Page 60 - Monocle Quarterly Journal Vol 3 Issue 2 Spring

MONOCLE QUARTERLY JOURNAL | DEEP LEARNING
Tay from the public’s view – and influence – to make what they described as “minor alterations”, and quickly deleted all her previously objectionable tweets. Tay never returned. After just 16 hours and over 96 000 tweets and comments, the Microsoft chatbot was laid to rest.
Another even stranger and more disturbing case of AI gone wrong involves what one may term virtual
process played out in satisfying their need for social interaction, as they first talked to inanimate objects without success but eventually learned that conversing with other living entities yielded positive results. In this way, the two entities began to associate different objects in their world with different outcomes.
Pleased with the initial success of the project, the developers decided to introduce another agent into the virtual environment. He was called Stan. Being at a slight disadvantage to Adam and Eve in terms of learning how his new virtual world worked, Stan was slightly awkward at first. Whilst Adam and Eve had now understood where to get food, rest and social interaction, the new agent needed some time to learn the ropes. Often, as the other two ate from the tree, for example, Stan would hover around aimlessly near them. This would have been harmless at first, but after a few more similar instances, something unexpected happened. Turning from the apple tree, Eve faced Stan head on and suddenly ate him up with one bite. The developers shuddered.
What the team finally learned was that whilst Stan was still trying to figure out the dynamics of his surroundings, Eve had begun to associate the new agent with food, as he was always hanging around when she was eating. But in comparison to Adam, Eve had never associated Stan with social interaction. And since they had never communicated, she did not recognise him as a fellow agent – something not to be eaten. What she had learned, however, was to associate organic substances with food, as well as the relative position of the tree as a potential source of food. Unfortunately, Stan met both these criteria.
Both Tay and Eve did exactly what they were programmed to do, yet their creators – and the public – were horrified by their subsequent actions. These examples
The two agents displayed
some fairly odd behaviour
in the early stages of the project, largely in trying to figure
out what would satisfy their programmed desires.
cannibalism. In the early 2000s, the Defence Advanced Research Projects Agency (DARPA) – the research and development arm of the US defence force – was experimenting with autonomous virtual social agents, with the aim of understanding how multiple virtual beings would interact and co-exist with one another, inhabiting a virtual world and programmed with various human needs and desires.
The decision was made by DARPA to start out with two autonomous virtual agents, naturally called Adam and Eve, and to introduce more entities if these prototypes interacted successfully. In the beginning, all was well. Adam and Eve seemed shy at first, but gradually became familiar with their surroundings and each other. Their programming was such that they needed social interaction, required sleep and sought out sustenance – which was provided in the form of fruit on an apple tree, as a tongue-in-cheek reference to the biblical tale of the Garden of Eden.
The two agents displayed some fairly odd behaviour in the early stages of the project, largely in trying to figure out what would satisfy their programmed desires. When becoming hungry, Adam and Eve would have to seek out what would satisfy their appetite. So, whilst they knew how to eat, they did not know what to eat. This learning process manifested in certain bizarre moments, as initially they tried to eat their house and other random bits of their environment, but eventually stumbled upon the apple tree, which they found satisfied their cravings – as intended by the developers. The same trial and error
Both Tay and Eve did exactly what they were programmed to
do, yet their creators – and the public – were horrified by their
subsequent actions.
of AI gone wrong may alarm those who are on the fence about the impact of artificial intelligence on society, further solidifying the pre-conceptions of those already
58