Manh-Tung Ho

Fatima Roumate argues that a “new Westphalian system” is taking shape, one in which AI is no longer simply a tool but a force restructuring the very foundations of international order. And in her book, Roumate offers a map of this AI-driven restructuring, tracing through both conceptual frameworks and technological reality surrounding lethal autonomous weapons (LAWS), psychological security, technological sovereignty, AI diplomacy, ethics and the global economic order. The author puts forth an account that AI is simultaneously transforming the nature of power, the holder of power, and the space of power, processes that classical international relations frameworks lack definitive tools to deal with. This account is, arguably, precisely understood as a pioneering research agenda rather than a fully formed scientific theory. Most emphatically, the author investigates and proposes various emerging roles of organizations such as the United Nations or the World Trade Organization to shape a peaceful world order through updating new international codes of conduct for technological transfer and cooperation. The book concludes with thought-provoking visions around artificial wisdom, i.e., AI guided by humanistic values; inclusive AI global governance; new international social contracts among states, citizens, and transnational big-tech companies. The book is an essential read for scholars and policymakers working to solve emerging challenges regarding human rights, international trade, and economic development in the new techno-geopolitical realities.

Open science adoption among Generation Z students in a developing country, with distinct educational culture, presents a critical test of a wide range of technology acceptance frameworks. This study examines factors predicting open science resource utilization (measured through self-reported frequency of diverse uses in academic contexts) among 1,422 Vietnamese undergraduate students using Bayesian regression analysis, which enables probabilistic inference and robust model comparison, adding to the methodological rigor and novelty to the literature in this area. We tested a theoretical framework integrating a multitude of factors such as capabilities, perceived benefits, institution-centered, value-alignment, etc., through progressive model building. Model comparison via WAIC identified the main effects model as optimal. Results revealed Technical Self-efficacy (β = 0.254) and Open Science Self-efficacy (β = 0.205) as strong predictors, with Institutional Support (β = 0.117) and Attitude (β = 0.119) showing moderate effects. Language Self-efficacy showed a weak but credible effect (β = 0.089). Contrary to Western technology acceptance models, Perceived Benefits showed uncertain influence (β = 0.054, 89% HPDI includes zero), and Value Alignment demonstrated no credible effect (β = 0.013). Hypothesized interaction effects between Technical Self-efficacy and Perceived Benefits were not supported by model comparison, suggesting additive rather than synergistic adoption mechanisms. These findings challenge the digital native assumption and reveal that Vietnamese students adopt open science for practical reasons, relying on skills and institutional support rather than ideology. Interventions in resource-constrained settings should therefore prioritize technical skill development and visible institutional support, rather than relying primarily on value-based or normative appeals. This pragmatic approach has implications for advancing open science in the age of AI.

Recent advances in machine learning and neuroscience, the abundances of sensors and emotion data have endowed machines with ability to detect, classify, and interact with human emotions. This study philosophize about affective computing devices by examining emotional artificial intelligence (AI) through the lens of affective artifacts, focusing on as personal AI assistants, work-related emotion trackers, and emotional AI toys and robots. Drawing from philosophical accounts on affective artifacts and empirical evidence on human-AI interaction, we argue how emotional AI technologies fulfill the criteria of being affective artifacts from the four key properties: underlying algorithmic complexity, artifactual nature, semi-agentive capabilities, and semi-interpersonal interactions. Furthermore, recognizing that the underlying algorithmic complexity renders these technologies easily manipulated for emotion-related tasks, we also analyze how these tools help us regulate emotions and influence self-perception, interconnecting with the maintenance and construction of our sense of self and identity, blurring the lines between the infosphere and lived experience.

