Introduction
It is commonly found that:
Creativity is often found at the intersection of different knowledge areas.
The reason for this truism is that if you try to solve a problem using only knowledge that is found in a single field, the resulting solution must occur within that field’s established boundaries and foundational assumptions.
This means to say, since all knowledge within that field is a demonstration of the basic principles of the field, therefore regardless of the specific knowledge you apply, you are always operating under the same set of principles, and so are limited to finding only those solutions that can be stated using those basic principles.
In Other WordsFields of knowledge act like “thinking substrates.” Each field—whether it’s mechanical engineering, biology, data analytics, or fine arts—has its own common assumptions, methods, and conceptual frameworks. These bases form a mental bedrock that shapes how problems are defined and approached. Although new ideas do emerge within a single domain, they are typically incremental improvements that involve recombining or refining the same shared elements. However major leaps in originality can be hard to achieve within a single domain, because the fundamental ways of thinking remain anchored to the same “thinking substrate.” |
Subsequently, in order to achieve true creativity, it is often necessary to combine knowledge from different areas. This is because once you bring in knowledge from another field, the conceptual frameworks of the two fields can “collide” in a useful manner.
The second field’s mode-of-thinking introduces assumptions, tools, and mindsets previously unknown or underused in the first field. This collision can upend old assumptions, spark imaginative solutions, and produce truly original ways of seeing the issue and finding a solution.
Knowledge Domain Dissimilarity and Information Gain
Assuming that what we have stated is correct, it stands to reason that the more dissimilar the areas of knowledge being combined, the more likely we are to come to a novel conclusion.
This is because dissimilar areas of knowledge approach problems and concepts in fundamentally different ways. Therefore, by bringing them together, we create an environment where diverse modes of thinking intersect and we significantly increase the probability of arriving at innovative conclusions.
In Other WordsThe basic proposition is that when you combine two (or more) fields of knowledge that are as different from each other as possible, you stand to gain a higher level of new insight—or “information gain.” This is because truly dissimilar systems have the least conceptual overlap, so when their ideas collide, they can generate the most unexpected and fruitful solutions. The further removed two domains are from one another, the more surprising—and thus more fruitful—their conceptual synthesis is likely to be. The upshot is simple: if you want genuinely novel insights, look for a form of collaboration that breaks out of the standard frames within a single field and instead leverages expertise from another, quite distant discipline. |
In summary: the more different (or dissimilar) two fields are, the fewer overlapping concepts they share, and the greater the potential for something radically new to emerge when you merge them.
Creativity in Solving Real World Problems
Solving real-world complex problems often requires insights and expertise from multiple domains. This is why organizations frequently assemble teams of experts from diverse fields, each bringing their unique perspectives and skills to the table.
However, when experts from various backgrounds collaborate, the way their knowledge is combined can significantly influence the creativity and effectiveness of the solutions developed.
This raises an important question:
Can we devise a methodology that strategically combines expert knowledge to maximize creativity and achieve the most innovative outcomes?
Based on the idea of information gain through knowledge domain dissimilarity, we can propose a structured methodology to enhance creativity and innovation in problem-solving. This approach ensures that the combination of diverse expertise leads to novel and effective solutions.
- Identify All Relevant Fields
Start by listing the knowledge areas or departments that can possibly contribute to solving your problem. For example in a corporate setting, this might include marketing, finance, design, IT, operations, and so on. - Rank Fields by “Conceptual Distance”
Next, estimate how different each field is from the others. For instance, finance and accounting might be closely related, while finance and user-interface design could be considered far apart. The more distant two fields are, the less overlap they share in terms of assumptions, methods, or “thinking substrates.” - Combine the Most Dissimilar Fields First
Instead of beginning with the easiest or most obvious pairings, deliberately start with the fields that have minimal common ground. This is where the biggest “idea collision” can occur—where you’re likely to get fresh or disruptive viewpoints that neither field would produce on its own. - Iterate and Layer in Additional Fields
Once the initial insights have emerged from that high-contrast combination, bring in the next most distant field. Each new perspective adds another layer of creative input, building on the novel foundation already established.
By sequencing in this order—most dissimilar to least—you maintain maximum openness to creative and innovative ideas at every step. - Refine with the Closely Related Fields
After you’ve tapped into truly novel directions, then circle back to the fields or departments that are more conventionally associated with the problem. They can help refine the radical ideas, testing feasibility and ensuring alignment with practical goals (e.g., budget constraints, regulatory requirements, company culture).
This methodology ensures you systematically extract—and then refine—the greatest creative potential from the diversity of knowledge within your organization (or across disciplines in any collaboration).
