Advancement Analysis
Advancing Global Citizenship Education through AI: Balancing Neoliberal, Liberal, and Critical Approaches in Knowledge-Based Economies
Paper Presentation in a Themed Session
Nancy Xu,
Yihang Li
Global Citizenship Education (GCE) is crucial for addressing global challenges like inequality, poverty, and social violence. In a rapidly advancing technological society, knowledge-based economies (KBEs) require individuals to possess new skills to thrive. This study explores how to prepare students as global citizens with the skills needed for the digitalized world, particularly in KBEs. It highlights the importance of transforming education to prioritize diversity, equity, and inclusion (DEI) through personalized learning models enabled by artificial intelligence (AI). While existing research has explored AI's role in supporting GCE, there is limited analysis of various organizations—public, private, and nonprofit—implementing AI in GCE. This study examines how these organizations apply AI to support personalized learning and GCE, identifying their practices within neoliberal, liberal, and critical educational frameworks. Using typologies that categorize AI-driven education initiatives as industry-driven, social-driven, and mixed industry-social-driven, the study analyzes different approaches to GCE. Findings suggest that neoliberal AI education emphasizes standardized, market-oriented outcomes, potentially perpetuating disparities. In contrast, critical GCE, driven by social initiatives, focuses on ethical practices that promote DEI and empower marginalized communities. A mixed liberal approach balances economic goals with humanitarian values, fostering both human capital and educational equity. This study underscores the potential of mixed industry-social-driven AI in education to enhance personalized and equitable learning, address global challenges, and promote ethical AI use. It provides insights for educators, policymakers, and technology developers on fostering GCE in a knowledge-based economy, emphasizing the need for a more inclusive and globally sensitive approach to AI-driven education.
What is the Flip Side of This Coin?: The Impact of Automation Risk at Work on Health Outcomes in Germany
Paper Presentation in a Themed Session
Mariia Vasiakina
Automation transforms work at a rapid pace, with gradually increasing shares of the workforce being at risk of replacement by machines. However, little is known about how this risk is affecting workers. In this study, we investigate the impact of high risk of automation at work on subjective (self-reported health, anxiety, and health satisfaction) and objective (healthcare use and sickness absence) health outcomes of workers in Germany. We build our analysis on the survey data from the German Socio-Economic Panel (SOEP) and administrative data from the Occupational Panel for Germany (2013-2018). Employing panel regression, we demonstrate that exposure to high risk of automation at the occupational level worsens self-reported health and health satisfaction of workers and increases their sickness absence and, depending on how the risk is measured, anxiety. No effect is found on healthcare use. We also conduct several robustness checks with results remaining mostly consistent with our main findings, while uncovering some heterogeneity in effects among the analyzed groups.
Advancing Architectural Design Research Methods through AI Visualization Tools
Paper Presentation in a Themed Session
Yong Huang
Traditional architectural design research is predominantly based on images and drawings of precedents from built projects or speculative theoretical models, in a process of critical analyses or points of departure for design iterations. Emerging AI visualization tools enable users to generate visual concepts and models that are derived from ever-evolving web data beyond pre-conceived and pre-categorized sources. This research project experiments AI tools in visualization that can negotiate the established boundaries of theoretical and practical design concepts in both literal and metaphorical dimensions. In "The Datafied Society: Studying Culture Through Data", a ‘query design strategy’ has become more user-defined. A query normally begins with keywords which posit certain sets of notions, hints, or clues that enable researchers to find a cipher or code. A topic of architectural research can be further interpreted or defined as a sequence or a set of keywords. Through the inductive method of trials-and-errors, these AI visualization tools are capable to translate meanings and ideas into images, therefore, a wide range of images generated by AI can be selected to serve as visual interpretations and inspirations for architects and designers. As images and the meanings of images are also contextual, and the context and constraint of each research topic exercises can be systematically defined, which allow the outcomes to be compared and analyzed. Fundamentally, architectural design-based research is interpretive and creative. Humanistic AI visualization tools can generate both analogous and metaphoric images, which can be developed with great potentials in advancing architectural research methodology.
The Brazen Head of Vector Analysis: Robert Grosseteste and Albertus Magnus as Technological Forrunners
Paper Presentation in a Themed Session
Seth Strickland
Generative Artificial Intelligence (GAI) is so often presented as something new -- what can ancient texts teach us about it? In John Gower's "Confessio Amantis", the real-life medieval scientist Robert Grosseteste is said to have built a head of bronze that said "such things as they happened." This head is one of many such attributions to medieval scientists -- many working on the edge of scientific innovation in the 10th through 12th centuries were rumored to have automaton helpers who spoke truth, answered questions, or aided in experiments. These technologies, although imaginary, served the same cultural function that GAI does for modern writers and thinkers. This paper compares medieval philosophies of these technologies with current suspicion and enthusiasm for GAI. The comparison, made through medieval literary and philosophical texts, demonstrates that medieval attitudes toward these imagined technologies are key to articulating the limitations and expectations of real technological dependence. This argument serves to 'humanize' Artificial Intelligence and articulate the real edges of its philosophical scope. GAI is truly new only in its technological instantiation -- its ethical problems have been discussed for centuries.
