Abstract
Distant disciplinary interactions between artists, scientists and technologists have been a topic of interest. However, systematic knowledge on how diverse collaborative structures form and function is limited. The current study seeks to address this gap by investigating the social ecology of collaboration between artists, scientists and technologists engaged in inter/transdisciplinary (ITD) creative and cultural practice. The study explores the collaborative experiences of 42 participants with the use of Q-methodology. From the data, five thematic narratives emerge. Three narratives reveal collaborative styles grounded in embodiment and experimentation, fostering cultures and methods suited to co-creating ITD knowledge marked by uncertainty and serendipity. A fourth narrative highlights how artworks critically engage with science and technology, while a fifth, bipolar theme captures conflicting views on the mediated ‘third space’ in art–science–technology collaborations. This research reveals the influence of art on ITD research and science domains through creative collaborations. The findings support the development of transformative structural models for designing and facilitating collaborations across distant disciplinary knowledge cultures.
Keywords
Introduction
There is mounting interest in creating synergies between epistemically and ontologically distant disciplines in the interest of addressing complex problems and reimagining desired futures. This interest also manifests itself empirically. Significant initiatives on national and regional scales, including the New European Bauhaus and European Commission Horizon Programmes, particularly S + T + ARTS and Leonardo in the US, the Wellcome Trust in the UK, the Australian Network for Art and Technology's Synapse programme, the Los Angeles County Museum's 1960s Art and Technology Program and Artists in Labs, to name a few, provide considerable funding for joint projects encouraging the participation of art, science and technology. Incontestably, these initiatives invite the most complex forms of distant disciplinary interactions. Existing studies provide ample insights into the relationship between creativity, innovation and interdisciplinary collaboration (Barrett et al., 2021; Cuérel et al., 2019; Moirano et al., 2020; Santoro et al., 2020). Several theoretical frameworks discuss models for interdisciplinary collaboration in social work, healthcare and team science (Bronstein, 2003; Bryson et al., 2015; Hall et al., 2012). Specific to art–science interactions, Leach (2005) presents a detailed account on his participant observations of the New Technology Arts Fellowships scheme. He reflects on the fundamental ideas behind the interactions between arts, science and technology collaborations, most notably arriving at the push for techno ethics—the imperative for social and cultural stitching between society, the environment, technology and the sciences in which they are situated.
Despite the depth of specific analyses of exemplar schemes and collaborative projects, systematic knowledge of how such collaborations form and function is limited and mostly derives from individual case and ethnographic studies, which amplify the diversity in the field (Ede, 2005; Ball and Ede 2017; Shanken, 2005). Established theories therefore have limitations in extrapolating from systematic research across diverse cases addressing how collaborations in creative practices involving wide interdisciplinarity develop and function (Gray and Wood, 1991). A simple review of one of the largest repositories of art–science projects, the Ars Electronica archives, 1 evidences that art–science collaborations are infinitely diverse and heterogeneous with respect to disciplinary domains. The field inherently resists attempts to reduce methods and processes to normative structures, while practitioners, scholars and policymakers push the boundaries to do so. We therefore propose to adopt a social ecological view, which enables us to consider the agency of diverse actors, contexts and resulting dynamics in making sense of the collaborative environment. While the term ‘ecology’ traditionally referred to the relationship between organisms and their environment, ecology studies later developed to incorporate social, cultural and psychological layers, evolving also in the direction of a social ecology, most notably within the domain of health and team science, as well as environmental and ecological studies (Rawluk et al., 2020; Stokols, 1996; Stokols et al., 2008). The social ecological paradigm is predominantly grounded in social ecological systems research and is claimed to be useful in exploring context-dependent emergent processes, social interdependencies and participatory processes in inter/transdisciplinary (ITD) collaborations (Schlüter et al., 2019).
The lack of systematic knowledge on collaborative processes involving wide interdisciplinarity and creative research and practice leads to several drawbacks. Most notably, designing methodologies and processes that offer meaningful spaces of interaction and co-producing outputs becomes a non-scalable, non-replicable effort necessitating reinvention each time. Although arts–science–technology (AST) collaborative projects embed unique characteristics, understanding the key elements of AST collaborative processes, dynamics and culture can help to facilitate devising useful methodological approaches and tools. In addition, diversity in motivations and processes calls for a framework approach and mapping to devise inclusive methodological lenses and tools that are sensitive to the diversity of the art–science domain. The current study establishes such a framework through investigating the experience of collaboration between artists, scientists and technologists 2 and mapping dominant narratives resulting from this research. Finally, an evergreen challenge is in constructing a meaningful set of criteria for evaluation and impact that respect the unique environment and dynamics of wide interdisciplinarity, creative research and practice involving artists, scientists and technologists. An inclusive mapping and framework underscoring key attributes of AST collaborations can potentially aid in building sensitive and meaningful criteria for evaluating various collaborations and outcomes. Several attempts to build toolkits as part of European Commission initiatives evidence the need for systematic and methodological steps in this direction, such as the S + T + ARTS Collaboration Toolkits 3 and Pathways to Interdisciplinary and Transdisciplinary Research: The SHAPE-ID Toolkit (Vienni Baptista et al., 2020).
Henceforth, in the current study, we investigate how AST collaborations form and function by exploring the real-life experiences of artists, scientists and technologists with the use of Q-methodology. Understanding the collaborative structures and processes in art–science can be instrumental in forming, navigating and strengthening the outcomes of these collaborations. However, modalities are diverse (long-term open-ended, short-term outcome-focused, autonomous/institutional, shared goals/individual interests, organically formed/purposefully built teams, etc.), therefore posing a range of challenges for undertaking such tasks of investigating collaborative structures and processes.
First and foremost, establishing an ontological anchoring for AST remains a work in progress. The prominence of art invites further contemplation on how science and technology interface with society, non-human ecologies with an interest in situated knowledge creation, and its surrounding creative and cultural practices (Scott, 2006). The presence of art-making and artistic research bridges ITD and emerging theories of AST, acknowledging and manifesting the complexity of assemblages in practice (Law and Mol, 2002; Rogers et al., 2021; Salter, 2021). Extant literature and scholarly works suggest that one of the overarching motives in AST collaborations is the inherent interest in knowledge creation and collaboration across epistemic cultures. As knowledge cultures evolve, there is a discernible shift from traditional matters of fact to matters of concern (Latour, 2004) and matters of care (De La Bellacasa, 2017). Such transitions counterbalance the need to acknowledge the dynamics of deeply rooted expert knowledge systems and how they function in contemporary knowledge societies (Cetina, 1999). As knowledge cultures shift and reform in the face of democratizing knowledge creation, the politics of and ethics in science and technology come to the forefront through the critical engagement of arts (Star, 2016; Wilson, 2003). Furthermore, AST collaborations raise important questions about meaning-making, which takes shape at the intersection of knowledge-making, imagery and object-making (Galison and Jones, 1998). Hence, the attempts to explore and explain why collaborating across art, science and technology can be potentially transformative, how meaning-making, cultural production and knowledge creation interact at different levels and the associated challenges constitute a large portion of the scholarship in this domain (Bernstein, 2015; Malina, 2016; Schnugg, 2019). Consequently, in this research, AST can be viewed as the practice of creative research, as well as a hybrid form of contemporary aesthetic and knowledge production whereby the scientific and technological material is contextualized in its relationship to society, environment and culture. Such framing embraces different contexts in which artists and scientists collaborate.
