It works only by means of what the designer put into it, not how the designer did that.
You might as well say then that a rationalist only succeeds by his actions, not by the process of choosing those actions, since performing those same actions for any reasons would result in the same success. However, the reasons for those actions are important. Systematic success requires systematically choosing good actions.
A rationalist will often encounter a familiar situation, and without rebuilding his model or recalculating expected utility for various actions, will simply repeat the action taken previously, executing a cached result. This is still rational. Despite the fact that the rationality occurred much earlier than the action it caused, it still caused that action and the resulting success. Notice, using rationality does not necessarily mean going through the rational process. In this case, it means using the results that were previously produced by rationality.
A thermostat follows rational rules, despite being incapable of generating rational rules or even evaluating the effectiveness of the rules it follows. If it were completely “screened off” from the rationality that produced those rules, it would lose access to those rules. You might consider it partially “screened off” in that the rational process does not update the thermostat with new rules, but the initial rules remain a persistent link in the causal chain between rationality and the thermostat’s success. I will consider a thermostat’s success to be arational when it is actually produced arationally.
As for evolved control systems, evolution is a crude approximation of evidence based updating. Granted, it does not update deep models that can be used to predict the results of proposed actions. It simply updates on propositions of the form that a given allele contributes more to reproductive fitness than alternatives, as represented by the allele frequencies in the population. The crudeness of the approximation and the lack of more advanced rationality features explain why the process is so slow, but the weak rationality of the approximation explains why it works eventually. And the success of evolved control systems owes the effective rules they follow to this weak rationality in the process of evolution.
I don’t think the two of you disagree about any actual thing happening when a person designs a thermostat and sets it to run, or when a homeostatic biological system evolves. You only disagree about how to use a certain word.
Well, then let me taboo the issue of whether we call the control systems arational and present my position that I have been arguing for.
Control systems are systematically correlated to features of their environment, particularly the variable they control and their mechanisms for manipulating it. This correlation is achieved by some sort of evidence processor, for example, evolution or a deliberative human designer. This explains why out of the space of possible control systems, the ones we actually observe tend to be effective, as well as why control systems can be effective without processing additional evidence to increase their correlation with their environment.
Perhaps RichardKennaway could follow the same taboo explain his position that the success of control systems indicates a problem with the importance we place on Bayescraft.
Control systems are systematically correlated to features of their environment, particularly the variable they control and their mechanisms for manipulating it. This correlation is achieved by some sort of evidence processor, for example, evolution or a deliberative human designer.
They work either because they were designed to by people or because evolution stumbled on something that happened to work. No disagreement there. What I’ve been at pains to emphasize is what is in the control system and what is not. Unless one is clear about what is actually present in the control system, it is impossible to understand how it operates—see the recent confusion about the concept of a model.
In particular, the reasons for what is in a control system being in it are among the things that are not to be found in the control system. The mechanism by which it works is completely different from the mechanism by which it was created. To discover how it works, the primary source is the mechanism itself. It is not unknown for a designer to be mistaken about how his invention really works, and “reproductive fitness” will not predict any particular mechanism, nor illuminate its operation. We already know that mammals can regulate their body temperature: “reproductive fitness” is merely an allusion to a very general mechanism that happened to come up with the phenomenon, but tells nothing about how the mammals do it.
In the case of my running examples, there is no Bayescraft* being performed by the systems themselves. That it may have happened elsewhere does not illuminate their operation.
* I suspect this word may be being stretched as well. I have understood it to mean Bayesian reasoning as a self-conscious mental art, as practiced and taught by the fictional beisutsukai, but scarcely attained to in the real world, except fitfully by occasional geniuses, and certainly not performed at all by the blind idiot god. But sometimes it seems to be being used to mean any process describable in Bayesian terms.
What I’ve been at pains to emphasize is what is in the control system and what is not. Unless one is clear about what is actually present in the control system, it is impossible to understand how it operates—see the recent confusion about the concept of a model.
Seriously, you can stop belaboring that point. I am well aware that the control system does not itself process evidence into correlation between itself and its environment or contain a mechanism to do so. I have also explained that the reason it does not need to process evidence to be successful is that an outside evidence processor* has created the control system with sufficient correlation to accomplish its task. Yes, we can understand specifically how that correlation causes success in particular control systems independently of understanding the source of the correlation. So what? This explanation is not the one true cause. Why is it surprising to the theory that reality funneling power comes from Bayescraft, that there is an intermediate cause between Bayescraft and the successful reality funneling?
