A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents
arXiv:2601.09869v2 Announce Type: replace Abstract: Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise of large language model (LLM)-based conversational agents (CAs). Unlike earlier chatbots, LLM-based CAs routinely generate interactional and linguistic cues, such as first-person self-reference, epistemic and affective expressions that empirical work shows can increase engagement. On the other hand, anthropomorphisation raises ethical concerns, including deception, overreliance, and exploitative
The proliferation of sophisticated LLM-based conversational agents makes the ethical implications of anthropomorphisation an increasingly pressing research and societal concern.
Understanding the ethical dimensions of AI anthropomorphism is crucial for guiding responsible AI development, mitigating potential harms, and shaping public perception and trust in advanced AI systems.
The focus is shifting towards formalizing the ethical risks associated with AI anthropomorphism, moving beyond mere technological capability to address societal and psychological impacts.
- · AI ethicists
- · Regulatory bodies
- · Responsible AI developers
- · Developers prioritizing engagement over ethics
- · Users susceptible to manipulation
- · Platforms lacking ethical guidelines
Increased scrutiny and debate around the human-like qualities of AI systems and their design.
Development of industry standards or regulations specifically addressing AI anthropomorphism and user deception.
Shifts in consumer expectations and perceptions of AI trustworthiness, potentially leading to 'de-anthropomorphisation' design principles.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI