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I've previously argued that genetic fitness is a measure of selection strength, not the selection target. What evolution selects for are traits that happen to be useful in the organism's current environment. The extent to which a trait is useful in the organism's current environment can be quantified as fitness, but fitness is specific to a particular environment and the same trait might have a very different fitness in some other environment.
I think if you have access to a group interested in doing social events with plausible deniability, that group is probably already a place where you should be able to be honest about your beliefs without fear of "cancellation."
You may not know exactly who belongs to that group before going to the event and seeing who shows up.
- Somehow people who are in good physical health wake up each day with a certain amount of restored willpower. (This is inconsistent with the toy model in the OP, but is still my real / more-complicated model.)
This fits in with opportunity cost-centered and exploration-exploitation -based views of willpower. Excessive focus on any one task implies that you are probably hitting diminishing returns while accumulating opportunity costs for not doing anything else. It also implies that you are probably strongly in "exploit" mode and not doing much exploring. Under those models, accumulating mental fatigue acts to force some of your focus to go to tasks that feel more intrinsically enjoyable rather than duty-based, which tends to correlate with things like exploration and e.g. social resource-building. And your willpower gets reset during the night so that you could then go back to working on those high-opportunity cost exploit tasks again.
I think those models fit together with yours.
(I believe @Kaj_Sotala has written about this somewhere wrt Global Workspace Theory? I found this tweet in the meantime.)
There's at least this bit from "Subagents, akrasia, and coherence in humans":
One model (e.g. Redgrave 2007, McHaffie 2005) is that the basal ganglia receives inputs from many different brain systems; each of those systems can send different “bids” supporting or opposing a specific course of action to the basal ganglia. A bid submitted by one subsystem may, through looped connections going back from the basal ganglia, inhibit other subsystems, until one of the proposed actions becomes sufficiently dominant to be taken.
The above image from Redgrave 2007 has a conceptual image of the model, with two example subsystems shown. Suppose that you are eating at a restaurant in Jurassic Park when two velociraptors charge in through the window. Previously, your hunger system was submitting successful bids for the “let’s keep eating” action, which then caused inhibitory impulses to be sent to the threat system. This inhibition prevented the threat system from making bids for silly things like jumping up from the table and running away in a panic. However, as your brain registers the new situation, the threat system gets significantly more strongly activated, sending a strong bid for the “let’s run away” action. As a result of the basal ganglia receiving that bid, an inhibitory impulse is routed from the basal ganglia to the subsystem which was previously submitting bids for the “let’s keep eating” actions. This makes the threat system’s bids even stronger relative to the (inhibited) eating system’s bids.
Soon the basal ganglia, which was previously inhibiting the threat subsystem’s access to the motor system while allowing the eating system access, withdraws that inhibition and starts inhibiting the eating system’s access instead. The result is that you jump up from your chair and begin to run away. Unfortunately, this is hopeless since the velociraptor is faster than you. A few moments later, the velociraptor’s basal ganglia gives the raptor’s “eating” subsystem access to the raptor’s motor system, letting it happily munch down its latest meal.
But let’s leave velociraptors behind and go back to our original example with the phone. Suppose that you have been trying to replace the habit of looking at your phone when bored, to instead smiling and directing your attention to pleasant sensations in your body, and then letting your mind wander.
Until the new habit establishes itself, the two habits will compete for control. Frequently, the old habit will be stronger, and you will just automatically check your phone without even remembering that you were supposed to do something different. For this reason, behavioral change programs may first spend several weeks just practicing noticing the situations in which you engage in the old habit. When you do notice what you are about to do, then more goal-directed subsystems may send bids towards the “smile and look for nice sensations” action. If this happens and you pay attention to your experience, you may notice that long-term it actually feels more pleasant than looking at the phone, reinforcing the new habit until it becomes prevalent.
To put this in terms of the subagent model, we might drastically simplify things by saying that the neural pattern corresponding to the old habit is a subagent reacting to a specific sensation (boredom) in the consciousness workspace: its reaction is to generate an intention to look at the phone. At first, you might train the subagent responsible for monitoring the contents of your consciousness, to output moments of introspective awareness highlighting when that intention appears. That introspective awareness helps alert a goal-directed subagent to try to trigger the new habit instead. Gradually, a neural circuit corresponding to the new habit gets trained up, which starts sending its own bids when it detects boredom. Over time, reinforcement learning in the basal ganglia starts giving that subagent’s bids more weight relative to the old habit’s, until it no longer needs the goal-directed subagent’s support in order to win.
Now this model helps incorporate things like the role of having a vivid emotional motivation, a sense of hope, or psyching yourself up when trying to achieve habit change. Doing things like imagining an outcome that you wish the habit to lead to, may activate additional subsystems which care about those kinds of outcomes, causing them to submit additional bids in favor of the new habit. The extent to which you succeed at doing so, depends on the extent to which your mind-system considers it plausible that the new habit leads to the new outcome. For instance, if you imagine your exercise habit making you strong and healthy, then subagents which care about strength and health might activate to the extent that you believe this to be a likely outcome, sending bids in favor of the exercise action.
