This paper explores the current state, trends, and possible futures of the telecommunication ecosystem in Italy, outlining strategies for development. We adopt a combined methodology, integrating participatory scenario building through the Nominal Group Technique with a structured literature review. The analysis starts from the current situation (Scenario 1) and major transformation trends (Scenario 2) to project two contrasting futures (Scenario 3), providing a rationale for strategic choices.Various dimensions are considered: market and economic models, technological advancements, and regulatory frameworks, with both European and Italian perspectives. In the market domain, we assess opportunities linked to enabling technologies and digital services built on connectivity. On the technological side, we evaluate the role of network programmability, low-orbit satellites, aerial networks, edge computing, novel materials, and services, while also addressing sustainability and AI integration. The regulatory analysis highlights how evolving policies can impact network evolution and identifies reforms to foster innovation, inclusivity, and industry participation.From this integrated view, we infer two boundary scenarios for 2040: a utopic one, marked by innovation and inclusivity, and a dystopic one, characterized by digital inequality and stagnation. Finally, we outline strategies and policies to steer the telecommunications ecosystem towards the preferable scenario.

This paper explores the key role played by heuristics and biases in futures thinking. Heuristics and biases shape how individuals and groups envision futures, often leading to errors or narrower scenarios. Twenty-five common heuristics and biases related to future-oriented thinking have been identified from previous literature and classified into three categories. The Cherry Picking category includes nine heuristics and biases that may impact information collected and used in foresight. The Group Bubble category contains eight heuristics and biases in social interactions. Finally, the eight heuristics and biases of the Outcome Misperception category lead the focus to a “desired” outcome rather than various possible scenarios. Building on this classification, we explore possible mitigation strategies in foresight methodologies. We argue that awareness of these cognitive mechanisms in foresight practices could enable futurists to uncover neglected future possibilities, improving both the richness and applicability of foresight processes and helping to address future myopia. Rather than providing an exhaustive review, this paper aims to equip foresight practitioners with tools to enhance creativity and critical thinking.

This article examines whether generative artificial intelligence (Gen-AI) can be considered creative when evaluated through a dynamic cross-cultural framework of creativity. Integrating the dynamic model of creativity (Corazza et al., 2022) with the four-criterion construct of creativity (Kharkhurin, 2014), the analysis evaluates Gen-AI across four dimensions: originality, effectiveness, aesthetics, and authenticity. The article advances the thesis that human and artificial creative potentials unfold through different architectures. Human creativity develops through integrative processes grounded in autobiographical experience, embodied perception, and evolving identity. Gen-AI systems expand creative search spaces through statistical learning and large-scale computational exploration. The analysis shows substantial convergence between human and artificial creativity in potential originality and effectiveness, and partial convergence in aesthetics. The principal divergence appears in authenticity. Authentic creative expression requires autobiographical grounding, reflective self-integration, and value-oriented interpretation of experience, capacities that current AI systems do not possess. Emerging technologies such as persistent memory architectures, agent-based systems, multimodal models, and quantum computing may expand the originality, effectiveness, and aesthetic range of AI-generated outputs, while only approximating surface-level features of authenticity. These findings suggest that Gen-AI can participate meaningfully in creative processes as a human-made, non-living tool, while lacking the experiential grounding that characterizes authentic human creativity. The article therefore positions Gen-AI as a collaborator and enhancer within cyber-creative processes whose value depends on human purposes, ethical responsibility, and cultural interpretation.

