How Behavioural Science Reveals How We Really Think, Decide and Act

By Let’s Think

Behavioural Science AI combines behavioural science methods with GenAI and advanced analytics to surface, evolve, and amplify expert knowledge. It’s a prized asset rarely captured by traditional systems. In Part 1 of our explainer series, we unpack what behavioural science really is—and what it’s not.

Image copyright: Becky Stevens: “Memory Leak” by CREST Research, CC BY-NC-SA 2.0

As AI rapidly transforms how we work and live, there's growing recognition of something essential: that technology is only as useful as our understanding of the humans using it. Behavioural science offers a powerful lens for this understanding, but it’s often misunderstood.

For many, it’s associated with nudging—those subtle design tweaks that steer people toward safer, healthier (or more profitable) decisions. Think opt-out organ donation, default pension schemes, or perfectly-timed app notifications. 

The popularity of “nudges” grew from the work of Daniel Kahneman and Amos Tversky, who famously revealed how we’re prone to cognitive biases—mental shortcuts that can sometimes lead us astray. Their research helped launch behavioural economics, and it has become shorthand for a diverse field deeply rooted in scientific rigour.

But behavioural science is much broader than that. 

So, what is behavioural science?

Behavioural science is the study of human behaviour: how people think, decide, communicate, and act, especially in social and systemic contexts. It’s a multidisciplinary field dedicated to  understanding not just what we do, but what, where, when, why and how we do things. It blends insights from both natural and social sciences, such as:

• Psychology: how we perceive, learn, remember, think and feel

• Neuroscience: what’s happening in the brain

• Sociology, anthropology & political science: how we interact within groups, institutions and systems

Behavioural scientists use diverse methods: from self-report questionnaires and experiments, to brain imaging and ethnographic observation, not just to describe behaviour, but to understand why it happens, and how it can be supported and improved. 

A common misconception, rooted in the “nudge theory”,  is that behavioural science focuses on how humans are flawed, irrational, or easy to trick.

In reality, many of these so-called flaws are adaptations that work incredibly well in real life, especially when decisions are fast, high-stakes, and complex. 

How experts actually think

Other fields of cognitive science  look not at average consumers in controlled experiments, but at real experts making tough decisions in real environments—like emergency responders, pilots and military leaders. 

Initially developed by cognitive psychologist Gary Klein, this research shows that experts often don’t compare options rationally at all. Instead, they:

• Rapidly assess the situation by matching it to past experience

• Use intuition to recognise patterns and simulate likely outcomes

• Make fast, high-quality decisions under pressure

This explains why experience matters—not because it makes people smarter, but because it shapes their internal understanding of how things work.

Enter tacit knowledge: The hidden engine of expertise

So how do experts actually know what to do, if they’re not consciously reasoning through every step? The answer lies in different types of knowledge:

• Explicit knowledge: formal, written information (books, policies, training)

• Implicit knowledge: what you know from experience, but can explain if asked

• Tacit knowledge: deep, intuitive understanding that’s hard to articulate. It just feels right

Tacit knowledge is elusive—difficult to elicit and measure, and often invisible in traditional systems. Yet most people instinctively know it exists and that it’s critical to expert decision making. For example, a trauma surgeon may instantly recognise signs of internal bleeding and act without waiting for a scan, or a fire commander may detect subtle cues of a structural collapse and change strategy on the spot. These are not guesses—they’re rapid, experience-based decisions powered by pattern recognition and mental simulation. This is tacit knowledge in action.

“I help people and organisations navigate human complexity, not with guesswork, but with insight. Technology can be a delivery mechanism for that process, and behavioural science principles can be used to design the technology” – Anna Leslie, Chief Scientific Officer and Co-founder, Let’s Think

Why this matters in knowledge work

While behavioural science insights can be used to influence others, its greater power lies in helping organisations understand and support how people actually work, especially in complex fields with frequent high stakes decisions such as law, financial services, law enforcement, and medicine. 

We can use Behavioural Science to:

• Understand expert decision making

• Support judgement under uncertainty

• Design tools and systems that work with, not against, human cognition

• Make tacit knowledge shareable and visible

At Let’s Think, we’re applying behavioural science principles to build tools that help people think brilliantly—because when they do, they make better decisions, solve harder problems, and create real impact. That’s the kind of thinking the world needs more of.

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If you are new to decision making research, a helpful jargon-busting overview can be found in this A–Z of decision-making from CREST, which outlines key terms and frameworks used across the field.

From Idea to Innovation: Building the Let’s Think Knowledge Exchange

Today marks a moment of reflection on our journey at Let’s Think—one that began with a deceptively simple question: How do we capture expert knowledge before it walks out the door of a company? 

As behavioural scientists, our team has long understood how difficult it is to surface what people know, especially when that knowledge is tacit, embedded in experience, and rarely documented. Our earliest insights came from recognising that organisations everywhere suffer from knowledge loss—whether someone is leaving a role or simply too busy to share what they know.

That idea resonated widely. At events like London Tech Week, it connected us to people like the Head of Innovation at a leading financial institution. She got it. Her team faced exactly this problem: talented secondees rotating in and out, but no scalable way to retain their learnings.

So we started building—with interviews, handwritten notes, and a prototype concept for the Knowledge Exchange.

That early work laid the foundations for something far more ambitious. Serendipity played its role again when I met Sarah Harris, Director of Innovation and Knowledge at Kingsley Napley, at a UKRI Innovation Lab. Her experience in legal investigations helped bridge our thinking to a high-stakes, knowledge-rich sector: Law. The Lab’s ESG and data access goals helped refine our proposition. We realised we weren’t just capturing knowledge. We were generating a novel expertise dataset that doesn’t currently exist in most organisations.

And then came the wildcard: LLMs. Fresh on the scene in late 2022, they offered a powerful new tool for micro-eliciting knowledge. Could we develop a product that captured meaningful insights in just five minutes? In an industry like law, where time is measured in six-minute increments, that challenge was not only exciting but necessary.

We've spent the last year testing, validating, and iterating the Knowledge Exchange. We’ve trialled the product internally. We’re running pilots with law firms like Kingsley Napley. And we’re seeing, with growing confidence, Behavioural Science AI is a technology that can transform knowledge management. 

What’s been most striking is how much the journey itself has shaped the product. Unexpected opportunities like innovation labs and pivots into new industries became forcing functions—shaping our assumptions, surfacing new needs, and accelerating our thinking.

The ideas were always there. But the path forward emerged only as we walked it, and heeded the signals for the best direction to go to solve a pressing customer problem. 

Wendy Jephson is the CEO and Co-founder of Let’s Think. She is a serial entrepreneur and dually qualified as a Behavioural Scientist and Lawyer.