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Should Human Artists Fear AI? A Report on the Perception of Creative AI
Abstract
The question of whether a machine can be creative has been at the center of many scholarly debates. But what does the public think about the possibility for AI to gain a place alongside human artists? This paper presents the results of a survey conducted at the University of Nottingham which investigated the public reception of the application of Artificial Intelligence to the creative sector. The study examined the attitudes and beliefs of participants to the prospect of a future scenario where machines create art alongside and in collaboration with humans. The responses, collected both through an online questionnaire and a focus group, reveal that participants do not exclude the possibility that in the medium-term AI may earn the attribute ‘creative’. Still, this does not mean that this scenario is welcomed.
... Because it might very well be that the you know the video game industry which is being employing such a huge slice of human image producers is going to go through a major major reduction in numbers. -(11, M,(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44) Narrative Designer) ...
... I don't see that that threatening anymore. -(5, M,(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44) Artist) I was at first definitely very, very fascinated and interested in AI, but after well, quite an intensive experimenting I found out that there's also a lot of things that I don't like about it.-(12, M, 45-54, Lead Artist) PS.3 Characterising systems: In a comparatively weaker theme, few participants have been anthropomorphising the systems, especially to downplay them as dumb, emotionless and soulless: First things I've been thinking about so much so it's hard to say, but like first, first things are like soulless machine created art. ...
... Because like already now in half a year things have changed a lot.-(5, M,(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44) Artist) Often, these statements come along with observations of increasing system capabilities and output quality, a separate code within PSD. This challenges what our participants deem feasible applications at present and in the future: I feel like stuff that was impressive even a month ago or two months ago feels like really crappy by today's standards. ...
Text-to-image generation (TTIG) models can generate images based on a text description, and have begun to rival the work of professional creatives, and sparked discussions on the future of creative work, loss of jobs, and copyright issues, amongst others. To support the sustainable adoption of TTIG, we must provide rich, reliable and transparent insights into how professionals perceive, adopt and use TTIG. Crucally though, the public debate is shallow, narrow and lacking transparency, and academic work has focused on studying the use of TTIG in a general artist population, but not the perceptions and attitudes of professionals in a specific industry. In this paper, we contribute a qualitative, exploratory interview study on TTIG in the Finnish videogame industry. Through a Template Analysis on semi-structured interviews with 14 game professionals, we reveal 12 overarching themes, structured into 49 sub-themes on professionals' perception, adoption and use of TTIG systems in games industry practice. Experiencing (yet another) change of roles and creative processes, our participants' (ethical) reflections can inform discussions within the industry, be used by policymakers to inform urgently needed legislation, and support researchers in games, HCI and AI to support sustainable, professional use benefit games as cultural artefacts.
... The contribution that this paper aims to bring to the debate is to offer an additional quantitative and qualitative analysis of this phenomenon and to test whether the attribution of creativity to artificial systems that engage in processes of scientific discovery would meet the same amount of resistance to the one registered by previous studies on the evaluation of 'artistic' creativity displayed by artificial systems (Hristov 2020;Moruzzi 2020;Natale & Henrickson 2022). ...
... The study presented in this paper addresses some of the limitations that past surveys on perceptions of artificial creativity by the author had, making a clear distinction between 'creativity' and 'art', notions that originated confusion in previous studies (Moruzzi 2020). In so doing, this study explicitly refers only to the process of creation of an artefact, excluding the evaluation of the features of the outcome from the dimensions addressed in the survey. ...
... Results obtained from a survey conducted by Moruzzi (2020), aimed at investigating the public perception in respect to the possibility for AI to be 'creative', revealed a generalised discontent and, almost, and aggressive fear in respect to the application of artificial intelligence systems in the creative sector. The uneasiness displayed by participants to the study emerged from the belief that automated systems do not, and could not, possess the empathy and charisma that are necessary for performing creative processes. ...
