The Creative Mind: Myths and Mechanisms
Abstract
How is it possible to think new thoughts? What is creativity and can science explain it?
When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover the nature of human creativity in the arts, science and everyday life.
The Second Edition of The Creative Mind has been updated to include recent developments in artificial intelligence, with a new preface, introduction and conclusion by the author. It is an essential work for anyone interested in the creativity of the human mind.
... Varios autores han dado su opinión de por qué esto es así. Boden (2004) argumenta que la creatividad abarca múltiples niveles, como la innovación radical de Einstein o las pequeñas soluciones diarias, y depende de sistemas complejos, con lo cual definirla es difícil y, a menudo, una tarea subjetiva. Gardner (1993) plantea que la creatividad varía según el ámbito; la creatividad de un poeta no es la misma que la de un ingeniero, por ejemplo. ...
... Estos criterios son interdependientes; un producto altamente creativo suele destacar en varios de ellos. Por ejemplo, comparar la teoría de la relatividad, una innovación radical, con una solución improvisada como arreglar un carburador con una goma de mascar ilustra la necesidad de categorías más precisas (Boden, 2004). Ejemplos adicionales incluyen el iPhone, que transformó la telefonía móvil; "Las Señoritas de Avignon" de Picasso, que rompió convenciones estéticas; y la estructura del ADN, que revolucionó la biología. ...
... Pero la creatividad humana va más allá del pensamiento divergente y la sensibilidad a los problemas: también surge de reinterpretar y redefinir elementos y conceptos familiares. Esta transformación conceptual (Boden, 2004) puede ser realizada por los algoritmos, pero siempre dentro de patrones predefinidos, lo cual limita su capacidad para generar transformaciones que, en el contexto humano y bajo ciertas circunstancias, puedan ser consideradas realmente profundas. Y también hay cualidades esenciales de la creatividad humana que, dada su naturaleza subjetiva y emocional, están ausentes en los algoritmos: la motivación necesaria para encarar el desafío, la aceptación de la incertidumbre que supone comenzar a crear (Robinson y Stern, 1997), la aceptación de riegos, la capacidad de adaptarse intencionalmente a los cambios y, en definitiva, todo lo relacionado con el coraje para cuestionar certezas que es una característica de la creatividad humana (De Bono, 1985) imposible de replicar en entidades no conscientes. ...
Este artículo analiza la creatividad desde el enfoque organizacional, utilizando el modelo conceptual de las 4 P’s (persona, proceso, producto y contexto) para explorar si la inteligencia artificial puede considerarse creativa. A partir de una revisión teórica y ejemplos prácticos, el trabajo identifica las condiciones bajo las cuales los aportes generados por IA cumplen criterios de creatividad, destacando tanto similitudes como diferencias esenciales respecto a la creatividad humana. El análisis enfatiza aspectos humanos como la sensibilidad emocional, la motivación intrínseca y la capacidad de reinterpretar situaciones inciertas, características que permanecen ausentes en los sistemas algorítmicos. El estudio concluye proponiendo un marco claro y útil para que las organizaciones gestionen la creatividad, identificando áreas en las que la IA puede complementar, aunque no reemplazar, la creatividad humana.
... This study compares specific examples of AI-created painting, poem, song with those usually created by humans, exploring promises and limitations that AI can bring into the arts. The result of this study is to contribute to the debate about whether AI should be considered a creative agent in its own right or rather a tool increasing human creativity by providing new possibilities for artistic expression (Fossa 2017;Boden, 2004). Through a review of the capabilities and limitations of the current generation of AI in creating 1 GPT (Generative Pre-trained Transformer) is a series of language models developed by OpenAI, designed for natural language processing tasks. ...
... Personal experience, emotional expression, and cultural context are the usual causes of human creativity, qualities that AI operates without, based merely on statistical pattern recognition. As Boden (2004) aptly points out, although AI can be programmed to produce novel combinations of pre-existing elements (the so-called combinatorial forms of creativity) it lacks the capacity for true innovation or personal insight, both of which are key aspects of human creativity. ...
... When ChatGPT composes a poem, it selects probably the most statistically appropriate words and phrases from its dataset based on grammatical rules and stylistic convention. While the result can be coherent and even poignant, it is semiotically superficial when compared to works produced by creative humans: their symbols and metaphors carry a great deal of personal and cultural baggage (Boden, 2004). In further support of this chasm between human-generated and AI-generated content, Peirce's semiotic theory (which extends Saussure through the inclusion of a triadic model of the sign that incorporates the "representamen," "object," and "interpretant") provides further insight. ...
The paper presents a comprehensive analysis on the various capabilities of ChatGPT, a chatbot developed by OpenAI that is capable of generating creative content in areas such as visual arts, poetry, and music.
... According to Catarau-Cotutiu et al. (2022) and Russell and Norvig (2016), AI models are capable of learning and representing knowledge, identifying patterns and knowledge structures, and using them to establish useful and appropriate connections and inferences. AI models use a process known as representational learning, in which the model learns to identify and represent features of the data that help it identify patterns and generalizable rules that describe the data meaningfully (Boden, 2004;Vear and Poltronieri, 2022). For all these reasons, AI tools support human creativity by providing explicit representations of relevant knowledge, knowledge structures, and generative rules at different levels of representational abstraction (Boden, 2004). ...
... AI models use a process known as representational learning, in which the model learns to identify and represent features of the data that help it identify patterns and generalizable rules that describe the data meaningfully (Boden, 2004;Vear and Poltronieri, 2022). For all these reasons, AI tools support human creativity by providing explicit representations of relevant knowledge, knowledge structures, and generative rules at different levels of representational abstraction (Boden, 2004). ...
The rise of generative artificial intelligences (AIs) has quickly made them auxiliary tools in numerous fields, especially in the creative one. Many scientific works already discuss the comparison of the creative capacity of AIs with human beings. In the field of Engineering Design, however, numerous design methodologies have been developed that enhance the creativity of the designer in their idea generation phase. Therefore, this work aims to expand previous works by leading a Generative Pre-trained Transformer 4 (GPT-4) based generative AI to use a design methodology to generate creative concepts. The results suggest that these types of tools can be useful for designers in that they can inspire novel ideas, but they still lack the necessary capacity to discern technically feasible ideas.
... Combinational Creativity Margaret A. Boden's seminal work (M. A. Boden, 1998Boden, , 2004M. Boden, 2009) identifies three fundamental types of creativity, with combinational creativity-the generation of novel ideas through familiar combinations-being particularly relevant to Artificial Intelligence (AI) research. ...
... For AI systems to achieve this form of creativity, Boden argues they must develop three critical capabilities: rich associative memory, understanding of human values, and computational expression of these values . Despite recent advances in AI, these fundamental aspects remain largely unexplored in modern research (M. A. Boden, 1998Boden, , 2004Ma et al., 2023). ...
The ability to combine existing concepts into novel ideas stands as a fundamental hallmark of human intelligence. Recent advances in Vision-Language Models (VLMs) like GPT-4V and DALLE-3 have sparked debate about whether their outputs reflect combinational creativity--defined by M. A. Boden (1998) as synthesizing novel ideas through combining existing concepts--or sophisticated pattern matching of training data. Drawing inspiration from cognitive science, we investigate the combinational creativity of VLMs from the lens of concept blending. We propose the Identification-Explanation-Implication (IEI) framework, which decomposes creative processes into three levels: identifying input spaces, extracting shared attributes, and deriving novel semantic implications. To validate this framework, we curate CreativeMashup, a high-quality dataset of 666 artist-generated visual mashups annotated according to the IEI framework. Through extensive experiments, we demonstrate that in comprehension tasks, best VLMs have surpassed average human performance while falling short of expert-level understanding; in generation tasks, incorporating our IEI framework into the generation pipeline significantly enhances the creative quality of VLMs outputs. Our findings establish both a theoretical foundation for evaluating artificial creativity and practical guidelines for improving creative generation in VLMs.