While AST collaborations are widely accepted as forms of ITD practice and research, the epistemological and ontological implications of including art in the (science-dominated) discourse of ITD remain largely inconclusive. Bringing art-making and creative research into science domains transcends simply recombining disciplines and emerges as a new thought style that calls for a ‘de-disciplinarization’ of knowledge structures. Collaborators seek to deconstruct ‘discipline’ as a demarcation of a knowledge domain, expertise or even a sense of identity attributed to the knowledge cultures of institutionalized disciplines (Darbellay, 2015; Vellodi, 2019). In that vein, de-disciplinarization has implications for devising new methodological, pluralist approaches to collaborative research methods, as well as evaluations of outcomes. Building on such a notion of disciplinary transcendence, we aim at understanding collaboration situated in a creative and cultural context as opposed to the solution orientation of team science, Mode-2 knowledge creation or any multiple helix models referenced in ITD research and practice (Gibbons et al., 1994; Hall et al., 2012; Nowotny et al., 2010; Pohl and Wuelser, 2019).
This study makes several important contributions to the domains of ITD, creative transdisciplinary research and organization studies, as well as art–science and technology studies. First, this study provides a solid attempt to situate art in wider ITD practice and discourse. Second, from a methodological point of view, it employs a research methodology appropriate for systematic inquiry into subjective experiences of diverse groups of practitioners, which is quite different from the mostly encountered case-study approach in this field. Finally, our study provides a conceptual framework for creative ITD collaborations of AST resulting from mapping such diversity. This framework highlights the contextual primacy of concepts such as knowledge, experimentation and integration within the hybrid culture of AST, which for further research can be used as informants of meaningful evaluation criteria.
AST: A form of collaborative, creative ITD research and cultural practice
AST research and practice is a complex form of creative collaboration. Complexity emerges from methods, underlying theoretical frameworks and diverse forms, as illustrated, for example, by collaborative exchanges in new media art, which set the ground for the complex interplay between knowledge flows, innovation and creativity (Anzures and Marques, 2022). In that vein, AST collaborative research and practice build heavily on ITD and arts-based research. Contextually, they involve diverse motivations and modalities (Born and Barry, 2010). Attempts to suggest a formula of ‘how to’ collaborate remain an empirical concern in organization studies, social ecological systems and ITD research, as well as social studies of science.
The process of ‘doing collaboration’ can unfold through methods, tools and best practices (Shanken, 2005) as well as through contexts that relate to antecedents and expected outcomes of collaborations (Thomson and Perry, 2006). In relation to tools, methods, best practices and outcomes, few scholarly works unveil unique characteristics of creative collaborations. Two systematic literature reviews on interdisciplinary collaboration in creativity introduce elements such as conflict and improvisation as contributors to collaborative creativity in multidisciplinary teams (Barrett et al., 2021; Moirano et al., 2020). The authors of the two reviews argue that ‘conflict’ in creative collaborations can potentially serve as a catalyst for creativity, creating moments of engagement and empathy in well-established collaborative relationships among the creative members. Cuérel et al. (2019) investigate the antecedent conditions of sociodynamic processes in creative co-working spaces. This study provides insights into the behavioural dynamics that foster or hinder creativity among individuals who do not belong to the same formal organizations. Collaborations between artists, scientists and engineers resemble autonomously organized clusters to a certain extent. They may subscribe to similar dynamics, such as knowledge sharing, trust and learning (Cuérel et al., 2019). However, a fundamental difference is that contrary to a ‘cluster’, they inhabit intellectually distant spheres of knowledge, and motivations for collaboration go beyond the drive for innovation. In that vein, Born and Barry's (2010) foundational argument posits that art, science and technology are heterogeneous fields contributing to the unity of knowledge through logics of innovation, accountability and, more critically, ontology.
To briefly elaborate, the logic of innovation relates to science contributing to the creation of economic value. The effect of heterogeneity of knowledge sources and absorptive capacity on innovation performance is an emerging research topic in the creative industries. There is evidence that heterogeneous knowledge sources have a positive impact on the innovation performance of informal collaborative structures (Santoro et al., 2020; Vrontis et al., 2016). In addition, combining culturally distant knowledge and practices finds increasing currency in organizations (Schiuma and Antonio, 2014). The logic of innovation resembles the notion of Mode-2 Science and Mode-2 Society, both of which promote the overarching purpose of finding solutions to complex societal issues in an attempt to close the gap between science, technology and society (Gibbons et al., 1994). Nevertheless, innovation offers a rather limited drive and foregrounds an embedded utility whereby actors collaborate with an understanding of common goals and complementary aims towards a solution. Empirical studies suggest that AST collaborations rather exist on a broad spectrum of practices from being an open-ended, experimental, collaborative culture to being a coordinated, close-ended, structured approach akin to design thinking (Leach, 2005; Minsky, 2020).
The logic of accountability relates to art's catalyst role in rendering science and technology accountable to society. Most art-science collaborations adhering to this paradigm are contested on the basis of art serving science, often in the form of communicating science. Finally, the logic of ontology foregrounds the motive for stimulating ontological change in the knowledge-creation process of involved disciplines. In turn, it potentially invites less harmonious interactions as change; and critical thinking can involve agonistic–antagonistic social dynamics, while being perceived as the most interesting and intellectually charged form of creative collaboration involving artists, scientists and technologists (Barry et al., 2008; Born and Barry, 2010; Malina, 2016; Schnugg, 2019).
