1.3 Storytelling can convey compelling scenario worlds
Scenarios of the future vary widely in terms of approach, style, and depth of detail (Kishita et al., 2016), yet often only describe a possible future world, based on projections and interpretations of large amounts of data. While descriptive scenarios can be creative, these approaches often fail to inspire action, engage the public, or interest policymakers (Milkoreit, 2017). Story-based scenarios with characters and plot development have emerged as successful vehicles for impactful sustainability scenarios (Calvert, 2019; Johnson & Winkelman, 2017; Merrie et al., 2018; Spijkers et al., 2021). Story-based methods can be understood as narrative, fictional depictions of future worlds.Storytelling methods are meaningfully different from narrative approaches, since they represent a deeper exploration of future worlds (Carbonell et al., 2017), and they allow participants to explore how their daily lives, values, and habits can be mapped onto different contexts (Raven & Elahi, 2015).
The purpose of the present work is to demonstrate how a latent Dirichlet allocation (LDA) analysis may input directly into a creative, structured futuring process (Fig 1). We define structured futuring as asystematic, multi-step approach for creatively developing a story setting, set of characters, and plot that interrogates a particular topic or set of topics. We are explicitly not aiming to provide a definitive new set of comprehensive scenarios, especially given the absence of participation with Indigenous and local communities in the Arctic. On the contrary, we are piloting this approach in the Arctic region both because of the extensive, existing scenario work available for comparison, as well as the diversity of challenges that are being faced by Arctic societies (Akiwenzie-Damm et al., 2019).
However, this does not mean that we ignore the context or the place where the text data originated. While our project is not participatory, we have endeavored to situate each story thoughtfully and critically in a specific future context, by telling multiple stories that reflect the diversity of the Arctic population, including ethnicities, gender identities, ages, and Indigeneity. Moreover, we aim to provide a “multiplicity of voices” through the eventual stories that are told (D’ignazio and Klein, 2020), while acknowledging the partiality of the perspectives that we can bring to bear given the limits that our perspectives permit (Weinberger, 2009). Finally, our scenarios aim to engage the humanities via the transformation of a computational text analysis into stories (and later artwork) that embrace open-interpretation, ambiguity and complexity (Drucker, 2011). We reflect more on the future of these methods in the Discussion section.