... This can lead to more coherent and persuasive writing. In addition, the E-M-M technique can also stimulate creativity and idea generation (Boden, 2005). By allowing writers to freely associate ideas and concepts, electronic mind mapping can help them generate new and innovative ideas that might not have occurred to them otherwise. ...
... The results showed that the E-M-M technique significantly influenced the Iranian EFL learners' persuasive writing. The outcomes align with some studies (i.e., Boden, 2005;Kiewra, 2011;Kozlowski & Ilgen, 2009) or peers for feedback. This allows for timely and constructive feedback, which is crucial for improving writing skills. ...
This study examined the potential effects of implementing the E-Mind-Mapping (E-M-M) technique vs. teaching Rhetorical Devices (RDs) on the overlooked yet frequently used persuasive writing skill among Iranian EFL learners. Following a quasi-experimental design, 52 Iranian upper-intermediate EFL learners were conveniently selected and divided into experimental and control groups in which participants in the former were taught the material using MindMeister mind-mapping software, and the ones in the latter experienced learning ethos, pathos, and logos persuasive strategies for 15 ninety-minute sessions. The instruments included the Oxford Quick Placement Test (OQPT) and valid and reliable writing tests in the pre- and post-test phases. The results showed that while the E-M-M technique and teaching RDs enhanced persuasive writing among Iranian EFL learners, the aforementioned effect was considerably more beneficial compared to the influences of the second-mentioned. The outcomes may benefit TEFL, including EFL teachers, learners and teacher trainers, educational technology, and educational psychology.
... According to Boden [5], "Creativity is the ability to come up with ideas or artefacts that are new, surprising and valuable." Ideas could be concepts, narrative, musical composition, and scientific theories, whereas artefacts could be paintings, novels, sculptures, robots, and so on. ...
... Novelty and innovations are fundamentally connected to creativity [5]. Thus, we were expecting to see novel visualizations such as the UpSet plots [46] or Treemaps [2] in our corpus. ...
Understanding the role of creativity in visualization design becomes increasingly important as the field matures, particularly with the emergence of various visualization authoring and recommendation systems. In this paper, we examine how creativity manifests in visualization design processes and how academic research has conceptualized it over time. Through a systematic review of 58 visualization papers that use the terms "creativity" or "creative," we analyze the evolution of creative practices in visualization design. Our findings show that prior literature predominantly used atypical designs through free-form drawings, infographics, pictorials, and data comics to define creative representations. However, creativity in visualization design extends beyond visual representations to encompass early needfinding design activities such as sketching, storyboarding, discussion, and card sorting. Data visualization can also support a wide variety of creative tasks (e.g., fiction writing). We discuss the implications of these findings for fostering innovation within established design paradigms and for developing more sophisticated visualization authoring systems. The full list of coded papers are available here: https://vizcreativity.notion.site/coded-papers.
... To further explore this potential, we propose Imagine360, a proof-of-concept prototype that integrates co-creation principles [5,11,31] with AI agents for panoramic video generation in immersive environments. Our system enables users to generate panoramic videos with AI assistance, evaluate generation outcomes in real time, provide speech-based text prompts that are refined and supported by the AI agent, and recenter the panorama video's focal point based on an egocentric perspective. ...
... Participants completed two assessments to evaluate cognitive workload and creativity. The NASA TLX [17] measured workload across six dimensions on a 10-point Likert scale, while Boden's Creativity Framework [5] assessed novelty, value, surprise, and relevance on a 7-point scale. After the tasks and surveys, participants joined a 10-minute semi-structured exit interview for qualitative feedback. ...
The emerging field of panoramic video generation from text and image prompts unlocks new creative possibilities in virtual reality (VR), addressing the limitations of current immersive experiences, which are constrained by pre-designed environments that restrict user creativity. To advance this frontier, we present Imagine360, a proof-of-concept prototype that integrates co-creation principles with AI agents. This system enables refined speech-based text prompts, egocentric perspective adjustments, and real-time customization of virtual surroundings based on user perception and intent. An eight-participant pilot study comparing non-AI and linear AI-driven workflows demonstrates that Imagine360's co-creative approach effectively integrates temporal and spatial creative controls. This introduces a transformative VR paradigm, allowing users to seamlessly transition between 'seeing' and 'imagining,' thereby shaping virtual reality through the creations of their minds.
... A GenAI media interaction and psychological safety in teams Psychological safety (Edmonson, 1999;Edmondson & Mogelof, 2006) How is psychological safety implicated in the team interaction with GenAI as a medium in the context of the creative work? What type of interactions and relationships with a GenAI medium are needed for different types of creativity The Creative Mind (Boden, 1998(Boden, , 2004 What affordances of GenAI will allow users to approach it as a medium for different types of creativity? thoughts and ideas, or will they use it as the means for easy automation and with that create automated thoughts and responses? ...
Generative AI (GenAI), a subcategory of Artificial Intelligence (AI), leverages machine and deep learning algorithms to produce original content in various formats, including text, images, video, and sound (e.g., ChatGPT, Midjourney). An intuitive interaction through natural language commands (prompts), in combination with an element of surprise in the generated output, has fuelled widespread enthusiasm for GenAI. Yet the quality, originality, and value of the output vary based on user commands and training data. This often raises questions about consistency and optimal use of GenAI, especially compared to the established uses of AI. Meanwhile, while the predominant application of AI in the workplace is focussed on predictable algorithmic models for task automation and work efficiency, this attention towards automation has also led to questions about meaningful work and employee contribution at work. In this chapter, we explore the emerging affordances and malleability of GenAI to produce original and useful output, often associated with a creative act. To differentiate it from the tool-for-the-task usage of AI (e.g., credit rating), we position GenAI as a medium—a channel for exploration, innovation, and creative experience at work—a shift to more human-oriented work participation in a digitalised environment.
... After this training phase, the NN can generate new scores with similar musical properties to the examples it was trained on. This approach closely resembles the intuitive methods composers often use, grounded in experiential processes shaped by the musical cultures in which they are immersed (Pearce and Wiggins, 2007;Wiggins, 2006;Boden, 2004). The strength of this method is also its weakness; since it is based on statistical predictions, we should not expect any output that substantially differs musically from the training set. ...
We present 'NeuralConstraints,' a suite of computer-assisted composition tools that integrates a feedforward neural network as a rule within a constraint-based composition framework. 'NeuralConstraints' combines the predictive generative abilities of neural networks trained on symbolic musical data with an advanced backtracking constraint algorithm. It provides a user-friendly interface for exploring symbolic neural generation, while offering a higher level of creative control compared to conventional neural generative processes, leveraged by the constraint solver. This article outlines the technical implementation of the core functionalities of 'NeuralConstraints' and illustrates their application through specific tests and examples of use.
