Promoting sustainable mobility requires technological innovation and changes in individual travel behavior. Using the Theory of Planned Behavior, we examined how attitudes, norms, and perceived control shape the willingness to adopt alternatives to car use. We designed 38 future commuting scenarios, each of which isolated a single dimension across three mobility concepts: public transportation, cycling, and shared automated vehicles. In an online survey (N = 168), participants rated their willingness to switch modes and pay more. To deepen our understanding, we conducted follow-up interviews (N = 10), exploring their everyday mobility practices and their likes and dislikes regarding the practicality of the future scenarios. Our findings show that features linked to instrumental attitudes and control beliefs elicit stronger intentions than affective cues, ecological appeals were less persuasive. We argue that effective behavior change depends on linking motivational factors to the realities of everyday mobility contexts.

In today’s workplaces, digital distractions and frequent task-switching significantly impact productivity and well-being. With the integration of AI tools and Large Language Models (LLMs), we face new challenges in managing attention between human cognition and AI-assisted workflows. This workshop will explore the dual nature of AI tools, examining their potential to enhance productivity and mitigate the risks of "metacognitive laziness" and digital distraction. Through collaborative design activities and discussions, participants will examine strategies for developing attention management that support mindful task-switching between human and AI-driven work. We will focus on designing workplaces that leverage AI capabilities while preserving deep work and cognitive well-being. The workshop aims to generate practical insights for creating sustainable work practices in an AI-augmented workplace.