Hacking in the World of Artificial Intelligence - The Ape Machine

One of the things we haven't talked about much is the concept of human intervention when it comes to the dangers of artificial intelligence, especially in its early stages, where we are now with the technology. This may be far less of a "doomsday" or apocalyptic scenario, but the consequences could still be quite devastating on a person by person basis, or even affect larger groups depending on where a machine learning algorithm is deployed. We want to look at very specific cases where reinforcement learning is deployed with public access, much like how you can tell Google Translate that a translation is incorrect, and submit your improvements to them. Another good example would be marking an email that is not in your spam folder, but definitely belongs there, as such so the machine learning algorithm will become better over time. Exploiting these technologies can be done in a variety of ways, and while I initially thought it would take a large group to skew the learning of a machine by flooding it with many badly labeled training examples, it would not be impossible to have this done by some kind of botnet. See, most machine learning algorithms learn by training them on a so-called "labeled" data set, which is a large set of input data, and a label which is the desired perfect output of that input data.