The article presents strategic ideas for understanding elements of a human–AI collaborative framework that seeks to enable philosophy researchers to participate more effectively in the global discourse on science and philosophy in the AI age. With its ability to process large amounts of data and recognize complex patterns, current AI systems can extend human epistemological and ontological reach, concurrent with the situated cognition viewpoint. However, AI still lacks the capacity for meta-reflection, embodied meaning-making, and existential engagement—hallmarks of human intelligence and wisdom. Therefore, the human–AI co-creative discovery framework is a partnership of inter-agent creativity between the “agents of meaning” (humans) and the “agents of syntactic manipulation” (AI), generating two-way value in the exploration and communication of knowledge. Indeed, AI can help spark curiosity, foster new intuitions, and revive the tradition of learning through dialogue, a classical philosophical method. Here, we discuss the rise of AI-assisted philosophical counseling and argue that the power of multimodal AI systems can be channeled into producing more precise and creative philosophical dialogues, enriching our humanity. We also discuss several cross-cultural ethical oversights for mitigating the potential downsides of AI-augmented philosophical dialogue.

Starting the book by asking the readers to ponder a thin line between “A green brave world” and “A green panopticon,” Mark Coeckelbergh’s Green Leviathan or the Poetics of Political Liberty explores the paths of political thinking’s evolution in response to current technological and environmental challenges, highlighting the overlooked deep connection between traditional philosophical notions of political freedom and the threats of authoritarianism and hidden manipulation amid our urgent ecological challenges. This review examines how the book offers a philosophical orientation for navigating the delicate balance between security and liberty, proposing a “third way” that promotes a relational, capabilities-focused, and positive understanding of freedom. It advocates for the integration of AI and other technologies into a larger “poetic-political project of liberation and democratization,” seeking to construct new common worlds that support both human and non-human flourishing. This vision emphasizes that freedom should be associated with human dignity and the genuine conditions necessary for prosperity, extending beyond individuals to include non-humans, animals, climate, viruses, and indeed AI. The vision presented in the book contributes to the enriching of our growing understanding of the human–technology–nature nexus, as it bridges political philosophy with environmental ethics and technological ethics through the concept of freedom.

This review article focuses on Matteo Pasquinelli’s recent work, The eye of the master: A social history of Artificial intelligence, which offers a politicized genealogy of AI and highlights the inseparability of AI’s ontology from the social and political conditions that produce its algorithms. Here, we use Hybrid Semantic Formalism, a hybrid language that utilizes generative AI strength of manipulating symbols and tokens, to create a logic map of Pasquinelli's categorization of social algorithm, formal algorithm, and automated algorithm. Crucially, Pasquinelli connects Babbage’s labor theory of automation and principle of labor calculation to Marx’s concept of the general intellect and reveals how various forms of machine intelligence mirrors, embodies, and amplifies the analytical intelligence of collective labour. Pasquinelli traces AI’s history alongside labour analysis, psychometrics, and the drive for a ‘control revolution,’ unpacking technical concepts such as self-organization and cybernetics to show that capitalist technologies are fundamentally sociomorphic and sociogenic: they formalize proven patterns of social cooperation rather than the biomorphic replication of how an individual’s mind performs a given task. This article argues that Pasquinelli’s analysis contributes vital insights into AI’s sociopolitical underpinnings and thus, advocating for democratic technopolitical practices to reshape algorithmic governance. This article concludes with four recommendations from Pasquinelli’s account for the development of Vietnam and the country’s searching for a vision of human-AI coexistence.

This essay reviews _Cultural Analytics_ by Lev Manovich as a foundational text that not only charts the historical and technical emergence of cultural analytics but also provokes a deeper interrogation of how digital and generative AI-driven methods reconfigure the very ontology, cognition, and ethics of cultural inquiry. Cultural analytics combines computer science, data visualization, and media arts to study cultural phenomena at scale; generative AI further extends this paradigm by producing new artifacts that blur boundaries of authorship and challenge traditional categories. This review, following Manovich’s admonition throughout the book, concludes that that meaningful human-AI co-creative cultural studies require both advanced computational methods and philosophically informed safeguards, ensuring that the richness of human experience and the agency of communities remain central.

