shrink)

Generative Artificial Intelligence (GenAI) is fundamentally transforming notions of creativity and creative production across disciplines, yet a comprehensive understanding of professional attitudes and integration patterns remains challenging. This scoping review examines how creative professionals perceive and integrate GenAI technologies across four domains: visual art and design, writing and literature, performing arts, and environmental and spatial design. Following PRISMA-ScR guidelines, we analysed 57 papers (2022–2025) from multiple databases, focusing mainly on empirically based studies of professional creative practice. We identify (...) universal trends, including the shift from creation to curation and meta-creation, the emergence of new literacies (prompt engineering, AI evaluation), and the reconfiguration of expertise hierarchies. Career stage emerges as a critical factor: across domains, entry-level professionals demonstrate enthusiasm and view GenAI as a natural extension of digital tools, while senior practitioners express scepticism about expertise devaluation. All fields consistently position GenAI in early-stage conceptualisation rather than final production, developing hybrid methodologies that preserve human judgment in convergent creative phases. However, impacts manifest differently based on each field/ sub-field’s relationship to embodiment and materiality. Integration levels follow an inverse relationship with traditional notions of “pure” creativity—fields prioritising embodied practice and cultural authenticity (fine arts, literary fiction, classical music) show the most significant resistance. At the same time, commercially oriented domains embrace higher adoption for efficiency gains. Visual artists face “erasure by obscurity” from AI output volume; writers negotiate between nonlinear, associative language generation and AI’s tendency toward coherence and cliché; performers uniquely embrace computational unpredictability as a generative force; architects balance efficiency imperatives with concerns about cultural homogenisation effects of Western-centric AI systems. Our conceptual framework positions creative professionals’ attitudes along two dimensions: knowledge codifiability (tacit/embodied to explicit/codifiable) and output materiality (physical/permanent to digital/ephemeral). Key tensions include balancing productivity with meaningful engagement, volume with distinction, precision with serendipity, and individual with collective intelligence. Ultimately, our findings reveal complex patterns of ambivalence shaped by competing value systems. This review contributes a comprehensive mapping of GenAI applications across creative disciplines, potential disconnects between educational emphasis on critique and industry’s pragmatic adoption, and gaps for future research on longitudinal skill impacts, emerging AI-native practices, Global South perspectives, and forms of creative resistance. (shrink)

This paper explores how our concept of creativity has to be rethought in light of the increasing role of emerging generative Artificial Intelligence (GenAI) technologies in creative practice, thereby enriching the concept to include collective creativity produced by humans and AI. Collective creativity arises from the collective practices of people in relation to their nature, environment, cultures, societies, techniques, technologies, and AI. This conception of collective creativity challenges the traditional idea of the individual genius. By (...) expanding our concept of creativity, we are able to acknowledge the processes and products of humans and AI as creative. Exploring case studies of co-created art, music, and text, I argue that AI can be creative and demonstrate how AI can be creative and enhance our creativity. (shrink)

This article examines the relationship between artificial general intelligence and the image of God. After identifying various models that Christian theologians use to classify or define the imago Dei, particular attention will be given to the ‘created co-creator’ model. Scholars have interpreted this model in different ways, based on the nature of human creative action. This action is seen as either subordinate to divine creation action or the human creative action is truly cooperative with divine creative action. Whether AGI (...) would be made in the image of God in these models is then explored, highlighting the differences between humans as sub-creators versus humans as cooperative co-creators. If human creative action is cooperative, then the question arises as to whether AGI can be made in ‘the image of humanity’. Some elements of this image are explored, and then the discussion turns to whether AGI would be made in ‘the image of humanity’, and if so, could AGI still be made in the image of God?Contribution: The argument concludes by pointing to future work using the various models of imago Dei to help inform the relationship between humans and AGI by briefly mentioning two examples. (shrink)

. Interpreting children 's ideas: Creative thought or factual belief? A new look at Piaget's theory of childhood artificialism as related to religious education. British Journal of Educational Studies: Vol. 41, No. 2, pp. 164-173.

