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We Are at an Extreme Point Where We Have to Go All in on What We Really Believe Education Should Be About
Get PDFIn this interview, Juliane Jarke and Teresa Cerratto Pargman discuss the implications of AI for the postdigital future(s) of education with Dan McQuillan. They start off with an introduction to the main ideas of Dan’s recent book (McQuillan 2022) and ask why we need to resist AI in education. Dan argues that the answer to the question is partly based on our understanding of education, what it means to us and how we imagine its future. He points to the harmful effects of AI and the narratives that perpetuate and boost its use in education and beyond. In the last part of the interview, Dan considers ways of resisting AI in education and sketches alternative educational futures. The interview took place end of March 2023 through an online video conference system and was subsequently transcribed and edited
A Just Transition Means Resisting AI
No full textThere can be no just transition without challenging the AI apparatus that is accelerating the social and environmental crisis, writes Dan McQuillan for The Scottish Left Review
Performative Experiments
No full textThe relationship of sociology to experiments is torn: For both quantitative and qualitatitve sociologists, experiments are the other, the unachievable or problematic descendent of the natural sciences: Unachievable, because proper experiments depend on a level of artificiality that for sociologists makes the results unusable and problematic, because they are the opposite of the naturalistic logic that qualitative sociology loves. But there is a different way to think about experiments. We can think of experiments as generative, as speculative as a way of creating and inventing new social worlds. Instead of denouncing their artificiality, we can take social research more seriously as a mode in which the social is made. Once we have accepted this, we can begin to embrace experiments as formats that do not only produce data about the social world, but in which the social world is reordered in surprising ways. Such a form of experimentation is also an appropriate form of critique for a time when critique as the domain of the academic who can see behind the veil of ideology has vanished. The article will demonstrate these experimental logics by discussing two research projects, one about disaster scenarios and the second about cooking and taste
Framework for Personalized Chronic Pain Management: Harnessing AI and Personality Insights for Effective Care
Get PDFThis paper introduces a cutting-edge framework for personalized chronic pain management, leveraging the power of artificial intelligence (AI) and personality insights. It explores the intricate relationship between personality traits and pain perception, expression, and management, identifying key correlations that
influence an individual's experience of pain. By integrating personality psychology with AI-driven personality assessment, this framework offers a novel approach to tailoring chronic pain management strategies for each patient's unique personality profile. It highlights the relevance of well-established personality theories such as the Big Five and the Myers-Briggs Type Indicator (MBTI) in shaping personalized pain management plans. Additionally, the paper introduces multimodal AI-driven personality assessment, emphasizing the ethical considerations and data collection processes necessary for its implementation. Through illustrative case studies, the paper exemplifies how this framework can lead to more effective and patient-centered pain relief, ultimately
enhancing overall well-being. In conclusion, the paper positions the need of an "AI-Powered Holistic Pain Management Initiative" which has the potential to transform chronic pain management by providing personalized, data-driven solutions and create a multifaceted research impact influencing clinical practice,
patient outcomes, healthcare policy, and the broader scientific community's understanding of personalized medicine and AI-driven interventio
Živná půda ekofeminismu [Cultivating Ecofeminisms]
No full textThe talk „Živná půda ekofeminismu“ [Cultivating Ecofeminisms] is a part of a public programe series accompanying exhibition 'Pěstovat plevel, sklízet vichřici' at the Hraničář Gallery, Czech Republic (5/10/2023-09/02/2024). The talk focuses on the contribution of ecofeminism to ecological approaches in contemporary art, theory and activism. The talk draws from symposium 'Gardening Ecofeminisms' curated by Lenka Vráblíková in collaboration with Kateřina Vídenová, Amálie Bulandrová and others from the Center for Art and Ecology UMPRUM at Kafkárna in October 2023
TLP-NEGCN: Temporal Link Prediction via Network Embedding and Graph Convolutional Networks
Get PDFTemporal link prediction (TLP) is a prominent problem in network analysis that focuses on predicting the existence of future connections or relationships between entities in a dynamic network over time. The predictive capabilities of existing models of TLP are often constrained due to their difficulty in adapting to the changes in dynamic network structures over time. In this article, an improved TLP model, denoted as TLP-NEGCN, is introduced by leveraging network embedding, graph convolutional networks (GCNs), and bidirectional long short-term memory (BiLSTM). This integration provides a robust model of TLP that leverages historical network structures and captures temporal dynamics leading to improved performances. We employ graph embedding with self-clustering (GEMSEC) to create lower dimensional vector representations for all nodes of the network at the initial timestamps. The node embeddings are fed into an iterative training process using GCNs across timestamps in the dataset. This process enhances the node embeddings by capturing the network’s temporal dynamics and integrating neighborhood information. We obtain edge embeddings by concatenating the node embeddings of the end nodes of each edge, encapsulating the information about the relationships between nodes in the network. Subsequently, these edge embeddings are processed through a BiLSTM architecture to forecast upcoming links in the network. The performance of the proposed model is compared against several baselines and contemporary TLP models on various real-life temporal datasets. The obtained results based on various evaluation metrics demonstrate the superiority of the proposed work
English Language Hegemonies in the Internationalization of Two State Universities in Brazil: Unintended Consequences of English Medium Instruction
Get PDFA larger qualitative study, which we draw upon here, investigated the perceptions of academics and students, in two state funded universities, regarding internationalization and the use of English as a medium of instruction (EMI). In this article, we focus on their concerns about EMI policy, drawing on interviews and focus groups. The range of concerns that were identified during this study were: the negative impact on content learning, language hierarchization, the emotional impact (confidence in using English), low student enrolment, exclusion, (re) production of inequality, impact on identity and collegiality. Taking account of these findings, we argue that it is important for language policymakers in both institutions to consider the concerns of academics and students as part of their planning process, and to address them responsibly