Creativity is the primary driver of our cultural evolution. The astonishing potential of artificial intelligence (AI) and its possible application in the creative process poses an urgent and dramatic challenge for humanity; how can we maximize the benefits of AI while minimizing the associated risks? In this article, we identify all forms of human–AI collaboration in this realm as cyber-creativity. We introduce the following two forward-looking scenarios: a utopian vision for cyber-creativity, in which AI serves to enhance and not replace human creativity, and a dystopian view associated with the pre-emption of all human creative agency caused by the rise of AI. In our view, the scientific community is called to bring its contribution, however small, to help humanity make steps towards the utopian scenario, while avoiding the dystopian one. Here, we present a decalogue of research challenges identified for this purpose, touching upon the following dimensions: (1) the theoretical framework for cyber-creativity; (2) sociocultural perspectives; (3) the cyber-creative process; (4) the creative agent; (5) the co-creative team; (6) cyber-creative products; (7) cyber-creative domains; (8) cyber-creative education; (9) ethical aspects; and (10) the dark side of cyber-creativity. For each dimension, a brief review of the state-of-the-art is provided, followed by the identification of a main research challenge, then specified into a list of research questions. Whereas there is no claim that this decalogue of research challenges represents an exhaustive classification, which would be an impossible objective, it still should serve as a valid starting point for future (but urgent) research endeavors, with the ambition to provide a significant contribution to the understanding, development, and alignment of AI to human values the realm of creativity.

Researchers and educators interested in creative writing need a reliable and efficient tool to score the creativity of narratives, such as short stories. Typically, human raters manually assess narrative creativity, but such subjective scoring is limited by labor costs and rater disagreement. Large language models (LLMs) have shown remarkable success on creativity tasks, yet they have not been applied to scoring narratives, including multilingual stories. In the present study, we aimed to test whether narrative originality-a component of creativity-could be automatically scored by LLMs, further evaluating whether a single LLM could predict human originality ratings across multiple languages. We trained three different LLMs to predict the originality of short stories written in 11 languages. Our first monolingual model, trained only on English stories, robustly predicted human originality ratings (r = .81). This same model-trained and tested on multilingual stories translated into English-strongly predicted originality ratings of multilingual narratives (r >= .73). Finally, a multilingual model trained on the same stories, in their original language, reliably predicted human originality scores across all languages (r >= .72). We thus demonstrate that LLMs can successfully score narrative creativity in 11 different languages, surpassing the performance of the best previous automated scoring techniques (e.g., semantic distance). This work represents the first effective, accessible, and reliable solution for the automated scoring of creativity in multilingual narratives.

In the present work we explored in two separate studies the modulatory role of trait emotional intelligence (EI) over the effect exerted on children’s creative potential by two other key elements defining creativity, namely cognitive resources (here explored through basic executive functions, Study 1) and contextual-environmental factors (that is, teachers’ implicit conceptions of the factors influencing children’s creativity, Study 2). Confirming previous research, executive functions (particularly interference control and working memory) emerged as main predictors of children’s creative performance; however, their positive effect arose especially when associated with a high trait EI level. In the same vein, teachers’ implicit conception about children’s creative potential and about their efficacy in teaching creativity emerged to exert a facilitatory effect on children’ creative potential. This effect occurred particularly when associated with low trait EI levels, affecting differently girls and boys. Trait EI emerged from these studies as an important individual resource to consider in order to understand the potential benefit of other (cognitive and contextual-environmental) resources on children’s creative potential. The implications on the role of trait EI as a constitutional element of children’s creativity, capable of promoting the expression of their creative potential, are discussed.

Creativity is a phenomenon that emerges in the human-sociocultural and machine-artificial layers. With the advent of Artificial Intelligence (AI), the field of creativity faces new opportunities and challenges. This manifesto explores several scenarios of human-machine collaboration on creative tasks and proposes "fundamental laws of generative AI" to reinforce the responsible and ethical use of AI in the creativity field. Four scenarios are proposed and discussed: "Co-Cre-AI-tion", "Organic", "Plagiarism 3.0", and “Shut down”, each illustrating different possible futures based on the collaboration between humans and machines. In addition, we have incorporated an AI-generated manifesto that also highlights important themes, ranging from accessibility and ethics to cultural sensitivity. The fundamental laws proposed aim to prevent AIs from generating harmful content and competing directly with humans. Creating labels and laws are also highlighted to ensure responsible use of AIs. The positive future of creativity and AI lies in a harmonious collaboration that can benefit everyone, potentially leading to a new level of creative productivity respecting ethical considerations and human values during the creative process.

