Thousands of things we call innovations are actually more like transplants. In Guns, Germs, and Steel, Jared Dimond makes an excellent case that most radical changes in society come from ‘solutions in search of problems.’ Abraham Flexner, in The Usefulness of Useless Knowledge, makes a similar point: many great inventions were founded on pre-existing knowledge that some scientist discovered to satisfy curiosity.
How often have you thought of an excellent idea, only to realize that you are in no position to carry it out? This happens commonly for me, not just when I have ideas, but when others pitch them to me. My response, is ‘sounds like a good idea, but not for me.’
The research institutions of the world are all busily amassing a pool of knowledge, often without any particular application in mind. Yes, of course some research is targeted, but less than we all would like to believe. The truth is that academic research lives disconnected from practicality. While many researchers are also teachers, unfortunately their interests are often too narrow or advanced to spill into teaching. In addition, researchers are often not as motivated to teach as they are to research.
Frequently, in conversation, I realize how much knowledge I have about my area of expertise that others don’t. Conversely, I often realize how uninformed I am about many, many things outside of my expertise. Most knowledge has a diffusion problem. You may think the internet has made this better, but it’s not true. The internet has increased access, so knowledge is now reachable, but it has also flooded all of us with so many new avenues to pursue that we can’t keep up. Our brains have insufficient parking to absorb the output of the information superhighway.
All of this points to two major possibilities for innovation:
In order for society to advance at a rapid pace, we can’t waste time with unimportant knowledge. Knowing which celebrity married and divorced which other celebrity just doesn’t help very much. We need to remove the noise, and leave the important stuff.
News aggregation websites are excellent tools, because they effortlessly sort news, but they often fall victim to the voting biases of the community. Hacker News is one of the best in the category, but it is perhaps a bit too narrowly focused.
Magazines are the other end of the spectrum: carefully selected articles of high quality. The Economist is the shining example here, in my opinion. But, like Hacker News, it requires very sophisticated readers, and there is a huge amount to digest. Reading every issue of The Economist cover to cover is a part-time job. (I know, I did it for a while.)
There is a solution out there, waiting to be had, and perhaps machine learning holds the key. The best fix is one that can handle a large quantity of content, and select the stuff that has the highest potential to be new, interesting, and useful to the highest number of readers. I have no idea what training data might allow for tuning an algorithm, but the goal is clear: select content which leads to the generation of new solutions (as opposed to the content with the highest consumption value.)
The Economist recently ran an interesting story about spaghetti code. The idea was that academics write novel programs that solve difficult problems, but they don’t make it easily accessible to practitioners. Some firms have started making a business of translating this ‘spaghetti code’ into more industry friendly code.
There is no reason one can’t mine this principle for new businesses. Stackoverflow has a large source of problems and solutions. It would be straightforward to find things with a high degree of value but a low degree of user-friendliness, and turn them into products. Amazon has a habit of taking tools it uses for operations and spinning them off into market-facing products. Academics publish new, amazing findings every day, and there is a vast opportunity to translate the jargon into simpler language for a popular audience.
For useful new ideas to blossom into real solutions, the right knowledge needs to make it into the hands of those with the right skills. Without this, new information is like the proverbial tree falling in the forest that nobody sees.
For some reason, disseminating information isn’t as sexy as creating it. But it is desperately needed.
If you are thinking of starting a startup, perhaps consider that you don’t need to create something the world has never heard of. You can provide massive value just by showing people what already exists.
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