Study Reviews Ethical Implications of Anthropomorphizing AI Chatbots

Global: Study Reviews Ethical Implications of Anthropomorphizing AI Chatbots

A new scoping review posted on arXiv on January 26, 2026 examines the ethical dimensions of giving human‑like qualities to large‑language‑model (LLM) conversational agents. The authors surveyed literature across five scholarly databases and three preprint repositories to identify how researchers define, measure, and evaluate anthropomorphisation in AI‑driven chat interfaces.

Conceptual Foundations

The review finds broad agreement that anthropomorphisation involves attribution‑based definitions, wherein non‑human systems are ascribed mental states, intentions, or emotions. However, the authors note substantial variation in how studies operationalize these concepts, ranging from self‑referential language cues to affective expression patterns.

Ethical Challenges and Opportunities

Among the ethical concerns highlighted are potential deception, user overreliance, and the framing of relationships that could be exploitative. Conversely, several scholars argue that anthropomorphic cues might enhance user autonomy, promote well‑being, and foster inclusion for diverse populations.

Methodological Landscape

The analysis reveals a fragmented methodological terrain. While some investigations employ controlled experiments to assess engagement effects, many rely on qualitative content analysis, leading to limited empirical evidence that directly links observed interaction outcomes to concrete governance recommendations.

Normative Perspectives

Most of the literature adopts a risk‑forward normative framing, emphasizing precautionary principles over potential benefits. This trend reflects broader societal apprehensions about AI systems that appear to possess agency or consciousness.

Recommendations and Future Directions

To address these gaps, the authors propose a research agenda that includes standardized metrics for anthropomorphic cues, longitudinal studies on user behavior, and interdisciplinary governance frameworks. Design recommendations call for transparent disclosure of AI capabilities and user‑centred evaluation of anthropomorphic features before deployment.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.