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Artificial intelligence (AI) has reached creative industries such as music. Algorithms now produce high-quality artistic content (e.g. original songs), for hedo consumption and utilitarian business applications. While available literature to-date focuses mainly on technological development and applications, this paper aims to address the resulting research gap by investigating listeners’ perceptions towards music composed by AI.

First, an online survey was conducted with 446 respondents and compared perceptions of music professionals (n = 72) and non-professional listeners (n = 374). Following this, a 2 × 2 laboratory experiment was conducted, where 86 participants listened to songs composed by AI but were presented different narratives regarding the composition process (human versus AI).

Overall, results from the online survey indicated a rather negative perception, low purchase intention for AI music and a negative credibility perception of musicians using AI. Findings from the experiment indicated no significant differences between the groups, suggesting that the awareness of the use of automation did not influence the perception towards the music.

This paper contributes by highlighting the current perception of both listeners and music professionals towards the application of artificial creativity in music composition. Furthermore, it contributes to the existing literature on artificial creativity applied in music, by providing evidence of its impact on listeners’ perception. Results reveal the importance of further investigation on the topic.

The main aim of the paper is to show the necessary convergence of two promising but under‐explored research fields, intellectics and inventics, into a new one, that of intellectual invention, and to discuss new ways of thinking which can be efficient in building an invention culture.

These purposes are achieved in an interdisciplinary way, in which the various scientific approaches are governed by a philosophical perspective that ensures the conceptual level and the unity of the discourse. The philosophical approach itself is practised in several specific fields and at various levels, being used in order to lay the foundations of a new domain of research. Specific theoretical problems are elucidated through concrete examples furnished by sciences and discussed from the perspective of inventics. Graphical representations help in giving a systemic and integrative perception of complex issues.

The paper defines in a comprehensive way the two partially studied and till now separately conceived research fields; delimitates and characterizes a new domain of study, of crucial theoretical and practical interest; analyses some types of intellectual techniques involved in all sorts of inventive activity; identifies the main new ways of thinking encouraged by the information technologies and shows their forms and manifestations, as well as the new values promoted by their development. There are proposed some improvements on sociological thinking from the perspective of inventive thinking. The emergence of an invention ethics is anticipated as a necessary component of an invention culture.

Proposes a new field of research, that of the intellectual invention, analyses the main instruments of its study and development, and uses the results of different sciences in order to lay the philosophical foundations of invention ethics as part of the future invention culture.

This paper aims to clarify the notion of artificial intelligence (AI), reviewing the present scope of the phenomenon through its main applications. It aims at describing the various applications while assessing the markets, highlighting some of the leading industrial sectors in the field. Therefore, it identifies pioneering companies and the geographical distribution of AI companies.

The paper builds upon an in-depth investigation of public initiatives focusing mostly on the EU. It is based on desk research, a comprehensive review of the main grey and scientific literature in this field.

The paper notes that there is no real consensus on any definition for this umbrella term, that the definition does fluctuate over time but highlights some of the main changes and advances that took place over the past 60 years. It stresses that, in spite of the hype, on both the business and consumer sides, the demand appears uncertain. The scope of the announced disruptions is not easy to assess, technological innovation associated with AI may be modest or take some time to be fully deployed. However, some companies and regions are leading already in the field.

The paper, based on desk research, does not consider any expert opinions. Besides, the scientific literature on the phenomenon is still scarce (but not the technical one in the specific research sectors of AI). Most of the data come from consultancies or government publications which may introduce some bias, although the paper gathered various, often conflicting viewpoints.

The paper gives a thorough review of the available literature (consultancies, governments) stressing the limitations of the available research on economic and social aspects. It aims at providing a comprehensive overview of the major trends in the field. It gives a global overview of companies and regions.

This study aims to investigate about the use of artificial intelligence (AI) (man machine relationship) regarding organizational behavior. The aim of this research paper is to analyze whether the current AI is used also to replace man in “creative” activities.