The current literature in artificial intelligence and robotics awareness focused on the dark side of AIRA. Accordingly, this study sheds light on the positive effect of AIRA on employee creativity by exploring how and when hotel employees may take proactive behavior facing the threat of AI and robotics to further stimulate creativity. Based on the work adjustment theory and the locus of control theory, this study constructs a moderating multiple mediation model to explain the influence of AIRA (...) on employee creativity, in which active learning and task crafting are used as mediating variables, and locus of control is used as moderating variable. Data collected from 264 employees in a Chinese hotel are used for empirical analysis. Results show that AIRA indirectly positively affects employee creativity via active learning and task crafting and Locus of control not only moderates the mediating effect of active learning between the relationship of AIRA and employee creativity but also moderates the mediating effect of task crafting between the relationship of AIRA and employee creativity. The theoretical and practical implications are discussed. (shrink)

The article analyzes the possibilities and limitations of artificial intelligence. The article considers the subjectivity of artificial intelligence, determines its necessity for solving intellectual problems depending on the possibility of representing the real world as a deterministic system. Methodological limitations of artificial intelligence, which is based on the use of big data technologies, are stated. These limitations cause the impossibility of forming a holistic representation of the objects of cognition and the world as a whole. As a (...) tool for deterministic description of the universe it is proposed to use empirical-metaphysical general theory of systems, which is an extension of existing general theories of systems due to ontological justification of the phenomenon of isomorphism and definition of a limited set of laws, rules, patterns and primitives of forms and relations of objects in the universe. The distinction of natural (human) and artificial intelligence is considered, including the realization of multisystem integration of intelligence in physical, biological, social and spiritual systems. A philosophically grounded approach to ensuring the evolutionary properties of artificial intelligence is formulated, based on the inclusion of non-equilibrium mechanisms through which stability is realized. (shrink)

The relationship between creativity and artificial intelligence has been recently discussed in both the expert community and the broader public, with the discussion being driven not only by the challenges of practice or academic interest but also significantly influenced by societal anxieties. Large Language Models (LLMs), such as Chat GPT, Midjourney, DALL-E, have become central to the dialogue on human/machine creativity. Questions arise: Can AI be truly creative and if so, is AI creativity of the same (...) nature as human or non-human animal creativity? If we affirm both of these questions, what implications does that hold for our future selves? This contribution establishes meaningful links of personal and collective identity bridging the debates on AI creativity and human enhancement. (shrink)

Can Artificial Intelligence (AI) be creative? In order to address this question, we need to understand creativity before moving to apply our chosen definition to the assessment of AI. With this in mind, this article focuses on one component of one definition of creativity: flair. Flair is Berys Gaut’s addition to value and originality, the components typically included in accounts of creativity. Flair is the basis of Gaut’s rejection of AI creativity; but is he right (...) to reject this possibility on these grounds? In this article I argue that flair is possible for AI. I begin by outlining the flair condition. I then turn to assess whether flair is possible for AI, arguing that it is potentially achievable. I will then consider Gaut’s objection to the possibility of AI creativity through flair. I argue that if we are happy to accept that skill is sufficient for flair in place of understanding, then flair is possible for AI. However, there remain two issues, which I will then turn to examine. The first issue is to clarify the relationship between skill and understanding in order to establish whether they can indeed be pulled apart in flair. The second issue is to consider whether flair is inextricably linked to agency, and thus is not possible for AI. I conclude that flair is possible for AI systems to achieve if we do not require understanding, suggesting that we can instead rely upon skill to help delineate creative processes in non-agents. (shrink)

This edited book explores the process of creating using the seven C's of creativity framework. It discusses the creative process as a collaboration between humans and Artificial Intelligence (AI), here identified as the cyber-creativity process. Through nine chapters written by leading scholars in the field, this collection delves into the rapidly emerging area of Generative-AI (Gen-AI) applications and sheds light on the parts of the creative process that will remain fundamentally human throughout the foreseeable future, as well (...) as those that will benefit more from AI-augmentation. Drawing on the dynamic definition of creativity, the contents encompass the Dynamic Universal Creative Process (DUCP) and the DA VINCI model, the design principles of Gen-AI algorithms, the cyber-creativity process in education, journalism, design, fashion, music, and its implications on intellectual property protection. A timely reflection on the complex and evolving relation between creativity and technology, this volume will interest academics, researchers, and students alike across humanities, social and hard sciences. (shrink)