The article presents strategic ideas for understanding elements of an appropriate human–AI collaboration framework that will enable philosophy researchers to participate more effectively in the global discourse on science and philosophy in the AI age. With its ability to process large amounts of data and recognize complex patterns, current AI systems can extend human epistemological and ontological reach, concurrent with the situated cognition viewpoint. However, AI still lacks the capacity for meta-reflection, embodied meaning-making, and open-endedness hallmarks of human intelligence and wisdom. Therefore, the human–AI co-creative discovery framework is a partnership of inter-agent creativity between the “agents of meaning” (humans) and the “agents of formalism” (AI), generating two-way value in the exploration and communication of knowledge. Indeed, AI can help spark curiosity, foster new intuitions, and revive the tradition of learning through dialogue, a classical philosophical method. Here, we discuss the rise of AI-assisted philosophical counseling and argue that the power of multimodal AI systems can be channeled into producing more precise and creative philosophical dialogues, enriching our humanity.

This essay reviews Cultural Analytics by Lev Manovich as foundational text that not only charts the historical and technical emergence of cultural analytics but also provokes a deeper interrogation of how digital and generative AI-driven methods reconfigure the very ontology, cognition, and ethics of cultural inquiry. Cultural analytics combines computer science, data visualization, and media arts to study cultural phenomena at scale; generative AI further extends this paradigm by producing new artifacts that blur boundaries of authorship and challenge traditional categories. This review, following Manovich’s admonition throughout the book, concludes that that meaningful human-AI co-creative cultural studies require both advanced computational methods and philosophically informed safeguards, ensuring that the richness of human experience and the agency of communities remain central.

The concept of the self has been central to both psychological and philosophical discourse, with recent developments emphasizing the 4E approach—embodied, embedded, enacted, and extended cognition. Peripersonal space (PPS), defined as the immediate space surrounding the body, serves as a critical interface between the individual and the external environment, facilitating action and perception. Despite its significance, the role of PPS in shaping various aspects of the self remains underexplored. This article examines how perception within PPS influences different dimensions of the self. That is to say, it affects the narrative self and bodily self through its impact on autobiographical and procedural memory, respectively. Additionally, PPS perception contributes to the minimal self by influencing the sense of bodily ownership. Moreover, this understanding offers significant implications for technological applications. On the one hand, it reveals methods by which individuals' memories and sense of self can be influenced through the manipulation of peripersonal perception. On the other hand, it underscores the role of technology in prompting a reevaluation of the concept of self.

Các trào lưu như hiện tượng “túi mù”, hầu hết các xu hướng tiêu dùng dựa trên nền tảng và được điều khiển bởi thuật toán, dù thúc đẩy tăng trưởng kinh tế và tạo việc làm, hoàn toàn thiếu tính bền vững—chúng góp phần làm gia tăng đa khủng hoảng hơn là mang lại lợi ích. Những vấn đề này bao gồm: (i) khủng hoảng giá trị; (ii) khủng hoảng sức khỏe tinh thần; (iii) khủng hoảng hệ sinh thái. Giới trẻ có thể dành hàng giờ để xem các influencer trên TikTok và Instagram phản ứng với những gì họ tìm thấy trong túi mù. Giá trị sử dụng thực sự của những sản phẩm ấy là gì? Còn hàng triệu người đang trong độ tuổi hình thành nhân cách—như trẻ em, thanh thiếu niên và người trẻ—đắm chìm trong thói quen xem, lướt và mua sắm không kiểm soát, cuối cùng rơi vào tình trạng “quiet quitting”, tuyệt vọng, suy giảm nhận thức, trầm cảm, thậm chí ý nghĩ tự tử thì sao? Chúng ta có thể làm gì trước lượng rác thải nhựa khổng lồ và lượng khí nhà kính phát sinh từ sản xuất và tiêu thụ trong các ngành công nghiệp văn hóa này? Trong bài viết này, chúng tôi lập luận rằng sức mạnh của AI có thể được khai thác để cung cấp giải pháp cho những vấn đề đó. Trước hết, chúng ta phải nhìn nhận AI như một tác nhân đảm bảo công bằng trong tiếp cận thông tin. Thứ hai, sự lên ngôi của các “nhà khoa học nhân dân” (citizen scientists) AI và quy trình làm việc theo cơ chế tác nhân AI có thể hạ thấp rào cản để thúc đẩy khoa học công dân vì các mục tiêu sinh thái. Cuối cùng, AI có thể được tận dụng để hình thành và thúc đẩy cam kết cộng đồng về trách nhiệm và đạo đức liên ngành trên ba lĩnh vực: con người, môi trường và công nghệ.

