English title: Cultural Stereotypes and Bias Towards the Indians in Writing of Rudyard Kipling. The aim of this paper is to characterize and dispute the cultural stereotypes and prejudices against the Indians depicted in the writings of Rudyard Kipling (1865–1936), one of the most popular British novelists of the Victorian era. The starting point for these reflections is George Orwell’s essay in which he describes Kipling as a racist and imperialist as well as a morally insensitive and aesthetically disgusting figure. (...) To verify this view the present author undertakes an analysis of the cultural stereotypes and prejudices embedded in the selected novels by Kipling. In reconsidering Kipling’s works, she traces the connections between his own world-view and the negative reception of Indians within the Anglo-Indian community by which he was largely shaped. The paper concludes by supporting Orwell’s criticism and demonstrating how Kipling reinforced the stereotype of an Indian, thus reflecting the cultural cliché widespread among the xenophobic and conservative Anglo-Indians in the 19th century. (shrink)

The idea that human cognition is, or can be understood as, a form of computation is a useful conceptual tool for cognitive science. It was a foundational assumption during the birth of cognitive science as a multidisciplinary field, with Artificial Intelligence (AI) as one of its contributing fields. One conception of AI in this context is as a provider of computational tools (frameworks, concepts, formalisms, models, proofs, simulations, etc.) that support theory building in cognitive science. The contemporary field of AI, (...) however, has taken the theoretical possibility of explaining human cognition as a form of computation to imply the practical feasibility of realising human(-like or -level) cognition in factual computational systems, and the field frames this realisation as a short-term inevitability. Yet, as we formally prove herein, creating systems with human(-like or -level) cognition is intrinsically computationally intractable. This means that any factual AI systems created in the short-run are at best decoys. When we think these systems capture something deep about ourselves and our thinking, we induce distorted and impoverished images of ourselves and our cognition. In other words, AI in current practice is deteriorating our theoretical understanding of cognition rather than advancing and enhancing it. The situation could be remediated by releasing the grip of the currently dominant view on AI and by returning to the idea of AI as a theoretical tool for cognitive science. In reclaiming this older idea of AI, however, it is important not to repeat conceptual mistakes of the past (and present) that brought us to where we are today. (shrink)