... One of the central questions in digital poetics is whether AI-generated poetry can be considered genuinely creative. Boden (2004) defines creativity as the ability to produce novel and valuable outputs. Transformer models undoubtedly generate novel combinations of words, but whether these combinations carry intrinsic aesthetic value or merely mirror training data remains contentious. ...
Recent advancements in Natural Language Processing (NLP), particularly the emergence of transformer-based models like GPT-3 and BERT, have revolutionised the way machines generate and understand human language. This paper delves into the artistic potentials of these models, exploring how they craft poetic content with human-like creativity. While early NLP systems were limited to rule-based generation, transformers have enabled machines to engage in complex linguistic patterns, metaphorical expressions, and emotional resonance. This article reviews the theoretical foundations of digital poetics, examines the role of large-scale language models in poetic generation, and evaluates the limitations and future trajectories of machine creativity. With the boundary between human and machine authorship becoming increasingly blurred, this study argues that transformer-based NLP models are not only tools for linguistic emulation but also catalysts for reimagining the very nature of poetic creativity.
... The concept of machine-assisted storytelling has roots in early computational creativity, which sought to model creativity algorithmically (Boden, 2004). With the advent of deep learning and the transformer architecture introduced by Vaswani et al. (2017), the field experienced exponential growth. ...
The emergence of Natural Language Processing (NLP) has revolutionised the narrative landscape by enabling the creation of dynamic and interactive storytelling experiences. By bridging computational linguistics and literary creativity, NLP is not only automating textual analysis but also generating context-aware narratives in real time. This paper explores the convergence of artificial intelligence and storytelling, analysing how NLP facilitates user-centred narratives, interactive literature, and machine-authored prose. The research discusses leading transformer-based models, such as GPT and BERT, and their role in reshaping narrative structures. It further investigates the implications for authorship, reader engagement, and the philosophical boundaries between human and machine creativity. Ultimately, the paper reveals that while NLP introduces vast opportunities for innovation in storytelling, it also presents challenges in terms of ethical authorship, bias, and the authenticity of narrative voice. Through an interdisciplinary lens, this study proposes that the future of storytelling lies in collaborative human-AI authorship, where computational tools augment, rather than replace, human imagination.
... Wadinambiarachchi et al. [28] argue that using AI compromises the kind of creativity people can exhibit and undermines divergent thinking, making it less likely that people can creatively transform a given domain. To understand these concerns here, it can be helpful to recall the important distinction drawn by Margaret Boden [4,3] between three kinds of creativity: exploratory, combinational and transformational. We associate the latter with discovery in art and science, it is when an individual transcends the conceptual space beyond what was previously considered possible, producing something highly novel, surprising and valuable. ...
After ‘Théâtre D’opéra Spatial’ won a prize in the Colorado State Fair’s annual art competition in 2022 there was a very strong outcry in the media that this signified the ‘end of art’. Allen himself was quoted in the New York Times saying ‘Art is dead, dude. It’s over. AI won. Humans lost.’ While some dismissed the idea that AI generated images constitute real art, others more optimistically argued that the creative process is undergoing transformation. In this paper I want to address several worries regarding AI art. I argue that far from signifying the end of art or not qualifying as legitimate art, we should be focusing on what value generated art could have. I first explore how algorithmic bias, data extraction, and environmental concerns can affect how we engage with AI generated art and whether we find it valuable. I then explore whether there are conditions under which these moral flaws could be overcome to engage the audience with generated artworks in a meaningful way, offering thus conditions under which the choice of using the technology can be seen as artistically valuable, despite its moral flaws.
... In recent decades, creativity has been the topic of prominent studies in cognitive psychology (Cropley 1968) with major implications in the worlds of design, innovation and the new information and communication technologies (Rowe 1987, Boden 2004, Hemlin and Allwood and Martin 2004, Sawyer 2006. Creative processes have even become an academic subject and working methodology -brainstorming, design thinking, co-creation, etc. - (Design & thinking 2011). ...
... In particular, many researchers have expressed concerns (Epstein et al. 2023;Levent and Shroff 2023;Hancock et al. 2020;Buschek et al. 2021) about potential homogenization effects (Anderson et al. 2024) that these tools may exert on the creative output of their users, and a range of studies have found some degree of evidence for increased homogeneity of human creative output stemming from the use of AI-based CSTs in the creative process (Arnold et al. 2020;Jakesch et al. 2023;Padmakumar and He 2023;Doshi and Hauser 2023). Given that definitions of creativity often include originality (Torrance 1966) or novelty (Boden 2004) as one of creativity's key facets, it has become important to understand the mechanism by which AI-based CSTs can sometimes apparently undermine the originality of their users-and how these threats to originality can be mitigated or reversed. ...
We characterize and discuss the “death of the author”: a problem that emerges when AI-based creativity support tools (CSTs) allow their users to produce highly detailed output artifacts—such as lengthy written stories, or high-resolution pieces of visual art—from very small amounts of input (e.g., brief textual prompts). When small amounts of user input are extrapolated by a CST into a highly detailed output, the CST itself has to make many creative decisions that would otherwise fall to the user, disrupting the usual close relationship between input intentionality and output detail in the creative process and yielding output artifacts that contain much more of the tool’s than the user’s creative signature. Though users of such tools are often able to inject more intention into the output through the adoption of more sophisticated creative practices, these high-intentionality practices tend to be more effortful than the default modes of use of AI-based CSTs, and the use of such practices is not always immediately apparent in the output artifacts. We analyze the death of the author from an information-theoretic perspective, focusing on the informational ratio between intent and meaning in creative artifacts; examine implications of the death of the author, including homogenization of creative outputs and rhetorical confusion around the “soulfulness” or “soullessness” of art produced with AI assistance; and suggest strategies for mitigating the death of the author in future AI-based CSTs.
... McKinsey (2025a) highlights AI's $4.4 trillion productivity potential, partly from creative automation, amplifying this shift. This challenges views of creativity as uniquely human (Boden, 2004;Csikszentmihalyi, 1996), tied to cultural and emotional depth (Frey & Osborne, 2017;Menger, 1999). While generative models replicate style (Gatys et al., 2016), In financial services, expertise externalizes through algorithmic trading, risk assessment, and advisory systems. ...
This perspective paper examines a fundamental paradox in the relationship between professional expertise and artificial intelligence: as domain experts increasingly collaborate with AI systems by externalizing their implicit knowledge, they potentially accelerate the automation of their own expertise. Through analysis of multiple professional contexts, we identify emerging patterns in human-AI collaboration and propose frameworks for professionals to navigate this evolving landscape. Drawing on research in knowledge management, expertise studies, human-computer interaction, and labor economics, we develop a nuanced understanding of how professional value may be preserved and transformed in an era of increasingly capable AI systems. Our analysis suggests that while the externalization of tacit knowledge presents certain risks to traditional professional roles, it also creates opportunities for the evolution of expertise and the emergence of new forms of professional value. We conclude with implications for professional education, organizational design, and policy development that can help ensure the codification of expert knowledge enhances rather than diminishes the value of human expertise.
... They have excelled in generating high-quality, human-like content, ranging from code generation (Ni et al. 2023;Liu et al. 2024a) and music composition (Yuan et al. 2024) to literature (Gómez-Rodríguez and Williams 2023;Liu et al. 2024b) and educational tools (Lan and Chen 2024;Orenstrakh et al. 2023). Creativity in LLMs is often evaluated using frameworks like Margaret Boden's taxonomy (Boden 2004), which categorizes creativity into combinational, exploratory, and transformational types. While LLMs perform well in combinational creativity, achieving true transformational creativity remains a significant challenge (Franceschelli and Musolesi 2023). ...