Trong kỷ nguyên bùng nổ của trí tuệ nhân tạo (AI), việc hiểu biết đúng và kịp thời về bản chất của AI trở thành yêu cầu cấp thiết đối với cả cá nhân lẫn quốc gia nhằm tận dụng hiệu quả các cơ hội và giải quyết được các thách thức cũng như yêu cầu của thời đại. Trên cơ sở đó, bài viết nghiên cứu khái niệm “vô thức thuật toán” (algorithmic unconscious) như một khái niệm chứa đựng những yếu tố tiềm ẩn trong hệ thống vận hành của AI dưới lăng kính tâm lý học phân tích của Carl Gustav Jung (1875- 1961). Phân tích tập trung vào các cổ mẫu của trường phái Jungian như “Kẻ Tinh Quái” (Trickster) và “Cái Bóng” (Shadow), qua đó làm rõ cách những hình tượng cổ mẫu này được phản ánh trong hoạt động của thuật toán hiện đại. Đồng thời, bài viết cũng phân tích hiện tượng “phóng chiếu” trong mối quan hệ giữa AI và con người thông qua minh họa về việc con người vô thức gán các kỳ vọng hay nỗi sợ hãi của bản thân lên AI. Qua đó, vấn đề “cá nhân hóa giả” (pseudo-individuation), trong đó AI tạo ấn tượng như một chủ thể có nhân cách riêng nhưng thiếu ý thức tự thân và sự thiếu hụt khả năng tự phản tỉnh ở AI được làm rõ. Thông qua những nội dung trên, bài viết đề xuất các định hướng thiết kế giúp cho AI tích hợp yếu tố tự nhận thức và các giá trị nhân bản, nhằm tăng cường tính minh bạch, củng cố niềm tin và phát triển mối quan hệ giữa con người và máy móc vì lợi ích chung của xã hội.

This study investigates the determinants of utilizing open science practice among researchers through structural equation modeling analysis. Drawing on responses from 1,002 Vietnamese students across disciplines, we investigate how self-efficacy, institutional, attitudes, perceived benefits, and value alignment separately predict open science usage. Our enhanced model records better fit indices (CFI = 0.994, TLI = 0.958, SRMR = 0.011) and accounts for 55.6% variance in utilization behavior. Results indicate that self-efficacy is the strongest direct predictor of use (β = 0.478, p < 0.001), while institutional factors possess strong direct (β = 0.184, p < 0.001) as well as indirect effects via attitudinal paths (β = 0.570, p < 0.001). Contrary to our hypotheses, perceived benefits and value alignment did not directly predict use but had mediational effects. The hypothesized roles of language proficiency, research experience, and support from institutions were not supported. These findings integrate psychological and institutional explanations of scientific practice adoption, suggesting that effective interventions need to develop simultaneously researchers’ self-efficacy through intensive training and institutional environments conducive to favorable attitudes toward open science utilization. This empirical model makes theoretical contributions and has practical implications for driving open science adoption in academic settings.

