Overview
Could an AI-generated community help you test engagement ideas before going public? In this session, we explore the rise of synthetic audiences — virtual focus groups built from real-world data. Through a live guessing game and practical examples, you’ll discover how these “AI citizens” can accelerate research, reduce costs, and reveal hidden insights — while also confronting questions of authenticity, ethics, and trust. Learn where synthetic audiences add value, and where only real people can speak for themselves.
This deep-dive explores one of the most talked-about innovations in engagement technology — synthetic audiences. Led by Daniel Ferguson, this interactive segment demystifies what synthetic audiences are, how they’re built, and what role they can play in modern community engagement.
Key Points
- Interactive Icebreaker: Participants compare two feedback reports — one real, one AI-generated — and guess which is which. This playful exercise opens discussion on authenticity and the human element in public feedback.
- Defining Synthetic Audiences: Explanation of how AI models can simulate “virtual citizens” representing real demographic or attitudinal segments, allowing safe testing of ideas and messages before live rollout.
- Use Cases & Benefits: Examples of practical applications — pre-testing surveys, predicting reactions to controversial policies, and ethically exploring hard-to-reach viewpoints. Highlights include speed, scale, and cost savings.
- Authenticity & Ethics: Discussion of the “authenticity paradox” — synthetic audiences may mirror statistical reality but lack genuine emotion and nuance. Raises key ethical questions about legitimacy and transparency.
- Responsible Use: Clear best-practice guidance: always disclose when synthetic data is used, treat it as a supplement to real engagement, and validate with actual community input.
- Wrap-Up & Discussion: Ends with a short Q&A to explore participants’ perspectives on the opportunities and boundaries of synthetic audiences.