Undeniably, logics of interdisciplinarity offer a theoretical basis for understanding various types of collaborations, as well as motivations. ITD practice and research contribute to the ITD discourse's key concepts, such as integration through subject–object unification, shared language, combining practice and theory, problematization, interdependence, methodological pluralism, integrative methods and knowledge (Borgdorff, 2012; Gibbons et al., 1994, Hall et al., 2012; Klein, 1990, 2004, 2017; Malina, 2016, Nicolescu, 2014; Pohl and Hirsch Hadorn, 2007; Pohl and Hirsch Hadorn, 2008; Rust, 2007; Stokols et al., 2008; Taylor, 2021; Wickson et al., 2006). In relation to ‘doing’ or implementing collaborative transdisciplinary research, empirical ITD scholarship offers various methods and process knowledge largely aimed at providing solutions to complex societal and environmental problems through sustainability research and team science. Based on ideal-typical approaches in ITD research practice, the process of collaboration involves an iterative cycle of collaborative problem framing, building a collaborative research team, co-producing viable solutions and engaging in knowledge transfer and group learning through collaborative research, and finally reintegrating solutions and knowledge into the problem environment (Lang et al., 2012; Pohl and Hirsh Hadorn, 2008; Scholz et al., 2006; Stokols et al., 2008). While providing a useful empirical basis, the empirical approach of ideal-typical is rather limiting, considering the diverse modalities employed by AST collaborative practices, particularly due to its focus on ‘solutionism’.
In response to current scholarly debates, ITD research is increasingly moving towards transformative science—a reflective, critical engagement with complexity that challenges simplistic solutionism (Wehling, 2022). So-called ‘wicked problems’—often social in nature—require more nuanced, systemic responses than those offered by highly ambitious technological fixes (Mazzucato, 2021). In this context, being solution-oriented means fostering collective, systemic approaches rather than pursuing merely utilitarian endpoints. Arts-based interventions in science and technology—rooted in societal, cultural and ecological urgencies—can play a vital role in shaping such differentiated modes of knowledge production. This underscores the need for inclusive ITD frameworks that support creative collaborations, embrace contradictions and integrate critical thinking with making.
In contrast to how scholarship and discourses of ITD developed in science and knowledge creation, interdisciplinarity is claimed to be endemic in the arts and humanities, building on philosophy as the cradle of intuitively transdisciplinary knowledge (Gibbons et al., 1994; Klein and Frodeman, 2017). However, methodologically speaking, ITD in arts appears to be confined to how various artistic disciplines and mediums blend to generate new concepts, experiences and artistic expressions (Augsburg, 2017). Informed by such insights, we attempt to unveil the ‘doing’ of collaboration, integrating diverse angles of arts-based research, ITD and collaborative art to suggest a social-ecological framework for AST collaborations.
Methodology
For methodological purposes, to define art, science and technology, we employ core conceptual definitions, avoiding complex political and contemporary debates surrounding these terms, which would be beyond this paper's scope. Moisei Kagan (1994) provides such perspective based on each term's function and meaning. Science is defined by its pursuit of universal laws governing observable phenomena, concerning itself with understanding of a conceivable objective reality. Conversely, technology is seen as the practical application of knowledge, equipping humanity with tools to transform nature within material production systems (Kagan, 1994). Art, in its most widely recognized expression grounded in its Latin root ‘ars’, refers to both crafted objects and the implicit knowledge required for their creation (Rogers et al., 2021). While these definitions help to ensure a shared conceptualization of these highly loaded meta disciplines, they at the same time accentuate the absence of boundary thinking across art, science and technology.
The current study adopts a Q-methodological approach to investigate how a social ecology of collaborations among artists, scientists and technologists forms and functions as a transdisciplinary cultural and creative practice. Because of the immense diversity of these experiences, AST collaborations offer a Q-friendly environment. Q-methodology is a statistical derivative of factor analysis. It was developed by William Stephenson in 1935 as an innovative approach for the systematic study of human subjectivity (Watts and Stenner, 2012). Q-methodology is appropriate in this context, as it enables examinations and analyses of the distinct subjective viewpoints held by the subject communities. It is a semi-quantitative approach employing principal components analysis (PCA) or factor analysis (FA) as the data reduction technique. The distinct feature of Q-methods is that, instead of demonstrating the relationship between variables, they rely on correlations of the respondents to explain the relationships between them in reference to specific viewpoints. The result presents a small set of sorted statements (typically known as factors), which are differentiated from each other and summarize the perspectives shared among the respondents (Zabala, 2014). In Q-methodology, participants are asked to provide their personal judgements and opinions pertaining to the subject of investigation through rank ordering a number of statements relevant to the topic of investigation. It is expected that participants draw from their cultural and social understandings and perceptions, thereby rendering the exercise an intuitively culturally situated sense-making effort (Brown, 1980). There are no pre-established criteria for the number of statements to be included in a study; however, a theoretical construction is recommended to follow a ratio of 1:2 between the number of statements and the participants, although there are studies with a larger number of participants (Watts and Stenner, 2012). The present study employs a 51-item concourse and is conducted with the participation of 42 practitioners from the field of AST.
Procedure
Devising the Q-statement set
The Q-set of 51 statements was designed based on three distinct criteria: coverage, balance and language (Watts and Stenner, 2012). Three distinct sources informed the construction of the present Q-concourse. These were (i) relevant theories and literature primarily focusing on ITD practice and research, art–science, art-based research, collaborative art and collaboration; (ii) six exploratory interviews with experts in the field of art–science, selected based on diversity in experience, knowledge domains and roles in art–science collaborations; and (iii) two pilot studies that helped us establish shared language attributes and meaning.
The principle of coverage refers to a Q-concourse that is broadly representative of the universe of opinions pertaining to the experience of collaboration in art–science, for which we relied on theories and literature (i) and interviews (ii). Generally, conversations, stories, commentaries and interviews provide statement material rather than facts (Brown, 1980). Each interview focused on a set of 30–35 similar statements. Across the six interviews, we worked with a total of 198 statements. The recordings were transcribed and coded to highlight key ideas and discussion points. Using a reflexive and iterative process, we arrived at the final Q-set of 51 statements (Table 1).
AST collaboration styles.
AST collaboration styles.
The second critical element was balance, as explained by Watts and Stenner (2012). In respect to balance, the aim was to include all possible arrays of opinions that could be associated with the participants in art–science collaborations. This condition was mostly met by the use of a theoretical framework pertaining to the study of ‘collaboration’. To that end, Q-design was inspired by a framework of collaboration by Thomson and Perry (2006). In a very broad sense, statements were created to reflect antecedent conditions, processes and expected outcomes of collaboration (Thomson and Perry, 2006).
The third principle involved the language constructs and adhered to criteria such as non-bias and clarity, for which we relied on two pilot studies (iii). A native speaker without prior knowledge in the field reviewed the statements in terms of grammatical sensitivities, word choice and pronunciation in language culture context (US English).
Due to COVID-19 restrictions at the time of data collection, the Q-studies were conducted online via Zoom using Q-sorting software. The study consisted of two parts: Q-sorting and interviews. Before the actual Q-sorting, a seven-question profiling survey was conducted, in which each participant was defined using a set of criteria. This initial survey enabled a detailed understanding of each participant's background, expertise, collaboration type and role, and the typical group-sizes in their collaborations.
