Abstract Previous studies have primarily focused on artificial intelligence (AI) discourse within specific language media, with limited contrastive analyses across different cultural contexts. This study analyzes the representation of AI in German and Chinese media discourses from 2018 to 2023, employing a modified version of Ruth Wodak’s discourse analysis framework alongside advanced machine learning methods. Our findings indicate that both German and Chinese media concentrate on AI issues pertinent to their regions. Chinese media adopt a perspective strategy by frequently quoting political figures, particularly President Xi Jinping, and consistently maintain a positive stance on AI. Conversely, German media, especially after the launch of ChatGPT, highlight high-tech figures and adopt a more critical and cautious approach toward AI. These differences in media discourses arise from distinct media cultural systems shaped by their respective contexts. In China, media outlets are party-affiliated and promote a narrative framing AI as a national strategic endeavor crucial for economic growth, reflecting governmental viewpoints. In contrast, media from Germany, Austria, and Switzerland present diverse perspectives on AI, expressing significant concerns about its potential risks. This study offers valuable insights for interpreting and formulating AI policies across different nations.
We mathematically prove that chemical reaction networks without hidden layers can solve tasks for which spiking neural networks require hidden layers. Our proof uses the deterministic mass-action kinetics formulation of chemical reaction networks. Specifically, we prove that a certain reaction network without hidden layers can learn a classification task previously proved to be achievable by a spiking neural network with hidden layers. We provide analytical regret bounds for the global behavior of the network and analyze its asymptotic behavior and Vapnik-Chervonenkis dimension. In a numerical experiment, we confirm the learning capacity of the proposed chemical reaction network for classifying handwritten digits in pixel images, and we show that it solves the task more accurately and efficiently than a spiking neural network with hidden layers. This provides a motivation for machine learning in chemical computers and a mathematical explanation for how biological cells might exhibit more efficient learning behavior within biochemical reaction networks than neuronal networks.
Surya Aymanda Nababan, Aditya Darma, Muhammad Ricky Hardiyansyah
This study aims to examine the use of historical sites in the city of Medan as a source of learning local history for students of the History Education Study Program, the Islamic University of North Sumatra (UISU). The research uses a descriptive qualitative approach with the type of field research. The research subjects consist of students and lecturers teaching local history courses. Data collection was carried out through observation, in-depth interviews, and documentation. The data was analyzed using an interactive model that included data reduction, data presentation, and conclusion drawn, and was tested for validity through triangulation of sources and techniques. The results of the study show that the use of historical sites in the city of Medan in learning local history has been carried out, but it has not been systematically integrated in lecture planning. Sites such as Maimun Palace, Al-Mashun Grand Mosque, Tjong A Fie Mansion, and the Kesawan area are used as contextual learning resources that can increase students' interest in learning, active engagement, and understanding of local history. Historical site-based learning also has a positive impact on the development of students' historical thinking skills and fosters awareness of the importance of preserving local cultural heritage. However, this study found several obstacles, including limited lecture time, the lack of optimal integration of field activities in the Semester Learning Plan, and the lack of academic guidance for historical site-based learning. This study recommends the need to develop an integrated and sustainable historical site-based local history learning model to improve the quality of history learning in higher education.
Abstract Recently there has been a call to deploy AI technologies in secondary education. An accompanying worry is that if students became overly reliant on LLMs, they would become cognitively deskilled - and this would be an impediment to the growth of their cognitive character. One pedagogical approach aiming to offset this worry consists of teaching students how to critically evaluate the outputs of LLMs while they are using them – the Use-First Critical Thinking approach (UFCT). We argue that UFCT alone cannot assuage this worry insofar as it misses an important, prior step in equipping students with the skills to be aware of, and reflect upon, by what lights decisions whether to delegate tasks to LLMs are appropriate. We propose an alternative pedagogical approach involving film, specifically Memento , which allows students to identify delegative choice points and what (in)appropriate delegation looks like.
