A tentative peek into the Transhuman
Copied into DU series
Very probably, the Transhuman Word(s) are out of reach for human thinking. Nevertheless, as far as they will perceptible by us, they will have understandable structures or entities.
We can try to think of them as networks of "nodes". Our access points into them will be nodes that are somehow connected to humans... and we can think of humans as nodes also.
Let's use the neuronal model to start with. Each neuron receives signals from one, some or many neurons, applies them a summation function and sends the result to other neurons. On the other way round, retropropagation translates the answers of the external word to the successive neurons, starting from the outputs.
Any object can be so described. Generally with very simple function: a purely material objects radiates its mass and transmits (reflection, diffraction) or light and sound it receives. There is properly no retroprogation.
On the other hands, very complex objects have complex summation and retropropagation functions.
And, somehow indefinitely, each node can be considered as a network of subnodes.
This general model can be seen as an extension of the classical systems theory, of which we have tried a synthesis in our Systemics (1973, in French, of little interest today). We use here "node" where we used "processor" at that time. Better to look for network theory on Wikipedia (which looks quite like graph theory).
Let's note that such a collective image of a transhuman being was yet proposed by Fred Hoyle in his Black Cloud novel (1957). He does not elaborate much on this Cloud's structure, but I tend to remember that there is some kind of democratic (and long) deliberative process. An aspect no seen by Asimov, we think).
Node ranking
We can use the kind or algorithm used by Google for website ranking: sum up the related nodes, weighing them according to their importance (the function is recursive, but works fine, as any Google user can see).
Tentatively, we could sum :
- the input related nodes x their weight in this node x their global rank
- the output related nodes x the weight they apply to this node x their global rank.
Hence we see that a node is powerful if if receives many important inputs and influences strongly many other important nodes.
A system could be said hierarchical if there is one node that outweithts all other inputs in the other nodes.
"Natural" evolution of networks
A natural trend of networks is the concentration. On the 2010's that's impressive as well for machines as for humans. Among two recent titles, you could nearly think that these two books deal with the same topic : The Uptstarts (by Brad Stone, Bantam, 2017) and $uperhubs (by Sandra Navidi, Brealey 2017). In fact, the first one tells the history of Uber and AirBnB, the second describes the super-power-people who typically meet at Davos. In both cases, the networks control tends to concentrate into few hands. And in Virtual Competition (Harvard University Press, 2016), Ariel Ezrachi and Maurice Stucke show how the computer cloud fosters concentration and makes difficult any anti-trust regulation.
Biological evolution. Crossover/fitness, death.
Centralization
Then we can speculate that the same laws will apply in the transhuman worlds. And so more so since the frenetic move to Singularity is geared by Gafa and Cy.
The tripod coherenc.
Cloud needs Memory. Relation addresses. Local storage to limit data traffic.
Cloud needs Processing. Procotos use.
Mind demands connection : at least to be in relation, to see. Cooperation
Self protection.
Biological membranes.
Antiviruses. IBM Immune. Cyberwar.
Generation, cloning.
...
A tentative panorama of node kinds
We tend to see the transhumanism as the emergence of super-humans, more or less organised as we are.
Very probably, high level nodes will be of many different kinds.
According to their evolution from present beings.
- Material/mechanical. Robots of all kinds. Drones (including insect like swarms. Autonomous cars, planes, ships, submarines.
- Vegetals. See some works by Sommerer & Mignonneau.
- Animals. More and more connected, for feeding, milking.
- Humans. Cyborgs. 7 billions
- Texts and codes. Hypertext. (I could make some analysis on my own network, personal or website).
According to their materialization in space
Machine networks can be more extended in space than biological ones, since they transmit information at light speed, and not biological speed. E.g. in one seconds hundredth, 3000KKm instead of the 2 meters from foot to brain.
According to their position in time and duration
Temporary nodes Vs. "eternal"
According to their complexity
The logic gate.
The basic feed-back regulation.
According to energy acquiring
The mains socket. Batteries. Solar cells. Grass eating.
According to the technology used
- silicium
- carbon and "DNA"
Communication channels/technology : biology/neurons
but also light signals, sound, odor, other ones.
Network Theory
Dumbar's number : no more than 150 persons really known.
Elemntary negative feedback
Negative feedback
One level/h6>Feedback, one level
Multiple levels
Then what should we do?
The easy way: accept the determinism and stay quiet at home.
Think humans as nodes into the Cloud.