Each study started with a 10-minute introduction to the procedure by the first author, which also included an overall review of the 51 statements by the participants. Such freedom enabled us to understand which aspects most mattered and related to them. Some tended to focus on motivations, requisite assumptions and values (antecedents), while others preferred to express their experience through process-related or outcome-related statements. Each study lasted an average of 90 minutes, including the Q-sorting, discussions and a concluding interview focusing on the items most strongly ranked. The interview length varied between 32 and 240 minutes based on participants’ preferences. The studies were video recorded on Zoom as well as voice recorded using transcription software to further aid in qualitative narrative analysis.
Participant sample
The study included participants (n = 42) from a range of diverse disciplinary backgrounds, experience levels and types of collaborations they engage with in AST. Due to the highly niche profile of the population, we adopted purposive sampling with an open invitation to participate primarily through global sci-art networks (including the Sci-Art Initiative, Science Gallery, SymbioticA, CERN Arts Residency and Ars Electronica Creative Producer Program), combined with snowballing (Taherdoost, 2016). Disciplinary interest areas included pure sciences, such as mathematics and physics, and more broad or interdisciplinary areas, such as environmental science, sociology, humanities and art. Twenty participants identified themselves as hybrid, sixteen as artists, and six as scientists. This distribution reflects the nature of the AST field, in which a small group of scientists often participate in multiple collaborations. The participant group primarily consisted of practitioners with a certain level of experience (n = 40) of having been involved in multiple projects over the course of years. Most worked in small to medium-sized teams. The geographical distribution was wide, including Europe (n = 20), North America (n = 13), South America (n = 4), the Asia–Pacific (n = 4) and Africa (n = 1).
Of the participants, 12 described collaboration as working together with individual interests, while an equal portion (n = 13) reported seeing collaboration as working with shared interests while maintaining a certain level of autonomy. The remaining participants (n = 17) described collaboration as working together for a common goal. The nature of collaborative activity was quite diverse. Most significantly, almost all participants identified ‘experimentation/exploration’ as a primary orientation of the collaborative effort. This was often combined with and followed by ‘citizen engagement and collective action’.
Data analysis
The program R was used to run the Q-method analysis. Data were first analysed using Principal Component Analysis to find the associations across Q-sorts, with a varimax rotation to produce orthogonal (uncorrelated) factors (as per Brown, 1980), and Pearson correlation analysis was used to extract factors (Table 1).
The preliminary reference point was the collaboration framework (Thomson and Perry, 2006), which already suggested the possibility of a minimum of three factors centred around antecedent, process and outcome. However, the initial consideration of a three-factor solution did not reflect the depth and differentiating narratives already suggested by the qualitative interview content. After experimenting with five- and six-factor solutions, the six-factor solution was decided upon based on two key considerations. First was the common Kaiser–Guttmann criterion according to which the researcher typically keeps EV > 1.00 (Watts and Stenner, 2012: 106). However, Brown (1980) argues that this criterion alone may sometimes lead to the exclusion of meaningful factors. Therefore, we also relied on interview content that allowed meaningful interpretations of factor loadings (Watts and Stenner, 2012). Combining distinguishing and consensus statements, factor arrays and interview content made us conclude that the AST collaboration scheme can best be explained with a six-factor scheme. One of the factors (#5) was excluded from the analysis on the basis that factor loadings were too low (two participants) and the interview commentaries were insufficient in providing a meaningful interpretation. The correlation analysis of the factors demonstrates one entirely distinct (Factor 6), two closely correlated to each other (Factors 1 and 2), and otherwise distinct and differentiated factors (Factors 1, 3, and 4). The resulting five factors, explaining 48.5% of the variance, were labelled according to the dominant narratives in each: (i) complexity and embodied knowing, (ii) creative research and discovery, (iii) change in knowledge cultures, (iv) art-making and public engagement, and (v) navigating the ‘third space’.
The five narratives provide a synopsis of the dominating viewpoints with reference to the experience of collaborations between artists, scientists and technologists. In order to determine the significance of each statement in the style categories, we relied on sorts that correlate above 0.36, implying that they are meaningful to the narratives (Brown, 1980). In addition, distinguishing and consensus statements, as well as factor arrays for each factor, are used to present a thorough description of the narratives. A factor array is a statistically confounded Q-sort to represent the common viewpoint underlying a particular factor (Watts and Stenner, 2012). Factor arrays offer a rather reduced yet optimized scope for interpreting and distinguishing consensus and closely ranked statements in the Q-sorts.
Results: The five AST narratives for ITD collaborations
The current study aims to offer a social ecological interpretation and conceptual mapping for how collaborations among art, science and technology form and function. The conceptual framework (Figure 1) demonstrates that emergent themes are layered, inviting a rhizomatic reading that is informed by the qualitative content of interviews.
Conceptual mapping of AST collaborations (A = antecedent; P = process; N = narrative).
Factor 1 loads on five Q-sorts accounting for 11.8% of the explained variance. Most participants that contribute to this factor have hybrid profiles, combining scientific and artistic backgrounds. They all engage with issues such as environmental science, climate, ecology and biotechnology through art. They have a strong science orientation, which is manifest in their interest and questions that can be site-specific or related to the (biological) materials and system of an environment. Whereas their conversations with scientists can be deep and engaging, they commonly do not co-create with scientists. Collaboration for this group relies on working together with shared goals/interests, where scientists are typically only involved on demand from the artist. As one participant points out: I actually often refer to partnerships … And not collaboration, because with collaboration, I always feel that you have to agree otherwise and it's not a collaboration. So, I actually often describe my practice as partnering with science. (ASTQ03)
At the onset of any project, most participants experience that their subject matter is complex and layered. They acknowledge that the complexity comes from the context, but it is not an aspect they discuss in detail in the interview. What seems to engage them is the prospect of approaching complex systems, and the possibilities therein. As their research focus and the subject of interest involve an interaction with the environment and ecology, they use multiple and complementary ways of creating knowledge with no hierarchy among them (Dieleman, 2012). Collaboration in this context involves situated, embodied and enacted forms of cognition and therefore offers multiple trajectories in the ways new knowledge is created (Borgdorff et al., 2019; Gibbs, 2013).
This narrative is also rich with references that relate to the elements of uncertainty and ambiguity. While art and science superficially stand in contrast on the basis of certainty, fact and objectivity, this type of collaboration celebrates uncertainty and its potential to uncover possibilities.
