Your search

In authors or contributors
  • This chapter explores the philosophical and practical implications of attributing self-consciousness to machines equipped with generative artificial intelligence. Drawing on Immanuel Kant’s als ob framework, it is argued that treating these systems “as if” they were conscious is a strategic move essential for enabling effective interaction. Such an approach allows humans to engage with AI systems in ways that foster trust, effective communication, and practical integration. The chapter examines self-consciousness not as an intrinsic property, but as a cognitive function designed to facilitate complex social interactions. Mechanisms like reflexive consciousness and inner speech are highlighted as critical tools for enabling machines to navigate human environments effectively. Social robotics provides practical examples of how this perspective can foster collaboration and improve human-machine relationships. This theoretical move is framed not as a claim about the nature of AI systems, but as a pragmatic condition for their integration into social contexts. The social theory of consciousness appears to hold significant relevance even in the realm of artificial consciousness. Self-conscious machines promise substantial benefits, particularly by elevating the quality of social interactions, improving decision-making processes, and refining behavioral predictions. While acknowledging the philosophical and technical challenges of developing artificial self-consciousness, the chapter argues that this approach expands the boundaries of cognition and redefines human-machine dynamics, paving the way for more meaningful interactions and advancing both technological innovation and philosophical inquiry.

  • Recent debates on artificial consciousness are shaped by two converging developments: cognitive robotics, emphasizing embodied agency and internal models, and large language models (LLMs), whose conversational fluency invites strong attributions of mindedness. While these advances do not resolve whether subjective experience can arise in non-biological systems, they demand a methodological shift: optimized behavior alone is no longer reliable evidence of consciousness. This chapter treats artificial consciousness as a research program rather than a binary verdict, distinguishing phenomenal consciousness, access consciousness, and self-consciousness. It reframes the other-minds problem for machines as inference under engineered uncertainty, integrates classical debates on meaning and grounding with contemporary concerns about anthropomorphism, individuation, and evaluation, and argues that the near-term focus should be on carefully defined, weak forms of structural or instrumental self-consciousness, together with their ethical and governance implications.

Last update from database: 8/18/26, 1:00 AM (UTC)