Abstract This study investigates expert figures’ roles in alien-related UFO conspiracy theories, focusing on their impact on public perception through social media analysis. Utilizing a blend of content and trend analysis, we examine the invocation of scientific authority in UFO conspiracy narratives, identifying a reliance on expert endorsement to legitimize claims about extraterrestrial activity and government secrecy. Findings highlight a common use of expert figures, often without empirical backing, to bolster conspiracy theories.The research reveals the challenge of distinguishing credible information from conspiracy in a landscape where expert authority is easily co-opted. This underscores the importance of scientific literacy and critical thinking in combating disinformation. The study’s implications extend to educational and policy measures aimed at fostering a skeptical and informed public debate on controversial topics. By exploring the dynamics between authority, belief, and disinformation, this work contributes to understanding the mechanisms behind the spread of conspiracy theories and the complex role of expertise in shaping public discourse in the digital age.
History of scholarship and learning. The humanities, Social Sciences
In an era of rapid technological progress that promises to reshape the relationship between workers and machines in unprecedented ways, an oft-invoked claim concerns the potential of automation to “free” the human body, predicting a decline in the role of embodied know-how. To counterbalance the lack of empirical analysis underlying such assumptions, our qualitative study surveys two automated work environments to explore how automation renders specific modes of bodily engagement irreducible: the emerging case of automated driving and the case of skilled cork workers. Drawing on a theoretical and empirical stance anchored in the field study tradition of work psychology and activity ergonomics, Study 1 reveals that automated vehicles are designed around a discreet bodily presence, though a vigilant body and ready to intervene, and thus irreplaceable in dealing with dysfunctions of automatisms. In turn, Study 2 illustrates how automated cork processing calls for a specific bodily intelligence that defies artificial compartmentalisation: a sensorial, subjective, cognitive, and social presence. Taken together, these findings support a critical reassessment of the Cartesian associations of duality and the promise that automation physically “relieves” workers. Building on a non-dualist ontology of the body and its work environment, we discuss how the role and relevance of bodily engagement are today reconfigured by emerging technologies, remaining vital in increasingly automated settings. Our research also contributes to practice and intervention by providing situated implications for occupational health and safety, skills preservation and development, and professional identity, with the aim of fostering collaborative and sustainable human-technology configurations.
History of scholarship and learning. The humanities, Social sciences (General)
Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data remains on the device. However, since all data is collected by clients, federated learning is susceptible to latent noise in local datasets. Factors such as limited measurement capabilities or human errors may introduce inaccuracies in client data. To address this challenge, we propose the use of a stochastic neural network as the local model within the federated learning framework. Stochastic neural networks not only facilitate the estimation of the true underlying states of the data but also enable the quantification of latent noise. We refer to our federated learning approach, which incorporates stochastic neural networks as local models, as Federated stochastic neural networks. We will present numerical experiments demonstrating the performance and effectiveness of our method, particularly in handling non-independent and identically distributed data.
Premiered at the 2024 Adelaide Festival, Is This the Gate? is an opera excerpt composed by Nicholas Lens and set to a libretto written by J. M. Coetzee. It is adapted from the last section of Coetzee’s novel Elizabeth Costello (2003), revolving around the eponymous character’s trial before the gate in the afterworld. This article explores the literary, musical and dramaturgical elements of Is This the Gate? and contends that the adaptation, despite its brevity and incompleteness, indexes and reworks some of the most important intertexts, localities and motifs that connect Coetzee’s early and late works. Allusions to Kafka and Dante frame the scenario for Costello in limbo—a state mirroring a writer’s late-in-life predicament—while references to Australia’s weather and fauna reflect Coetzee’s relationship to his South African roots and adopted home. Further, Costello’s conviction that she is “a secretary of the invisible” holds clues to Coetzee’s deployment of voices and fictional personae since his debut, Dusklands (1974). The last few acts of the opera excerpt evoke themes of desire and mortality that chime with Coetzee’s other Costello narratives, including his latest collection, The Pole and Other Stories (2023). The adaptation ends with Costello’s declaration of her subjectivity, which suggests a writer’s yearning and resolution to go beyond the threshold of life and death.