A Practical Example
Let’s use ChatGPT (o1) to apply the methodology of starting with the most dissimilar fields first, to address the issue of the increasing prevalence and severity of wildfires globally.
The following output was generated by ChatGPT o1 based on a prompt which consisted of this entire blog post plus a request for a solution to increasing global wildfires:
A Practical Example: Tackling Increasingly Severe Wildfires Using a Contrast-Driven ApproachWildfires have grown in frequency and intensity worldwide, posing significant threats to ecosystems, property, and human life.
Traditional firefighting measures and environmental policies often aren’t enough to cope with these escalating challenges. To devise novel, more effective strategies, we can apply the methodology of combining the most dissimilar fields first, leveraging AI to tie them all together in a concrete, data-driven approach. Step 1: Identify All Relevant FieldsFor a large-scale, complex issue like global wildfire management, a variety of expert domains is crucial. Potential contributors might include:
Step 2: Rank Fields by “Conceptual Distance”We look for pairs of fields that seem to share the least in common—those where the “thinking substrates” are most distinct:
From this rough assessment, Climate Science and UX Design appear to be the most distant in conceptual terms. One is hyper-focused on scientific data and modeling; the other is built around human interaction and experience. Their overlap is minimal, which maximizes the potential for creative “idea collisions.” Step 3: Combine the Most Dissimilar Fields FirstClimate Science + UX Design Climate Science Contributions:
UX Design Contributions:
Outcome of the Initial CombinationFrom this high-contrast synergy, the team develops a concept for “FireSense Dashboard”:
Even at this early stage, the product breaks new ground because it merges the granularity of climate data with a deeply human-centered design ethos—a stark departure from many existing tools that are technical yet not user-friendly. Step 4: Iterate and Layer in Additional FieldsAdding AI & Data Science With an initial framework in place, we bring AI & Data Science into the mix:
New Integrations
Why This Matters The synergy between climate data, user interface design, and AI-driven analytics amplifies the tool’s usefulness. Emergency managers can now see real-time data on how a fire might evolve in the next six hours, displayed in a manner that is instantly understandable to both technical experts and laypeople. Step 5: Incorporate Insurance & Risk AnalysisTo make the solution financially robust and widely adoptable, we next introduce Insurance & Risk Analysis:
Benefits
Step 6: Refine with Forestry & Ecology, Emergency Management, and Public PolicyFinally, we loop in Forestry & Ecology alongside Emergency Management & Public Policy—the more traditionally associated fields: Forestry & Ecology:
Emergency Management & Public Policy:
By incorporating these closer fields at the end, the project gains essential validation, feasibility checks, and policy frameworks to ensure that the creative ideas from earlier stages can be successfully executed on the ground. Concrete Results: “FireSense Ecosystem”Real-Time Wildfire Risk Monitoring:
Enhanced Community Engagement:
Incentivized Risk Mitigation:
Data-Driven Forestry Practices:
Policy Alignment:
Performance Metrics
Why Starting with Dissimilar Fields Makes All the Difference
ConclusionThe severity of global wildfires calls for innovative, data-driven solutions that step beyond traditional siloed approaches. By systematically combining the most dissimilar fields first—climate science and UX design—this FireSense initiative unlocked an entirely new way of visualizing, predicting, and mitigating fire risks. Gradually layering in AI, insurance analysis, and established fields like forestry management and public policy refined these innovative ideas into a powerful, integrative platform. This methodology of leveraging knowledge dissimilarity for information gain illuminates how even the most daunting, complex problems can be tackled with unprecedented creativity and efficacy. Starting with starkly contrasting perspectives lays the groundwork for breakthroughs that redefine what is possible, a lesson that holds true not only for wildfire management but for nearly any complex challenge in our rapidly changing world. |
Conclusion
Assuming a theory of Knowledge Dissimilarity Information Gain, we can posit a strategic approach to problem-solving that emphasizes the deliberate combination of conceptually distant fields.
Using this method, when tackling a problem, you can:
- Identify Fields That Are Conceptually Distant: Start by selecting knowledge areas or departments that operate on fundamentally different “thinking substrates.”
- Fuse Their Insights or Methodologies: Integrate the distinct approaches and tools from these disparate fields.
- Seek Subsequent Fields That Are Most Distant from the Newly Formed Hybrid Approach: Continue to layer in additional fields that maintain a high level of conceptual distance from the existing hybrid. Each new layer introduces fresh methodologies and viewpoints, further expanding the creative potential and depth of the solution.
By doing so, you can maximize the potential for groundbreaking innovation and creative problem-solving. This methodological approach leverages the minimal conceptual overlap between diverse fields to trigger significant information gain, resulting in solutions that are effective, original and transformative.
