In this article we will look at four of these models and methods, ‘Discovery’, ‘Good enough competence’, ‘Knowns and unknowns’ and ‘Awareness of change’. Let us start with the nature of ‘Discovery’.
The nature of discovery
“…great discoveries in science and mathematics often come from leaps of intuition and imagination rather than following a linear scientific method” – Rory Stewart, The Long History of Ignorance
The problem of probing the seemingly infinite possibilities of the future is at first daunting. We are used to applying our intellect and methods to the seemingly knowable present and short-term forecasts. If we look at inspiring pieces of art and creativity, we find a different kind of thinking that can also be pragmatic and actionable.
Consider the architectural masterwork Basílica de la Sagrada Famíliaiv envisioned by Antoni Gaudi. When Gaudi designed the physical support, he used a suspended string model and weights to ascertain the ideal curvatures to bear the load of the soaring roofline.
Sagrada Familia (l) and Maqueta polifunicular (r)
When we work in foresight, we need to make our own leaps of intuition and imagination not only in granular ideas about science and people but also the structures we use. When people forecast, they use projections forward from the present. When we do foresight, we look at possible futures and cast back to the present. For example, consider the difference in outputs a forecast of EV adoption over three years versus possible ten-year futures of :
- Hydrogen energy transport
- Non-lithium batteries
- Mixed energy-source environments
- Post-office based working
Each possible future having an actionable, back cast transition path to the present. In our first contact with foresight, how can we be confident about our ability to work with it? When do we know we are good enough?
‘Good enough’ competence
“Algebra’s like sheet music, the important thing isn’t can you read music, it’s can you hear it. Can you hear the music, Robert?” – (allegedly) Niels Bohr to J. Robert Oppenheimer
A useful mindset in foresight is less about a deep subject matter expertise and more about a wide-ranging generalist and adaptive one. When we work on the possible future, we are constantly learning new things flickering between competence and incompetence.
The ‘conscious competence’ or ‘four phases of competence’ model allows us to situate our learning journeys. In the table below, each level leads to the following one.
Key to the generalist nature of dealing with many possibilities of the future and many components of it, is having a ‘good enough’ competence.
Take quantum computing as an example and run it through our matrix.
| Competence level | Narrative |
| Unconscious incompetence
|
Never heard of it
You’re happy in your ignorance. |
| Conscious incompetence
|
We assume in a ‘hand wavy’ way that it is “another technology improvement wave” and “it just means better and more powerful computing than today.” “It is something to do with indeterminacy meaning beyond binary ‘0’ and ‘1’s.”
It’s not ‘good enough’ competence yet. Sharing your thoughts detracts from you |
| Conscious competence
|
We understand that this is a new paradigm in computing that goes beyond classical computing. Depending on our line of inquiry we appreciate that (1) it will have application to specific types of problems classical computing struggles with (including security) (2) as it becomes more accessible to many people, more uses will be found and (3) it can help us solve complex combinations and large number problems such as the role of cell mutation in cancer.
‘good enough’ competence. High level concepts and high-level implications to the everyday world. |
| Unconscious competence
|
Here we are a quantum expert, and the world revolves around it super positionally.
You might have gone too far but may also have discovered a new career in the process |
We can learn new things, but our understanding of knowledge is that not everything is known of or conceived yet.
Knowns and unknowns
Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know. – Donald Rumsfeld, former US Secretary of Defence
There are many surface reasons that people want to do a foresight project e.g. Future of Spaceflight, while deep underneath is the core drive for discovery. A useful simple model of directing our efforts for discovery is the ‘Rumsfeld Matrix’ you can see in the ‘Awareness-understanding matrix’ below.
Awareness-understanding matrix modified to show Imperial facilities for exploring ‘Knowns and unknowns’ using the example of an electronic vehicle manufacturer. We have indicated where the two methods of insight about the future, expertise and foresight come into play,
| Aware | Not aware | |
| Understand | Known knowns:
Things we are aware of and understand Solution: In place. Example: EVs, battery variants and capacity improvement projections (expertise) |
Unknown knowns:
Things we can understand but are not aware of Solution: Change Scanning + Foresight + Expertise Example: Early-stage developments in battery life extension. (expertise) Possible futures of ICE alternatives (See also Discovery above) (foresight) |
| Don’t understand | Known unknowns:
Things we are aware of but do not understand Solution: Expertise Example: Changes in short term (expertise) and long-term (foresight) age-cohort transport preferences |
Unknown unknowns:
Things we are neither aware of nor understand Solution: Foresight + Expertise Examples: Increase in biothreats (expertise) and possible future impacts upon social behaviour (foresight) |
The above shows how Imperial Tech Foresight (scanning, research and workshops) draws upon Imperial expertise from one of the world’s leading research-driven universities to work in the ‘Not aware’ and ‘Not understood’ spaces above. While people are kept awake at night by ‘Known unknowns’ they are also worrying about their sleep quality tomorrow night caused by the ‘Unknown knowns’ and ‘Unknown unknowns’.
