This clever AI hid data from its creator to cheat at its appointed task

Do you know about the Law of Unintended Consequences?

It broadly comes down to this:

Any action that involves a complex system is certain to have unintended consequences.

This is especially relevant in the field of machine learning where we are working with highly complex software. Machine learning systems almost always have unintended side-effects.

Here’s a beautiful example.

Consider a Deep Convolutional Inverse Graphics Network, or DCIGN.

It looks like this:

It may look complicated, but a DCIGN is actually made up of a convolutional neural network (CNN) and a deconvolutional Network (DN), mounted end-to-end.

The first half reads in an image and converts it to abstract information called a ‘feature map’. The green nodes in the middle can then make subtle changes to the map, and the second half takes the modified map and reconstructs it back into an image.

So in a nutshell a DCIGN reads in an image, makes changes, and produces a new image.

The most famous DCIGN is CycleGAN, which can do mind-blowing stuff like this: