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>Human systems are just another example of this problem domain. It isn't. Of course, both are systems of some sort, but there are several differences: 1. You

>Human systems are just another example of this problem domain. It isn't. Of course, both are systems of some sort, but there are several differences: 1. You can simulate a systems engineering problem and if it doesn't give you an acceptable solution in the first go, change some parameters and re-run again. In human systems, you (usually) do not get such luxury. 2. Components in an engineered system behave predictably. Humans are free agents who often act in irrational, surprising ways. You cannot simulate and analyze that. This is why there are black swans. We cannot bundle these two systems as one and the same thing.

icebraining 9y ago
Your view of engineering seems too narrow. How would you classify a traffic engineering problem? Humans area a crucial component, and it certainly doesn't have an objectively correct solution (except possibly in narrow cases).
- pixl97 9y ago
  Current traffic engineering is almost a complete human problem. Swap it out to driverless cars and it becomes more like routing IP packets.
  - greenyoda 9y ago
    Not so simple, since driverless cars will still have to interact with pedestrians, bicyclists, etc. Not to mention that humans will still ultimately determine where the cars go, and when - even if all cars are driverless, massive numbers of people will hit the road the day before Thanksgiving.
    - pixl97 9y ago
      >Not to mention that humans will still ultimately determine where the cars go Incentives. Right now the road network has no information on where you are going. Because of this it is near impossible to route or plan traffic beforehand other than using historical estimates. It is everyone for themselves. In a completely driverless world people could submit their driving route the day before a major event like Thanksgiving so the network has more information on what traffic will look like then. The people that plan ahead could then be given a 'queue credit' or 'queue boost' that routes their car in to the faster moving lanes, where those that did not get stuck in the slower lanes for longer.
AstralStorm 9y ago
1. You can simulate human systems too in big enough numbers. Guess what half of marketing is. Guess what crowd engineering is. Or economics. 2. Humans in general also behave predictably, though not rationally. Human engineering is surprisingly quite similar to debugging native crashes, but not, say civic engineering or software design. It is also similar to art, with its rule governed creativity. 3. Most engineers promoted into leaders were not great engineers, and especially not great systems engineers. Peter principle is hard at work here. Not even good managers. 4. Many of the problems posed to managers are completely ill-posed (heck, not even amenable to satisficing) and likely not possible to solve properly. 5. There is a difference between a leader and a manager. One does not necessarily excel at the other's job either. 6. It's a terrible mistake to not apply engineering methods to society. Author has it completely backwards. The problem is almost always not the method, but optimization algorithm and the metric used. Author presupposes changes that are immeasurable. Well, how does he know about them then? Guesses? 7. The standard solution to an open optimization problem is to use powerful methods for analysing infinite impulse response systems and nonlinear systems. And multivariate analysis. Since these are hard, they are often glossed over and preference is given to simpler ones. 8. Author provides no good concrete examples. Only suppositions. 9. Uses correlation with IQ ignoring the fact that social and mental problems are more pronounced at the extremes and it is a well known fact, this reversing causation. (Consider how sane you have to be to explain the obvious thing time and again.) 10. The unsaid rule about leadership is that you're not a good leader when you don't get elected for the next term or people you lead start to resent you. Even if you can convince them. The thing about convincing people, it never works in the long term because it does not solve any cause. 11. Many people touted as great leaders are actually pretty shielded from consequences and also employ or employed armies of lower rank leaders and managers.

icebraining 9y ago

Your view of engineering seems too narrow. How would you classify a traffic engineering problem? Humans area a crucial component, and it certainly doesn't have an objectively correct solution (except possibly in narrow cases).

pixl97 9y ago
Current traffic engineering is almost a complete human problem. Swap it out to driverless cars and it becomes more like routing IP packets.
- greenyoda 9y ago
  Not so simple, since driverless cars will still have to interact with pedestrians, bicyclists, etc. Not to mention that humans will still ultimately determine where the cars go, and when - even if all cars are driverless, massive numbers of people will hit the road the day before Thanksgiving.
  - pixl97 9y ago
    >Not to mention that humans will still ultimately determine where the cars go Incentives. Right now the road network has no information on where you are going. Because of this it is near impossible to route or plan traffic beforehand other than using historical estimates. It is everyone for themselves. In a completely driverless world people could submit their driving route the day before a major event like Thanksgiving so the network has more information on what traffic will look like then. The people that plan ahead could then be given a 'queue credit' or 'queue boost' that routes their car in to the faster moving lanes, where those that did not get stuck in the slower lanes for longer.

AstralStorm 9y ago

1. You can simulate human systems too in big enough numbers. Guess what half of marketing is. Guess what crowd engineering is. Or economics. 2. Humans in general also behave predictably, though not rationally. Human engineering is surprisingly quite similar to debugging native crashes, but not, say civic engineering or software design. It is also similar to art, with its rule governed creativity. 3. Most engineers promoted into leaders were not great engineers, and especially not great systems engineers. Peter principle is hard at work here. Not even good managers. 4. Many of the problems posed to managers are completely ill-posed (heck, not even amenable to satisficing) and likely not possible to solve properly. 5. There is a difference between a leader and a manager. One does not necessarily excel at the other's job either. 6. It's a terrible mistake to not apply engineering methods to society. Author has it completely backwards. The problem is almost always not the method, but optimization algorithm and the metric used. Author presupposes changes that are immeasurable. Well, how does he know about them then? Guesses? 7. The standard solution to an open optimization problem is to use powerful methods for analysing infinite impulse response systems and nonlinear systems. And multivariate analysis. Since these are hard, they are often glossed over and preference is given to simpler ones. 8. Author provides no good concrete examples. Only suppositions. 9. Uses correlation with IQ ignoring the fact that social and mental problems are more pronounced at the extremes and it is a well known fact, this reversing causation. (Consider how sane you have to be to explain the obvious thing time and again.) 10. The unsaid rule about leadership is that you're not a good leader when you don't get elected for the next term or people you lead start to resent you. Even if you can convince them. The thing about convincing people, it never works in the long term because it does not solve any cause. 11. Many people touted as great leaders are actually pretty shielded from consequences and also employ or employed armies of lower rank leaders and managers.