Superintelligence summary

Since the invention of computers in 1940, scientists have been working to build a machine that can think. What progress has been made? One major advance in Artificial Intelligence (or AI) are man-made machines that mimic our own intelligence.

The story begins with the 1956 Dartmouth Summer Project, which endeavored to build intelligent machines that could do what humans do.

It’s clear that imitating human intelligence is an effective way to build technology, but imitation comes in many forms. So, while some scientists are in favor of synthetically designing a machine that simulates humans (through AI, for instance), others stand by an exact imitation of human biology, a strategy that could be accomplished with techniques like Whole Brain Emulation (or WBE).

So what are the differences between the two?

Most of the great discoveries of humanity were achieved either by a single scientist who reached a goal before others got there or through huge international collaborations. So, what would each route mean for the development of SI?

Well, if a single group of scientists were to rapidly find solutions to the issues preventing AI and WBE, it’s most likely their results would produce a single superintelligent machine. That’s because the field’s competitive nature might force such a group to work in secrecy.

You’ve probably heard it a million times, but there is some wisdom in being careful what you wish for. While we may be striving to attain superintelligence, how can we ensure that the technology doesn’t misunderstand its purpose and cause unspeakable devastation?

The key to this problem lies in programing the motivation for SI to accomplish its various human-given goals. Say we designed an SI to make paper clips; it seems benign, but what’s to prevent the machine from taking its task to an extreme and sucking up all the world’s resources to manufacture a mountain of office supplies?

But enough about decimation and total destruction. Before panicking about the impending machine-led apocalypse, let’s take a look at how general intelligence technology can be developed and put to productive use.

It’s likely that the increasing availability and decreasing cost of technology will lead to the cheap mass production of machines capable of doing jobs that currently require the hands and mind of a human. This means that machines will not only replace the entire human workforce but will also be easily replaceable.

It’s clear that an entirely robotic workforce would completely transform the economy, as well as our lifestyles and desires; as machine labor becomes the new, cheaper norm, the pay of workers will drop so low that no human will be able to live off a paycheck. Also, the few employers of the mechanical workforce would accrue a lot of money.

But this brings us back to an earlier point, because where that money ends up also depends on whether SI is designed by a single exclusive group or is the result of a slow collaborative process. If the former turns out to be true, most people would be left with few options for income generation, likely renting housing to other humans or relying on their life-savings and pensions.

It’s clear that the development of SI comes with a variety of safety issues and, in the worst case scenario, could lead to the destruction of humankind. While we can take some precautions by considering the motivation for the SI we build, that alone won’t suffice.

So what will?