The mathematical capabilities of AI systems are complex and multifaceted. Most existing research has predominantly focused on the correctness of AI-generated solutions to mathematical problems. In this work, we argue that beyond producing correct answers, AI systems should also be capable of, or assist humans in, developing novel solutions to mathematical challenges. This study explores the creative potential of Large Language Models (LLMs) in mathematical reasoning, an aspect that has received limited attention in prior research. We introduce a novel framework and benchmark, CreativeMath, which encompasses problems ranging from middle school curricula to Olympic-level competitions, designed to assess LLMs' ability to propose innovative solutions after some known solutions have been provided. Our experiments demonstrate that, while LLMs perform well on standard mathematical tasks, their capacity for creative problem-solving varies considerably. Notably, the Gemini-1.5-Pro model outperformed other LLMs in generating novel solutions. This research opens a new frontier in evaluating AI creativity, shedding light on both the strengths and limitations of LLMs in fostering mathematical innovation, and setting the stage for future developments in AI-assisted mathematical discovery.
... Our definition of a creative composition task is in the product category. In the product view of creativity, previous work has outlined both the importance of value and novelty in achieving creativity (Boden, 2004;Gaut, 2010;Lamb et al., 2018); evaluating the creativity of a product necessitates the evaluation of these dimensions at a minimum. The multiobjective evaluation of creativity distinguishes creative outputs from merely high entropy generations. ...
Foundation models that are capable of automating cognitive tasks represent a pivotal technological shift, yet their societal implications remain unclear. These systems promise exciting advances, yet they also risk flooding our information ecosystem with formulaic, homogeneous, and potentially misleading synthetic content. Developing benchmarks grounded in real use cases where these risks are most significant is therefore critical. Through a thematic analysis using 2 million language model user prompts, we identify creative composition tasks as a prevalent usage category where users seek help with personal tasks that require everyday creativity. Our fine-grained analysis identifies mismatches between current benchmarks and usage patterns among these tasks. Crucially, we argue that the same use cases that currently lack thorough evaluations can lead to negative downstream impacts. This position paper argues that benchmarks focused on creative composition tasks is a necessary step towards understanding the societal harms of AI-generated content. We call for greater transparency in usage patterns to inform the development of new benchmarks that can effectively measure both the progress and the impacts of models with creative capabilities.
... As explained above, we focused on these creativity myths-beliefs about creativity that are not supported by scientific evidence (Benedek et al., 2021;Boden, 2004). These creativity myths are suggested to have negative influences on creativity education (Benedek et al., 2021). ...
... Domnievame sa, že uvedené nezrovnalosti sú jedným z dôvodov prevahy definícií zohľadňujúcich primárne aspekt novosti a inovatívnosti. V tomto ponímaní možno kreativitu definovať ako schopnosť produkovať nápady a artefakty, ktoré sú nové, neočakávané a disponujú určitou pridanou hodnotou (Boden 2004), ako proces interného "prenastavenia" jednotlivca, pri ktorom dochádza k inovatívnemu riešeniu problémov (Garrido 2021) či ako schopnosť produkovať nové a inovatívne nápady, ktoré príjemcu motivujú k objavovaniu nových spôsobov myslenia a nazerania na určitý jav (Hutson 2023a). Uvedené definície tak nespájajú kreativitu výlučne s umeleckým vyžitím jednotlivca, ale chápu ju aj ako jeden z predpokladov riešenia problémov, a to nezávisle od umeleckého prostredia. ...
Vývoj digitálnych technológií je javom, ktorého dynamika má v poslednom desaťročí výrazne vzostupnú tendenciu. Ide o dôsledok dlhodobo narastajúceho objemu dát a potreby ich efektívneho spracovávania, ktorá súvisí aj s narastajúcimi nárokmi na produktivitu a kreativitu človeka v pracovnej a študijnej oblasti. Do centra pozornosti sa preto dostávajú nástroje, ktoré umožňujú čeliť týmto výzvam, vrátane textových generátorov či generátorov obrázkov. Vzhľadom na ich popularizáciu sa postupne stávajú prirodzenými partnermi pri vytváraní (informačných) produktov, ktoré by bez ich využitia v mnohých prípadoch podliehali limitom ľudskej mysle. Cieľom príspevku je predstaviť koncept kooperácie medzi človekom a nástrojmi umelej inteligencie, s ohľadom na príležitosti vyplývajúce zo silných stránok oboch zúčastnených strán. Autorka tak na jednej strane vyzdvihuje význam integrácie týchto nástrojov v rámci rôznorodej ľudskej aktivity, no zároveň poukazuje na potenciálne riziká spojené so znižujúcou sa úrovňou kreatívneho myslenia. Okrem toho berie do úvahy aj narastajúcu mieru dôvery voči technológii, ktorej limity sa dodnes prejavujú v nepresnosti poskytovaných informácií, a teda aj v potrebe ich overovania zo strany relevantných autorít. Technologické inovácie totiž nepostačuje prijať; je potrebné ich tiež usmerňovať spôsobom zamedzujúcim nevedomej chybovosti na strane používateľa.
... As creativity manifests as a complex, context dependent phenomenon, it precludes reduction to a monolithic, universally applicable definition. While traditional frameworks of creativity emphasize three core attributes-novelty, utility and surprise [19,53,7], recent empirical investigations on AI-mediated creativity have both challenged and expanded these human-centric constructs. ...
Small business owners (SBOs) often lack the resources and design experience needed to produce high-quality advertisements. To address this, we developed ACAI (AI Co-Creation for Advertising and Inspiration), an GenAI-powered multimodal advertisement creation tool, and conducted a user study with 16 SBOs in London to explore their perceptions of and interactions with ACAI in advertisement creation. Our findings reveal that structured inputs enhance user agency and control while improving AI outputs by facilitating better brand alignment, enhancing AI transparency, and offering scaffolding that assists novice designers, such as SBOs, in formulating prompts. We also found that ACAI's multimodal interface bridges the design skill gap for SBOs with a clear advertisement vision, but who lack the design jargon necessary for effective prompting. Building on our findings, we propose three capabilities: contextual intelligence, adaptive interactions, and data management, with corresponding design recommendations to advance the co-creative attributes of AI-mediated design tools.
... True originality, as seen in Einstein's and Darwin's insights, involves reframing fundamental concepts rather than merely extending existing knowledge. AI's current capabilities remain within the bounds of interpolation rather than genuine theoretical breakthroughs (Boden, 2004). ...
As artificial intelligence (AI) systems grow increasingly sophisticated, the need for a meaningful test of intelligence becomes more pressing. Traditional approaches, such as the Turing Test and the Lovelace Test, assess conversational ability and creativity, respectively, but these metrics fail to measure the deeper cognitive capabilities associated with scientific reasoning. This paper proposes a superior test of intelligence: the capacity for scientific discovery. Two levels of discovery are distinguished. Level 1 involves synthesizing existing knowledge from the scientific literature-an ability that AI, with its vast processing and recall capabilities, can potentially achieve. Level 2, however, entails the formulation of novel theoretical frameworks that extend beyond simple interpolation, exemplified by Einstein's theory of relativity and Darwin's theory of evolution. While Level 1 discoveries demonstrate advanced pattern recognition and synthesis, only Level 2 discoveries serve as a true benchmark for human-level intelligence in AI. This paper refines the argument for scientific discovery as an intelligence test, presents counterarguments regarding AI's capacity for creativity, and explores potential pathways for AI to reach Level 2 discovery.