In this article, the problem of understanding multiple layers of complexity in our universe is addressed, with particular emphasis on explaining creative evolutions in the material, biological, and psycho-social layers. Perspectives from physics, biology, psychology, and philosophy are utilized in the discussion. Process philosophy is used to justify the theoretical foundation of the dynamic universal creativity process. The concepts of unified and final theories are discussed from a position that criticizes reductionism. The concept of the adjacent possible is reviewed as introduced by Kauffman to exclude the possibility that a theory from physics could be extended to explain the biological layer. In a similar way, the adjacent possible is shown to be useful but insufficient to explain the psycho-social layer of complexity, missing fundamental human abilities such as thinking of long-term futures, wisdom, and dynamic creativity leaps that use the impossible as an inspiration.

Past research showed that apparently irrelevant information for a creative task at hand can lead to higher creative performance, especially in open-minded individuals. Through two diverse experimental procedures, the present work investigated which type of irrelevance information can inspire (i.e., increase) the creative performance during a divergent thinking (DT) task and how open-minded individuals can be inspired by this kind of information. In Experiment 1, the attentional processing of information that was either apparently relevant or irrelevant for the execution of a verbal DT task was assessed by means of an eye-tracking methodology. In Experiment 2, creative performance was explored through a verbal priming paradigm, which forcedly introduced apparently irrelevant information during the DT task. In both experiments, the level of irrelevance was operationalized in terms of semantic distance between the different kind of information. Results from both experiments highlighted the role of the semantic meaning of the irrelevant information as one of the main determinants, along with Openness, of inspiration (i.e., enhancement) of the creative performance.

Creativity research commonly involves recruiting human raters to judge the originality of responses to divergent thinking tasks, such as the alternate uses task (AUT). These manual scoring practices have benefited the field, but they also have limitations, including labor-intensiveness and subjectivity, which can adversely impact the reliability and validity of assessments. To address these challenges, researchers are increasingly employing automatic scoring approaches, such as distributional models of semantic distance. However, semantic distance has primarily been studied in English-speaking samples, with very little research in the many other languages of the world. In a multilab study (N = 6,522 participants), we aimed to validate semantic distance on the AUT in 12 languages: Arabic, Chinese, Dutch, English, Farsi, French, German, Hebrew, Italian, Polish, Russian, and Spanish. We gathered AUT responses and human creativity ratings (N = 107,672 responses), as well as criterion measures for validation (e.g., creative achievement). We compared two deep learning-based semantic models-multilingual bidirectional encoder representations from transformers and cross-lingual language model RoBERTa-to compute semantic distance and validate this automated metric with human ratings and criterion measures. We found that the top-performing model for each language correlated positively with human creativity ratings, with correlations ranging from medium to large across languages. Regarding criterion validity, semantic distance showed small-to-moderate effect sizes (comparable to human ratings) for openness, creative behavior/achievement, and creative self-concept. We provide open access to our multilingual dataset for future algorithmic development, along with Python code to compute semantic distance in 12 languages.

This article presents how Problem- and Project-Based Learning (PBL) in engineering education can exploit the theoretical framework of the Space-Time (ST)-Continuum, according to which educational contexts can be classified in terms of the tightness vs. looseness of the relevant conceptual space S and available time T. By crossing these two dimensions, four quadrants are obtained in the ST-Continuum: tight space and tight time, loose space and tight time, tight space and loose time, loose space and loose time. Different pedagogies are adaptive to different quadrants. We show how PBL can be mapped onto the ST-Continuum depending on the context characteristics or the chosen problem or project. Further, this article discusses how the intelligence and creativity constructs can be developed through diverse educational scenarios, giving examples of PBL interventions that can be located in different quadrants. Moreover, the analysis shows how through suitable planning, it is possible to have educational activities that consider all the quadrants of the ST-Continuum, even in traditional education curricula or teacher-centered approaches. Finally, the article discusses how teaching practices can promote intelligence and creativity in the curricula at different PBL organisational levels depending on their relationship with the ST-Continuum.