This study is based on a qualitative and explorative approach. It is made a review of the literature with “Scopus” and “Web of Science” databases. The research fields are AI, organizational behavior, man-machine relationship and creativity.

Analyzing whether the intensive use of AI in organizational behavior can replace human work in creative activities.

The connection of AI with creative activities within the organization is only just beginning. For this reason, other sources, like Harvard Business Review, public reports and professional papers found on the internet have been considered. The most important limitation of this paper is that all the results presented here do not concern a single case study.

In this paper, there are some examples that can show the use of AI in creative activities; however, this does not complete the situation facing companies in any sector because the AI technologies used within enterprises are constantly evolving. It is possible to continue to do research in this field.

The paper is meaningful because highlights the development of AI toward creative activities typically of human resources. It is also interesting because it analyzes the exploratory use of AI in increasingly human work, generating positive and negative externalities.

Aritificial intelligence (AI)-focused enterprises purpose to provide value-creating and differentiated products and services using innovative technologies. For this reason, it is aimed to examine the effects of value creation, intellectual property and organizational creativity variables to make evaluations to increase the success of such enterprises.

Random sampling method was used in the research. The population of the research consists of AI-oriented enterprises in technoparks. On the specified days, short-term visits and surveys were conducted face-to-face. Name and similar personal information was not taken in the research and participation was made on a voluntary basis. A sample size of 500 units is a sufficient size at the 0.05 significance level. SmartPLS (4.0.8.4) licensed software was used in the research.

As a result of the collected data, it has been supported by hypotheses that value creation, intellectual property and organizational creativity have positive effects so that artificial intelligence-oriented enterprises can be successful in performance criteria.

Since the research was conducted by collecting data from artificial intelligence-oriented enterprises in technoparks in Istanbul, it would not be correct to evaluate the analysis results by making generalizations. For this reason, it is recommended that similar studies planned to be conducted in the future should contribute to the literature by developing the research model, taking into account the limited situation in the sample.

According to the results of the analysis of the effects of value creation, intellectual property and organizational creativity in artificial intelligence-oriented enterprises, in order to increase the success of such enterprises, they should offer more value to their customers, protect their technologies and increase their innovation capacity.

Value creation, intellectual property, and organizational creativity in AI-focused enterprises are important topics in a rapidly growing industry such as AI-focused enterprises. Therefore, a research investigating these variables together offers a different perspective than previous studies.

The purpose of this paper is to investigate the relevance and the appropriateness of Turing-style tests for computational creativity.

The Turing test is both a milestone and a stumbling block in artificial intelligence (AI). For more than half a century, the “grand goal of passing the test” has taught the authors many lessons. Here, the authors analyze the relevance of these lessons for computational creativity.

Like the burgeoning AI, computational creativity concerns itself with fundamental questions such as “Can machines be creative?” It is indeed possible to frame such questions as empirical, Turing-style tests. However, such tests entail a number of intricate and possibly unsolvable problems, which might easily lead the authors into old and new blind alleys. The authors propose an outline of an alternative testing procedure that is fundamentally different from Turing-style tests. This new procedure focuses on the unfolding of creativity over time, and – unlike Turing-style tests – it is amenable to a more meaningful statistical testing.

This paper argues against Turing-style tests for computational creativity.

This paper opens a new avenue for viable and more meaningful testing procedures.

The novel contributions are: an analysis of seven lessons from the Turing test for computational creativity; an argumentation against Turing-style tests; and a proposal of a new testing procedure.

The purpose of this research is to explore the transformative impact of AI-augmented tools on design pedagogy. It aims to understand how artificial intelligence technologies are being integrated into educational settings, particularly in creative design courses, and to assess the potential advancements these tools can bring to the field.

The research adopts a case-study approach, examining three distinct courses within a creative technology curriculum. This methodology involves an in-depth investigation of the role and impact of AI in each course, focusing on how these technologies are incorporated into different creative disciplines such as production design, fine arts, and digital artistry.