... For example, if children are asked to "draw an animal that does not exist", they can generalize from prior experience to produce an imaginary animal, such as a dog-like creature with six legs, three camel humps, and three pig tails 12 . An infl uential hypothesis is that this seemingly unbounded generali zation depends on a n internal representation of discrete units (symbols) that can be recombined into composite representations, in a process called compositional generalization [1][2][3][4][5][6][7][8][9][10][11] . Symbols support generalization because they enable the systematic derivation of a large set of possible representations from a smaller set of components, such as new animals imagined as rule-based combinations of discrete parts (e.g., new animal = 1 torso + 8 arms + 4 legs ). ...
At the core of intelligence is proficiency in solving new problems, including those that differ dramatically from problems seen before. Problem-solving, in turn, depends on goal-directed generation of novel thoughts and behaviors ¹ , which has been proposed to rely on internal representations of discrete units, or symbols, and processes that can recombine them into a large set of possible composite representations 1–11 . Although this view has been influential in formulating cognitive-level explanations of behavior, definitive evidence for a neuronal substrate of symbols has remained elusive. Here, we identify a neural population encoding action symbols—internal, recombinable representations of discrete units of motor behavior—localized to a specific area of frontal cortex. In macaque monkeys performing a drawing-like task designed to assess recombination of learned action symbols into novel sequences, we found behavioral evidence for three critical features that indicate actions have an underlying symbolic representation: (i) invariance over low-level motor parameters; (ii) categorical structure, reflecting discrete classes of action; and (iii) recombination into novel sequences. In simultaneous neural recordings across motor, premotor, and prefrontal cortex, we found that planning-related population activity in ventral premotor cortex encodes actions in a manner that, like behavior, reflects motor invariance, categorical structure, and recombination, three properties indicating a symbolic representation. Activity in no other recorded area exhibited this combination of properties. These findings reveal a neural representation of action symbols localized to PMv, and therefore identify a putative neural substrate for symbolic cognitive operations.
... For this reason, it is important to employ evaluation paradigms that go beyond the simple quantitative evaluation of the produced recommendations but rather evaluate the recommendation process itself and its capability of potentially producing serendipitous recommendations [121]. The literature on computational creativity offers many paradigms for evaluation [122] and for the description of how a conceptual space is explored [123,124], and we believe that it would be possible to employ many of those ideas in the context of serendipitous recommendations. ...
The importance of recommender systems has grown in recent years, as these systems are becoming one of the primary ways in which we access content on the Internet. Along with their use, concerns about the fairness of the recommendations they propose have rightfully risen. Recommender systems are known to be affected by popularity bias, the disproportionate preference towards popular items. While this bias stems from human tendencies, algorithms used in recommender systems can amplify it, resulting in unfair treatment of end-users and/or content creators. This article proposes a narrative review of the relevant literature to characterize and understand this phenomenon, both in human and algorithmic terms. The analysis of the literature highlighted the main themes and underscored the need for a multi-disciplinary approach that examines the interplay between human cognition, algorithms, and socio-economic factors. In particular, the article discusses how the overall fairness of recommender systems is impacted by popularity bias. We then describe the approaches that have been used to mitigate the harmful effects of this bias and discuss their effectiveness in addressing the issue, finding that some of the current approaches fail to face the problem in its entirety. Finally, we identify some open problems and research opportunities to help the advancement of research in the fairness of recommender systems.
... In practice, creativity often involves a dynamic interplay among them [51]. For instance, breaking existing frameworks may precede bending those components into new configurations, which are then blended with unrelated ideas to produce transformative innovations [52]. Understanding these processes provides a framework for developing strategies to enhance creativity in individuals and teams, grounded in the workings of the human brain [25]. ...
Creativity is one of the most sophisticated and essential capabilities of the human brain, enabling the generation of novel and valuable ideas across domains such as art, science, and technology. Grounded in neuroscience, this paper explores the intricate neural mechanisms underlying creative thinking. It focuses on the dynamic interplay of three large-scale neural networks: the Default Mode Network (DMN), responsible for spontaneous ideation and divergent thinking [1]; the Executive Control Network (ECN), critical for evaluative processes and convergent thinking [2]; and the Salience Network (SN), which mediates cognitive transitions and prioritises relevant information [3]. Additionally, the cognitive processes of bending (restructuring information) [4], breaking (deconstructing established ideas) [5], and blending (synthesising novel constructs) [6] are discussed as essential mechanisms of creative ideation. The paper also examines how collaborative environments, particularly virtual ones, amplify creative potential by integrating diverse neural activity [7]. Practical implications are offered to enhance creativity in individuals and teams, with a focus on optimising individual cognitive functioning [8], leveraging collaboration [9], and applying visual representations to connect and integrate ideas [10]. These findings bridge the gap between neuroscientific theory and real-world applications, contributing to a deeper understanding of how creativity can be nurtured and harnessed.
... Novelty refers to the originality of the idea or product, while value refers to its usefulness or appropriateness in a particular context. These two characteristics form the bedrock of creativity, transcending disciplinary boundaries and providing a common thread linking diverse conceptions of creativity (Boden, 2004). ...
This study explores AI creativity through a two-pronged experiment: ChatGPT for language processing and MidJourney for text-to-image synthesis. Both models focused on expressing Ekman's six basic emotions. By manipulating ChatGPT's 'temperature' to vary linguistic creativity and using these outputs to guide MidJourney's image creation, the research examines the nuanced capabilities of AI in generating emotionally resonant artworks and linguistically complex prompts. The study's findings highlight two significant contributions of AI to creative domains: firstly, AI's ability to evoke specific emotions in viewers through art, effectively bridging the gap between synthetic cognition and human emotion; and secondly, AI's development of unique artistic styles, a result of assimilating and reinterpreting diverse artistic influences. These insights not only broaden our understanding of AI's creative capabilities but also point towards its potential to significantly enrich the artistic landscape.
... Then, participants were briefed on the design task which involved creating as innovative a design as possible under the assistance of two different Generative AI tools. Additionally, we introduced CombinatorX, a representative GenAI-assisted design method [12], which utilizes combinational creativity-merging two concepts into a novel idea [7]. The CombinatorX process involves identifying additive embodiments and forming textual combinational ideas, followed by using text-to-image technology to visualize these ideas. ...
Generative AI (GenAI) provides new opportunities for creativity support, but the phenomenon of GenAI design fixation remains underexplored. While human design fixation typically constrains ideas to familiar or existing solutions, our findings reveal that GenAI similarly experience design fixation, limiting its ability to generate novel and diverse design outcomes. To advance understanding of GenAI design fixation, we propose a theoretical framework includes the definition, causes, manifestations, and impacts of GenAI design fixation for creative design. We also conducted an experimental study to investigate the characteristics of GenAI design fixation in practice. We summarize how GenAI design fixation manifests in text generation model and image generation model respectively. Furthermore, we propose methods for mitigating GenAI design fixation for future creativity support tool design. We recommend adopting the lens of GenAI design fixation for creativity-oriented HCI research, as the unique perspectives and insights it provides.
