Patterns of change & conflict 3 of 3

There is a little of the old and the new in the imagery I have used in this post.  I took the banner picture on an evening walk along the Ridgeway from its official start on Overton Hill.  The Ridgeway is one of the ancient pathways in Europe, and it can be walked as far as Ivinghoe Beacon, which is around 90 miles in length.  It takes the high ground on the chalk downs and has been used since prehistoric times.   It is one of my sunset locations when I have limited time.  One of the reasons for that is that all the ancient barrows are covered with trees, which form a unique silhouette on the horizon in Wiltshire. Still, I also like to get into the trees at times, and there is a cluster of three barrow mounds just off the main Ridgeway, one of my favourite places to sit and think as the sun goes down, although I do not linger past twilight.   It is a landscape that (Wo)man has patterned over thousands of years, and you can read the patterns when you become familiar with them.  Some can be taught, some have to be experienced, and some can only be known in the act of knowing.  In reading the landscape, we can sense when something different is happening; we pay attention to anomalies and ignore the routine.

My other image to the left shows patterns from a project we ran last November in Washington to look at attitudes toward AI, and the material is in the public domain.  Yesterday, Anna wrote an excellent post on our long-running open-source narrative capture project, which is a part of our climate and sustainability programme and shows similar images.  For those unfamiliar with SenseMaker®, we combine the persuasive narrative in the form of stories, observations, opinions and so on with the objectivity of numbers.   Triads have a lot of science behind them in triggering a cognitive load (in contrast with a linear scale) in that the respondent cannot guess what response would reflect them in the best light.  Balancing three positive qualities also makes you think more deeply, especially on tablets and smartphones, where there is a tactile element to placement.

Another crucial element to SenseMaker®, and is epistemic sovereignty, is the right of any individual to interpret their own experience rather than have it interpreted by an algorithm or an expert.  That principle also extends to our work on reducing bias from facilitation and an over-dependency in organisational design and change initiatives to depend on workshops.  This is not to deny their value, but there are issues with even the most gifted in avoiding influencing the group, and that is before we get to the pseudo-psychological facilitator at the end of the spectrum between pragmatism and ideology,  when the facilitator has firm ideas about their capacity to extract the real meaning of what people are saying.   We also see anthropological criticism of Participative Action Research in privileging those participants who match the cultural expectations of the facilitator.  None of this is deliberate, by the way; it just is.  The visuals I have shown here don’t make causal statements, but they do represent patterns.

I’ve also shown two perspectives here.  They are also slightly different in style; I did think of getting them the same but decided, instead, that it shows there are options in SenseMaker® for analysts and decision-makers.  Now, for each triad, I could have had three Likert scales, but then they could all be scored high; by getting people to balance three positive qualities, we get much closer to how they feel.  It also means we need fewer checks and balances and can reduce the response time burden.  We recommend feeding the results back to participants within a day or so of their entry and gathering how they interpret the patterns revealed – make it a consultative operation, not another survey.  The feedback from that can also be stored in narrative form, and we start to build a lessons-learning database, narrative-based, which allows for peer-to-peer knowledge flow.

The triads in question are testing the motivation for using AI. We see the hyperfocus on convenience in the first and a more nuanced approach in the second between convenience and intrigue.  That could be between different groups, or it could change over time.  You can see how this works to manage the five things we need to do from the second post in this series.  We haven’t got any complex statistical reports; we have a straightforward set of patterns requiring little knowledge for active sense-making.  They also ask straightforward questions: Why do we see it like this, and they see it like that?   Creating anomalies, showing differences and critically making no judgements.   And, of course, I still have the original narratives to go with the data.   I’ve shown below one of the slides we put together on this project to illustrate that.

Once you have that data, the change mechanism is pretty simple; you ask the question: How would we create more stories like these and fewer like those?  The context is carried with the question; it requires no elaboration or specialist knowledge, and there is nothing about abstract qualities, causal factors or whatever.  And given it’s based on mass input with qualitative data, I can measure if that change is being achieved.  In effect, we measure vectors, not outcomes; we manage shifts from where we are rather than fantasising about some ideal future state.  Going beyond that, I can present the visuals for the organisation or any part thereof.  So people are only asking the vector question (How would we create more stories like these and fewer like those?) at their level of competence to act.  Rather than a one size fits all change programme, we have a context-specific one with multiple small initiatives that will align the organisation over time.  That also allows us to adjust our direction of travel as we go.  And, of course, we can confidently combine triad data into full landscapes. Still, people have to trust the results:  Landscapes are more valuable in that no one can trace input to output, but equally, they require more trust for precisely the same reason.

In the work we are about to start on citizen engagement, we can also use this technique, at scale, to identify issues which warring factions have in common and algorithmically trigger micro-investments to get them working together. At this point, they can talk about their differences when they are ready to do so.  The same technique and the Triopticon can be used for trans-disciplinary and cross-silo work in organisations.

Everything is about patterns and responding to patterns.  Next week, we will launch some easy-to-get-started options for organisations in cultural change and AI awareness.  I’ll blog on the latter tomorrow or the day after.  But what I have been doing here since the conclusion of the Twelfetide series is to lay down the reasoning behind this approach.  Next week, there will be more of a marketing focus.