Abstract This study aims to comprehensively review scientific journal articles related to the adjustment of international employees within the management and business domain from 1990 to 2022. The study seeks to identify trends and patterns in research topics and to propose a future research agenda. To achieve this, we analysed 222 articles from the Web of Science Core Collection database through two main steps: (1) a bibliometric analysis to track the field’s evolution over time and (2) a content analysis of abstracts to examine covered topics and pinpoint research gaps. Our findings indicate that the theory surrounding the adjustment of international employees is still in the process of maturation, with several potential areas for future research emerging. The analysis reveals that factors influencing adjustment are the most extensively researched for assigned expatriates, leaving other international employees relatively under-researched. Moreover, quantitative research emerged as the most prevalent methodological approach among the included studies. Most study samples predominantly consisted of individuals moving between Asia, Europe, and North America, underscoring the significance of Africa—characterised by substantial migration flows within the region—as a focal point for future adjustment research. Moreover, individual-, organisation-, and country-related antecedents of international employees’ anticipatory and in-country adjustments were analysed to present conclusions for future research. This study supplements the domains of international human resource management and international business by identifying research priorities concerning the adjustment of international employees and outlining an agenda for further research.
History of scholarship and learning. The humanities, Social Sciences
Este artículo reflexiona los signos más importantes erigidos alrededor de la clase media por el cine mexicano de la Época de Oro, esto es, la producción cinematográfica de finales de la década de los treinta y los primeros años de los cincuenta del siglo XX. Durante este periodo correspondió también un impulso muy importante a la industrialización y urbanización nacional desde el grupo en el poder, que conllevó la consolidación y expansión de la clase media mexicana. Derivado de esto, este estrato social experimentó contradicciones alrededor de su identidad, debatiéndose entre elementos como el amor, el dinero o la familia. El cine participó dentro de este proceso, discutiendo los mecanismos de ascenso social, reproduciendo y nutriendo prácticas, dando pie a otras, y constituyendo un delicado discurso que encarnó las tensiones, miedos y sueños de esta clase social. Todo ello a través de mecanismos de mediación tejidos entre el espacio histórico y fílmico, que pueden ser un vehículo historiográfico valioso para comprender la complejidad de la yuxtaposición que se vivía durante el periodo entre el México tradicional y el moderno.
History of scholarship and learning. The humanities, History (General) and history of Europe
Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann
et al.
Ecological rationality refers to the notion that humans are rational agents adapted to their environment. However, testing this theory remains challenging due to two reasons: the difficulty in defining what tasks are ecologically valid and building rational models for these tasks. In this work, we demonstrate that large language models can generate cognitive tasks, specifically category learning tasks, that match the statistics of real-world tasks, thereby addressing the first challenge. We tackle the second challenge by deriving rational agents adapted to these tasks using the framework of meta-learning, leading to a class of models called ecologically rational meta-learned inference (ERMI). ERMI quantitatively explains human data better than seven other cognitive models in two different experiments. It additionally matches human behavior on a qualitative level: (1) it finds the same tasks difficult that humans find difficult, (2) it becomes more reliant on an exemplar-based strategy for assigning categories with learning, and (3) it generalizes to unseen stimuli in a human-like way. Furthermore, we show that ERMI's ecologically valid priors allow it to achieve state-of-the-art performance on the OpenML-CC18 classification benchmark.
We study the data-generating mechanism for reconstructive SSL to shed light on its effectiveness. With an infinite amount of labeled samples, we provide a sufficient and necessary condition for perfect linear approximation. The condition reveals a full-rank component that preserves the label classes of Y, along with a redundant component. Motivated by the condition, we propose to approximate the redundant component by a low-rank factorization and measure the approximation quality by introducing a new quantity $ε_s$, parameterized by the rank of factorization s. We incorporate $ε_s$ into the excess risk analysis under both linear regression and ridge regression settings, where the latter regularization approach is to handle scenarios when the dimension of the learned features is much larger than the number of labeled samples n for downstream tasks. We design three stylized experiments to compare SSL with supervised learning under different settings to support our theoretical findings.