... CMT sheds light on the cognitive nature of metaphors, thus avoiding a restrictive definition of this linguistic phenomenon as a mere rhetorical device. Metaphors seem to reflect the very structure of our cognitive system since the latter adapts packages of knowledge already acquired to understanding concepts that are difficult to grasp (Boden 2004). This means that metaphorical thinking allows humans to fill the gap in the comprehension processes of unfamiliar, abstract, subjective, and vague phenomena (Gentner, Holyoak, Kokinov 2001). ...
This study aims at investigating the metaphorical expressions stemming from the experience of depression to deepen our comprehension of this mental disorder and its consequences. To this end, four online fora dealing with mental illness were selected to gather data concerning the metaphorical description of depression as offered by online users who suffer from it. The personal accounts of 71 users were chosen to qualitatively analyse the most recurrent metaphorical patterns employed to conceptualise depression. The results were interpreted by means of Conceptual Metaphor Theory (CMT) and Embodied Cognition Theory (ECT). According to CMT, linguistic metaphors are a reflection of our innate capacity to think metaphorically in order to create mental models of reality based on analogical and associative mode of thinking, two powerful mental forces of the human cognitive system. This is the reason why metaphors, due to their cognitive power, are able to shape our mental comprehension of the world by organising and constructing a cognitive representation of reality. Moreover, as claimed by ECT, metaphors stem from our daily interactions with the world which are unconsciously internalised and later used as a conceptual basis to structure abstract, subjective and intangible domains of experience. By combining these two frameworks of reference, the study reconstructs a view of the conceptual world of depression. Not only does this analysis offer an insight into the depressive disorder, but it also contributes to showing that the conceptual world of depression is not only thought and conceptualised, but it is also intensely experienced and lived, in line with the hypothesis that conceptualisation entails simulation.
... In this, however, it is important to note that both "big-C" and "small-c" creativity involve working imaginatively and engaging in process of exploration, combination and transformation (Boden, 1990). Moreover, both types of creativity rely on the acquisition of knowledge and skills, and operate under certain constraints (of a conceptual, material or practical nature) which paradoxically actually contribute to making creativity possible: "it is the partial continuity of constraints which enables a new idea to be recognised, by author and audience alike, as a creative contribution" (Boden,1990: 83). ...
... Margaret Boden suggests human creativity can be defined through three methods: combination, exploration and transformation [2]. It could be argued ambiguity, uncertainty and indeterminacy respectively align with these approaches. ...
This article evaluates how creative uses of machine learning can address three adjacent terms: ambiguity, uncertainty and indeterminacy. Through the progression of these concepts it reflects on increasing ambitions for machine learning as a creative partner, illustrated with research from Unit 21 at the Bartlett School of Architecture, UCL. Through indeterminacy are potential future approaches to machine learning and design.
... Semantic networks represent knowledge in the form of graphs that consist of vertices and edges [52]. Vertices indicate individual concepts, whereas edges between pairs of vertices indicate specific semantic connections [53]. Graphs could be divided into directed or undirected depending on the type of edges contained in the graph. ...
Human creativity originates from brain cortical networks that are specialized in idea generation, processing, and evaluation. The concurrent verbalization of our inner thoughts during the execution of a design task enables the use of dynamic semantic networks as a tool for investigating, evaluating, and monitoring creative thought. The primary advantage of using lexical databases such as WordNet for reproducible information-theoretic quantification of convergence or divergence of design ideas in creative problem solving is the simultaneous handling of both words and meanings, which enables interpretation of the constructed dynamic semantic networks in terms of underlying functionally active brain cortical regions involved in concept comprehension and production. In this study, the quantitative dynamics of semantic measures computed with a moving time window is investigated empirically in the DTRS10 dataset with design review conversations and detected divergent thinking is shown to predict success of design ideas. Thus, dynamic semantic networks present an opportunity for real-time computer-assisted detection of critical events during creative problem solving, with the goal of employing this knowledge to artificially augment human creativity.
... Vocal identity of these artists may be manifested and described in terms of other attributes auxiliary to the basic characteristics of singing voice that we will explore below. The same is true for other individuals such as politicians, movie stars and other celebrities who are not singers but whose vocal identity is exposed to cloning 7 . ...
Focused on the phenomenon of human voice, the paper purports to develop approaches to legal protection of ordinary people's voices and those of artists as the technologies for sound synthesis, music and vocal performance are becoming more sophisticated. It was demonstrated the problem of legal protection of human voice has become especially pressing one in the context of artificial neural networks such as vocaloid designed for sound synthesis and voice cloning. The study provides a systemic arrangement of legally meaningful knowledge of human voice useful for the development of legal provisions to protect this personal good. The legal substance of vocal impersonation as a way to simulate and manipulate a synthesized voice was explored. Theoretically applicable legal constructs for protection of voice and computerized cloning technologies were analyzed. A trend to use copyright rather than patent for protecting vocaloid-like generative neural networks and other technological solutions for vocal synthesis was identified. The concept of voice was critically analyzed to propose a viable legal provision for its protection. The primary and auxiliary features of the concept of voice were parametrized for possible use in disputes on the legitimacy of voice cloning or vocal impersonation. The concept of vocal identity of ordinary people and artists was proposed for legal protection of this personal good as a set of performative sonic features including the basic parameters of singing voice as well as acoustic-phonetic and articulatory features of vocalization. A comprehensive legal and technological methodology for the protection of vocal identity was proposed.
... Since it was coined by Boden in her theory of the creative mind, the term has attained "an almost biblical status" (Forth et al., 2010, p. 504) in creativity research. Boden uses it to refer to a significant type of individual creativity-as opposed to other mundane typesthat makes conventional ways of thinking cease to work (Boden, 1995(Boden, , 2004(Boden, , 2009b. Boden explains this phenomenon in a computational framework of the creative mind. ...
Margaret Boden famously theorizes that the highest form of creativity is more than the production of new ideas—it involves the transformation of a conceptual space consisting of all possible ideas that a person can obtain. This article examines whether this notion of transformative creativity can be applied to the field of biology. Biological transformative creativity (BTC) is theoretically conceivable if an extension of Boden’s original framework is allowed to include non-conceptual spaces as the object of transformation. However, identifying specific biological phenomena that warrant the label of transformative creativity in living systems poses a substantial challenge. After scrutinizing two recent theories regarding BTC—one connecting BTC to evolution and the other equaling it to self-organization—this paper turns to a third alternative hypothesis that emphasizes the autonomous, self-productive mechanisms through which novel organizational patterns and morphological features take shape. To unpack this idea, the paper draws on extensive evidence in epigenetic studies and argues that autonomous transformation of overall possibilities of living organisms occurs at the individual level primarily due to flexible modifications of gene expression norms in the organism. Then, the paper analyzes the developmental plasticity of C. elegans and the origin and differentiation of castes in social insects as two examples of the epigenetic form of BTC. The account is expected to contribute to a more appropriate understanding of the origin of human creativity and the creative nature of life.
Creative practitioners rely on tools to capture and manage ideas as a foundational aspect of their work. However, we have little knowledge about how idea management practices vary in different creative domains. Combining insights from qualitative surveys ( N 200) and follow-up in-depth interviews ( n 60) with creative professionals from four domains (interaction design, research, music, and graphics) of creative work, we report on (1) how ideas are externalized in practitioners’ archives, (2) what they consider important when choosing tools to capture ideas, and (3) how these tool collections resemble and differ from each other. Our cross-domain study demonstrates that participants’ tool use reflects idea capture characteristic needs as well as domain-specific views about the creative process. We conclude with a discussion about capturing as an externalizing activity, practitioners’ use of the term ideas , and four suggestions for directions in the design of creativity support tools.
