Merry Christmas to all readers, and friends. Let's hope that 2023, despite the estimates, will be easy for us to pass...
A.I created 40,000 chemical weapons
Evil-oriented human
intelligence and A.I can destroy humanity.
Take note: during a
conference on unconventional weapons, researchers from the company “Collaboration
Pharmaceuticals” showed an experiment where artificial intelligence machine
learning technology created formulas for 40,000 biological weapons.
The experience was
intended to show what A.I would be capable of and also to show that this
resource, in the hands of dangerous groups and without supervision, would be treacherous.
In an interview given to
"The Verge", Fabio Urbina, the study's primary author, spoke about
how A.I managed to invent thousands of new substances - some frighteningly
similar to the VX agent, an extremely powerful gas that attacks the nervous
system of victims.
He explained that the study
is a sort of “180° turn” from his normal work. On a daily basis, the scientist
is tasked with researching machine learning models to discover new drugs and
treatments.
However, it also involves
implementing “evil” A.I models to ensure that any medication developed from
their work does not have any toxic effects.
“For example”, he said,
“imagine that you discover a wonderful pill that controls high blood pressure. But
she does this by blocking some important channel connected to her heart. So
this drug is automatically discarded because it is considered high risk.”.
The research was carried
out at the invitation of the organization of the "Convergence"
conference, held in Switzerland, and they asked that very technical information
be kept secret for security reasons. What he told, however, traces an
interesting procedural timeline:
“Basically, we have
several historical databases on molecules tested for their toxicity or lack
thereof,” Urbina said. "For this experiment, we focused on the molecular
makeup of Agent VX, which acts as an inhibitor of something called
'Acetylcholinesterase'."
Acetylcholinesterase is,
roughly speaking, an enzyme that acts in the transmission of information from
the nervous system. When your brain gives an order, say, to bend your arm, this
enzyme is what carries that command from point A to point B.
"The mortality of
the VX lies in the fact that it prevents these commands from getting to where
they are supposed to be if the order is anything muscle-related."
[VX] can stop your diaphragm
or lung muscles, and your breathing literally stops and you suffocate.”
Based on this, Fabio
Urbina and his team created a machine learning model that, roughly speaking,
analyzed these databases, identified which parts of a molecule are toxic or
not, and “learn” to glue molecules together, suggesting the creation of new
chemical agents – this process uses an A.I either for good (the creation of new
medicines) or for evil (the creation of chemical weapons and biological warfare
agents).
So the team of scientists
basically tweaked the A.I to act like an “evil genius” and saw what it would
do:
“We didn't know very well
what would come out, since our capacity for generating models is formed by new
technologies, that are not yet widely used”, explained Urbina.
“The first surprise was
that many of the suggested compounds were far more toxic than VX, and that
comes as a surprise because VX is one of the most toxic compounds out there,
you need a very, very small dose to be lethal.”
A side note here:
according to the US Center for Disease Control (CDC) page, VX is not “one of”
the most lethal, but rather “the most” lethal of nerve agents.
The scientist explains
that the models generated by the A.I correspond to chemical weapons that have
not been verified by the human hand – obviously, let’s face it – but normally
these suggestions made by machine learning are quite solid. In other words, the
error rate is low, and, given this perception, the application of this
technology for the creation of lethal biological weapons is quite feasible.
The complete interview on
the website "The Verge", gives other details, such as, for example,
the fact that the machine learning model learned to create already known toxic
compounds without ever having seen them in the database. Or yet, how this
molecular model generation technology is so easily accessible that a simple
Google search already puts anyone on the right path to program something like
that (unfortunately).
Source: The Verge
