HUMAN + AI Interaction Science Lab jhb

In this session, we breakdown Interaction Personality, a way to understand how users navigate, respond, and engage across digital experiences. We’ll explain how Interaction Personality is identified using behavioral signals, what different interaction types look like, and how they evolve over time. Through a real use case in a banking context, we’ll show how all businesses can apply these insights to drive contextually relevant customer engagement across digital channels.

Production and testing environments play a critical role in reliable AI delivery. In this session, we explore why environment separation matters, how different teams use each environment, and what activities belong where. We’ll show how testing environments support faster experimentation while protecting production systems from disruption.

You’ll also learn how structured environments reduce downtime, prevent failed deployments, and ensure models stay live while innovation continues.

Behavioral algorithms are designed to model how people actually think, decide, and change over time. In this session, we explain what behavioural algorithms are, why they matter, and the distinct purposes each type serves within our Platform.

We’ll also walk through the algorithm selector and show how it helps teams choose the right approach without deep algorithm expertise, reducing guesswork while keeping systems aligned with real human behavior.

Large language models are powerful, but accuracy depends on how they’re grounded. In this session, we demonstrate how to use ecosystem.Ai’s Fact Injection framework within an AI agent. You’ll learn how this core capability reduces hallucinations and improves response reliability. We’ll explore practical patterns for controlling outputs, maintaining context, and ensuring agents respond using trusted, contextual and up-to-date information.