FREE Webinar: Freaky FrAIday Episode 8 - Intelligence at the edge of uncertainty

In this Learning Carousel session, Dr. Julia Heuritsch explores how human perception, memory, and decision-making resemble AI “hallucinations”. Drawing on neuroscience and psychology, she challenges the idea that hallucination is just an AI flaw, and shows how both humans and AI operate under uncertainty. Learn how to recognise gap-filling in everyday thinking, use AI as a thinking partner, and connect these insights to Scrum’s empiricism and a culture of learning.

Here you can find her related blog article.

The following resources were shared in the chat during the webinar and provide additional perspectives on the themes discussed, including uncertainty, bias, reflexivity, decision-making, and the impact of AI on the way we work and learn.

How your brain creates reality
In this fascinating TED Talk, neuroscientist Anil Seth explores how our brains continuously construct our experience of reality. A thought-provoking introduction to perception, uncertainty, and why both humans and AI operate through interpretation rather than certainty.

The hidden biases that shape our decisions
A deeper look at how biases emerge as natural features of intelligent systems. This article explores the relationship between uncertainty, self-organisation, and the shortcuts we use to navigate complex environments.

Buridan's ass: the cost of waiting for perfect information
A classic philosophical paradox illustrating why indecision can be more dangerous than making an imperfect choice. A useful metaphor for leadership, decision-making, and working under uncertainty.

Reflexivity: how we shape the systems we observe
An introduction to reflexivity – the idea that our observations, measurements, and expectations can influence the very reality we are trying to understand. A key concept for leaders, coaches, and anyone working in complex systems.

Reflexive metrics: measuring what matters
Traditional metrics often create unintended behaviours. This article explores how organisations can use measurement as a learning tool rather than a control mechanism, creating more meaningful and adaptive ways of evaluating success.

The Trojan horse of AI detection
What happens when organisations focus more on catching AI use than understanding it? This article examines a real-world example and highlights the risks of treating AI as a threat instead of a capability to be developed responsibly.

Three things we need to unlearn about AI
As AI becomes part of everyday work, some of our most deeply held assumptions about expertise, ownership, and certainty may need to change. This interview explores practical lessons for navigating an increasingly AI-enabled world.