The research findings highlight that the integration of AI with creative disciplines is not just a passing trend but signals the onset of a new era in technological empowerment in creative education. This amalgamation is found to potentially redefine the boundaries of creative education, enhancing various aspects of the learning process. However, the study also emphasizes the irreplaceable value of human mentorship in cultivating creativity and advancing analytical thinking.

The limitations of this research might include the scope of the case studies, which are limited to three courses in a specific curriculum. This limitation could affect the generalizability of the findings. The implications of this research are significant for educational institutions, as it suggests the need for a balanced interaction between AI's computational abilities and the intrinsic qualities of human creativity, ensuring that the core essence of artistry is preserved in the age of AI.

The originality of this paper lies in its specific focus on the intersection of AI and creative education, a relatively unexplored area in design pedagogy. The value of this research is in its contribution to understanding how AI can be harmoniously integrated with traditional creative teaching methods. It offers insights for educational institutions preparing for this technological transformation, highlighting the importance of maintaining a balance between technological advancements and humanistic aspects of creative education.

Artificial intelligence (AI) technologies have led to significant transformations across industries and society, including the field of education. The integration of AI in educational settings has the potential to improve students' learning experience and support their individual competencies when paired with non-AI methods. Despite the growing importance of AI in modern education, there remains a noticeable research gap regarding its use in entrepreneurship education and the effects of Chatbots on students' entrepreneurial competencies. To address this gap, an exploratory study was conducted on undergraduate students who were tasked with using ChatGPT to improve their business model canvas.

The chosen methodology aligned with the research purpose, aiming to explore the relationship between Generative AI and competencies. Due to the novel nature of the research problem, an exploratory study was conducted using a mixed methods approach. A survey with open- and closed-ended questions was designed, and statistical and text analyses were performed to interpret data and test identified propositions.

The findings of this study indicate that ChatGPT can enhance the types of students' entrepreneurial competencies considered in this study: spotting opportunities, creativity, vision, valuing ideas and ethical and sustainable thinking. The results show that ChatGPT can be particularly helpful to improve the ability of students of valuing ideas.

Overall, this study highlights the potential of adopting ChatGPT in experiential learning methodologies for enhancing students' entrepreneurial competencies and improving their learning outcomes.

The recent surge of subscription box services calls for research to understand how consumers respond to curation services. This study aims to develop and test a theoretical model to predict consumer response to AI (vs human). Particularly, the authors tested the role of stereotyping in shaping consumer perception of creativity in this context while considering the contextual moderators, shopping goals (hedonic vs utilitarian) and product category (fashion vs meal).

Two preliminary studies and the main study (total n = 761) tested the assumptions and hypotheses of the study. Preliminary study 1 (n = 511 Amazon mTurk, online survey) confirmed consumer stereotypes of humans and machines. Preliminary study 2, a single-factor between-subjects online experiment (recommender: human vs AI), was conducted at a large Midwestern university in the US (n = 56). The main study was conducted as a 2(recommender: human vs AI) × 2(product: fashion vs meal) × 2(goal: utilitarian vs hedonic) between-subjects online experiment (n = 194, Amazon mTurk).

The results confirmed that consumers are more likely to follow recommendations made by a human more than recommendations made by AI and the perceived creativity of the recommender explained the effect. Significant differences across product categories and shopping goals of the consumers were observed, calling for attention to the context of consumption.

This study extends the understanding of consumers' responses to recommendations in curation subscription services by highlighting the role of perceived creativity of humans versus AI.