This essay outlines ideas on how philosophers of science can utilize AI for making real contributions as it is becoming increasingly impossible to imagine a world where scientific breakthroughs are not co-created with AI systems. At the bare minimum, surely, we don’t want the role of human scientists and philosophers in scientific discovery to be purely reduced to ‘interpreters for AI scientists’, the hermeneutic role. Moreover, we have a huge untapped potential of scientific and philosophical minds in, especially, underdeveloped societies. For example, as philosophers of science working in the Vietnam, we are acutely aware of the pace in which scientific community in developed world is moving. How can underrepresented voices participate in the global dialogue regarding the future of AI-driven sciences? How can we leverage the power of generative AI and the AI co-scientists for this cause? What are the frameworks that will allow scientists and philosophers of science to make real contributions to the discovery of new scientific knowledge and engineering? We believe these are questions that the human-AI collaboration can help answer under a framework called human-AI cocreative discovery.
The proposed theory of the evolution of creativity in this article combines insights from Mumford, Wallas, and Simonton to argue that creativity is a product of both biological and environmental factors. It emphasizes the importance of understanding creativity within the broader context of human existence, including the interplay between space, time, and socio-biological elements. The theory of creative evolution suggested in this article emphasizes the connection between human-space-time wholeness and the evolution of creativity. It proposes that creativity has evolved from the emergence of momentary extended phenotype creativity to aesthetic creativity evolved from four essential socio-biological elements: "1", "Correct", "Proper", "Good", and "Love" to our physical-social surroundings in the journey to "Beauty," and the "Aesthetic,". Ultimately, the paper concludes by proposing that humanity can strive to save itself from potential extinction by nurturing a generation that combines creativity and empathy with a higher level of inner connection and a more creative educational system that will address the creation of a harmonious future.
Generative artificial intelligence (AI) technologies such as ChatGPT and DALL·E are rapidly transforming the landscape of brand communication by enabling automated content creation. While brands embrace these tools for their efficiency and novelty, their impact on creativity, authenticity, and consumer trust remains underexplored. This study investigates how generative AI is perceived by consumers in the context of branded content and whether it truly represents a new era of creativity. Adopting a qualitative and exploratory approach, the research involved 17 face-to-face semi-structured interviews with young consumers (average age 24) in the commercial division of an agri-food company. Participants were selected through convenience sampling, and the data were analyzed using content analysis supported by Nvivo software. The findings reveal an ambivalent perception of AI-generated content. While participants recognized its innovative and visually appealing nature, they often perceived it as emotionally shallow or impersonal. Trust in brand messages declined when AI-generated origins were disclosed, and most participants expressed a strong preference for human involvement in the creative process. The results suggest that while generative AI can augment formal creativity, it lacks the affective and symbolic depth consumers associate with authentic brand communication. This study contributes to ongoing debates on AI and creativity by highlighting the need for hybrid models that combine AI efficiency with human emotional intelligence. It calls for brands to use AI transparently and strategically, ensuring alignment with their identity and values.
The progression of AI technology has spurred a growing number of artists to engage in AI Art production. This trend has sparked a multifaceted societal discourse. Given the tight integration of AI Art with society, it is essential to explore the potential art innovations and impacts AI Art might introduce. This paper explores the relationship between AI visual art and conventional art, tracing the development of AI visual art and its societal reception. Through historical case studies, the paper forecasts the future influence of AI visual art in the following aspects: Regarding artistic creation, AI visual art challenges established criteria for artistic evaluation. It presents artists with enhanced learning and creative capacities, paving the way for a new artist archetype characterized by human-computer symbiosis. From a societal standpoint, AI visual art is to advance the democratization of art, developing alongside traditional art forms.
RESEARCH OBJECTIVE: This paper aims to present the results of a study on the creativity of individuals with moderate intellectual disabilities. THE RESEARCH PROBLEM AND METHODS: The research problem focuses on how selected individuals with moderate intellectual disabilities perceive creativity. The study employed the individual case method and used interviews to explore the participants’ views on creativity. THE PROCESS OF ARGUMENTATION: The paper begins by clarifying key terminology related to creativity. It then outlines the research methodology, followed by the presentation and analysis of the collected data. RESEARCH RESULTS: The data suggest that individuals with moderate intellectual disabilities perceive creativity similarly to those without intellectual disabilities. This is because the foundation of creative activity among the participants – like those without intellectual disabilities – rests on mechanisms such as understanding key concepts, motivation, and consideration of the opinions of their local environment. CONCLUSIONS, RECOMMENDATIONS, AND APPLICABLE VALUE OF RESEARCH: While this study cannot be used to generalize about creativity among people with intellectual disabilities, it offers an optimistic basis for future research involving a larger sample.
This chapter investigates the creative process of songwriting in the context of twenty-first-century music, focusing on the influences of cultural evolution, technological advancements and collaborative practices. It discusses the role of authenticity, audience expectations and genre-specific attributes in crafting songs that resonate within targeted musical communities. The chapter examines how songwriting has adapted to the digital age, where online platforms and streaming services reshape access, distribution and audience feedback. Key frameworks, including the Propulsion Model, the Systems Model and Csikszentmihalyi’s theories of creativity, provide insights into how songwriters balance tradition and innovation to produce music (the creative product) that feels both novel and culturally relevant. Additionally, the chapter explores intellectual property challenges in an era of accessible, remixable content. Through case studies and theoretical analysis, it presents a comprehensive view of contemporary songwriting’s evolving landscape.
This chapter examines the intersection of artificial intelligence (AI) and creative products, exploring the transformative role of AI in generating and enhancing creativity across domains such as art, music, literature, and science. It outlines the potential of AI tools like generative adversarial networks (GANs) and large language models (LLMs) to democratize creative expression by making sophisticated technologies accessible to diverse users. The chapter critically evaluates AI’s capabilities, including its strengths in ideational fluency and algorithmic problem-solving, while highlighting limitations such as the absence of emotional depth and originality. Case studies illustrate AI’s role in Human-AI collaboration, emphasizing its ability to augment human creativity through task automation and ideation support. The discussion also addresses ethical considerations, including authorship, intellectual property, and biases in AI-generated outputs. The chapter concludes by advocating for responsible AI integration to ensure a balanced partnership between human ingenuity and technological innovation.
Artificial Intelligence (AI) has changed paradigms of creativity and art, raising questions about the capacity of machines to create works that evoke emotional response and possess originality. This article explores whether AI systems can create �real� art and what this means in terms of philosophy, aesthetics and cultural norms. Examples of AI art such as �Theatre D�opera Spatial� and �Portrait of Edmond de Belamy� are analyzed to assess their emotional and artistic value. The question of originality of AI art is discussed through the lens of copyright, imitation theory and cultural perceptions, providing a deeper understanding of how AI affects traditional notions of creativity.
