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. (shrink)

Imagining AI: How the World Sees Intelligent Machines edited by Stephen Cave and Kanta Dihal (2023) was published as a result of the Global AI Narratives (GAIN) project of the Leverhulme Center for the Future of Intelligence, University of Cambridge. The book has 25 chapters grouped into four parts, corresponding to different geographical regions: Europe; the Americas and Pacific; Africa, Middle East, and South Asia; East and South East Asia. All chapters contributed comprehensively to the mission of showing “the imaginary (...) of intelligent machines is an incredibly rich site for exploring” and how the imaginaries shape the ways “different cultures reconcile the demands of being human in a technological age.”. (shrink)

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. (shrink)

In recent years, with the advances in machine learning and neuroscience, the abundances of sensors and emotion data, computer engineers have started to endow machines with ability to detect, classify, and interact with human emotions. Emotional artificial intelligence (AI), also known as a more technical term in affective computing, is increasingly more prevalent in our daily life as it is embedded in many applications in our mobile devices as well as in physical spaces. Critically, emotional AI systems have not only (...) the ability to not passively read and classify emotions, but most also have an ability to predict and ‘nudge’ users to certain desired emotional states. Drawing from Piredda (2020)’s account on affective artifacts and other recent accounts, we've examined various emerging emotion-sensing technologies such as recommender algorithms, personal AI assistants, work-related emotion trackers, and emotional AI toys and robots through the lens of affective artifacts. We show how these technologies fulfill the criteria of being affective artifacts: they are artifactual, multifunctional, semi-agentive, and semi-interpesonal. Emotional AI systems as affective artifacts can influence the affective states of the users (e.g., help regulate emotions of ourselves and others), and importantly, our manipulation of these algorithms can intersect with the maintenance and construction of our sense of self and identity. (shrink)

Sự thâm nhập của trí tuệ nhân tạo (AI) tạo sinh vào ngành báo chí đã tạo nên sự thay đổi về xu hướng tiêu thụ và sản xuất thông tin. Cụ thể, có năm thay đổi trong xu hướng hành vi tiêu thụ và sản xuất thông tin như sau: việc tạo ra nội dung trở nên dễ dàng và đa dạng hơn; AI tạo sinh có thể là tiếp điểm mới của con người đối với dòng chảy của (...) tin tức; ranh giới mờ giữa người tiêu thụ thông tin và người sản xuất thông tin; sự thuận tiện, dễ dàng trong việc tạo ra giá trị gia tăng cho các nội dung; sụ thay đổi quá trình sáng tạo và thậm chí là định nghĩa về sự sáng tạo trong nghề báo chí. Từ năm thay đổi trong hành vi trên, những ảnh hưởng lên kinh tế báo chí của AI tạo sinh đã được phân tích. Các phân tích chạm tới cả mặt tích cực của AI tạo sinh trong việc giảm chi phí và tăng giá trị của nội dung tin tức, cũng như những vấn đề đáng lo ngại đối với việc giảm doanh thu của báo chí: vấn đề tìm kiếm không nhấp chuột, bản quyền, đối tượng tiếp cận thông tin, kiểm soát chất lượng và nguồn tin. Những vấn đề trên cho thấy sự quan trọng trong việc sử dụng AI tạo sinh một cách có trách nhiệm xã hội và điều này đặt ra những câu hỏi đáng suy nghĩ cho toàn xã hội. (shrink)