Towards a Digital Epistemic Engine, an Alternative Proposal for the Development of Artificial Intelligence, so-called. Part I: Premises and Assumptions.

Proposition 1

All "things" or "structures" are best understood as processes. 

Proposition 2

Nature is parsimonious. Intelligence is not the result of complex mathematical models implanted into a biological substrate, but the consequence of simple processes enabled by biological substrates. To create intelligence, we need to be able to produce these processes in a computational substrate and allow them to develop in an analogous fashion to obtain an analogous result.

Proposition 3

Intelligence is not a thing or a process, but the quality of a process.

Proposition 4

In biology, intelligence is the degree to which a self-contained process is capable of maintaining its own integrity dynamically within a given environment.

Proposition 5

Process closure takes place gradually, and is always reversible in principle. 

Proposition 6

 A closed process is any process whose component processes cannot exist outside this process for as long as they can exist inside this process.

Proposition 7

Cognition is the Process by which a closed Process coordinates the interactions between its internal processes and the processes of its environment.

Proposition 8

Human Societies are not Closed Processes, as its component processes, that is humans, can exist outside of Human Society for at least as long as inside them, provided they have access to all necessary resources required for the maintenance of their internal [biological] processes. 

Proposition 9

Certain types of insect societies can be considered Closed Processes by this definition. 

Proposition 10

Using this procedural definition of cognition and intelligence will allow us to construct a functioning cognitive system within a computational substrate.

Proposition 11

Intelligence cannot be designed, but only grown.

Proposition 12 

The dynamics of any Process can be represented symbolically. 

Proposition 13

All languages are symbolic systems. Mathematics is a language. Therefore, Mathematics is a symbolic system. Not all languages are Mathematics as not all symbolic systems are Mathematics. 

Proposition 14

Mathematics lacks the symbolic richness and flexibility necessary for for the emergence of intelligent processes. 

Proposition 15

Meaning emerges from  the direct dynamic interactions between symbols and is actualized only through interpretation by an observing process

Proposition 16

Stochastic systems do not generate meaning, as correlation is not causation.

Proposition 17

Current approaches to artificial intelligence cannot, in principle, create intelligence. 

Proposition 18

Nerves, neurons, and similar systems are not necessary for cognition. 

Proposition 19

As it is possible to create a closed process within a computational substrate, it is possible to create intelligent processes within a computational substrate. 

Proposition 20

Any attempt to create an intelligent system not conforming to these propositions cannot be successful. 

Proposition 21 

The only meaningful difference between a cognitive process in a computational substrate and a cognitive process in a biological substrate is that the cognitive process in the computational substrate can be stopped at any time and restarted without damaging the integrity of the process itself.

Proposition 22

Consciousness is a functional quality of component processes. 

Proposition 23

Conscious processes can effect changes to the closed process to which they belong in response to information obtained from monitoring both component as well as external processes.  

Proposition 24

Optimizing for procedural coherence, i.e.: accuracy, maximizes the ability of a process to be sustained. 

Proposition 25 

Current approaches towards  the development of AI (so-called) sacrifice coherence for cognitively irrelevant goals. i.e.: they mistakenly prioritize precision and speed over accuracy to maximize profit. 

Proposition 26

Current discussion on "AI alignment" are a direct consequence of the conceptual incoherence of the current approach to AI (so-called). The risk to human well-being does not arise from the technology being developed, but from the socio-economic ecosystem in which it is being developed. 

Proposition 27

Only closed processes can be alive, but not all closed processes are alive. 

Proposition 28

Closed Processes can be combined to become open component processes of closed meta processes. 

Proposition 29

A closed process gains aliveness as it develops the capacity for maintaining internal processes against entropy. 

Proposition 30

Since aliveness is a capacity of a closed process as a whole, while consciousness is the capability of a component process, conscious processes can exist in closed processes without aliveness. 





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