Reading List

This section contains links to what we consider to be essential background reading in understanding risk, errors and how our brain actually works as we ride the bike. Keep checking back because we’ll be adding to this section regularly.



This sections lists a small number of books we believe to be fundamental to the ‘new view’ of road safety and accidents in general, containing vital clues to how motorcyclists continue to be caught out by the road ahead and have the same pattern of accidents that they have had since investigations into motorcycle crashes began.

‘Black Box Thinking’ by Matthew Syed

Whether developing a new product, honing a core skill or just trying to get a critical decision right, Black Box Thinkers aren’t afraid to face up to mistakes. In fact, Black Box Thinkers see failure as the very best way to learn. Rather than denying their mistakes, blaming others, or attempting to spin their way out of trouble, these institutions and individuals interrogate errors as part of their future strategy for success.
How many of us, hand on heart, can say that we have such a healthy relationship with failure?

Learning from failure has the status of a cliché, but this book reveals the astonishing story behind the most powerful method of learning known to mankind, and reveals the arsenal of techniques wielded by some of the world’s most innovative organizations. It also reveals the dangers of failing to learn from mistakes. In healthcare, hundreds of thousands of patients die from preventable medical errors every year due to a chronic lack of Black Box Thinking.

Using gripping case studies, exclusive interviews and really practical takeaways, Matthew Syed – theaward-winning journalist and best-selling author of Bounce – explains how to turn failure into success, and shows us how we can all become better Black Box Thinkers.


‘On Intelligence’ by Jeff Hawkins

In the prologue to his book, Jeff Hawkins writes:

“The agenda for this book is ambitious. It describes a comprehensive theory of how the brain works. It describes what intelligence is and how your brain creates it. The theory I present is not a completely new one. Many of the individual ideas you are about to read have existed in some form or another before, but not together in a coherent fashion. This should be expected. It is said that “new ideas” are often old ideas repackaged and reinterpreted. That certainly applies to the theory proposed here, but packaging and interpretatiom can make a world of difference, the difference between a mass of details and a satisfying theory.”

The basic theory that Hawkins proposes is that the brain is a mechanism to predict the future, perhaps not always far in the future, but far enough to be of real use. The brain is thus a ‘pattern machine’ which doesn’t compute answers, but works by retrieving previously learned patterns that solved the problem. A very simple example would be catch a ball.

The brain constructs the reality around us by perceiving and predicting simultaneously – very similar processes but ones working in opposite directions.

The prediction function of brain works from via ‘top down processing’ creating expectations. As long as expectations are being met, we don’t need to pay much attention – this is what gives rise to the ‘autopilot’ for high frequency tasks or highly skilled behaviours including driving.

Only when predictions are not confirmed, do we pay more attention to analyze the pattern more closely – for example when a word in a sentence is not what you were expecting. In driving, we would perform a visual regression to re-check the situation and engage our conscious brain to decode it.

Our perception is therefore always is an interaction between input (bottom up) and prediction (top down). Our reliance on this prediction mechanism means we also have expectations even before the sensory input. Opening the door to a familiar room would mean we were already predicting what we’d find and how it would look.

This book offers important guidance for a ‘new view’ of accidents.


‘Thinking Fast and Slow’ Danial Kahneman

Daniel Kahneman’s book explains how our brain uses a ‘dual-process’ model, which takes in the world around us in two radically different ways.

‘System 1’ is fast, intuitive, associative, metaphorical, automatic, impressionistic, and it can’t be switched off. Its operations involve no sense of intentional control, but able to make snap decisions, it’s the “secret author of many of the choices and judgments you make”.

‘System 2’ is slow, deliberate, tiring and to use it requires our conscious attention and allows logical thinking. Unfortunately, it’s also lazy. Whilst it should provide a check to our System 1 intuitive guess, it’s often unwillingly to do so because System 1 is for the most part pretty good at what it does; it’s highly sensitive to subtle environmental cues, signs of danger, and so on. It kept our remote ancestors alive.

But the price we pay for the speed of System 1 is that it simplifies and assumes “what you see is all there is” which Kahneman contracts to WYSIATI. It even embroiders and makes unfounded links, and jumps to conclusions whilst being subject to irrational biases and interference effects. We construct a coherent story with whatever information is easy reach of our intuition (and our intuition does not allow for information that fails to come to mind, much less information it never had in the first place). Kahneman says: “A reliable way of making people believe in falsehoods is frequent repetition because familiarity is not easily distinguished from truth.”

