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.