On this view, one way for the mind to maintain coherence and readjust its behaviors, is its ability to re-evaluate old habits in light of which subsystems get activated when reflecting on the possible consequences of new habits. An old habit having been strongly reinforced reflects that a great deal of evidence has accumulated in favor of it being beneficial, but the behavior in question can still be overridden if enough influential subsystems weigh in with their evaluation that a new behavior would be more beneficial in expectation.
Some subsystems having concerns (e.g. immediate survival) which are ranked more highly than others (e.g. creative exploration) means that the decision-making process ends up carrying out an implicit expected utility calculation. The strengths of bids submitted by different systems do not just reflect the probability that those subsystems put on an action being the most beneficial. There are also different mechanisms giving the bids from different subsystems varying amounts of weight, depending on how important the concerns represented by that subsystem happen to be in that situation. This ends up doing something like weighting the probabilities by utility, with the kinds of utility calculations that are chosen by evolution and culture in a way to maximize genetic fitness on average. Protectors, of course, are subsystems whose bids are weighted particularly strongly, since the system puts high utility on avoiding the kinds of outcomes they are trying to avoid.
The original question which motivated this section was: why are we sometimes incapable of adopting a new habit or abandoning an old one, despite knowing that to be a good idea? And the answer is: because we don’t know that such a change would be a good idea. Rather, some subsystems think that it would be a good idea, but other subsystems remain unconvinced. Thus the system’s overall judgment is that the old behavior should be maintained.
your psyche’s conscious verbal planner “earns” willpower
This seems to assume that there's 1) exactly one planner and 2) it's verbal. I think there are probably different parts that enforce top-down control, some verbal and some maybe not.
For example, exerting willpower to study boring academic material seems like a very different process than exerting willpower to lift weights at the gym.
I think that there is something like:
- Local beliefs about the usefulness of exerting willpower in a particular context (e.g. someone might not believe that willpower is useful in school but is useful in the gym, or vice versa, and correspondingly have more willpower available in one context than the other)
- To the extent that one has internalized a concept about "willpower" being a single thing, broader beliefs about willpower being useful in general
- Various neurological and biological variables that determine how strong one's top-down processes are in general, relative to their bottom-up processes (e.g. someone with ADHD will have their bottom-up processes be innately stronger than the top-down ones; medication may then strengthen the amount of top-down control they have).
- Various neurological and biological variables that determine which of one's processes get priority in any given situation (e.g. top-down control tends to be inhibited when hungry or tired; various emotional states may either reduce or increase the strength of top-down control)
My model of burnout roughly agrees with both your and @Matt Goldenberg . To add to Matt's "burnout as revolt" model, my hunch is that burnout often involves not only a loss of belief that top-down control is beneficial. I think it also involves more biological changes to the neural variables that determine the effectiveness of top-down versus bottom-up control. Something in the physical ability of the top-down processes to control the bottom-up ones is damaged, possibly permanently.
Metaphorically, it's like the revolting parts don't just refuse to collaborate anymore; they also blow up some of the infrastructure that was previously used to control them.
Sounds plausible to me. Alternatively, telling you that they didn't over-apologize still communicates that they would have over-apologized in different circumstances, so it can be a covert way of still delivering that apology.
A crucial part of every IFS session is to ask the protector what age they think you are (often, at least in examples, it would say something like 5-12) and then you could reveal to it that actually you're 30 (or whatever).
I wouldn't put it as strongly as to say that it's a crucial part of every IFS session. It can sometimes be a very useful question and approach, sure, but I've had/facilitated plenty of great sessions that didn't use that question at all. And there are people who that question just doesn't resonate with.
As far as I know, the latest representative expert survey on the topic is "Thousands of AI Authors on the Future of AI", in which the median time for a 50% chance of AGI was either in 23 or 92 years, depending on how the question was phrased:
If science continues undisrupted, the chance of unaided machines outperforming humans in every possible task was estimated at 10% by 2027, and 50% by 2047. [...] However, the chance of all human occupations becoming fully automatable was forecast to reach 10% by 2037, and 50% as late as 2116 (compared to 2164 in the 2022 survey).
Not that these numbers would mean much because AI experts aren't experts on forecasting, but it still suggests a substantial possibility for AGI to take quite a while yet.
Hmm... let me rephrase: it doesn't seem to me like we would actually have a clear community norm for this, at least not one strong enough to ensure that the median community member would actually be familiar with stats and econ.
I guess I don't really understand what you're asking. I meant my comment as an answer to this bit in the OP:
In that evolution selecting for "inclusive genetic fitness" doesn't really mean selecting for anything in particular; what exactly that ends up selecting for is completely dependent on the environment (where "the environment" also includes the species itself, which is relevant for things like sexual selection or frequency-dependent selection).
If you fix the environment, assuming for the sake of argument that it's possible to do that, then the exact thing it selects for are just the traits that are useful in that environment.
I think it's a bit of a category mistake to ask about the inclusive fitness of a species. You could calculate the average fitness of an individual within the species, but at least to my knowledge (caveat: I'm not a biologist) that's not very useful. Usually it's individual genotypes or phenotypes within the species that are assigned a fitness.