El siguiente trabajo plantea como objetivo una indagación preliminar de las ideas de Giddens en torno a lo social, expresado en términos de modernidad, confianza básica, sistemas expertos y políticas de riesgo, recorriendo metodológicamente sus principales textos, contrastados a su vez con otros (desde otras disciplinas) que permiten una nueva aproximación a los mismos. Giddens señala el lugar de la reflexividad y los sistemas expertos como estructuras que integran el mundo, lo social, las experiencias cotidianas y la constitución del yo y en esa versión de lo social que se denomina modernidad. Todos estos factores se aúnan en el riesgo y la oportunidad, pero enmarcados en el logro de un sentimiento de identidad a la que se siente como propia y auténtica. A partir de estas cuestiones, el presente artículo tiene por objetivo intentar profundizar sobre qué se entiende por lo social y especialmente, que grado de confiabilidad puede merecer el mismo, desde la perspectiva de Giddens, pero integrando a su vez otras perspectivas culturas, sociales y psicoanalíticas, para intentar situar las implicaciones epistemológicas en juego, señalando sus alcances y limitaciones. Como resultados se indica que es posible percibir una cierta concepción de la trama social en términos de integración y previsibilidad, pero siempre de acuerdo a un contexto social específico. De esta manera, las ideas sociales de Giddens son criticables, pero no dejan de ser atendibles en tanto su análisis sociológico no elude perplejidades, confusiones y dificultades, que indican un social que escapa a dimensiones racionales, funcionalistas y hasta estructuralistas.
History of scholarship and learning. The humanities, Social sciences (General)
Postmodern ve neoliberal anlayışlar moderniteye karşı açtıkları savaş sonucunda çoğulculuk ve görelilik iddiaları eşliğinde modernitenin uzun süre bastırmış olduğu mistik ve mitik algılama biçimlerinin geriye dönüşünü sağlamışlardır. 21. Yüzyılla birlikte neoliberal politikaların yarattığı hoşnutsuzluklar ve bu politikaları sürdüren küresel elitlere karşı artan tepkinin ise yeni sağ popülist hareketlerin yükselişlini beraberinde getirmiştir. Ancak, postmodern ve neoliberal hareketlerle yeni sağ popülist hareketler arasında, akıl ve modernite karşıtlığı bağlamında, bir karşıtlıktan çok bir devamlılık söz konusudur. Bu bağlamda neoliberal ve postmodern yaklaşımlar ve onlara tepki olarak ortaya çıkan yeni sağ popülist hareketler birbirinin devamı niteliğindedir. Postmodern ve neoliberal yaklaşımların eleştirel aklı tasfiye etme girişimi ve liderlik öğretileri yeni sağ popülist hareketler tarafından bir başka aşamaya taşınmıştır ve etno-dinsel hareketler 21. Yüzyıla damga vuran en önemli gelişmelerden biri olmuştur. Bu makale akıl karşıtlığının kökenlerini incelerken akıl karşıtlığının kuralsız/keyfi yönetimlere ve temel insan haklarının ihlaline yol açtığını göstermekte ve barış içinde birlikte yaşamak için akıldan vazgeçmek yerine aklı çoğaltmak gerektiğini öne sürmektedir.
History of scholarship and learning. The humanities
In the ethnographic introduction of the Primary Chronicle, the Slavic tribes living around the Polans are compared to forest animals, which is often regarded by researchers as a vivid example of the construction of a “foe” image and a clear evidence of the blatant ethnocentrism of the Kievan author. This is in stark contrast to the author’s general Slavic patriotism. According to the traditional interpretation of the Book of Hosea in Old Rus’, however, the Jews of the Old Testament were in league with animals as the prophecy that the pagan peoples would be baptized. The overlaps in the texts of the Primary Chronicle and other written sources following the above tradition suggest that the long-established idea, supported by many historiographers, about the unambiguously negative and pejorative juxtaposition of the Slavic tribes with the Polans should be revised. The fragment about the customs of different peoples found in the Primary Chronicle only emphasizes the special role played by the ancestors of the Kievans in the spread of Christianity in the surrounding territories. Furthermore, it was believed that the tribes that would adopt the new faith were not only savage pagans, but also those chosen for salvation.
History of scholarship and learning. The humanities
Consistency regularization on label predictions becomes a fundamental technique in semi-supervised learning, but it still requires a large number of training iterations for high performance. In this study, we analyze that the consistency regularization restricts the propagation of labeling information due to the exclusion of samples with unconfident pseudo-labels in the model updates. Then, we propose contrastive regularization to improve both efficiency and accuracy of the consistency regularization by well-clustered features of unlabeled data. In specific, after strongly augmented samples are assigned to clusters by their pseudo-labels, our contrastive regularization updates the model so that the features with confident pseudo-labels aggregate the features in the same cluster, while pushing away features in different clusters. As a result, the information of confident pseudo-labels can be effectively propagated into more unlabeled samples during training by the well-clustered features. On benchmarks of semi-supervised learning tasks, our contrastive regularization improves the previous consistency-based methods and achieves state-of-the-art results, especially with fewer training iterations. Our method also shows robust performance on open-set semi-supervised learning where unlabeled data includes out-of-distribution samples.
