Good points here. Causality can probably only really be understood formally. Take Newton's cradle, for example. The balls in the center never move. Inactivity can be as causally potent as activity. Moreover, if you take away their potential to move (and you get their elasticity right), Newton's cradle stops working altogether. So, it is not really the inactivity of the center balls that is causal, but their unrealized potential that matters. Lastly, the middle balls exemplify how causality follows transitivity: if a causes b and b causes c, then a causes c (akin to the diagonal line of an associative diagram in category theory). Most physical (mechanistic) models of causation struggle with that and insist on causality having a local origin. IIT differs from Turing computations in many other aspects. Turing computations are strictly binary (pairwise) operations. IIT is n-ary. This is arguably the main reason why biomorphic computers are interesting - they also go beyond pairwise operations (just like the brain). Computations cannot exist without time. They are procedural - a sequence of operations that have to be performed one after the other. IIT's math, like all math, exists independently of time. If you take 2+2, the computation lies in finding the solution. But math is the claim that 2+2 has always been 4. Simultaneously one and the same, independently of the process of someone or something calculating the solution. Computations describe the transitions in-between states. IIT describes the states in-between transitions. etc.
Good points here. Causality can probably only really be understood formally. Take Newton's cradle, for example. The balls in the center never move. Inactivity can be as causally potent as activity.
Moreover, if you take away their potential to move (and you get their elasticity right), Newton's cradle stops working altogether. So, it is not really the inactivity of the center balls that is causal, but their unrealized potential that matters.
Lastly, the middle balls exemplify how causality follows transitivity: if a causes b and b causes c, then a causes c (akin to the diagonal line of an associative diagram in category theory). Most physical (mechanistic) models of causation struggle with that and insist on causality having a local origin.
IIT differs from Turing computations in many other aspects.
Turing computations are strictly binary (pairwise) operations. IIT is n-ary. This is arguably the main reason why biomorphic computers are interesting - they also go beyond pairwise operations (just like the brain).
Computations cannot exist without time. They are procedural - a sequence of operations that have to be performed one after the other. IIT's math, like all math, exists independently of time. If you take 2+2, the computation lies in finding the solution. But math is the claim that 2+2 has always been 4. Simultaneously one and the same, independently of the process of someone or something calculating the solution.
Computations describe the transitions in-between states. IIT describes the states in-between transitions.
etc.