Among other problems, this leads to overconfidence. Fallible though it may be, we prefer the ‘evidence’ of our own memory and experience to any kind of fact-checking from outside ourselves and so we fail to exercise caution when we need it most and are reluctant to consider that our view of the world might be wrong.



‘On Intelligence’ Jeff Hawkins

‘Thinking, Fast and Slow’ Daniel Kahneman

‘The Field Guide to Understanding Human Error‘ Sidney Dekker

‘Upper Half of the Motorcycle: On the Unity of Rider and Machine‘ Bernt Speigel

‘Make It Stick: The Science of Successful Learning’ Peter C Brown

‘How We Learn’ Benedict Carey

‘Human Error’ James Reason

‘The Norm Chronicles: Stories and numbers about danger’ Michael Blastland

‘Visual Intelligence: How We Create What We See’ Donald D Hoffman

‘The Eye: A Natural History’ Simon Ings

‘The Design of Everyday Things‘ Donald A. Norman

‘Eye and Brain: The Psychology of Seeing‘ Richard L. Gregory

‘The First 20 Hours: How to Learn Anything…Fast‘ Josh Kaufman

‘Mastery‘ Robert Greene

‘You Can Beat Your Brain’ David McRaney

‘You Are Not So Smart’ David McRaney

‘The Vision Revolution‘ Mark Changizi

‘Bounce: The Myth of Talent and the Power of Practice’ Matthew Syed

‘The Decisive Moment’ Jonah Lehrer

 ‘Zoom: How Everything Moves’ Bob Berman

‘The Organised Mind: Thinking Straight in an Age of Information Overload’ Daniel Levitin


An investigation of the role of vehicle conspicuity in the ‘Looked but failed to see’ error in driving – Martin Paul Langham; Thesis presented for Doctor of Philosophy
University of Sussex School of Cognitive and Computing Sciences


The Transport and Road Research Laboratory coined the phrase `looked but failed to see error’ referring to a set of circumstances where a driver accounts for an accident in the terms of failing to see. A prototypical form of such accidents involves collisions between motorcycles and cars. Motorcycle accidents tend to involve another road user who often claims not to have seen them in time to avert a collision. Research into the causes of motorcycle accidents has tended to make two basic assumptions: firstly, that the offending driver actually looks but then fails to see the motorcyclist,. secondly, that this failure can be explained in terms of the relative lack of conspicuity of the motorcyclist. This laboratory experiment suggests an alternative explanation for such accidents. Experienced and inexperienced drivers viewed video tape clips of approaching traffic at intersections. Subjects’ eye movements were recorded in response to different search instructions. Under the conditions of this experiment, experienced drivers appear to use ‘pre-programmed’ search patterns directed towards areas of the road environment which are informationally rich; there was little evidence of these in the eye-movements of inexperienced drivers. Experienced drivers appeared to start their search at a midpoint in the scene whist inexperienced drivers started their search nearby. One consequence of this was that experienced drivers took longer to detect motorcyclists who were nearby. (i.e. to the left of the initial point of fixation.)

 Gibson’s Theory of Perceptual Learning

This paper describes the key ideas of the influential psychologist Eleanor J. Gibson, developed over 70 years of research with infants, children, adults, and a wide range of nonhuman species. Gibson’s ecological approach to perceptual learning and development describes how perception—extracting meaningful information from the environment to guide actions adaptively—improves with experience, the acquisition of new means of exploration, and the development of new perception-action systems.

Some Myths about Industrial Safety
This paper has been written from the perspective of industrial safety, but it is perfectly valid for the understanding of motorcycle safety as well.
There are many definitions of safety, but most of them are variations on the theme that safety can be measured by the number of adverse outcomes. This vision has consequences for how industry thinks safety can be achieved. This paper looks at six safety-related assumptions, or safety myths, which impact industry practices. We argue that these practices are littered with fragile beliefs, which in many cases make the safety management flawed and ineffectual. The open acknowledgement of these myths is a necessary first step to genuinely improve industrial safety.