The neurotransmitter dopamine plays a crucial role in human creative behaviour. Specifically, striatal dopamine seems to be associated with specific dimensions of divergent thinking performance, especially with categorical diversity (flexibility) of ideas. In experimental contexts, spontaneous Eye Blink Rate (sEBR) has been used as a proxy for striatal dopamine, and an inverted U-shape relationship between sEBR and flexibility has been demonstrated, such that a medium sEBR level predicts highest flexibility levels. The present study aimed at carrying out further investigations about the relationship between sEBR and idea generation through divergent thinking, specifically focusing on the relationship between idea originality and dopamine level, since originality is a key element for creativity. We asked 80 participants, whose sEBR at rest was measured, to perform an Alternative Uses Task (AUT) to measure their divergent thinking performance. Results revealed that the relationship between sEBR and originality, as measured through subjective ratings of external raters, followed an inverted U-shape function with medium sEBR being associated with highest originality scores. Moreover, and most importantly, we demonstrated that sEBR predicted originality through the mediation of flexibility. Our results provide further insights on the possible role of dopamine on divergent thinking performance, demonstrating that an adequate dopamine level may facilitate the generation of original ideas through the exploration of diverse conceptual categories (higher flexibility).

Abstract. The dynamic creativity framework (DCF) represents a new theoretical perspective for studying the creativity construct. This framework is based on the dynamic definition of creativity, and it has both theoretical and empirical implications. From a theoretical point of view, we review the characteristics of the dynamic creative process and its extension into the dynamic universal creative process, encompassing creativity at different layers of complexity. We discuss the key concept of creative potential, considering individual, sociocultural, and material viewpoints, and we show how the DCF is instrumental in clarifying the relationship between creativity and intelligence, between creativity and anticipation, as well as in introducing the concept of ‘organic creativity’. From the empirical perspective, we focus on the dynamic creative process broken down into four phases: i) drive, ii) information, iii) idea generation, iv) idea evaluation. We review results obtained through investigations accounting for the dynamic interplay between emotional and cognitive components defining creative performance for each. Experiments were conducted to measure the role of emotions and attention in driving the dynamic process, considering the processing of apparently irrelevant information and the interaction between idea generation and idea evaluation, always taking into account individual differences as measured through personality traits, performance variables, or lifetime achievement. Neurophysiological evidence is considered in discussing dynamic effects in divergent thinking, such as the serial order effect, as well as the possibility to enhance creative potential through neurofeedback. Finally, we report on the effects of different environments on the creative process, highlighting the dynamics produced by context-embeddedness.

Future-making is a collective enterprise. Learning and creativity are as much psychological as they are social and cultural phenomena. The creation of new technologies requires division of labour, their use connects us with those around us. And the future of the emerging field of learning, creativity and technology studies is ours to envision and to bring into being. Any speculation about the futures (always in plural) of creativity, technology and learning is therefore dialogical and depends on exchanges between different individuals and groups within society. Our final 'creative provocation', then, is meant to recognise and capitalise on the social roots of learning creatively, with technology, and speculate about these futures in an equally dialogical manner. This exchange brings together three authors with expertise in a range of relevant areas, from engineering and learning to sociocultural studies and the psychology of creativity. Our hope in using this format is that it will not only be more enjoyable and authentic but bring insights that both build on and expand what the present book offers in its rich array of contributions, views, and provocations.

Creative potential is a set of multidimensional resources concerning the latent ability to produce original and adaptive work. Confluent theoretical models, in particular, stated that, in order to express creative potential in an effective way, resources should converge and interact efficiently. Within such a confluent framework, the present study explored whether the increase in specific cognitive resources defining creative potential during childhood, as induced through a newly developed training intervention based on the creation of fairy tales, could be affected by another constitutional dimension, that is, children's emotional resources and, in particular, their trait emotional intelligence (EI). A total of 410 children from 3(rd) to 5(th) grade of primary school was involved in the study, equally divided in a training group and in a control group. Results showed that the fairy tale-based training protocol was effective in increasing children's creative potential. More importantly, results showed that the training intervention was particularly effective in increasing the ability to generate original contents in children with low-to-medium trait EI levels. These findings showed that emotional intelligence is a central factor to be considered when exploring the efficacy of a training intervention aimed at increasing children's creative potential.