Virus As A Power Optimisation Process: The Problem Of Next Wave

Biological global catastrophic risks were neglected for years, while AGI risks were on the top. The main reason for this is that AGI was presented as a powerful superintelligent optimizer, and germs were just simple mindless replicators. However, germs are capable to evolve and they are very extensively searching the space of possible optimisations via quick replication of viruses and quick replication rate. In other words, they perform an enormous amount of computations, far above what our computers can do.

This optimisation power creates several dangerous effects: antibiotic resistance (for bacteria) and obsolescence of vaccines (for flu) as well as a zoonosis: the transfer of viruses from animals to humans. Sometimes it could be also beneficial, as in the case of evolving in the direction of less CFR.

In other words, we should think about coronavirus not as of an instance of a virus on a doorknob, but as a large optimisation process evolving in time and space.

Thus, the main median-term (3-6 months) question is how it will evolve and how we could make it evolve in better ways. In other words, what will be the next wave?

There was a claim that second wave of Spanish flu was more dangerous, because of the large hospitals: the virus was “interested” to replicate in hospitals, so it produced more serious illness; Infected people had to go to hospitals, which were overcrowded after the war, and they infected other people there, including the medical personal which moved it to the next hospital.

Another point is that the size of the virus optimisation power depends on the number of infected and of the number of virus generations, as well as on the selective pressure. The idea of “flattening the curve” is the worst, as it assumes a large number of infections AND a large number of virus generation AND high selective pressure. Cruel but short-term global quarantine may be better.