ASU Scholarship Showcase

Much of the richness of human thought is supported by people’s intuitive theories—mental frameworks capturing the perceived structure of the world. But intuitive theories can sometimes contain and reinforce misconceptions, such as misconceptions about vaccine safety that discourage vaccination. We argue that addressing misconceptions requires awareness of the broader conceptual contexts in which they are embedded. Here, we developed a cognitive model of the intuitive theory surrounding vaccination decisions. Using this model, we were able to make accurate predictions about how people’s beliefs would be revised in light of educational interventions, design an effective new intervention encouraging vaccination, and understand how these beliefs were affected by real-world events. This approach provides the foundation for richer understandings of intuitive theories and belief revision more broadly.

As speculative aesthetics, what might feminist ontologies and artist imaginings do for rethinking the "real" assemblages and infrastructures of our quotidian experience, particularly with respect to those that standardize aggressive capital agendas, maximum industrial output and extreme waste? This paper draws connections between female artists' image and event-making, speculative design and tacit knowledge, as sensing tools for technological possibilities at a time when energy dependency, in the form of electricity, is the greatest generator of fossil fuel waste and pollution. I use Remedios Varo's paintings from the mid 1930-1960s as a springboard to think about sustainability and ecological design from an embodied, fem-magic and deep-time perspective, and I draw from other female artists whose work explores technologies and energy, such as Alice Aycock, Tania Candiani, Cassie Meador and Hito Steyerl. An analysis of these artists' works allows me to explore the ways that feminist imaginings function as an ontological orientation that shifts power away from contemporary infrastructures, to decolonize and re-feminize electrical possibilities as alternative ways of engaging with and sensing assemblages.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.