Generating Knowledge

The Amazing Jelly Bean Experiment

Treynor asked his class to estimate how many jelly beans there were in a jar. When added together and averaged, the group's estimate was 871— there were 850 beans contained within the jar. Only one student had made a better guess (a rogue genius, if you will). The now historic jelly-beans-in-the-jar experiment showed invariably that a group estimate is superior to the vast majority of individual guesses on a consistent basis.

Granted, there are limited situations in which knowing the amount of jelly beans in a jar is a significant accomplishment. Nevertheless, this example can be found a book by James Surowiecki called The Wisdom of Crowds. In his book, Surowiecki demonstrates myriad situations where the many are smarter than the few.

"If four basic conditions are met, a crowd's 'collective intelligence' will produce better outcomes than a small group of experts, Surowiecki says, even if members of the crowd don't know all the facts or choose, individually, to act irrationally. 'Wise crowds' need (1) diversity of opinion; (2) independence of members from one another; (3) decentralization; and (4) a good method for aggregating opinions." —Publisher's Weekly

To validate knowledge, we need to share it with many others and aggregate feedback because they will attest through their own experience (and not only logic) that the information you present is true or need some adjustment; in the diagram below only when you combine information + experience + collaboration or K=D+P+C, then you’ll get validation and better comprehension of a given theory and practice. In other words, you can learn something new through I+E , but you’ll find that there are situations where either it does not apply, or there are other conditions that you as a group need to take into account. Much like developing a new device, only when many people use it under different circumstances you’ll learn how to make it better. Even if your team is talented, they won’t be able to come up with every possible situation where the device might fail. Knowledge is only useful to humanity in the degree you share (it) and collaborate with others. The more you collaborate, receive feedback and incorporate others ideas, the more proof and wisdom you’ll have.

With these elements clear, from the IT perspective, we can transform the concept into a real software application that might transform the way we work today.

The Internet is proving what collaboration is capable of. As of today (May 2006) I can find many examples where the Internet is breaking every paradigm and industry upside down. Real state, publishing, Sales, marketing, just name it, and you'll see a tidal wave coming if not already happening. This is the effect of human collaboration at great scale.

The Model

The interaction generates information between data and collaboration and data and processes. In a big sheet of data, bring it into Excel(Computer program), and then make operations like Sum, Avrg, or filter the information, sort it, etc. You get information (more insight) from applying a process (in this case math operation) to the data. Same can be said about having data and collaboration. Sitting in a room with a team of people and sharing data, can give you valuable information, but different from what you get by applying a process. There is a limitation in how effective is having many people in one room sharing data, as automated processes can deal with vastly more data in a short period of time than what many people can quickly exchange through words. By simply having data combined with collaboration you get more insight, but still, you need process(es) to gain accurate information.

The interaction between processes and collaboration is what I call experience. Many iterations of it bring expertise. An example: Let say you want to take the bike you learned to ride and want to go up the mountain. The process defines that you will be successful and gain experience only if you finish going from the bottom to the top. If you decide to stop 1/4 or half way, is not the same as if you complete the journey or ultimate goal, the top of the mountain. Another example is the process of buying a house. The goal is to purchase a property and have it under your name. Going through the steps but falling short at closing, does not mean you already "know" how to buy a house. Finishing the process is important in earning true experience, if you don not , then you only know parts of it. One byproduct of not completing the process is cost. In the bicycle example would be psychological cost, in the house example is monetary cost and probably both.

All elements interacting as a whole is what makes rational knowledge come true from different points of view (ways of thinking), opinions, and experiences.

There are three major areas in modern society that generate knowledge. Those are: Scientific Community, Marketing research companies and intelligence agencies. Two are prime examples of the model and one is a sad example of what happens when you have two out of three elements. First example: the scientific process or discovery. After developing a theory through observation or practice and after gathering data through trials, experiments, etc, the scientist creates a paper, or document detailing his (her) findings. The reason of publishing in a magazine is to have a wide audience so that ideas can be refuted or enhanced. I call it performing wider collaboration. You want people to collaborate with feedback on your ideas to see if there are holes or parts missing ( as I did in this book), or if there is some unknown case where the theory does not apply.

The Internet is the by-product of scientists wanting to collaborate with a wider audience , making it even easier to accomplish it, and it is why Tim Berners Lee created the World Wide Web html scheme (and did not patent it or charged for it). The Internet is the biggest collaboration project in human history. The effects are rippling through every business, forcing many to reassess and rethink every business strategy from scratch.
The second example: Marketing companies like Gartner, IDC, and Forester rely on collaboration to bring insights to their clients. That insight comes in the form of surveys that when combined with statistical research, data and other elements provide extremely valuable insight or knowledge to someone. People have to be willing to fill out the surveys, in order to get meaningful and accurate data.

Some people do not see how collaboration plays a role in acquiring knowledge. One way of testing the theory 'without collaboration you do not have knowledge' is by looking at what happened in 9/11. Simply put, a lot of intelligence agencies had a lot of information, but no sharing and collaboration was taking place. Hence you actually don't "know" what is going on in order to take Action. So if you have information , but do not share it and collaborate around, the outcome is simply you still have information, because many times the person responsible in doing something about it is not the same one holding the information in this case. Hence, knowledge (the rational side of it) requires collaboration between groups so that proper action can be taken. This translates into "the wider the audience, the more points of view you get, the closer to actual knowledge you will get”. Another example I remember reading on the web, was about how the military use scientists to discover secrets on advance technologies (Flying devices) they have but that they did not create. In a very secretive environment, they expect a single scientist locked in a room to come out with all the knowledge on how these advanced technologies were built. My conclusion from it is that in a secretive setting, you can't go much further in understanding the unknown without collaborating with more people.