The Molecule of More

THE MOLECULE OF MORE

asserts that any response must include fundamental social change.

Global economic growth will have to be slowed down. People will need

to use less heat, less air conditioning, less hot water. They will have to

drive less,  fly  less,  and  consume less.  In  other words, behavior driven by 

dopamine will need to be drastically suppressed and the era of better,

faster, cheaper, and more will have to end.

This has never happened in the history of humanity—at least not

by our choice. Only breakthrough technologies will allow us to continue

our current rate of rising consumption, while reducing the production

of greenhouse gases.

LET’S ALL WELCOME OUR NEW

SILICON OVERLORDS

Computers that are smarter than people will fundamentally change
the world. Every year we make faster and more powerful computers
thanks to our dopamine-driven ability to use abstract concepts to create
new technology. Once computers become smart enough to build—and
improve—themselves, their progress will accelerate dramatically. At that
point no one knows what will happen. It’s possible it will occur sooner
than we  think. Ray  Kurzweil, the  world’s leading futurologist, believes
that we will have superintelligent computers as early as the year 2029.
Computers that are programmed using traditional techniques are
completely predictable. They follow a clear set of instructions to get
from the beginning of a calculation to the end. Newer developments
in  artificial intelligence, however, create unpredictable results. Instead 
of the programmer determining how the computer works, the com-
puter modifies itself based on  how successful it  is  in  reaching its  goal. 
It  optimizes its  programming to  solve problems. It’s  called evolutionary
computing. Circuits that lead to success are strengthened, and those that
lead to failure are weakened. As the process goes on, the computer gets
better and  better at  its  assigned task—recognizing faces, for  example. 
But no one can tell how it does it. As adjustments are made over time,
the circuits become too complex to understand.