Perhaps as a natural extension to complexity and ambiguity, participants expect to encounter serendipity in the collaborative process, which is one of the least discussed elements in ITD research and modern science. Darbellay et al. (2014) argue that serendipity is a driver of interdisciplinary research and the core notion that lies at the heart of discovery in science. Furthermore, serendipity is mostly seen as a constellation of meaningful events revealing the significance of the social and historical characteristics of innovation and the creative research process (De Rond, 2014). Serendipity is considered to be the emergent property of scientific discovery, as well as an impetus for creativity in ITD research and out-of-lab scientific knowledge creation. However, it is one of the least explored concepts in the ITD process in relation to how this element can be cultivated, recognized and responded to as a retrospective reflection (Copeland, 2019; Darbellay et al., 2014).
Finally, this narrative reflects on embodied knowledge, which results from bodily interactions, ecological interventions and the situatedness of the AST research and creative process. Hence, the interaction between art, science and technology involves multiple epistemologies and fuses scientific knowledge with embodied ways of knowing (through cognitive, sensory and conceptual agencies), contextualization, sense-making, critical and creative research, experimentation, emergence and improvisation (Augsburg, 2017; Borgdorff, 2012; Borgdorff et al., 2019; Calvert and Schyfter, 2017; Dieleman, 2012, 2017; Elkins, 2008; Hannula et al., 2014; Ozog, 2009; Schnugg, 2019). For example, one of the participants (an environmental artist) narrates her creative process that manifests the complex unfolding of natural landscapes informing her artistic research and creative directions. Despite extensive research of articles and aerial documentation in the beginning of the process, she unexpectedly discovers a completely different situation when she arrives at the site. Extensively immersed in a lake and its surroundings, she recreates the transformation, an embodied process that partially unfolds in her own words as: [The discovery of river poaching] was one of the most dramatic experiences I’ve had as something that really shifted the direction of my work. And so that kind of serendipity is something that I’ve learned to really work hard to be open to, because it takes me to all kinds of interesting places to see. Questions that I’m interested in are really questions of ecology, which are very complicated systems. (ASTQ01)
What the narrative ‘complexity and embodied knowing’ implies is that knowing and understanding are holistic processes that build on scientific as well as embodied ways of knowing and also engage with local and indigenous knowledge. Ultimately, this leads to the hope, aspiration and sometimes even observation that art–science collaborations have a bottom-up potential for transforming not only what is known, but also how knowledge is created.
Factor 2 narrative: Creative research and discovery
The second factor loads on the highest number of participants with a heterogeneous group of scientists (n = 2), artists (n = 4) and hybrids (n = 3). They are all experienced practitioners with long-term involvement in multiple AST collaborative projects and report to various disciplines. In terms of geographical distribution, they are based in Europe, North America, South America and Australia, and bring in distinct cultures of AST practices. Except for one, the majority work in small-sized teams.
The dominant characteristic of this narrative is the idea of exploration through creative research. Primarily driven by imagination and curiosity, the participants discover new ways of looking at the world and enjoy the collaborations as spaces for play and discovery. Another distinguishing characteristic in this narrative is ‘experimentation’. One participant, a scientist in a biotechnology lab, sees artist-led experiments as ‘experiential’ trials, in which the artist's engagement is focused on the materiality and unspoken cultures of the lab and their multisensory and critical interactions with it. An example the participant refers to is Kira O’Reilly's red lab coat interventions (O’Reilly, 2017). Another experimentation consists of methodological trials, exploring possible pathways and protocols within the creative process. An important aspect of experimentation is ‘freedom’ of thought and play, with an acute awareness of and care for the meticulous processes that the collaborators adhere to. Experimentation in AST collaborations differs significantly from experimentation in science. For AST artists, experimentation is a process for investigating possibilities, liberating thought from the confines of disciplinary practice, through which breakthrough discoveries can be made. Experimentations provide a platform for gauging the relative meanings and different views through piloting and testing, because ‘That's where the exciting possibilities come from’ (ASTQ06). Collaborators bridge theory and practice across arts, technology and science through prototyping conceptual ideations, as explained by a respondent: That something is possible in one field … you have something theoretically that works and that is proven … But you have no idea until you experiment with it. And so that is why I think experimentation, in my experience, has been the way to explore possibilities. (ASTQ31)
A substantial body of literature discusses the process and methodology of ITD research; however, not much attention is given to the practice, design and relative perception of what constitutes experimentation in the collaborative environment of artists, scientists and technologists. In this respect, Dieleman's (2012) ‘spaces of experimentation’ concept offers a theoretical underpinning, in which the flow between experimentation and imagination is discussed as a moment of engaging with the problem or research question, as an alternative to the step-by-step formulation of experimentation towards validation and resolution in science. Its strength lies in initiating the process with some action as a way to devise alternative problematizations and realities. These alternatives are constructed through the reflection and simultaneous introspection of the collaborators on how they relate to their environment (Dieleman, 2012). Such processes embrace surprise, puzzlement and confusion in a way that resembles the serendipity, ambiguity and uncertainty that are much valued by the participants of this study. The interactions between art, science and technology have historically started as experiments. The most distinct example was the E.A.T. experiments, in which Kluver and Rauschenberg not only experimented with technology as tool and expression but also explored and tried out unconventional ways of working and co-creating with artists, scientists and engineers. The ‘unconventional’ applies to connecting knowledge and creative ambitions of seemingly unrelated intellectual realms. The process is largely non-prescriptive, ultimately producing novelty on multiple levels, each individually and jointly meaningful. 4
Also, the notions of improvisation and free play in experimentation are not prominent in ITD research methods or science and appear to be distinct contributions of artful methodologies, as we come across in performative art and creative research (Dieleman, 2012). It should be noted, however, that artist participants emphasize that ‘play’ should not be considered as ‘arbitrary ways of doing’ and that improvisation requires ‘mastery’ on many levels to yield any outcomes that are meaningful.
Factor 3 narrative: Changing knowledge cultures
This factor loads on three participants who have been working in the AST field for a long time in the form of continued collaborations with scientists. The science disciplines are affiliated with ecology, quantum physics, systems science and neuroscience, all reflecting a fascination for the existence of beings and the relations between individuals and life systems. To this group, collaboration is rather about working with individual or shared interests, as opposed to common goals, reportedly more so when the outcome is purely an artwork. Where someone's work involves a performance-driven and innovative design, collaboration shifts to common goals.
