A primer on causal emergence
&gt; Measuring causal emergence is like you&#x27;re looking at the causal structure of a system with a camera (the theory) and as you focus the camera (look at different scales) the causal structure snaps into focus. Notably, it doesn’t have to be “in focus&quot; at the lowest possible scale, the microscale.<p>Talk about abstract metaphors that have no meaning.<p>The core of this argument seems to be:<p>1) Given a fixed state of a system, you can modify it by apply certain operators on the system.<p>2) You can model the &#x27;causal structure&#x27; by observing changes as you randomly apply operators.<p>3) High level systems at a macro scale have a greater information density than the sum of their parts.<p>Ie. In a nutshell, you can have high level (ie. real world) systems that display behaviour that is not just hard to predict from changes to low level systems... but actually <i>impossible</i> to predict from them.<p>Which is to say, basically asserting that you cannot predict the behaviour of macro systems from microscale systems; eg. you cannot predict the behaviour of a molecule based on its quantum state &#x2F; make up (clearly false) and you cannot predict the behaviour of say, a person deciding what to have to for lunch based on their quantum state&#x2F;<p>...but not that you can&#x27;t because it&#x27;s hard.<p>You can&#x27;t because its <i>not possible</i>.<p>Am I misunderstanding?<p>I think that sounds completely crack pot to me.