arXiv Computation and Language

Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations

arXiv AI
Aug 25

Why we need an AI-resilient society- Profiling Large Language Models

The article discusses the evolution of AI across three generations—from explicit logic to neural networks to large language models (LLMs)—and how LLMs introduce new systemic risks. It applies a forensic‑psychology profiling method to identify ten key features of LLMs, such as hallucinations, bias, and cognitive atrophy, revealing an entity that confabulates, amplifies user biases, and erodes human competence. The report concludes with a four‑pillar framework for AI resilience, emphasizing cognitive sovereignty, measurable control, partial autonomy, and openness to safeguard society.

By Thomas Bartz-Beielstein, Eva Bartz