Syed AbuMusab

The artificiality of AI, while often problematic in Western ethical frameworks, uniquely aligns with Islamic ethics. Where standard criticisms of carebots emphasize dignity, deception, and simulated care, I demonstrate that their artificial nature positions them as 'neutragents' (neutral agents) within Islamic care ethics. Through their neutragential status, carebots transcend the traditional mahram/non-mahram (permissible/non-permissible caretakers) dichotomy while protecting awrah (bodily privacy). However, this advantage becomes compromised if Muslim users' image and video data are exposed to human labelers during AI training, as such exposure would undermine the neutragential status. This analysis reveals a critical implication: the necessity of intercultural value alignment in AI ethics. As AI's global impact grows, integrating diverse ethical perspectives becomes essential, yet current approaches to AI ethics and value alignment have been slow to incorporate non-standard perspectives meaningfully.

The recent advances in Large Language Models (LLMs) and their deployment in social settings prompt an important philosophical question: are LLMs social agents? This question finds its roots in the broader exploration of what engenders sociality. Since AI systems like chatbots, carebots, and sexbots are expanding the pre-theoretical boundaries of our social ontology, philosophers have two options. One is to deny LLMs membership in our social ontology on theoretical grounds by claiming something along the lines that only organic or X-type creatures belong in our social world. Second, expand our ontological boundaries. I take the second route and claim LLMs implemented as social chatbots are social agents. Utilizing Brian Epstein's concepts of grounding and anchoring, alongside Dee Peyton's criteria for what makes a property social, I posit that the capacity for conversations is a social property. Further, within a framework where social agency is considered multi-dimensional, akin to agency, possessing a social property is sufficient for attaining social agency. Thus establishing chatbots as social agents. A helpful concept here is Levels of Abstraction (LoA). The LoA framework allows for extracting relevant and important information from the target domain (the social world). For example, the property of being a 'boy' and the capacity for conversation are social properties; hence, they are part of the social domain. LLMs have the capacity for conversations. So, if we focus on the conversational-LoA and not the gender-LoA, then LLMs occupy a dimension of sociality (i.e., conversational dimensions).