Have you ever seen a headline that felt shocking, urgent, or even scary, only to discover that once you dug into the data, the story didn’t quite hold up? That moment of realisation is where ethics in storytelling begin.

This session explores how sampling bias and the framing effect quietly shape data stories, often without malicious intent, yet with very real consequences. You’ll see how technically “correct” data can still distort understanding, steer decisions, and undermine trust through what’s included, what’s excluded, and how the narrative is constructed.

We then turn to responsibility. Using real examples, we’ll look at how to surface data limitations, avoid manipulative framing and headlines, and design visualisations that inform rather than mislead. You’ll leave with practical techniques for keeping your visuals on the right side of truth.

If you care about trust, integrity, and the real‑world impact of your data stories, this session will change how you design them.