The Big Scaling Problem For Social & Organisational Change: The Law of Misunderstanding

Scaling Social Change Leads to the Law of Misunderstanding

The big problem with scaling organisation and social change is the impact of the best ideas appears to diminish as you scale up. The Law of Misunderstanding describes the scaling problem as ideas spread, and increase in scope we tend to see their impact diminish. In the digital age, ideas and concepts spread around the world at an unprecedented rate. With the power of social media and rapid communication, what was once an obscure idea can become a global phenomenon in a matter of days. We should therefore social impact & organisational change increase at scale. But we don’t.

Whilst this increased connectivity and has the potential to inspire innovation, it also has a darker side. The exponential growth of misunderstanding. John-Paul’s Law of Misunderstanding provides a model for understanding this phenomenon. As well as its impact on the spread of information.

Why Does Scaling Social Impact Result in Decreased Understanding?

There are several factors that contribute to the scaling problem of the spread of misunderstandings as ideas that create social impact spread at scale:

• Learning Scaling Problem: Learning happens through context. We gain knowledge through our contextual understanding. This process adds variation to the knowledge as it is learned. The more people who learn the idea and the greater the social spread, the more the potential for variation.
• Changing Contexts Scaling Problem: As knowledge is shared across an increasing number of social or organisational contexts, over space and time, the contexts increase in type and variation from the original context. These contexts inevitably distance the understanding from the original context for the idea.
• Complexity Scaling Problem: Social systems and organisations are Complex Adaptive Systems. These systems tend to follow fractal mathematics and power laws. This means that information spread through a system is likely to follow an exponential distribution as it transmitted through a system. (An spreads like a virus, but also fails like one with increasing ‘variants’)
• Ambiguity Scaling Problem: Ideas that spread socially are always open to interpretation. Wherever they lack clarity or context, they can lead to a wide range of interpretations, some of which may not be consistent with the original intent. This ambiguity is likely to increase over time, changing the understanding of the original idea in ever new ways.
• Communication Barriers Scaling Problem: Differences in language, culture or prior knowledge can hinder the accurate understanding and transmission of ideas.
• Cognitive Biases Scaling Problem: Individuals may unconsciously process information in a way that confirms their pre-existing beliefs or values, leading to a distorted understanding.
• Malicious Intent Scaling Problem Some individuals or groups may deliberately spread misinformation or twist ideas to suit their own agenda. Especially for financial gain. They may intentionally skew and obscure original information for their own social impact.
• AI Feedback Scaling Problem. Now we’ve got AI creating its own version of ideas based on information from the internet. The variation of AI interpretations is likely to create a feedback loop, as information from AI systems goes back onto the internet is used to feed future AI systems. This obscures the original sources of information over time. There is a danger that by creating a self-feedback loop, AI will become increasingly detached and error-prone over time creating an ever increasing scaling problem as ai feeds back on itself. (This could have huge implications for the future of AI)

Science Shows us The Future is Unpredictable.

In a previous post I explain 12 scientific reasons the future is unpredictable. By definition if the future is changing that means the information about what worked in the past is becoming ever less relevant and out of date. In fact as we move further into the future the past information becomes exponentially more irrelevant and out of date. Sure it may have worked it might still do. But the chance of it not working is ever increasing. To keep making an impact we increasingly need to update and adapt historic knowledge.

What is John-Paul’s Law of Misunderstanding?

“As a model or idea spreads through social systems, the number and types of misunderstandings about it increase exponentially”.

John-Paul’s Law of Misunderstanding

I’ve coined this ‘law’ to describe the scaling problem of how the more popular an idea becomes, as does it’s social impact, the more likely it is to be misinterpreted, misconstrued or distorted by humans (and AI). As the original insight and meaning of the idea becomes increasingly obscured by the ‘noise’ of different interpretations of the idea.

