Great men and women of history are a subject of fascination. When their greatness is due to the quality, novelty, and impact of their ideas, they are often called geniuses. Limiting the concept of genius to purely academic / research / engineering, we can define genius as being the first to seriously explore high impact ideas.
Ideas don’t exist in isolation and are connected to other ideas via reasoning such as deduction, inference, intuition, etc. In this sense we can envision the world of ideas as a large graph. Nodes are ideas. Edges are the transition of one idea to another in a chain of thought via some reasoning mechanism. Not all nodes need to be true ideas, and not all edges need to be logically consistent transitions. But out there in the vast universe of idea space are ideas yet unexplored which have great consequence at an individual scale and at societal scale.
Now we can think of genius as a search problem. Historical geniuses achieve the title in retrospect for having seriously explored a cluster of idea space that was previously unknown and highly impactful.
Search problems in graphs are a familiar problem in computer science and mathematics and have been studies for many decades, if not centuries. We can reason a bit about factors that increase the chances of exploring these new frontiers of idea space:
- Where you start in idea space.
- The search process.
- The total amount of idea space explored.
These aspects are multi-dimensional (more than one thing can influence it). Some of it may depend on chance, creativity, or innate ability, and to explore idea space in a way of historic significance perhaps requires that. However, there are still factors within the control of the everyman. A non-exaustive list might include:
- You can choose where to start.
- You can choose the effort or persistence you put into exploring idea space.
- You can choose the tools available to explore idea space.
If the goal were to explore beyond the frontier of idea space, you might start on a problem that nobody has seriously explored, perhaps because it’s not thought to be possible, practical, or profitable. Hard work and persistence give you the best chance of exploring the most you can in the limited time you have. The tools you might use may be things like new technologies, existing technologies used in new ways, new data, new theories, etc. The tools you use can inform your search process by allowing you to traverse edges in idea space that might not otherwise be possible.
If this search problem ideation is correct, it naturally suggests the pitfalls to avoid. Such a scenario might look like starting on a high-visibility problem that is thoroughly explored (e.g. I’ve heard todo list apps and dating apps are very common software startups). The problem may have no or weak personal significance, making it hard to persist after so many failures, when nobody believes in you, and there is little financial incentive to keep trying. And there may be no differentiator in the toolset used compared to those who have come before you and failed.
I think it’s likely difficult to know where the frontier of idea space lies. For all we know the frontier of idea space may be all around us, limited only by capabilities of the human brain. Everyone one super-human deduction away from something extraordinary. Who could have guessed that classical blackbody radiation would be so close to the frontier of quantum mechanics, or number theory so close to the frontier of cryptography? That said, the most predictable frontiers are likely where the problems are. Problems themselves represent a lack of adequate solutions. Either the laws of physics define the boundary of what a solution might look like, discoverable in idea space, or the solutions exist, also discoverable in idea space.
There’s much that can be written about this search problem but my goal was to articulate impactful ideation as a search problem. If there is one inference that I think should be made, it’s that we should think strategically about how we might push past existing frontiers in idea space to solve problems. The gap all problems and their solutions is just a collection of paths in idea space.