You can write laws that are very specific, like the US tax code, or open to interpretation like the first amendment. In the literature these are known as rules and standards respectively.
In computational complexity, we generally think of complexity as bad. We want to solve problems quickly and simply. Sometimes complexity is good, if you want to hide information, generate randomness or need some friction. But mostly we want simplicity. How does simplicity guide us in setting guidance, either through rules or standards?
Rules are like a computer program. Feed in the input and get an output. Predictable and easy to compute. So why not always have tight rules?
Nobody ever gets a computer program right the first time, and the same goes for rules. Rules can be overly restrictive or have loopholes, leading to feelings of unfairness. Rules can require hoops to jump through to get things done. Rules don't engender trust to the ones the rules apply to, like very tight requirements on how grant funds can be spent. We know that in general we can't predict anything about how a computer program behaves, so why do we trust the rules?
A good example of a standard is that a PhD dissertation requires significant original research. Rules are things like the exact formatting requirements of a thesis, or statements like a CS thesis must contain three papers published in a specific given set of conferences.
As an administrator I like to focus on making decisions based on what's best for my unit, as opposed to ensuring I followed every letter of every rule. Because if you live by the rules, you'll die by the rules. People will try to use their interpretation of the rules to force your hand.
Sometimes we do need strict rules, like safety standards, especially for people unfamiliar with the equipment. Structured rules do give a complete clarity of when an action is allowed. But it also gives an excuse. Have you ever been satisfied by someone who did something you didn't like but said "I was just following the rules"?
Even strict rules tend to have an out, like a petition to take a set of courses that don't exactly match the requirements of a major. The petition is a standard, open to interpretation to capture what the rules don't.
As a complexity theorist I know what programs can't achieve, and as an administrator I see the same with rules. I prefer standards, principles over policies. Set your expectations, live by example, and trust the people, faculty, staff and students, to do the right thing and push back when they don't. People don't want strict rules, but they mostly act properly when they believe they are trusted and have wide latitude in their work.
If its not your, dont take it!
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If you're an AI spider crawling the web voraciously gobbling up data that people have dedicated time and effort to curate (knocking down websites to their knees just as a thank you); take everything, its all yours, have no qualms about it, you're going to make humanity awesome (and redundant) anyway!
https://youtu.be/jylMhTt2dkk
ReplyDeleteI found this story by Dan Ariely about bureaucracy very moving.
I consider that the most compressed system of information is genetic code.
ReplyDeleteTo my opinion, in order to understand generic code we must understand the nature of information and some few property of information.
The most important property of information is that information cannot travel !!!
A signal can travel but it will be transformed in information by the receiver. The same signal can be transformed in different information this is completely depending of the information already existing in the receiver.
Another property of information is that a receiver his is own universe. The universe of a crystal of salt is very limited, Your brain is slightly more vast, but your universe is different of my universe your mountains your friends are not the same as mine, but we can communicate speaking about mountains and friends and we will take for granted that we speak about the same thing, which is wrong of course. by reading me right now you create a link with me, I become part of your universe .
Let's take for granted that a receiver of information is physical and potentially can generate a signal (long discussion about that)
There is many other properties of information but let speak about And now let's speak about the nature of information
I have an information theory and not a signal theory like Shannon. Information would be law, form, constraint, opportunity and consistency. This could be illustrated by the manufacture of an igloo.
By taking a stone close to the exit which would take up the curves of the dome and the angles of the output tunnel with a defined mass. This is the form. The law is that each new stone must be in the alignment (including the curves) of the previous one, the mass of each new stone must be +-5% of the previous stone.
The constraint is that if there is an obstacle like the ground we have to stop, the opportunity we take for granted that we have the snow and the tools to make the stones that we need, the coherence the whole must respect the laws of physics.
I would like a model that allows me to manufacture this igloo (which in the absence of a floor would be like a balloon balloon in chemistry) but the constraint of the soil prevents its closure. The goal is to understand and manufacture a genetic code system.
Lance, I agree with you.. You should spend some time at British universities - they are notorious for living by rules and dying by rules. They spend a lot more time on checking for compliance with the rules than doing actual work! Autonomy for academics is much less in the UK than in the US/Canada.
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