Harvard Business Review's video on BrainSwarming has caused a minor stir and I have been swamped with requests to train people on the finer points of conducting this new group process that is modeled on how insects solve problems together (i.e., Swarm Intelligence).
By eliminating talking and having participants contribute to a structured graph visible to all, BrainSwarming has been shown to produce more ideas than brainstorming and in less time. Just as insects leave signals in their environment that influence other members of the swarm, BrainSwarming participants leave briefly-stated ideas on a structured graph for others to build upon. Goal refinement grows downward (see the Figure) and resource interaction (and resource addition) grows upward until the two directions meet, which indicates that solutions are starting to emerge (i.e., people are using the resources to accomplish the goal).
BrainSwarming's silence is ideal for introverts (nearly half of the population): http://ahauniverse.weebly.com/1/post/2014/04/introverts-shine-in-the-silence-of-brainswarming.html
BrainSwarming actually fulfills the original goals of Osborn much better than brainstorming by keeping the good of brainstorming and getting rid of the bad:
Online BrainSwarming is ideal for remote groups working online. Imagine a manager posting a new graph one night with merely the goal at the top and the known resources at the bottom. Imagine this manager waking up the next morning to see what contributions came in from colleagues in Paris, Australia, Singapore, etc. The graph keeps track of all contributions, how they relate to each other, and whether any solutions emerged (i.e., connections between the downward growing goal refinement and upward growing resources).
Online BrainSwarming Incorporates Machine Learning Techniques
The full power of online BrainSwarming only comes into effect when software incorporates my Obscure Features techniques as well as Machine Learning techniques. Since any innovation is built upon what is commonly overlooked (i.e., obscure), all my techniques for uncovering the obscure will run in the background and reveal hidden features, assumptions, and connections as the graph is being constructed. (Contact me to receive a published paper in Psychological Science on my Obscure Features techniques: firstname.lastname@example.org.)
Further, Machine Learning techniques will mine the history of all problem solving activity at the site to find solutions from other problems that are "like" (i.e., analogous to) the current problem. (Contact me to receive a published paper on these particular Machine Learning techniques: email@example.com.)
An eBay or eHarmony for Problem Solving
The final result is a site where some people come looking for solutions to their problems and others come looking for problems to solve. The result is a marketplace or "dating site" where problems and solutions find each other. It is like InnoCentive only with Obscure Features and Machine Learning techniques to make it better. (Contact me to receive a published paper on a fuller vision of this platform: firstname.lastname@example.org.)
BrainSwarming Satisfies Nielsen's Requirements
Michael Nielsen, in his book Reiventing Discovery, surveyed the vast array of attempts to problem solve together online or as he likes to say amplify collective intelligence. Nothing that Nielsen surveyed satisfied all of his requirements, but BrainSwarming does! (Contact me to receive a published paper on fulfilling Nielsen's requirements: email@example.com.)
In sum, the combination of insights from insect problem solving, human social and cognitive psychology, and machine learning and AI (artificial intelligence) make for a powerful new model that could transform how humans problem solve and innovate together.
Contact me to receive published papers on any of these aspects as well as the status of my fundraising efforts to make online BrainSwarming a reality: firstname.lastname@example.org.