This paper presents the results of a factorial survey research on perceptions of artistic and scientific creativity in humans and AI. A general reluctance at attributing creativity to artificial systems is well-documented in the literature on the theme. Aim of this survey is to test whether this reluctance is equally strong when participants evaluate scenarios where human and artificial agents are involved in processes of scientific discovery and scenarios where they are engaged in artistic creation processes. The starting hypothesis of the study is that participants should be less hesitant at attributing creativity to artificial agents when the latter engage in scientific discovery processes. Findings, however, disconfirm this assumption, showing that participants attribute significantly less creativity to artificial actors than to human ones, and even more so when they are involved in scientific processes.
... Namely, artificial systems possessing physical actuators through which to perform an action can be considered more creative than systems that reach the same result but with no physical intervention on the surrounding environment. This hypothesis is motivated by some studies carried out in online and live contexts (Herman and Hwang 2022), and by past surveys conducted by the author on creativity perceptions of the process and products by generative art algorithms (Moruzzi 2020b). Participants to these surveys expressed the belief that an essential dimension for creativity is the physical presence of the artist during the creative process, a dimension that was deemed as lacking from the systems under examination. ...
... The reflection on the role of embodiment for the perception of creativity in computational systems is included in a wider discussion on the reception of the engagement of AI systems in the creative sector. As mentioned, a generalized skepticism against AI engaging in creative activities is well-known and reported by the literature (Moruzzi 2020b;Mumford and Ventura 2015). The acquisition of problem-solving skills, agency, and other features of general intelligence has been indicated as a possible way for AI to gain the appreciation of the public (Bown and McCormack 2009;Gizzi et al. 2020;Moruzzi 2020a;Natale and Henrickson 2022), while other studies report how only the possession of anthropomorphic qualities and a general humanization of technology can lead AI to be perceived as creative (Moruzzi 2020b;Mumford and Ventura 2015;Wyse 2019). ...
... As mentioned, a generalized skepticism against AI engaging in creative activities is well-known and reported by the literature (Moruzzi 2020b;Mumford and Ventura 2015). The acquisition of problem-solving skills, agency, and other features of general intelligence has been indicated as a possible way for AI to gain the appreciation of the public (Bown and McCormack 2009;Gizzi et al. 2020;Moruzzi 2020a;Natale and Henrickson 2022), while other studies report how only the possession of anthropomorphic qualities and a general humanization of technology can lead AI to be perceived as creative (Moruzzi 2020b;Mumford and Ventura 2015;Wyse 2019). ...
The generation of artifacts through computational creativity (CC) systems is hitting the headlines with increasing frequency. Although impressive, this paper will not focus on the outcomes achieved by these systems, but rather on a specific dimension of artistic processes: embodiment. I discuss the results of a recent factorial survey study aimed at testing the influence that embodiment has on the evaluation of creativity. These findings show that the physical dimension of artificial systems interacting with human artists contributes to the perception of the interplay between artificial and human agents as a creative collaboration. I propose that a closer study of the dynamics of interaction between embodied machines, human artists, and the public can facilitate progress in both the artistic and the technology sector.
... However, to support this development, we must provide professionals, educators, policy makers and researchers with rich, reliable and transparent insights into how professionals perceive, adopt and use TTIG. We are at a crossroads where this vital knowledge is largely missing [48]. As for AI at large [16], we must study the good or harm that TTIG is doing to its users. ...
Text-to-image generation (TTIG) models, a recent addition to creative AI, can generate images based on a text description. These models have begun to rival the work of professional creatives, and sparked discussions on the future of creative work, loss of jobs, and copyright issues, amongst other important implications. To support the sustainable adoption of TTIG, we must provide rich, reliable and transparent insights into how professionals perceive, adopt and use TTIG. Crucially though, the public debate is shallow, narrow and lacking transparency, while academic work has focused on studying the use of TTIG in a general artist population, but not on the perceptions and attitudes of professionals in a specific industry. In this paper, we contribute a qualitative, exploratory interview study on TTIG in the Finnish videogame industry. Through a Template Analysis on semi-structured interviews with 14 game professionals, we reveal 12 overarching themes, structured into 39 sub-themes on professionals' perception, adoption and use of TTIG in games industry practice. Experiencing (yet another) change of roles and creative processes, our participants' reflections can inform discussions within the industry, be used by policymakers to inform urgently needed legislation, and support researchers in games, HCI and AI to support the sustainable, professional use of TTIG, and foster games as cultural artefacts.