This review essay focuses on Matteo Pasquinelli’s recent work, The eye of the master: A social history of Artificial intelligence, which offers a politicized genealogy of AI and highlights the inseparability of AI’s ontology from the social and political conditions that produce its algorithms. Crucially, Pasquinelli connects Babbage’s labor theory of automation and principle of labor calculation to Marx’s concept of the general intellect and reveals how various forms of machine intelligence mirrors, embodies, and amplifies the analytical intelligence of collective labour. Pasquinelli traces AI’s history alongside labour analysis, psychometrics, and the drive for a ‘control revolution,’ unpacking technical concepts such as self-organization and cybernetics to show that capitalist technologies are fundamentally sociomorphic and sociogenic: they formalize proven patterns of social cooperation rather than the biomorphic replication of how an individual’s mind performs a given task. This review argues that Pasquinelli’s analysis contributes vital insights into AI’s sociopolitical underpinnings and thus, advocating for democratic technopolitical practices to reshape algorithmic governance.

In this essay, we argue understanding how we over-trust AI sheds light on what it means to be human. The troubling fact is that we seem to knowingly accept the use of AI products with questionable accuracy and privacy safeguards even in the most high-stake or most intimate situations such as AI uses in war zones or as virtual companionship. We offer five potential explanations for this puzzling fact based on emerging literature on human-AI interactions and evolutionary theory centered around our relationship with information and tools. "Experienced and quite updated on the new technologies, Kingfisher says: – You guys have met rivals of the 4.0 age. You would for sure fail if you didn’t study them carefully. You must do thorough research on their behaviors to find a solution." - In Boogeyman, Wild Wise Weird: The Kingfisher Story Collection, Vuong (2025)-

Craig Delancey's The Passionate Engines presents a comprehensive account of “what basic emotions reveal about central problems of the philosophy of mind” (2001, p. vii). The book discusses five major issues: The affect program theory, intentionality, phenomenal consciousness, and artificial intelligence (AI). In this essay, I would like to briefly review the major tenets in the book and then focus on its discussion of AI, which has not been reviewed in detail. I outline some of the recent developments in cognitive science regarding counterfactual thinking and emotions, which I believe is beneficial for the core arguments in Delancey's book.

AI and Education in China: Imagining the Future, Excavating the Past authored by Jeremy Knox examines the relationship of AI and education in China by investigating the sociotechnical imageries in state policies, the thriving development of private sectors, both through the historical and political lenses. In the book, he examines holistically visions of AI-driven education in China through analyzing a wide range of key events and policies such as the establishment of the People’s Republic of China and the market reform in the late 1970s. " Kingfisher the Wise replies solemnly– Straight hook was once used to catch... an emperor."- In THE WEIRDEST FISH HOOK, , Wild Wise Weird: The Kingfisher Story Collection, Vuong (2025) -

In Cultural Analytics, Lev Manovich (2020) outlines the recent developments and the historical roots of a new, exciting research field called cultural analytics. Cultural analytics emerges as a discipline that utilizes methods from computer science, data visualization, and media arts for the exploration and analysis of cultural objects and their user interactions. Manovich continuously admonishes future researchers to think hard about the challenges of how cultural phenomenon can be represented as data to avoid the reductivism trap, as he quotes Gitelman and Jackson: “our zeal for more and more data can become a faith in their neutrality and autonomy, their objectivity. . .” Clearly, big, clever, and rigorous data must be the foundation for the advance of science in the 21st century. ".” Her entire being is like an ethereal painting, a playful creation of nature using colors, lines, dots, strokes, and patches. One can only exclaim, “Absolutely enchanting. Is this real or an illusion?" - In The Philosophy of Awakening, Wild Wise Weird: The Kingfisher Story Collection, Vuong (2025)-

In Why Information Grows, the complexity researcher César Hildago provides a compelling account of the growth of information in the universe [1]. Drawing on wide-ranging theories of statistical mechanics, the field of economic sociology, the theory of social capital, and the emerging science of complexity economics, Hildago argues information can grow in the universe whose law seems to favor the growth of entropy because of the following three conditions: out-of-equilibrium systems, solids, and the computational abilities of matters. These conditions are the foundation for the emergence of the ultimate computer, human economy, which can be viewed as a distributed computing networks that seek to generate embodiment of information (“crystals of imagination” (p.50)) that satisfy human needs and desires. First: Just listen to scientific news, but the environmental intelligence birds must keep the information simple. Throw away anything that sounds too complicated. Only keep what is simple to grasp. Keep whatever news that seems friendly to the ears. If the information appears fuzzy and causes the brain to implode after two sentences, toss it away and stop listening. Doing so will make the news as orderly and simple to understand as the truth! -In GHG emissions, Wild Wise Weird: The Kingfisher Story Collection, Vuong (2025) [0]-