This narrative is distinct in terms of its outcome expectations and the art's potential in triggering new inquiry and research. Expected outcomes relate to a change in knowledge cultures, as a gradual positive change in the ways in which knowledge is created. The respondents acknowledge that their mandate to obscure disciplinary boundaries eventually has an impact on the processes and cultures of knowledge creation. Nevertheless, in their opinion, modern science is far from reciprocating in this direction, partially confirming the epistemic solidity of science even in interdisciplinary practice (Nanni and Fallin, 2021). A paradigm change in the cultures of knowledge creation not only requires a long-term engagement in the AST domain but also a reciprocal interest from both science and art in achieving such change, as it was articulated: ‘What I have seen during my practice that it really transformed, it really affected the realms of art. [But] of science and knowledge it's going much slower and on the very fringes of it’ (ASTQ02).
The ‘changing knowledge cultures’ narrative implies ‘integration’ of diverse disciplinary methods and knowledge. Such integration uncontestably appears as one of the building blocks of transdisciplinarity. The literature distinguishes between different conceptual forms of integration, and, among those, ‘transgression’ seems to align most with how the participants in this research discuss the concept. Accordingly, integration for the purposes of ‘transgression’ contests dominant structures of knowledge with the aim to transform them (Pohl et al., 2021). In a larger discourse, integration seeks to establish a balance between retaining plurality and attaining a consensus across diverse thought styles, knowledge ideas or practices. Specifically, in the context of collaborative research undertaken by artists, scientists and technologists, integration is characterized by a multilevel convergence of diverse epistemological and ontological perspectives, experiential knowledge, the unity of subject and object in an investigation, and a synthesis of theory and practice mostly through arts-based research (Augsburg, 2017; Rust, 2007; Wickson et al., 2006). One of the participants contributing to this narrative designs games that target behavioural change and therefore works closely with fairly positivist disciplines of social and developmental psychology. The participant's creative works make it necessary for him to mimic the actual experience, such as aggression on a personal level, for which he uses immersion techniques preceding the creative process in order to understand the phenomena on a dimension that is beyond cognition or academics. He underscores the importance of immersion, embodiment as internalized methods of understanding, and knowledge of complex phenomena.
Perhaps not surprisingly, in a collaborative environment in which one of the key drivers is the change in knowledge cultures that collaborators want to effectuate, this narrative also foregrounds the need for a facilitating, mediating and curating role in the collaboration processes. Such a need becomes even more urgent when collaborations, next to other aims, entail a clear goal to produce a tangible innovative outcome.
Factor 4 narrative: Art-making and public engagement
Factor 4 distinguishes itself from other factors most notably by its interest in science for artistic purposes and its art form as a channel for societal engagement with science. Three participants contribute to this factor: one artist, one hybrid and one scientist. The topics of interest in terms of discipline lean towards climate, environment and agriculture as environmental and societal issues; the modes of investigation rely on critical and creative expressions in visual and performative art forms, sometimes involving experiments with the public or in public space. All have prior—although not long-standing—experience with art–science collaborations. Their collaborative efforts focus mostly on experimental/explorative types of activities coupled with innovation, citizen engagement and science communication. The scientist in this group has a background in cosmology, astronomy and neuroscience, but also explores the terrains of scientific questions through origami and virtual reality. Collaboration for this group is mostly working together with shared interests.
Characterizing and distinguishing statements suggest that this factor is primarily focused on generating publicly engaged art in which science and technology are the material and the lens through which artistic expressions are formed. There is a strong drive for connecting a science-driven agenda, for example, related to the environment, public understanding and debate, and even taking action. This resonates with scholarly literature on collaborative art that contributes the key notions about critical public engagement, social contextualization and collective action (Kester, 2011; Mara, 2017; Miller, 2017). Participants share the opinion that science-informed art is a vehicle for debunking the ‘cocooned’ positions of both art and science through socially relevant entry points. Most of the time, therefore, science, politics and art intersect and invite the public to be active participants in the discussion of the relationship between science, technology and society, through art. As testified: Making contact between art and science has great potential to demystify both fields … If we think of the space of all human activities, those silos are conventionally quite far apart, so a voyage between them is likely to pass near something else, which could be quite random, but brings everything closer to human experience. This enhances the power of each to inspire and, if appropriate, spur to action. (ASTQ16)
Characterizing statements in this narrative focus on meaning-making. These participants’ research and resulting works encourage the audiences to engage with natural phenomena and underlying technology—such as sensors and microscopes—to immerse through multisensory stimulations and explore the connections and interactions, and thereby, through art, convey the very essence of artists’ ambition to transcend the oversimplified position of art as simply the ‘illustration’ or ‘communication’ of science in AST. Valuable insights for scientific or technological exploration can emerge from artistic research and critical sensing. One of the artists, whose work is heavily informed by nature observations and what she calls ‘creative explorations’, shares examples in which she was invited as an artist to join a research team to develop multisensory research tools mimicking nature. A notable body of works derives from meticulous artistic research into techniques and methods of science, hacking or otherwise unveiling the inner workings of technology such as design parameters, functionality and use in consideration of ethical paradigms (Rogers et al., 2021; Schnugg 2019). Similarly, artistic research and critical making help in rearranging data and scientific imagery to reveal an often ‘fragmented’ or ‘localized’ gaze of science into the realms of human life, body and systems, at times limiting our ability to see humans as a system (Webster, 2005). Inherently, art's involvement with science and technology beyond that of societal relevance suggests an undeniable influence on how knowledge is created, and how technology is designed. Prominent examples are also seen in the collaborative works from the S + T + ARTS scheme (i.e., Broken Spectre by Richard Moss and Oceans in Transformation by Territorial Agency), which demonstrates how imaging and sensing technologies can be reimagined to reveal alternative and equally compelling realities when keeping the urgencies and injustices at the centre of collective responsibility of science, technology and art.
The narrative of ‘art-making and public engagement’ implies an emphasis on values such as trust and social cohesiveness as facilitating antecedent conditions in collaboration. Therefore, social cohesiveness may potentially provide a reassuring space for cohabiting adversaries, collective thinking, and co-creating in the absence of agreement. Finally, in Factor 4, unlike in other factors, ‘making’ is a central activity and is part of research and experimentation, while also being shared by the collaborators rather than being the sole property of the artists.
Factor 5 narrative: Navigating the third space
Interestingly, this narrative emerged as a bipolar factor. Bipolar factors arise when one group of Q-sorts mirrors another group that ranks the same items with exactly opposite scores. Although bipolarity may suggest splitting the same factor into two and exerting interpretations as separate factors (Brown, 1980; Watts and Stenner, 2012), the number of Q-loadings (3) on this factor in the current study would not justify splitting the narrative. Despite low loadings, the narrative of Factor 5 introduces a distinct discussion about ‘structure’ through facilitation and mediation, which Muller et al. (2018) define as the ‘third space’. Narrative 5 foregrounds the proposition that facilitated, mediated and structured collaborations are central to the experience. The bipolarity of this factor calls into question the contexts and conditions in which support structures would provide value to this third space.
