“The value is created in the friction, in the engagement between humans and AI—the pushing back by the humans, the pushing back by the machines.”

–Ross Dawson

About Ross Dawson

Ross Dawson is a futurist, keynote speaker, strategy advisor, author, and host of Amplifying Cognition podcast. He is Chairman of the Advanced Human Technologies group of companies and Founder of Humans + AI startup Informivity. He has delivered keynote speeches and strategy workshops in 33 countries and is the bestselling author of 5 books, most recently Thriving on Overload.

Website:

rossdawson.com

LinkedIn Profile:

Ross Dawson

What you will learn

The dangers of aiming for a frictionless experience between humans and AI
Why meaningful engagement—rather than passive approval—between humans and AI is crucial for cognitive augmentation
How human judgment and reasoning differ, and where AI excels versus where humans add irreplaceable value
The four key pitfalls of the traditional ‘human in the loop’ approach to decision-making with AI
Why too much delegation to AI can erode human vigilance, judgment, and accountability
The importance of adversarial, not just assistive, collaboration with AI for complex, high-stakes tasks
How ‘living strategy’—AI-augmented, continuously updated organizational strategy—addresses the limitations of static strategic planning
The role of AI in surfacing diverse perspectives, supporting dialogue, and enabling truly adaptive decision-making

Episode Resources

Transcript

Ross Dawson: I love speaking to the wonderful guests I have on my podcast. I always learn an enormous amount, but in this episode, I’ll share a little bit of an update for myself and delve into a few interesting things I’ve been seeing and doing lately, including some of the most interesting research papers I’ve seen on humans plus AI lately, looking at human in the loop and the ways in which we should be thinking about that, and AI and strategy.

So, just a quick scan of what’s going on in humans plus AI. I’ve been traveling quite a bit, doing a lot of keynotes as much as possible on humans plus AI, and the resonance around the theme is really rising very rapidly. In fact, somebody recently mentioned that humans plus AI was a cliché, or just overworn at the moment. Since I first started using the phrase three and a half years ago, I think it’s wonderful that now it is gaining a lot of currency. People are talking about it, framing that. Yes, some phrases outlive their usefulness, but I think I’ll stick with humans plus AI for the foreseeable future.

The research papers I’ve been looking at are focused on essentially cognitive augmentation and erosion, and that’s this critical domain where it’s not really clear around whether, or in which circumstances, our cognition erodes, and what it is we can do to make it augmenting.

One of the excellent papers is titled Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction. It’s a bit dense, but it has some great research and analysis in it. The key finding, which it begins with, is that in human-computer interface research literature over the last while, we saw that last year, 2025, there was a big, big rise in this idea of driving human sovereignty in how it is we interact with computers. However, since last year to the first part of this year, we’ve in fact seen that fall dramatically, where the human sovereignty paradigm is reducing dramatically, and we are seeing this big rise in what is called the frictionless paradigm, saying: how do we get as little friction as possible between humans and AI?

There are a number of really important points made in the paper, and really, the starting point is saying that we should stop treating frictionless AI as the goal. If we start to be frictionless, that is starting to essentially take the human out of the loop. The nature of humans is that we need to engage, we need to think, so we need to start building devil’s advocate agents into the systems and to aim for this thing where we start to have both this high degree of engagement with the AI, but also high friction.

That friction is where we are trying to, essentially, the more complex one rising, having more and more friction, and in lower frictions, it’s just more so. Label tasks, but where we’re not just showing the reasoning, giving people the ability to think through tasks and how they think about that, but ...