This research examines how personalizing LLMs impacts content safety, revealing crucial patterns in how AI personalities affect harmful outputs.

• Different personality traits significantly influence toxicity levels in LLM responses
• Personality-based interventions can be designed to reduce bias and toxic content
• Security teams can leverage personality configurations to enhance content safety guardrails
• Findings provide a framework for developing safer, more controlled AI assistants

For security professionals, this research offers actionable insights into how personality customization affects AI safety boundaries, helping organizations better manage deployment risks of conversational AI.

Exploring the Impact of Personality Traits on LLM Bias and Toxicity