Consequences of The Law of Misunderstanding on the Problem of Scaling Organisational Change & Social Impact

The exponential growth of misunderstanding as ideas are shared has several consequences for the scaling problem of social impact:

1. Dilution of the original idea: As misconceptions multiply, the core insight of an idea may be obscured or lost altogether.
2. Misapplication of ideas: Misinterpretations can lead to inappropriate or harmful applications of a concept, resulting in unintended consequences.
3. Exaptation: Misunderstandings can be a source of exaptation, leading to new ideas that are useful or beneficial. This in turn leads to further obscuration of the original idea.
4. Polarisation: Misunderstandings can lead to disagreement and conflict between different groups with opposing interpretations of the same idea. The more an idea is misunderstood, the more it is likely to be affected and come into conflict with other ideas, further distancing itself from the original meaning. A unifying ideas can be distorted into becoming a divisive one. e.g. concepts around socialism.
5. Discrediting the idea: An accumulation of misunderstandings can eventually undermine the credibility of the original idea, even if the idea itself is sound.
6. Stifling innovation: Creators may fear that their idea will be misunderstood. Fear of misinterpretation can deter individuals from sharing new or controversial ideas, limiting the potential for growth and innovation.
7. Originator Drift: Even the originator of an idea can adapt and distance himself from the original idea over time. No idea can be 100% faithful to the moment it was conceived.
8. AI Error Catastrophes: AI systems will inevitably progress towards error catastrophes if the information used for the models is based on AI outputs.
9. Human Error Catastrophes: As the social impact of idea increases and the misunderstanding of the idea also increases it means that unless action the social impact of an idea will decrease over time. The idea then is likely to become misaligned and discredited as a result. This would explain why and how why we see ideas go ‘in and out of fashion’, as they spread then decrease in impact and effectiveness.

10 Principles to Mitigating the Negatives of Scaling Problem of Social Impact and The Law of Misunderstanding

While it may be impossible to completely prevent misunderstandings from occurring, as we scale organisational change and social impact, there are steps we can take to mitigate the negative scaling problem for social impact:

1. Focus on the Original: Maintain primary sources as the main source of meaning and interpretation of an idea.
2. Keep things small: If scaling acts as a multiplier of misunderstanding it is better to have many small projects were a small group can focus on the idea. (This might help explain why small projects have a much higher success rate than larger projects.
3. Keep things simple: The more complex an idea the more room their is for misunderstanding.
4. Clarity in communication: Aim for clear, concise and precise language when communicating ideas to minimise ambiguity. Try to be grounded in known facts that are difficult to reinterpret.
5. Provide context: Provide background and context to help others understand the origin, purpose and limitations of the idea.
6. Encourage open dialogue: Foster an environment where questions, clarifications and diverse perspectives are welcomed and encouraged.
7. Engage in active listening: Make an effort to truly understand others’ ideas and seek clarification when needed.
8. Encourage critical thinking: Encourage individuals to evaluate information carefully, question assumptions and consider alternative viewpoints.
9. Make sure an idea is linked to practice. Practice will keep an effective idea in use.
10. AI must base it’s information on primary evidence. Not from AI generated content. This could create an ongoing dependency on humans (not a bad thing).

Social Change & Impact Leadership and The Law of Misunderstanding.

Much of the leadership of intentional social impact solutions relies on our understanding an interpretation of ideas. This creates the scaling problem for social change. Two models are very helpful here. The OODA loop with its emphasis on Bayesian Logic, means that we are asked to treat our ideas as hypothesis to be tested. Whilst it cannot stop us misunderstanding an idea, it can tell us whether the application of the ideas is working in the real world. Indeed this law provides a strong argument for use of the OODA loop in decision making, rather than assume our interpretation of an idea is correct.

The Cynefin Framework is also very helpful in helping in addressing scaling problems as it helps us adjust our decision making to the context we are in. By encouraging us to split our perspective between ordered and disordered domains, we can identify which aspects of an idea may be simple observable and therefore be testable. Whilst distinguishing from aspects that are complex where we cannot know whether an idea is true or not. By focusing on the ‘knowable’ aspects of a idea we can help improve our learning and understanding and future decision making.