Having discussed models of competence and the territories of the known and unknown, let’s look at developing our awareness of change.
Awareness of change
Superforecasters posited that some people are in fact better at predicting the future than others, and that what sets those people apart is a straightforward combination of open-mindedness, attention to detail, good habits, and a bit of technique – Philip Tetlock on teaming up with AI
The visibility of the ‘Knowns and unknowns’ we mentioned above is not just about how closely guarded they are kept, or their accessibility and understandability is ‘good enough’. They may be in plain sight, but we need to look or ‘scan’ for them. When it comes to scanning for change, we hear a lot of terms used that sound similar in meaning but are not. Here are a few in order of typical execution and granularity.
| Term | Narrative |
| Signals | Discrete instances of change not yet connected to others |
| Trends (foresight) | Named ‘collections of signals’, or rather ‘connections of signals’ |
| Trends (forecasting) | Quantitative driven extrapolations such as computation timelines. |
| Drivers | Long term trends likely to have an impact on the future. Note that in foresight, ‘drivers’ are used to create divergent possible futures. |
| Macrotrends | Pervasive shifts at a global level |
The ‘magic’ in Trends (foresight) are connections, particularly of unlike things, and the implications, particularly to unlike fields.
Connection of unlike things might be, for example, Quantum Computing (discussed in ‘good enough’ competence above) creating a new language to describe it. This leaks into business language, e.g. replacing terms of rules and logic with that of indeterminacy.
Implications to unlike fields might be, for example, Mobile Phones leading to EVs (Electronic Vehicles) due to their pioneering battery development.
Scanning is a subjective activity. We cannot suggest how you shape your eye for topics of scanning, but we can make suggestions for activity. We have a few thoughts for each of the intuitive and structured minds for looking at scanning.
- For structured technique to look for changes, consider using a scanning categorisation such as STEEPV (Social, Technological, Environmental, Political (including governance) and (Human) Values. Categorisation helps us look beyond our silo of preferable focus and expertise into the wider world. For example, consider the important interaction between social behaviour and consumer electronics.
- Others may use less structured and more intuitive approaches such as is advocated by Russell Davies in his book Do Interesting: Notice. Collect. Share. A key aspect if scanning doing this over a long period of time so you can see patterns emerge.
Some example tools to help you, structured around Davies’ simple structure of Notice, Collect, and Share with the addition of Play.
- Notice: Internet RSS feed aggregator e.g., inoreader.com. Publications (specialist, generalist and edge) e.g. The Economist, New Scientist and Monocle Magazine respectively. Conversation spaces e.g. Discord. Organised talks and events for serendipitous meetings with like minds e.g., book launch for Yuval Noah Harari.
- Collect: Physical collections e.g. clippings. Scanned and OCR materials into a searchable library. Internet bookmarks e.g. raindrop.io.
- Share: Distillation into linear thought for presentations, written pieces, videos. Presentation of the material non-linearly for reader navigation. Make this an iterative process of sharing your ideas with people to get feedback on your unique, novel and fringe views.
- Play: Use curated sets of ideas in workshops as provocations or as starting points for orchestration into meaningful content. For example, clustering ideas using post it notes, creating visualisations of collections, creating ‘decks’ of trend cards.
Conclusion
In this article we have explored some well-known mental models and connected them to foresight. Consider this an architecture to model the world and hang your own weights upon like Antoni Gaudi. The appreciation and understanding of the Pre-Futures ways of thinking is a helpful tool as a first contact to the world of foresight work as a client, participant and practitioner.
Imperial and mental models
As a world leading university, Imperial College London uses a swathe of mental models in its research and education. From the Scientific Method used for example in the likes of the Molecular Research Hub in the Department of Chemistry to the concept of the circular economy used in the I3 Lab