SIMPLICIO: But then what, on your view, is the better way?
I’m not sure if I’m more Simplicio or more the Visitor, but … the political side of it doesn’t seem that hard to fix. At least, I’ve been advocating a set of improvements to futarchy that address all the political-structure inadequacies discussed here, as well as several others not discussed here. I know it’s too much to hope that it’s free of such inadequacies … though I still hope, because I explicitly designed it with the intent to be free of them. So I decided to write up a description of it suitable for this crowd: Ophelia, a weapon against Moloch.
Since political inadequacy seems to underlie many other types of inadequacy, maybe I should reconsider making an alpha version Ophelia app. In the meantime, if any of you wish to criticize flaws in the idea, or point me to a better idea, please do.
Er, is that agreement or an objection? It reads like an objection to me, though that could be the lack of body language. But the content agrees with the post, which explicitly states at both the beginning and the end that the system is designed to start very small and then grow.
The total scores for Bills are not publicized until it is time to pass a Bill.
This means that the organization with the best machine learning algorithm to estimate the bill score gets a lot of political power.
The same goes for the actual making of predicitions.
Every Polling period, the Predictions for the most recent winning Bill are evaluated. The Polling periods should be much shorter than the Bill cycle so that there is quick feedback.
This looks like short-term effects of the bill become more important than it’s long-term effects.
There are likely some interesting Goodhard’s law problems where issues that benefit special interest groups aren’t asked about in the polling questions and thus there’s favors to be exchanged with those interests groups.
I would expect a few big organisations to arrise that have heavy machine learning capabilities and that hold the power about bill making.
In general the system is likely sufficiently intransparent that it’s hard to understand whats happening and how the big organisations use their power to get benefits but they likely will be able to get benefits.
This means that the organization with the best machine learning algorithm to estimate the bill score gets a lot of political power. … I would expect a few big organisations to arrise that have heavy machine learning capabilities and that hold the power about bill making.
It’s true I omitted the possibility of expending votes at a Vickrey auction level instead of an actual-bid level, so I grant the possibility that, if only one side had good polling data (implausible as that is), then they might buy votes a small fraction more cheaply. However, the “proportional influence” criterion is where most of the power of the system is. - i.e. How would one side actually increase their power long term, since the redistribution of spent votes eliminates their advantage after a single bill, which could then be cheaply repealed by the opposition? And since they’d still have to be maximizing the totals from the polling, would successfully gaining strategic advantage over bills have any downsides?
This looks like short-term effects of the bill become more important than it’s long-term effects.
Mostly true, but missing two significant refinements: (1) What actually matters is the effects of the entire legal code, to which the most recent bill ought to have made at most a small adjustment. (2) It’s the task of the questions to ask about short-term judgments of long-term effects. No system can select for long-term effects that aren’t predictable until the long-term has already arrived.
In general the system is likely sufficiently intransparent …
Entirely fair, though I’d propose that transparency is not a critical difference between a system like this, that can only be fully understood by people who read up on it, versus a system like the U.S. election laws, that can’t be fully understood even by people who read up on it. The U.S. election laws do have the appearance of simplicity as long as one explains First Past The Post and nothing more.
I’m not sure if I’m more Simplicio or more the Visitor, but … the political side of it doesn’t seem that hard to fix. At least, I’ve been advocating a set of improvements to futarchy that address all the political-structure inadequacies discussed here, as well as several others not discussed here. I know it’s too much to hope that it’s free of such inadequacies … though I still hope, because I explicitly designed it with the intent to be free of them. So I decided to write up a description of it suitable for this crowd: Ophelia, a weapon against Moloch.
Since political inadequacy seems to underlie many other types of inadequacy, maybe I should reconsider making an alpha version Ophelia app. In the meantime, if any of you wish to criticize flaws in the idea, or point me to a better idea, please do.
When creating a new governance system, don’t focus on creating something that’s supposed to work at the scale of a country.
Focus on something that works on a smaller scale. Student self-goverance at universities should be the perfect test bed for new governance models.
Er, is that agreement or an objection? It reads like an objection to me, though that could be the lack of body language. But the content agrees with the post, which explicitly states at both the beginning and the end that the system is designed to start very small and then grow.
This means that the organization with the best machine learning algorithm to estimate the bill score gets a lot of political power.
The same goes for the actual making of predicitions.
This looks like short-term effects of the bill become more important than it’s long-term effects.
There are likely some interesting Goodhard’s law problems where issues that benefit special interest groups aren’t asked about in the polling questions and thus there’s favors to be exchanged with those interests groups.
I would expect a few big organisations to arrise that have heavy machine learning capabilities and that hold the power about bill making.
In general the system is likely sufficiently intransparent that it’s hard to understand whats happening and how the big organisations use their power to get benefits but they likely will be able to get benefits.
It’s true I omitted the possibility of expending votes at a Vickrey auction level instead of an actual-bid level, so I grant the possibility that, if only one side had good polling data (implausible as that is), then they might buy votes a small fraction more cheaply. However, the “proportional influence” criterion is where most of the power of the system is. - i.e. How would one side actually increase their power long term, since the redistribution of spent votes eliminates their advantage after a single bill, which could then be cheaply repealed by the opposition? And since they’d still have to be maximizing the totals from the polling, would successfully gaining strategic advantage over bills have any downsides?
Mostly true, but missing two significant refinements: (1) What actually matters is the effects of the entire legal code, to which the most recent bill ought to have made at most a small adjustment. (2) It’s the task of the questions to ask about short-term judgments of long-term effects. No system can select for long-term effects that aren’t predictable until the long-term has already arrived.
Entirely fair, though I’d propose that transparency is not a critical difference between a system like this, that can only be fully understood by people who read up on it, versus a system like the U.S. election laws, that can’t be fully understood even by people who read up on it. The U.S. election laws do have the appearance of simplicity as long as one explains First Past The Post and nothing more.