Technological visionaries often paint a future powered by clean energy, yet these optimistic visions tend to overlook the messy socio-political realities of such transitions. As A Just Transition for All: Workers and Communities for a Carbon-Free Future (MIT Press) powerfully illustrates, there is a vast difference between a so-called ‘just’ transition and one that is genuinely just. This book offers a much-needed, thought-provoking, and meticulously documented exploration of how political and business leaders can ensure fairness for all stakeholders—especially vulnerable workers and their communities—as the world shifts toward a carbon-free future. "As time passes, news about the now hotter Earth buzzes through the bird village. Those kingfishers residing along the banks of the Red River often report drying riverbeds and skinny fish. As Kingfisher casts his gaze upon the events that have unfolded, he can’t help but feel a sense of unease creeping up within him. He decides to collect all the scientific information concerning climate change and greenhouse gas emissions. An elite squad with a unique talent for gathering vital information is formed for emergency information collection." -In GHG emissions, Wild Wise Weird: The Kingfisher Story Collection, Vuong (2025)-

Humanizing AI is one of the most pressing issues in the development and use of artificial intelligence in recent years, and many scholars have highlighted the critical need for emphasizes humanistic values as a core foundation for developing and using AI for societal goods. Here, human subjectivity should be in the forefront AI development and integration, because “while algorithmic knowledge of humans can be vast and can outperform their own knowledge, it remains foreign to their subjectivity”, noted Razinsky (2023). Numerous research works have attempted to apply the achievements of social sciences and humanities in making sense of AI development. Among these is Humanizing Artificial Intelligence: Psychoanalysis and the Problem of Control, edited by Fabio Tollon Possati, who pioneers applying psychoanalytic theories on AI and algorithms. Possati refers to this as “an odd couple,” a pairing he has explored in depth because he believes that focusing on neuropsychoanalysis and affective neuroscience, rather than solely on cognitive science, could yield more positive outcomes in AI development (Possati, 2021).

While generative AI has been embraced as a powerful tool for research, its integration into academic workflows has paradoxically undermined productivity in several ways. This essay explores four key challenges: secondary source of anxiety, where overreliance on AI-generated summaries fosters doubt about source credibility and scholarly rigor; operational inefficiency, as AI often generates redundant or misleading outputs that necessitate extensive verification; the hidden labor of AI integration, requiring researchers to develop new skills and oversight mechanisms to manage AI-driven processes; and ethical ambiguity, as evolving AI capabilities blur the boundaries of authenticity, originality, and responsible scholarship. These issues are further compounded by diverging institutional and cultural perspectives on what constitutes legitimate intellectual contribution. As AI continues to evolve, so too must the research communities’ strategies for its responsible use—ensuring it functions as a tool for discovery rather than a bottleneck of informational chaos that stifles innovation.

Jung once observed, “With glorious naivete a statement comes out with the proud declaration that he has no ‘imagination for evil.’ Quite right: we have no imagination for evil, but evil has us in its grip” (Jung, 2019). His words feel more relevant than ever, as we traverse—whether consciously or unconsciously—a world increasingly shaped by collective trauma. Jungian Analysis in a World on Fire: At the Nexus of Individual and Collective Trauma (2024), edited by Laura Camille Tuley and John R. White, delves into the profound impact of trauma—not just on individuals, but on entire societies. The book confronts the wounds we inflict upon nature, evident in the climate crisis, industrialized animal slaughter, and pandemics, alongside the fractures within human relationships, reflected in systemic oppression, gender inequality, and mass violence.