2 Matching Annotations
  1. Jul 2022
    1. we'll go into an example here with self-organized criticality so the idea 01:40:03 there is that was coined by back back bak in 87 the term self-organized criticality and it's it's really not a controversial that that living systems and 01:40:16 and many most systems in life complex systems organize in some way but the idea of self-organized criticality is that the organism itself is adjusting is is keeping some kind of adjustment 01:40:28 uh to uh to maintain a critical state and by critical state i mean a state on the ver like you can think of a saddle point so if you drop a model on us on a saddle it's going to not stay there it's going to you know 01:40:41 it's going to change it's going to change one way or the other right so a critical state is like that that threshold where things are about to change from one way to another way and uh 01:40:55 it turns out with you know work and information theory and other other fields of recent in recent years it turns out that uh processing uh whether it's we're talking about a computer or some other 01:41:07 you know machine or or a brain turns out that processing is kind of optimal in a sense when this when the system is at a this this this this critical state and 01:41:21 some people call it on the edge of chaos because things are things can easily change and sometimes it's you can think of that threshold as a 01:41:33 as a as a threshold of a critical state you can think of it as a threshold of the threshold we say between exploration and exploitation like should i should i go should i go 01:41:45 find a new planet for humans to live on or should i fix the planet that you know should i fix the systems on this planet first you know how do we balance exploration of the new versus using the information we have to improve 01:41:59 what we already have so you can think of that as exploration exploitation trade-offs stability agility trade-off do we do we remain stable and use ideas from the old in the past or do we are we more agile and we're more 01:42:13 flexible and we bring in new new ideas so it's like you can call it old new trade old new trade-off but whatever whatever trade-off you want to call it it's this sitting at the edge of going one way or the other 01:42:26 maximally flexible of going one way or the other and it's at that threshold that level that point the kind of that region of criticality that information processing seems to be 01:42:39 maximal so if uh it's no wonder then that the human brain is is organized in such a way to be living on this threshold between agility and stability 01:42:52 and uh now here's an example of that from like a real world example so a a system that is at a critical state is going to be maximally 01:43:03 sensitive to input so that means that there could you know when just when that marble is sitting on the saddle just a little bump to that saddle from one little corner of its universe and right like just one 01:43:16 little organism bumps it and maybe that marble rolls one way or the other right so that one one little input had a major impact on how the whole thing moves 01:43:29 its trajectory into the future right but isn't that what we isn't that kind of what we have in mind for democracy i mean don't we want everyone to have access of engaging into the decision-making processes 01:43:43 of a society and have every voice heard in at least in the sense that there's the possibility that just my voice just me doing my participation in this system might actually 01:43:56 ripple through the system and have a uh you know a real effect a useful effect i mean i think like maybe maybe self-organized criticality can help to inform us the concept of 01:44:10 self-organized criticality can help to inform us of what do we want from democracy or a decision-making process right you know that just makes me think about different like landslides 01:44:22 and that's something that criticality theory and catastrophe theory has been used to study and instead of cascading failure we can think about like cascading neighborhood cleanups so a bunch of people just say 01:44:34 today just for an hour i feel like doing a little cleanup and all of a sudden one person puts up the flag and then it's cascading locally in some just you know unspecified way but all of a sudden you're getting this this distribution with a ton of small 01:44:48 little meetups and then several really large sweeping changes but the total number of people cleaning up is higher because you offered the affordance and the ability for the affordance to sort of propagate 01:44:59 that's right that's right we're talking about a propagation of of a propagation of information a propagation of action and the possibility that even uh you know just one or a few individuals could start a 01:45:12 little chain chain reaction that actually does affect in a positive way society now it's a little too it's almost too bad that sand piles were the original uh you know topic of 01:45:23 of this of self-organized criticality because as you point out it's not really about things falling apart it's about it's about if you think of again if you think of a complex system as a system more capable of solving more 01:45:37 challenging problems then more often you can think of self-organized criticality as a way to propagate information when it is really needed when the system needs to change 01:45:51 uh then information is you know it ingests information from its world from its senses and can act accordingly we we just um submitted an abstract with criticality and active inference and one 01:46:04 of the points was actually the existence of self-organized criticality implies a far from equilibrium system that's actively pumping energy in that's because it's a passive system that's not 01:46:15 locked and loaded

      Example of self-organized criticality. It is a bit reminscent of social tipping points. The one variable that is not so discussed here, which would enrich it is the idea of progress traps as a gap between finite human, anticipatory models vs the uncountable number of patterns and possible states of the universe.

    2. now we talk i talk about a few ideas good regulators requisite variety self-organized criticality and then the 01:35:04 free energy principle from active inference um and uh maybe i'll just try to briefly talk mention what's what those means for what those ideas mean for people who 01:35:15 aren't familiar so good regulator really came from the good regular theorem or whatever it's called really came from cybernetics ash ashby yeah a lot his law of requisite 01:35:33 variety and uh the it's the concept is that a organism or a you know a system must be must be a model of that which it but 01:35:47 that needs to control

      These are technical terms employed in this model: * Good regulators * Requisite variety * Self-organized criticality * Free energy principle