A few weeks ago, I wrote a post inspired by reading ‘This is happiness‘ by Niall Williams [see ‘Are these the laws of engineering?’ onJuly 14th 2021]. On a more personal note, I enjoyed another description in the same book: ‘he was over sixty years…the moving bits of him could no longer be taken for granted, and twinges, pulls and strains in the elasticated parts were matched by aches, clunks and creaks in the skeletal.’ This description could apply to me but fortunately only on a bad day at the moment. I am going on a deep vacation [see ‘Digital detox with a deep vacation‘ on August 10th, 2016] for a few weeks in order to rejuvenate my mind and body by walking some sections of the South-West Coast Path [see ‘The Salt Path‘ on August 14th, 2019]. Regular posts will resume when I return in August.
The term ‘unknown unknowns’ was made famous by Donald Rumsfeld almost 20 years ago when, as US Secretary of State for Defense, he used it in describing the lack of evidence about terrorist groups being supplied with weapons of mass destruction by the Iraqi government. However, the term was probably coined by almost 50 years earlier by Joseph Luft and Harrington Ingham when they developed the Johari window as a heuristic tool to help people to better understand their relationships. In engineering, and other fields in which predictive models are important tools, it is used to describe situations about which there is deep uncertainty. Deep uncertainty refers situations where experts do not know or cannot agree about what models to use, how to describe the uncertainties present, or how to interpret the outcomes from predictive models. Rumsfeld talked about known knowns, known unknowns, and unknown unknowns; and an alternative simpler but perhaps less catchy classification is ‘The knowns, the unknown, and the unknowable‘ which was used by Diebold, Doherty and Herring as part of the title of their book on financial risk management. David Spiegelhalter suggests ‘risk, uncertainty and ignorance’ before providing a more sophisticated classification: aleatory uncertainty, epistemic uncertainty and ontological uncertainty. Aleatory uncertainty is the inevitable unpredictability of the future that can be fully described using probability. Epistemic uncertainty is a lack of knowledge about the structure and parameters of models used to predict the future. While ontological uncertainty is a complete lack of knowledge and understanding about the entire modelling process, i.e. deep uncertainty. When it is not recognised that ontological uncertainty is present then we have meta-ignorance which means failing to even consider the possibility of being wrong. For a number of years, part of my research effort has been focussed on predictive models that are unprincipled and untestable; in other words, they are not built on widely-accepted principles or scientific laws and it is not feasible to conduct physical tests to acquire data to demonstrate their validity [see editorial ‘On the credibility of engineering models and meta-models‘, JSA 50(4):2015]. Some people would say untestability implies a model is not scientific based on Popper’s statement about scientific method requiring a theory to be refutable. However, in reality unprincipled and untestable models are encountered in a range of fields, including space engineering, fusion energy and toxicology. We have developed a set of credibility factors that are designed as a heuristic tool to allow the relevance of such models and their predictions to be evaluated systematically [see ‘Credible predictions for regulatory decision-making‘ on December 9th, 2020]. One outcome is to allow experts to agree on their disagreements and ignorance, i.e., to define the extent of our ontological uncertainty, which is an important step towards making rational decisions about the future when there is deep uncertainty.
Diebold FX, Doherty NA, Herring RJ, eds. The Known, the Unknown, and the Unknowable in Financial Risk Management: Measurement and Theory Advancing Practice. Princeton, NJ: Princeton University Press, 2010.
Spiegelhalter D, Risk and uncertainty communication. Annual Review of Statistics and Its Application, 4, pp.31-60, 2017.
Patterson EA, Whelan MP. On the validation of variable fidelity multi-physics simulations. J. Sound and Vibration. 448:247-58, 2019.
Patterson EA, Whelan MP, Worth AP. The role of validation in establishing the scientific credibility of predictive toxicology approaches intended for regulatory application. Computational Toxicology. 100144, 2020.
While shopping on-line for books during a pandemic lockdown allows you to buy new books, I found it difficult browse online and find new authors. Perhaps because the algorithms employed by the booksellers are too busy guessing my interests or promoting the latest book that they want me to buy. So it was a pleasure to be able to walk into a bookshop again in a couple of months ago. One of the new authors that I discovered was Niall Williams. I have just finished reading his 2019 novel ‘This is happiness‘ which weaves together the life of an Irish village in which nothing ever changes until the coming of electricity, a tale of coming of age and another of burying the past. In the middle of this beautifully-told story, a salesman is extolling the virtues of the electrical gadgets that they can install in their new electrified homes and says that ‘the first law of engineering was to make the world a better place’. The narrator quietly tells us the second law, which the salesman doesn’t state, ‘that without exception everything that was engineered would one day break down … usually one day after each machine had become indispensable to living’. This is a consequence of the second law of thermodynamics, which is that entropy, or disorder, increases in all real processes. Hence, the localised order, which we create when something is engineered, is constantly being eroded until eventually the disorder leads to a break down. Or, as Murphy’s law states ‘Anything that can go wrong will go wrong’. However, the definition of the first law of engineering was the one that caught my eye and resonated with a corny introduction that I used in a talk on why we need to change the way we teach engineering. I played a recording of Louis Armstrong singing ‘What a wonderful world‘ and then talked about the wonderful world that engineers have created before highlighting the unsustainable environmental costs of our ‘wonderful’ engineered world and that it is inaccessible to a large portion of the world’s population. I gave that talk many times to groups of engineering professors in the USA between about 2006 and 2012; maybe I had some impact but there is still a lot of changes needed to achieve a sustainable society. So, the first law of engineering should be to make the world a better place for everyone.
How is your negative capability? The very term ‘negative capability’ conveys confusion and ambiguity. It means our ability to accept uncertainty, a lack of knowledge or control. It was coined by John Keats to describe the skill of appreciating something without fully understanding it. It implies suspending judgment about something in order to learn more about it. This is difficult because we have to move out of a low entropy mindset and consider how it fits in a range of possible mindsets or neuronal assemblies, which raises our psychological entropy and with it our anxiety and mental stress [see ’Psychological entropy increased by effectual leaders‘ on February 10th, 2021]. If we are able to tolerate an optimal level of ambiguity and uncertainty then we might be able to develop an appreciation of a complex system and even an ability to anticipate its behaviour without a full knowledge or understanding of it. Our sub-conscious brain has excellent negative capabilities; for example, most of us can catch a ball without understanding, or even knowing, anything about the mechanics of its flight towards us, or we accept a ride home from a friend with no knowledge of their driving skills and no control over the vehicle. Although, if our conscious brain knows that they crashed their car last week then it might override the sub-conscious and cause us to think again before declining the offer of a ride home. Perhaps this is because our conscious brain tends to have less negative capability and likes to be in control. Engineers like to talk about their intuition which is probably synonymous with their negative capability because it is their ability to appreciate and anticipate the behaviour of an engineering system without a full knowledge and understanding of it. This intuition is usually based on experience and perhaps resides in the subconscious mind because if you ask an engineer to explain a decision or prediction based on their intuition then they will probably struggle to provide a complete and rational explanation. They are comfortable with an optimal level of ambiguity although of course you might not be so comfortable.
Richard Gunderman, ‘John Keats’ concept of ‘negative capability’ – or sitting in uncertainty – is needed now more than ever’. The Conversation, February 21st, 2021.
David Jeffery, Letter: Keats was uneasy about the pursuit of perfection. FT Weekend, April 2nd, 2021.
Caputo JD. Truth: philosophy in transit. London: Penguin, 2013.