* I consider processing evidence into correlation of something with its environment to be the core feature of Bayescraft. Processing the evidence into correlation with models that can be extended by logical deduction is an advanced feature that explains the vast difference in effectiveness of deliberative human intelligence, which uses it, and evolution, which does not.
You might as well say then that a rationalist only succeeds by his actions, not by the process of choosing those actions, since performing those same actions for any reasons would result in the same success. However, the reasons for those actions are important. Systematic success requires systematically choosing good actions.
A rationalist will often encounter a familiar situation, and without rebuilding his model or recalculating expected utility for various actions, will simply repeat the action taken previously, executing a cached result. This is still rational. Despite the fact that the rationality occurred much earlier than the action it caused, it still caused that action and the resulting success. Notice, using rationality does not necessarily mean going through the rational process. In this case, it means using the results that were previously produced by rationality.
A thermostat follows rational rules, despite being incapable of generating rational rules or even evaluating the effectiveness of the rules it follows. If it were completely “screened off” from the rationality that produced those rules, it would lose access to those rules. You might consider it partially “screened off” in that the rational process does not update the thermostat with new rules, but the initial rules remain a persistent link in the causal chain between rationality and the thermostat’s success. I will consider a thermostat’s success to be arational when it is actually produced arationally.
As for evolved control systems, evolution is a crude approximation of evidence based updating. Granted, it does not update deep models that can be used to predict the results of proposed actions. It simply updates on propositions of the form that a given allele contributes more to reproductive fitness than alternatives, as represented by the allele frequencies in the population. The crudeness of the approximation and the lack of more advanced rationality features explain why the process is so slow, but the weak rationality of the approximation explains why it works eventually. And the success of evolved control systems owes the effective rules they follow to this weak rationality in the process of evolution.
I don’t think the two of you disagree about any actual thing happening when a person designs a thermostat and sets it to run, or when a homeostatic biological system evolves. You only disagree about how to use a certain word.
Well, then let me taboo the issue of whether we call the control systems arational and present my position that I have been arguing for.
Control systems are systematically correlated to features of their environment, particularly the variable they control and their mechanisms for manipulating it. This correlation is achieved by some sort of evidence processor, for example, evolution or a deliberative human designer. This explains why out of the space of possible control systems, the ones we actually observe tend to be effective, as well as why control systems can be effective without processing additional evidence to increase their correlation with their environment.
Perhaps RichardKennaway could follow the same taboo explain his position that the success of control systems indicates a problem with the importance we place on Bayescraft.
They work either because they were designed to by people or because evolution stumbled on something that happened to work. No disagreement there. What I’ve been at pains to emphasize is what is in the control system and what is not. Unless one is clear about what is actually present in the control system, it is impossible to understand how it operates—see the recent confusion about the concept of a model.
In particular, the reasons for what is in a control system being in it are among the things that are not to be found in the control system. The mechanism by which it works is completely different from the mechanism by which it was created. To discover how it works, the primary source is the mechanism itself. It is not unknown for a designer to be mistaken about how his invention really works, and “reproductive fitness” will not predict any particular mechanism, nor illuminate its operation. We already know that mammals can regulate their body temperature: “reproductive fitness” is merely an allusion to a very general mechanism that happened to come up with the phenomenon, but tells nothing about how the mammals do it.
In the case of my running examples, there is no Bayescraft* being performed by the systems themselves. That it may have happened elsewhere does not illuminate their operation.
* I suspect this word may be being stretched as well. I have understood it to mean Bayesian reasoning as a self-conscious mental art, as practiced and taught by the fictional beisutsukai, but scarcely attained to in the real world, except fitfully by occasional geniuses, and certainly not performed at all by the blind idiot god. But sometimes it seems to be being used to mean any process describable in Bayesian terms.
Seriously, you can stop belaboring that point. I am well aware that the control system does not itself process evidence into correlation between itself and its environment or contain a mechanism to do so. I have also explained that the reason it does not need to process evidence to be successful is that an outside evidence processor* has created the control system with sufficient correlation to accomplish its task. Yes, we can understand specifically how that correlation causes success in particular control systems independently of understanding the source of the correlation. So what? This explanation is not the one true cause. Why is it surprising to the theory that reality funneling power comes from Bayescraft, that there is an intermediate cause between Bayescraft and the successful reality funneling?
* I consider processing evidence into correlation of something with its environment to be the core feature of Bayescraft. Processing the evidence into correlation with models that can be extended by logical deduction is an advanced feature that explains the vast difference in effectiveness of deliberative human intelligence, which uses it, and evolution, which does not.