Deep uncertainty and meta-ignorance

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Decorative imageThe 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.

References

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.

Are these the laws of engineering?

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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.

Reference:

Niall Williams, This is happiness, London: Bloomsbury Publishing, 2019

Negative capability and optimal ambiguity

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Decorative photograph of sculpture on Liverpool waterfront at nightHow 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.

Sources:

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.

Noisy progressive failure of a composite panel

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Photograph showing close-up of progressive failure in a composite materialComposite materials have revolutionized many fields of engineering by providing lightweight strong components whose internal structure can be tailored to optimise their load-bearing capabilities. Engineering composites consist of high-strength fibres embedded in a lightweight matrix that keeps the fibres in position and provides the shape of the component.  While many composite materials have an impressive structural performance, some also exhibit spectacular failure modes with noises like guitar strings snapping when fibres start to fail and with jagged eruptions of material appearing on the surface, as shown in the image.  A year ago, I reported on our work in the DIMES project, to test the capabilities of our integrated measurement system to detect and track damage in real-time in a metallic section from an aircraft wing [see ‘Condition monitoring using infrared imaging‘ on June 17th, 2020].  Last month, we completed a further round of tests at Empa to demonstrate the system’s capabilities on composite structures which have been tested almost to destruction.  One of the advantages of composite structures is their capability to function and bear load despite quite high levels of damage, which meant we were able to record the progressive rupture of one of our test panels during cyclic fatigue loading.  Watch and listen to this short video to see and hear the material being torn apart – ignore the loud creaking and groaning from the test rig, it’s the quieter sound like dead leaves being swept up.

The University of Liverpool is the coordinator of the DIMES project and the other partners are Empa, Dantec Dynamics GmbH and Strain Solutions Ltd.  Airbus is the topic manager on behalf of the Clean Sky 2 Joint Undertaking.

The DIMES project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 820951.

 

The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.