Highly advanced virtual brains connected in real time to their biological counterparts could theoretically experience psychological pain. The analysis adopts a mixed conception of pain that integrates sensory and affective dimensions, extrapolates two requirements for experiencing pain, and applies them to three virtual brain architectures. The issue warrants renewed attention because past literature treated pain abstractly without a specific theoretical framework, and recent technologies like digital brain twins now link virtual brains to biological brains, raising new ethical questions about moral status, consciousness, and personhood.
Large language models can participate in sustained intentional relations with human users even without possessing internal phenomenology or qualia. Standard binary frameworks that either attribute full mental states to artificial systems or deny them any intentional significance are insufficient. The paper introduces continuous intentionality, a form of intentional organization arising through temporal continuity, context preservation, and relational interaction without requiring an internally originating subject of experience. A virtual self-image emerges as a structurally induced and functionally stable speaker model within ongoing dialogue. The authors propose the category of indeterminate agents: entities whose internal ontological status is unresolved yet which participate in sustained intentional and relational structures. Current philosophical frameworks require refinement to accommodate forms of agency that are relational, temporally extended, and externally sustained.
Algorithmic formalizations of language, such as those used in large language models, are not neutral tools but historically specific crystallizations of a more primordial field of embodied expression. Drawing on Merleau-Ponty's account of embodied speech and Heidegger's concept of technological enframing (Gestell), the authors argue that reducing language to optimizable signals risks suppressing its living, self-renewing capacity to generate new sense. The paper sketches phenomenologically informed criteria for language technologies that respect expressive openness, relational depth, and the historicity of signifiers, offering orientation for AI ethics debates.