The purpose of this paper is to present a fresh approach to stimulate individual creativity. It introduces a mathematical representation for creative ideas, six creativity operators and methods of matrix-algebra to evaluate, improve and stimulate creative ideas. Creativity begins with ideas to resolve a problem or tackle an opportunity. By definition, a creative idea must be simultaneously novel and useful. To inject analytic rigor into these concepts of creative ideas, the author introduces a feature-attribute matrix-construct to represent ideas, creativity operators that use ideas as operands and methods of matrix algebra. It is demonstrated that it is now possible to analytically and quantitatively evaluate the intensity of the variables that make an idea more, equal or less, creative than another. The six creativity operators are illustrated with detailed multi-disciplinary real-world examples. The mathematics and working principles of each creativity operator are discussed.

The unit of analysis is ideas, not theory. Ideas are man-made artifacts. They are represented by an original feature-attribute matrix construct. Using matrix algebra, idea matrices can be manipulated to improve their creative intensity, which are now quantitatively measurable. Unlike atoms and cute rabbits, creative ideas, do not occur in nature. Only people can conceive and develop creative ideas for embodiment in physical, non-physical forms, or in a mix of both. For example, as widgets, abstract theorems, business processes, symphonies, organization structures, and so on. The feature-attribute matrix construct is used to represent novelty and usefulness. The multiplicative product of these two matrices forms the creativity matrix. Six creativity operators and matrix algebra are introduced to stimulate and measure creative ideas. Creativity operators use idea matrices as operands. Uses of the six operators are demonstrated using multi-disciplinary real-world examples. Metrics for novelty, usefulness and creativity are in ratio scales, grounded on the Weber–Fechner Law. This law is about persons’ ability to discern differences in the intensity of stimuli.

Ideas are represented using feature-attribute matrices. This construct is used to represent novel, useful and creative ideas with more clarity and precision than before. Using matrices, it is shown how to unambiguously and clearly represent creative ideas endowed with novelty and usefulness. It is shown that using matrix algebra, on idea matrices, makes it possible to analyze multi-disciplinary, real-world cases of creative ideas, with clarity and discriminatory power, to uncover insights about novelty and usefulness. Idea-matrices and the methods of matrix algebra have strong explanatory and predictive power. Using of matrix algebra and eigenvalue analyses, of idea-matrices, it is demonstrated how to quantitatively rank ideas, features and attributes of creative ideas. Matrix methods operationalize and quantitatively measure creativity, novelty and usefulness. The specific elementary variables that characterize creativity, novelty and usefulness factors, can now be quantitatively ranked. Creativity, novelty and usefulness factors are not considered as monolithic, irreducible factors, vague “lumpy” qualitative factors, but as explicit sets of elementary, specific and measurable variables in ratio scales. This significantly improves the acuity and discriminatory power in the analyses of creative ideas. The feature-attribute matrix approach and its matrix operators are conceptually consistent and complementary with key extant theories engineering design and creativity.

First to define and specify ideas as feature-attribute matrices. It is demonstrated that creative ideas, novel ideas and useful ideas can be analytically and unambiguously specified and measured for creativity. It is significant that verbose qualitative narratives will no longer be the exclusive means to specify creative ideas. Rather, qualitative narratives will be used to complement the matrix specifications of creative ideas. First to specify six creativity operators enabling matrix algebra to operate on idea-matrices as operands to generate new ideas. This capability informs and guides a person’s intuition. The myth and dependency, on non-repeatable or non-reproducible serendipity, flashes of “eureka” moments or divine inspiration, can now be vacated. Though their existence cannot be ruled out. First to specify matrix algebra and eigen-value methods of quantitative analyses of feature-attribute matrices to rank the importance of elementary variables that characterize factors of novelty, usefulness and creativity. Use of verbose qualitative narratives of novelty, usefulness and creativity as monolithic “lumpy” factors can now be vacated. Such lumpy narratives risk being ambiguous, imprecise, unreliable and non-reproducible, Analytic and quantitative methods are more reliable and consistent. First to define and specify a method of “attacking the negatives” to systematically pinpoint the improvements of an idea’s novelty, usefulness and creativity. This procedure informs and methodically guides the improvements of deficient ideas.