AI Safety in Mental Health: Why Generic Guardrails Aren’t Enough

Join Ricardo Rei, Head of AI Research and Maya, Head of Clinical, for a critical discussion on AI Safety in Mental Health. In this webinar, we will explore the significant challenges that LLMs introduce into the sensitive domain of mental health, including the profound difficulty in accurately evaluating their performance in clinical scenarios. We will then examine the crucial role of guardrails, making the case that generic safety measures are insufficient and highlighting the necessity of building specialized guardrails tailored for mental health. Finally, we will outline a forward-looking approach to overcoming these challenges by co-designing new foundational models from the ground up, working in close collaboration with clinical teams to ensure safety and efficacy are built in by design.

Key takeaways

Understand why evaluating LLMs in mental health is uniquely challenging, and what makes traditional safety benchmarks insufficient.
Learn why generalized AI safeguards fall short in clinical use, and how tailored, condition-aware guardrails can make a real difference.
Explore a path forward through co-designed foundational models, built in collaboration with clinical experts to embed safety at the core.

Webinar Hosts

Ricardo Rei

Head of AI Research at Sword Health

Maya D'Leon

Head of Clinical at Sword Health

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Hosts

Meet your hosts

Learn how to navigate the safety risks of AI in mental health and discover the guardrails and model-design practices that help organizations deploy AI care with confidence.

Ricardo Rei
Head of AI Research at Sword Health
Ricardo Rei is the Head of AI Research at Sword where he leads a research team focusing on multimodal large language models for healthcare sector.
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Ricardo Rei
Maya D'Eon
Head of Clinical at Sword Health
Maya D’Eon, PhD, is the Head of Clinical at Sword Health, where she leads clinical strategy, safety frameworks, and evidence-based protocol development.
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Maya D'Leon

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