Just to add to the analogies I drew in “The Power of the Context”. In baseball, an “error” (or “failiure”) is not catching a catchable flyball, etc., But, striking out is not an “error” or “failure”—it is better considered as “the overhead for sometimes accomplishing something really difficult”.
To bring this analogy to Xerox Parc, the technical aspects of computing—such as building a physical computer or an operating system or new programming language—should be successful “98%” or more of the time (this is roughly the fielding percentage in baseball). These require technical skills for which quite a bit of knowledge and practice has to be acquired and done in advance. It is a kind of engineering, often with some new design elements, but where “the bridge has to stay up”.
The really difficult parts of computing lie in attempts at inventing ways to create enormous new leverages via new kinds of organizations and designs. Here we should be ecstatically happy if we achieve the .406 that Ted Williams reached in 1941. The 60% this doesn’t work out is just “overhead”.
The downside of skill and knowledge is the temptation to use memory before thinking things through. The downside of ignorance and cleverness is that usually worse than “reinventing the flat tire” (which is all too common these days).
I’ve advocated “learning everything” and then “forgetting it except for the perfume”. In other words, though “most ideas are mediocre down to bad”, one has to have them freely rather than just applying technique.
The abundance of bad ideas can interfere, so you have to get rid of them somewhere. A good idea will have something like an odor to it that will allow one to find relevant knowledge in the past (often a very different past than the one that led to the present). This knowledge will help vet the idea, and eventually allow the weakest part of the process—one’s cleverness—to possibly do something worthwhile for once.
The intuition I have is that in a research context striking out isn’t just overhead but a positive contribution; all the other people working on the problem can now see that is not the answer. We can also look at why it wasn’t the answer, which is a source of new information. Therefore the next guy is more likely to get a hit.
It seems like everyone treats this kind of thing as trivial—it’s why we have scientific journals after all—but what I don’t see is much articulation of what value comes from where, and how to keep it. It looks to me like Xerox PARC did an amazing job of capitalizing on all of the information valuableto progress, and I suspect that’s because it was captured in the environment.
As a specific example, you have mentioned elsewhere that peer review didn’t make sense for PARC. Clearly eliminating the bureaucracy was a factor, but I suspect it is more important that what was happening instead did a superior job of delivering the same value that peer review is meant to. The team-of-peers has knowledge of the environment, familiarity with the previous work, contact with the generative process for an idea, and they can provide a new perspective on most any element of each other’s work at any time. Regular peer review is a static and passive check of correctness; because the PARC example was active and dynamic I want to call it “peer stabilization”.
I guess what I am gesturing at is the group is the unit of action. I suspect that if we want to do great things, or even just good things consistently, we need to build the context for the group. Then if it is made up of amazing people it will do amazing things.
Maybe we can disentangle the context from the vision, or the how from the why. Then we could move building powerful contexts into technical execution territory, waiting only for an appropriate vision or need to motivate them. I bet if I could break all this down into “value-added” language businesses and governments would be more willing to give it a shot.
Just to add to the analogies I drew in “The Power of the Context”. In baseball, an “error” (or “failiure”) is not catching a catchable flyball, etc., But, striking out is not an “error” or “failure”—it is better considered as “the overhead for sometimes accomplishing something really difficult”.
To bring this analogy to Xerox Parc, the technical aspects of computing—such as building a physical computer or an operating system or new programming language—should be successful “98%” or more of the time (this is roughly the fielding percentage in baseball). These require technical skills for which quite a bit of knowledge and practice has to be acquired and done in advance. It is a kind of engineering, often with some new design elements, but where “the bridge has to stay up”.
The really difficult parts of computing lie in attempts at inventing ways to create enormous new leverages via new kinds of organizations and designs. Here we should be ecstatically happy if we achieve the .406 that Ted Williams reached in 1941. The 60% this doesn’t work out is just “overhead”.
The downside of skill and knowledge is the temptation to use memory before thinking things through. The downside of ignorance and cleverness is that usually worse than “reinventing the flat tire” (which is all too common these days).
I’ve advocated “learning everything” and then “forgetting it except for the perfume”. In other words, though “most ideas are mediocre down to bad”, one has to have them freely rather than just applying technique.
The abundance of bad ideas can interfere, so you have to get rid of them somewhere. A good idea will have something like an odor to it that will allow one to find relevant knowledge in the past (often a very different past than the one that led to the present). This knowledge will help vet the idea, and eventually allow the weakest part of the process—one’s cleverness—to possibly do something worthwhile for once.
Honored to hear from you!
The intuition I have is that in a research context striking out isn’t just overhead but a positive contribution; all the other people working on the problem can now see that is not the answer. We can also look at why it wasn’t the answer, which is a source of new information. Therefore the next guy is more likely to get a hit.
It seems like everyone treats this kind of thing as trivial—it’s why we have scientific journals after all—but what I don’t see is much articulation of what value comes from where, and how to keep it. It looks to me like Xerox PARC did an amazing job of capitalizing on all of the information valuable to progress, and I suspect that’s because it was captured in the environment.
As a specific example, you have mentioned elsewhere that peer review didn’t make sense for PARC. Clearly eliminating the bureaucracy was a factor, but I suspect it is more important that what was happening instead did a superior job of delivering the same value that peer review is meant to. The team-of-peers has knowledge of the environment, familiarity with the previous work, contact with the generative process for an idea, and they can provide a new perspective on most any element of each other’s work at any time. Regular peer review is a static and passive check of correctness; because the PARC example was active and dynamic I want to call it “peer stabilization”.
I guess what I am gesturing at is the group is the unit of action. I suspect that if we want to do great things, or even just good things consistently, we need to build the context for the group. Then if it is made up of amazing people it will do amazing things.
Maybe we can disentangle the context from the vision, or the how from the why. Then we could move building powerful contexts into technical execution territory, waiting only for an appropriate vision or need to motivate them. I bet if I could break all this down into “value-added” language businesses and governments would be more willing to give it a shot.