The Hierarchy of Social Intervention is a useful tool for scaling social change. We can minimise scaling problems by working at the right level where information for decisions is strongest. It can help with understanding the right level to interact with to better target social interventions. Based on the principal of making decisions where the best level of information exists, it also enables us to test our ideas. By making decisions close to the optimum level of information it allows us to sense check the ideas we use with the information to ensure there is a practical way of acting to create social impact.

The Origin of the Law of Misunderstanding

I had long noticed that scaling social change has often worked on a small scale. But as the projects are scaled up their appeared to be a real scaling problem as their social impact appears to diminish. This is also reflected in Rossi’s Iron Law. “The Iron Law of Evaluation: The expected value of any net impact assessment of any large scale social program is zero.”

Rossi’s Iron Law of Evaluation: The expected value of any net impact assessment of any large scale social program is zero.

Peter H. Rossi

Having worked in the NHS I’ve seen a multitude of grand plans. All of which talk about scaling up, but never address or understand scaling problems. The latest being the Long Term Plan all of which promise to improve prevention and through scaling up local pilots into national impact.

Though undoubtedly well meaning they completely ignore the long history in the NHS of scaling problems being a challenge. (Hence their endless and completely ridiculous complaining about ‘ Unwarranted variation‘. As if sameness of human systems was unnatural). These all end up drifting into nothingness such as they scale up failure to scale up the Vanguard sites (Much trumpeted in the ‘5 year forward view’ which optimistically promised a ‘a radical upgrade in prevention and public health”… from 2014 to 2019. This does not seem to have quite happened.

This is not limited to the NHS and we can see no end of proposed social initiatives being promised by local and national government ‘based on promising research’. Whilst the sad reality is social and economic disparities and associated negative social impacts appear to be mercilessly increasing.

Surely this should be reversed by the better sharing of information online. I have noticed that there is a lot of high-level discussion and debate on social media about what ideas or concepts mean. And what the author originally intended. This seemed to be accompanied by people who clearly misunderstood the discussion becoming increasingly involved in trying to debunk the idea. Creating more misunderstanding. For me the misunderstanding in communications is at the heart of the scaling problem.

I’ve seen this pattern happen repeatedly, and find that the ideas seem increasingly ‘lost’ in the debate. I propose this ‘law’ because the recognition of the idea gets lost as it increases in social impact and spreads through society. Based on the thinking i set out above as well as my understanding of complexity and the mathematics of communication.

Proof of the Law of Misunderstanding.

Of course, this idea itself is susceptible to misunderstanding. So I hope that this law will be shared and spread widely until it is itself completely misunderstood. So increased misunderstanding of the law of misunderstanding may itself prove of the Law of Misunderstanding. Although the proof itself is also likely be misunderstood as it is communicated.

In seriousness, this is measurable. I’m sure that we can track the fidelity of an idea, and how it varies in description over time over the internet. It’s criticial to our interconnected human ear that we get to grips with the problems of scaling. It would be good to see what the relationship to variation is. It may not be truly exponential as ideas also get revived and rediscovered. But it seems pretty clear that it becomes increasingly hard to keep true to an original idea as we scale up and that it is a very significant challenge to scaling social impact.

This may seems like silly idea. But AI and the spread of knowledge is important. Yet it’s clearly not working. If our best ideas break down over time how can we achieve social impact at scale. This is not an insignificant problem.

Disproving the Law of Misunderstanding.

I set out 10 principles for mitigating the problem of the law of misunderstanding. However, taking a Bayesian logic perspective. It does not necessarily matter if an idea is misunderstood. What really matters if an idea inspires desirable change in the world and ‘works here’. It is far better to have a positive impact even if the idea itself is not exactly the same as it’s inspiration. As long as the intent and action have a positive impact, it doesn’t really matter if it is the result of a misunderstanding.

Conclusion

Their is a big scaling problem for organisational change and social impact, As ideas continue to spread rapidly in our interconnected world, it’s vital that we recognise and address the challenges posed by the Law of Misunderstanding. By striving for clarity, openness and critical thinking, and by focusing on original sources, we can help minimise the harmful effects of misunderstanding. While working towards a more informed and collaborative global community. In reality though we must primarily be focused on the results. Misunderstanding can also be opportunity to have even better more effective ideas.

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