Like Factor 4, this factor also loads on three participants: one artist, one scientist and one hybrid. Two of the participants are experienced collaborators, while the scientist has noted that they have limited experience with science–art projects. The collaborative activity focuses on experimentation–exploration and science communication. Collaborators work in small teams. Factor 5 participants seem to converge on the topic of life sciences (including biology, climate and soil science) and bio-art, as well as neighbouring fields such as medical and health humanities and public health. As this is a bipolar factor, it is notable that two participants perceive collaboration as working with individual goals, and the other participant experiences collaboration as working with common goals.
Two participants (one with a hybrid profile, the other a scientist) strongly share the viewpoint that facilitation, curation and mediation are beneficial in the process, and experience collaboration as co-creating with a common goal. They both focus on experimentation and science communication with a clear and collective goal of creating an artwork. Conversely, ASTQ38, an artist, mostly engages in what they describe as ‘symbiotic’, long-term collaborations heavily exploratory in nature, without a predetermined artwork or output at the outset. Hence, they share the opposite opinion in relation to curation and facilitation. This outcome leads us to suggest that an attempt to impose structure by design should be carefully considered. Tools such as facilitation, bridging and mediation across diverse disciplines can be valuable and productive when dealing with close-ended, output-oriented interactions. The same type of tools can be undesired when the interactions take place in small ‘symbiotic’ or organically formed collaborations having an exploratory and open-ended nature. In short, the implications of the narrative ‘navigating the third space’ are explaining the conditions for including a role for facilitation and acknowledging that an intermediary role and process should be designed based on the specific needs, purpose and composition of the collaboration.
Towards an emergent and experimental framework of collaboration in AST
Our study design is inspired by an organizational process approach of antecedent(s) and outcome(s) to collaborations (Gray and Wood, 1991). Through conceptualizing the social ecology of AST collaborations, we intended to bridge arts into the ‘science’-dominant space of ITD research, practice and culture. Such bridging can change the way that we form and methodologically design collaborations engaging distant epistemic cultures of science, art and technology. The resulting framework demonstrates that the social ecology of AST collaborations is too complex to yield themselves as distinguished categories of practice. Instead, we observe that collaborators make use of shifting collaborative intentions, which are highlighted in the ‘narratives’, which set the direction of how the collaboration process may unfold. For instance, where collaborators share an interest in complex phenomena, which invites embodied methods of knowing and serendipity, the collaborative process is likely to be emergent. Similarly, where critical engagement with science and technology conceives potentially antagonistic relationships, collaborators seek trust, social cohesion and familiarity, while the process calls for integration (Figure 1).
Discussion and conclusion
This study sought to investigate how collaborations between artists, scientists and technologists form and function to propose a conceptual mapping. Such a mapping can be useful for nuanced design, facilitation and evaluation of creative collaborations in which art, science and technology as meta-disciplinary cultures work together with an imperative to act on matters of collective interest and concern (Latour, 2004) through engaging in creative ITD research and cultural practice. This outcome supports the intention to integrate art into ITD and provides insights into emergent concepts such as uncertainty and experimentation.
The study contributes to existing scholarship and practice on three dimensions. First, by adopting a social ecological approach, we reveal the connections between experience, purpose, interest and concern that set the tone for collaborations at the outset, as they form. Hence, instead of following relatively structured organizations of transdisciplinary teams designed around solving complex problems, we are encouraged to think how shared interests and curiosities can be navigated by acknowledging forces of imagination, uncertainty, ambiguity and serendipity. In parallel, we suggest that deliberate interventions to build trust and social cohesion can be valuable while forming such collaborative structures across distant disciplines. Furthermore, we propose a conceptual framework that offers distinct qualities of collaborative process, reflecting on the question of how they function. In that vein, we reveal distinct elements such as embodied knowing, the imperative of changing knowledge cultures, creating the third space, and art-making bridging societal and environmental contexts with science and technology. Second, we offer a conceptual framing for AST collaborations that suggests an intellectual shift in how we formulate transdisciplinary research, with a prominent role for art intentionally obscuring boundaries, identities (artist, scientist, engineer] and aesthetics, challenging ontological units through language, experience, relations, contextual meaning-making and emergent methods (Barad, 2007; Leach, 2011).
A final contribution is a methodological one. Through employing Q-method, we offer an alternative methodological approach to predominantly case and ethnographic studies to respond to the need for a systematic investigation of diverse practices and experiences. As a result, we are able to introduce a temporal but holistic conceptualization of AST collaborations, inviting future research to further explore how the emergent key concepts can be used to advance these highly complex interactions.
The analysis of how 42 participants rank ordered 51 statements resulted in five thematic narratives characterizing these collaborations, which extend our insights into the diversity, antecedents and processes of AST collaborations. Ultimately, we offer a deeper understanding of elements informing their formation and functioning.
The first narrative, ‘complexity and embodied knowing’, is characterized by an interest in approaching complex systems, which call for plural and complementary methodological approaches in research and knowledge creation. The collaboration is situated in the environment of investigation, and research embeds embodied and enacted forms of cognition and interaction with data and/or the subject of inquiry.
The second narrative, ‘creative research and discovery’, brings a stark distinction between science experiments and experimentation in AST collaborations as a tool for engaging with the problem with the use of imagination, free play and freedom of thought, which are proposed to enable fresh narratives and breakthrough discoveries.
The third narrative, ‘changing knowledge cultures’, emerges as a result of long-standing collaborations. Collaborators hold the future-looking perspective that their approach and methodological choices target art's potential in triggering new inquiry and research.
The fourth narrative, ‘art-making and public engagement’, reflects a clear interest in bridging science, technology and society through adopting a critical attitude towards their relationship, explicitly enforcing ethical and moral considerations in the agendas of technological innovation and scientific research.
The fifth narrative, ‘navigating the third space’, focuses on the role of facilitation in the process of art–science collaborations. As the critical tone of art-making takes precedence, the need for mediating and facilitating functions becomes prominent in these types of collaborations. However, such attempts should be carefully considered, as they can be useful or limiting depending on team dynamics and purpose. This final narrative also problematizes ‘disciplinarity’ and helps us understand how disciplinary integrity functions in both transgressing boundaries and enriching ITD dialogue with deep disciplinary expertise.
On a theoretical level, the present study aids in uncovering possible influences of integrating art in the science-dominated ITD discourse and methodologies, embracing ambiguity and serendipity in science culture and ITD research. While science is often burdened with a demand for certainty, reducing or resolving ambiguity, artistic thinking and humanities in a broader sense shift our understanding of these notions. Ambiguity, often defined as loose concepts inviting multiple interpretations, is argued to create a common ground among diverse stakeholders by offering negotiated spaces and creative pluralist readings into complex ideas or propositions, and fostering social learning as well as a social construction of facts and value-based decisions (Fleming and Howden, 2016).