End-to-end learning for visual robotic manipulation is known to suffer from sample inefficiency, requiring large numbers of demonstrations. The spatial roto-translation equivariance, or the SE(3)-equivariance can be exploited to improve the sample efficiency for learning robotic manipulation. In this paper, we present SE(3)-equivariant models for visual robotic manipulation from point clouds that can be trained fully end-to-end. By utilizing the representation theory of the Lie group, we construct novel SE(3)-equivariant energy-based models that allow highly sample efficient end-to-end learning. We show that our models can learn from scratch without prior knowledge and yet are highly sample efficient (5~10 demonstrations are enough). Furthermore, we show that our models can generalize to tasks with (i) previously unseen target object poses, (ii) previously unseen target object instances of the category, and (iii) previously unseen visual distractors. We experiment with 6-DoF robotic manipulation tasks to validate our models' sample efficiency and generalizability. Codes are available at: https://github.com/tomato1mule/edf
Harshit Sikchi, Akanksha Saran, Wonjoon Goo
et al.
We propose a new framework for imitation learning -- treating imitation as a two-player ranking-based game between a policy and a reward. In this game, the reward agent learns to satisfy pairwise performance rankings between behaviors, while the policy agent learns to maximize this reward. In imitation learning, near-optimal expert data can be difficult to obtain, and even in the limit of infinite data cannot imply a total ordering over trajectories as preferences can. On the other hand, learning from preferences alone is challenging as a large number of preferences are required to infer a high-dimensional reward function, though preference data is typically much easier to collect than expert demonstrations. The classical inverse reinforcement learning (IRL) formulation learns from expert demonstrations but provides no mechanism to incorporate learning from offline preferences and vice versa. We instantiate the proposed ranking-game framework with a novel ranking loss giving an algorithm that can simultaneously learn from expert demonstrations and preferences, gaining the advantages of both modalities. Our experiments show that the proposed method achieves state-of-the-art sample efficiency and can solve previously unsolvable tasks in the Learning from Observation (LfO) setting. Project video and code can be found at https://hari-sikchi.github.io/rank-game/
This study aims to determine the perception of historical education students at Syiah Kuala University (USK) towards online learning in terms of several indicators, namely learning materials and evaluation questions, community, online lecturers, collaboration opportunities, and multimedia. The approach used in this research is a qualitative approach with the type of phenomenological research. The subjects of this research were USK history education students batch 2018. Data collection was carried out by interview. Data analysis techniques with data reduction, data presentation, and drawing conclusions. The results showed that the materials and evaluation questions were available and could be downloaded by students. Have a community to learn and discuss together. Students are more inclined to video conference-based media in the implementation of online learning, namely Google Meet with Google Classroom as a forum for collecting assignments. The use of media has not been maximized.
This study aims to find out how the application and response of class XI IPS 1 students in the application of problem solving learning models assisted by roulette media in history learning at SMA Negeri 1 Kuta Cot Glie, Aceh Besar District. This research uses a qualitative approach with descriptive research type and the sampling purposive sampling. The subjects in this study were students of class XI IPS 1, totaling 24 students. Based on the results of the research, it is known that (1) The application of the problem solving learning model assisted by roulette media in history learning in class XI IPS 1 has been carried out well according to the problem solving syntax. This can be seen from the results of the analysis of the application of the learning model, an average score of 78,3% is included in the good criteria and the results of the learning mastery analysis show that 21 people scored above the minimum criteria of mastery learning or equivalent to 87,5%, while 3 people scored below the minimum criteria of mastery learning or equivalent to 12,5%. (2) The response of class XI IPS 1 students in the application of learning with problem solving models assisted by roulette media is good. This can be seen from the activities and behavior of students shown in learning activities, students listen and follow the teacher’s directions in accordance with the learning syntax. Students solve the problems given by the teacher carefully and keep the class organized.