On the threshold of the new millennium nurturing human elements has emerged as the epicentre of challenges, competition, and changes. In the era of global competitiveness, harmonising the innovative dimension seems to be the buzzword with continuous change and progression. Laying much importance and relevance on education has emerged as one of the transformative mechanisms to develop human agency. The paper focuses on how creativity is embraced by human elements culminated by integrity, enthusiasm and harmony creates a hub of knowledge potential for a strategic growth path in the long run. The key objectives of the paper revolves around revisiting literature on educational creativity, innovation on project centric learning, traditional and modern educational prospective, creative evaluation, innovative student engagement, teacher creative commitment and integrating HR with innovation. The key objective of the paper aims to understand people's perception about innovation and creativity in teaching and learning and its impact towards skill-linked knowledge system. The research design is exploratory using of primary and secondary data collection methods through non-probabilistic convenient sampling techniques. The study utilises a quantitative research design with regression analysis to evaluate the effect of each factor. The findings project a prominent connectivity between active learning and digital engagement and also a significant correlation between encouraging awareness and positive awareness. The coverage of the paper makes a realistic attempt to highlight creative and innovative skills for building a holistic education framework and opening the doors to a new human renaissance..
In South Africa, the influx of foreign clothing has resulted in the decline of local production by over 50 per cent since 2010. This decline has contributed to the failure of some SMEs in the clothing industry. In South Africa, more than 70 per cent of SMEs fail to succeed. Most SMEs exist mainly as survivalist businesses with limited ability to attain sustained growth. Researchers attribute this low success rate of SMEs to increased competition as well as a lack of innovation in the products offered.
The aim of this study was two-fold. Firstly, the study sought to gain an understanding of the growth challenges facing SMEs in the South African clothing industry. Secondly, the study sought to identify innovations in the customisation of ready-to-wear clothing that these SMEs may use as potential growth strategies. This study addressed the gap in the existing literature by reporting on the challenges faced by SMEs in the South African clothing industry and by linking it to research regarding models for the customisation of ready-to-wear clothing as a potential growth strategy.
The framework employed in this study was the Venture Life Cycle (VLC). The VLC was used to represent the life cycle of SMEs in the South African clothing industry. A qualitative research approach was utilised and by employing a multiple case study design, the researcher was able to compare numerous cases to establish the circumstances in which the concepts of the proposed growth strategies will be viable for SMEs in the South African clothing industry. A sample of seven SMEs was purposefully and conveniently sampled. The primary data collection strategy was that of individual face-to-face interviews utilising a semi-structured line of inquiry guided by the VLC.
The VLC was instrumental in guiding the researcher in understanding the challenges experienced by the SMEs and what resources were required to grow and achieve maturity. The most prevalent growth challenge was regarding the aspect of access to adequate finances. A lack of finances meant that the SMEs were unable to assemble a skilled team, allocate resources towards branding and marketing efforts as well as the investments in the technology that are needed to implement the models for clothing customisation.
The main resource required by the SMEs to implement the innovative models was adequate financing as that would increase other core areas of the business. Industry support and access to developmental programs such as incubation hubs were also cited as vital interventions necessary. Support is vital in assisting these SMEs to be competitive and to achieve the growth needed to transition beyond the inception and survival phases of the VLC. Co-design, as a way to customise ready-to-wear clothing, can be a viable growth strategy for SMEs that desire to differentiate their products, meet consumer needs, increase the area of sales and finances and grow their businesses to the stages of expansion and maturity in the VLC. However, it was noted that without adequate financial resources, SME owners may not be able to acquire any of the other secondary resources needed to implement these innovative models for the customisation of ready-to-wear clothing..
The rapid evolution of artificial intelligence (AI) has spurred a complex discourse on its ethical, social, and technological implications. This paper explores the intersection between AI narratives in speculative fiction and media discourse, focusing on how these narratives shape public perceptions and societal engagement with AI. Drawing on data from Technovelgy.com, a science fiction repository, and the GDELT Project, a global media analysis database, this study examines thematic parallels between science fiction-inspired AI narratives and real-world media discussions. By analyzing public sentiment, emotional intensity, and engagement across multiple AI sub-topics, this research highlights the influence of technological narratives on shaping societal views of AI. The findings suggest that AI narratives from speculative fiction significantly inform and reflect societal hopes and concerns, providing critical insights for policymakers, developers, and media professionals to foster responsible AI innovation aligned with ethical and social values.
The latest advancements in machine learning have led to a notable increase in interest in Artificial Intelligence (AI) research. The integration of AI and machine learning is becoming more prevalent across various sectors within different industries. AI presents opportunities for businesses and employees by facilitating enhanced data analysis, improved security frameworks, efficient automation, and more advanced technological interactions. This has encouraged further exploration of potential AI applications in a range of fields, as well as important discussions regarding challenges such as the interpretability of AI systems, the limitations of machine intelligence, associated risks, and societal issues. As the examination of the ‘human versus AI’ relationship progresses, one particularly intriguing area of interest is the creation and understanding of art. The rise of a new category of tools has the potential to generate high-caliber artistic content across various domains including visual arts, concept art, music, fiction, literature, video, and animation. These tools, equipped with generative capabilities, are expected to transform the creative processes related to idea generation and production. This creativity change is projected to have a significant impact on multiple sectors of society. Understanding the consequences of generative AI and developing effective policies necessitates an interdisciplinary scientific approach that encompasses culture, economics, law, algorithms, and the interaction between technology and creativity. The position advanced in this paper is that generative AI does not signify the end of artistic endeavours; instead, it introduces a new medium with its unique features. Accordingly, the paper explores the ramifications of this innovative medium on creators, considering factors such as aesthetics and culture, ownership and attribution, the future trajectory of creative activities, and its influence on the contemporary media landscape. Within these contexts, the paper identifies key research questions related to Artificial Intelligence and its advantageous uses.
In this article, I discuss the implications of generative AI in future of creative work in the music industries through an ethnographic study of music technologists in Melbourne, Australia. Drawing on visual ethnography methods, I explore how researchers, developers, as well as professional and aspiring artists, across sectors in Melbourne’s ecosystem, value the role of mistakes, glitches and uncertainty in the creative process with music technology. This stands in opposition to the controlled processes within generative AI models, based on the management of uncertainty as an input value. Thus, I reframe the concept of creative uncertainty which emerges as a shaping force in the creative process, and in opposition to the controlled outputs of generative AI. Furthermore, this article shows the limitations and misalignment of dominant visions about the impact of generative AI, on creative workflows and practices, by highlighting the experiences, motivations and expectations of the research participants in this multi-sited ethnography.
This paper examines the various functions of the imaginary starting from the case of Jeanne d’Arc. Assuming Castoriadis’ conception that the imaginary, in its ultimate and radical dimension, is the place of creation, I will explore in the lived experience of young Jeanette the alternation of what Margaret Boden distinguishes as three peculiar forms of creativity (combinational, explorative and transformative). In the first part, in particular, we will identify in Jeanne’s attachment to the religious and political tradition of her people the enactment of reproductive-combinatorial functions of the imaginary, while in the second part, we will seek to demonstrate how her voices and visions imply the creation of a new imaginary reality.
Este estudio de caso se sumerge en la relación compleja entre la inteligencia artificial (IA) y la psicología de la creatividad, utilizando como muestra algunas de las inteligencias artificiales más destacadas en la actualidad. Se analizarán las capacidades creativas de estas IA, explorando cómo emulan o desafían los procesos cognitivos humanos asociados con la generación de ideas innovadoras. Este estudio de caso busca arrojar luz sobre la capacidad creativa de las inteligencias artificiales, explorando su potencial para contribuir a campos como la literatura, el arte visual, los juegos estratégicos y la música. A través de un análisis detallado de casos específicos, se espera proporcionar una comprensión más profunda de la intersección entre la inteligencia artificial y la psicología de la creatividad.
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