Another key concept introduced by artistic thinking is serendipity. As an understudied topic in ITD discourse, serendipity has emerged as one of the distinguishing qualities of AST collaborative processes. Serendipity in science is the underlying principle of discovery, while in arts and humanities, it is the faculty for revealing latent connections. Responding to serendipitous phenomena can possibly be enriched by arts-based methods and instruments, as the process requires acute attention to connections and retrospective reflection on a course of events (Copeland, 2019; Foster and Ford, 2003). Methodologically speaking, serendipity has not figured prominently in ITD research and discourse, possibly due to its unpredictability. Future research, therefore, could investigate further the conceptual and methodological approaches and implications of uncertainty, ambiguity and serendipity in ITD research by closely studying emergent processes of creative research and making in AST collaborations. The development of established criteria and procedures for evaluating ITD-based research remains a work in progress. Existing scholarship mostly focuses on devising measures related to integration, effective problematization and contributions to solutions (Pohl et al., 2011; Pohl and Hirsch Hadorn, 2008). An explicit recognition of ambiguous or uncertain elements of AST collaborations can provide valuable insights into new and unexpected impacts of ITD research and practice (Klein, 2006; Mansilla and Gardner, 2003). Transdisciplinary sustainability research and participatory and creative research in environmental and ecological contexts can provide ample insights into how research and collaborative processes can be designed to allow space for serendipity and build agility to navigate uncertainty ultimately presenting unique opportunities to capitalize on latent resources (Otero et al., 2020).
Besides ambiguity and serendipity, experimentation emerges as a fundamental element in AST collaborative contexts. This proposition has two important implications. First, it calls into attention the nature of a collaborative focus of ‘experimenting and exploring’ into alternative possibilities, challenging the status quo and being concerned with questions rather than resolutions (Calvert and Schyfter, 2017; Dieleman, 2017; Vesna et al., 2019). Second, experimentation in AST takes on a different meaning from experimentation in science, which is most widely recognized as the process of testing based on stability and reproducibility. The role and nature of experiments in science are emergent topics of interest in the philosophy of science; however, a systematic analysis of practice, process and methodology is yet to develop (Radder, 2009).
Several limitations should be noted for consideration in future research. The current study did not control for particular modalities of collaboration, aiming instead to be inclusive. This could possibly have an impact on the explained variance, which is currently at 48.5% with the six-factor solution, meaning that, essentially, the results are derived from 25 Q-sorts (25 participants). Further analysis of the interviews reflecting the viewpoints of outlier participants can provide deeper insights. A few participants have noted that it was methodologically challenging while sorting the statements to make judgement calls on quite a few of them in a way to differentiate between what truly described their experience and what they semantically agreed with or what they aspired to. These nuances were balanced out by noting such instances throughout the interviews.
Future research on the topic can investigate several key aspects, focusing on process, policy and organization. In terms of process, AST collaborations are often recognized for their complexity, and much resolution is sought at the level of methodology and tools. Mechanics and methods of equitable participatory design remain a challenge. Collaborations involving scientific and non-scientific communities in addition to disciplinary divides often lead to conflicts, inertia and compromised outcomes (Musch and Von Streit, 2020; Newig et al., 2019). Our research has shed some light on the significance of cultural shifts, on ambitions to influence how modern knowledge is created (Narrative 3), and in what ways art-making can potentially intervene for alternative meaning-making and critical approaches to science and technology (Narrative 4). However, further research can investigate conditions contributing to dialogues across, and deliberate designs for bridging, diverse epistemic cultures.
As for policy, the current research has identified several unique characteristics of AST collaborations. Narratives 1 and 2 establish the significance of experimentation and situated, embodied knowledge practices as dominant narratives in terms of their contribution to the explained variance. These two narratives amplify the shift towards more-than-solutions in AST collaborations. The integration of arts invites the challenge of moving away from ‘certainty’ to situated knowledge and meaning-making in ‘uncertainty’, where experimentation assumes new connotations. Future research can support policymaking, which equally needs to shift its orientation from incentivizing ‘projects’ to incentivizing ‘experiments’.
Regarding organization, Narrative 5 unveiled the interesting tension between deliberate designs for mediation and facilitation to bridge diverse disciplines and organically forming and functioning collaborations evolving through long-term, open-ended assemblages. While there are some indications in Narrative 5 that there are several influencing factors in the design and organization of AST collaborations (such as duration, size of teams, interacting disciplines and the nature of collaboration), future research can explore these conditions in more detail to explain the relative influence of process design versus complementarity in team formations (for example, matchmaking) in devising mutually beneficial collaborations in AST. Policy could also support organization-level experiments to build creative ITD structures and arts-based initiatives, with a mission to develop deliberate methodological designs (through interactions, communication, orientation, upskilling, knowledge and data sharing, and performative actions) that can explicitly contribute to transformation at the organizational and individual levels. Such structures should reconstruct the balance between resource allocation, asymmetries of decision-making and knowledge hierarchies (Schnugg and Song, 2020; Wernli and Ohlmeyer, 2023). Examples, among many, can be the Founding Lab, and artist or creative research residencies in labs such as CERN Arts. Lastly, AST practice can benefit from dedicated research agendas focusing on evaluation, impact, models and methodologies for AST collaborations.
This study aims to offer a social ecological understanding and resulting concept-mapping illustrating how collaborations among art, science and technology form and function. Such mapping can ultimately inform structure, method and design considerations for creative collaborations by shedding light on the ‘doing’ of collaboration at the intersection of art, science and technology. Ultimately, we intend to open a space for deeper discussions in which the alternative knowledge cultures on the ridges of disciplines evolve as pathways to ‘meet the universe halfway’ (Barad, 2007: 39).
Footnotes
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Notes
Author biographies
Zeynep Birsel is a PhD Candidate at the Erasmus School of History, Culture and Communication (ESHCC), Erasmus University. Her research focuses on inter/transdisciplinary collaborations in cultural and creative industries. She investigates boundary crossing works and co-working practices involving art, science and technology.
Ellen Loots is an assistant professor at ESHCC, Erasmus University. She is specialized in arts management, cultural organizations and creative entrepreneurship, and has a special interest in the motivations and behaviours of individuals and organizations in the cultural and creative industries. Social challenges such as justice, community and sustainability influence many of her choices in research and teaching.
Leniá Marques is an assistant professor at ESHCC, Erasmus University. Her research focuses on the development of cultural and creative industries and their relationships with other fields, such as tourism and events. Her interest is particularly in cities and the development of cultural and creative policies, and the relationship of creativity and urban processes.