... Another key aspect of the aesthetics of AI-generated artifacts is the very knowledge that the artifact was created by generative AI, and how that knowledge influences the viewer's perception [52]. As mentioned above, viewers often engage in "intention guessing," and the presence of human intention leads to enhanced perceptions of creativity and creative value [53,54,55,56]. ...
A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation. The generative capabilities of these tools are likely to fundamentally alter the creative processes by which creators formulate ideas and put them into production. As creativity is reimagined, so too may be many sectors of society. Understanding the impact of generative AI - and making policy decisions around it - requires new interdisciplinary scientific inquiry into culture, economics, law, algorithms, and the interaction of technology and creativity. We argue that generative AI is not the harbinger of art's demise, but rather is a new medium with its own distinct affordances. In this vein, we consider the impacts of this new medium on creators across four themes: aesthetics and culture, legal questions of ownership and credit, the future of creative work, and impacts on the contemporary media ecosystem. Across these themes, we highlight key research questions and directions to inform policy and beneficial uses of the technology.
... In the face of increasing technical automation, many see creativity as a final bastion of humanity (Moruzzi, 2020), claiming that computers cannot supplant artists (Hertzmann, 2018). Technology companies, however, see creativity as a profitable opportunity: 2020 heralded the "creator economy," an explosion of technologies for creators. ...
In this doctoral research programme, I propose a set of three thematic research projects to investigate the influence of algorithmic curation on artists’ creative processes and viewers’ subsequent creative perception. In the context of the burgeoning “creator economy,” I first review evidence of algorithmic impact on creator’s outputs. Considering the role of process in creative output evaluation, I bring an embodied, situated perspective to online creativity. Based on these discussions, I propose three research streams: first, I tease apart the consid-eration of process from the consideration of embodiment, asking how each (process & embodiment) influence creative perception in the context of algo-rithm-made versus human-made art. In this workstream, I also consider the im-pact of the art viewer’s embodiment (physical versus digital). Next, I construct an algorithmically-curated website of visual images which controls information about the artist, their process, and their output, using the website as an experi-mental sandbox to interrogate the role of these variables in online creative per-ception. Finally, I supplement these findings through ethnography with artists and curators, examining the role of algorithmic considerations in their process. Simultaneously, I prompt artists to imagine the possibility of a co-designed algo-rithm that prioritizes creativity over existing metrics for engagement.
... The suggested interpretation can offer a contribution to the debate on both natural and artificial creativity by providing a conceptual framework in which to couch estimates of the creativity displayed by a system, thus parading these results in favor of or against the possibility of non-human creativity. Pursuing further an unprejudiced analysis of natural and artificial creativity can help us dispel the biases that we may have toward non-human systems (Jordanous 2011;Moruzzi 2020) and to better design tools for human-computer interaction in the creative sector. 24 ...
Despite the recent upsurge of interest for the investigation on the topic of creativity, the question of how to measure creativity is arguably underdiscussed. The aim of this paper is to address this gap, proposing a multidimensional account of creativity which identifies problem-solving, evaluation, and naivety as measurable features that are common to every creative process. The benefits that result from the adoption of this model are twofold: integrating discussions on creativity in various domains and offering the tools to assess creativity across systems of different kinds. By situating creativity within this framework, I aim to contribute to a non-anthropocentric, more comprehensive understanding of the notion and to debates on natural and artificial creativity.
Despite substantial interest in developing theoretical models and technology for creativity enhancement, existing creativity research across various fields lacks a user-centered definition of creativity that can be operationalized in today’s digital spaces. To address this, we conducted a mixed-methods longitudinal research on a study website mirroring content from Bēhance, a popular online platform for creatives. Specifically, we examined how content creators and consumers explored and reflected on online creative content through textual, visual, quantitative, and behavioral data. Analyzing and triangulating these multiple data streams, we conceptualize creativity from the perspectives of its genuine “users,” the viewers. Collectively, we highlight (1) constructs of creativity that have not been emphasized in the existing literature, (2) the impact of users’ roles on content exploration and conception of creativity, and (3) the difference between machine and human users’ perception of creative content. We discuss theoretical and practical implications accordingly.
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