An interactive virtual learning experience to help healthcare professionals examine AI through ethics, equity, and real-world application.


● AI in Healthcare - VILT

Scale + Signal

▸ 186 staff audience

▸ 171 post-session responses

▸ 4.65/5 engagement

▸ 90% rated the session 4 or 5

▸ 92% felt more prepared to discuss AI in healthcare

▸ 82% likely to apply what they learned in their roles


VILT Abstract


AI was already influencing diagnostics, treatment, prediction, and workflow, but the conversation needed to go beyond innovation.

The session was designed to help staff understand where AI was showing up, recognize ethical risks such as bias and health disparities, and explore what responsible, equitable use looks like in practice.


The question wasn’t whether AI belongs in healthcare. It’s how we ensure it works responsibly, equitably, and for everyone.


The experience moved AI from an abstract, emerging topic into a practical conversation about healthcare decisions, equity, and responsibility.


Learning Experience Designer + Facilitator


My Role

I designed and facilitated the session, translating a complex and rapidly evolving topic into a structured, discussion-based experience grounded in real-world healthcare decisions.

The experience moved from awareness and baseline knowledge into case comparison, ethical tension, reflection, and practical action.

What I Built

▸ Virtual slide deck

▸ Pre-session survey

▸ Post-session evaluation

▸ Kirkpatrick evaluation

▸ Word cloud activities

▸ Polls + knowledge checks

▸ Scenario-based case studies

4 Design Moves

Start with their experience


Pre-session insights surfaced concerns around privacy, accuracy, bias, and limited exposure.

Impact:
▸ 154 pre-session responses
▸ 73% cited privacy concerns

Design for Participation


Word clouds, polling, knowledge checks, and discussion kept participants actively involved.

Impact:
▸ 4.65/5 engagement
▸ 73% valued polling

Use contrast to create tension


Paired scenarios showed how the same technology could produce very different outcomes.

Impact:
▸ 67% valued stories
▸ Case studies ranked among the
most valuable elements

Move from Reflection to Action


Participants were asked what they would question, change, and influence in practice.

Impact:
▸ 92% felt more prepared
▸ 82% likely to apply the learning

Participants rated engagement 4.65/5.

92% felt more prepared to discuss AI in healthcare, and 82% reported they were likely to apply what they learned in their roles.