Skynet begins to learn at a geometric rate. It becomes self-aware…

The Terminator series is a favourite film series in our household. Computers become self aware. Take over military systems. Attack the enemy – humans. Thankfully nothing like that could ever happen. The humans are in control. They write the code, and they have the off switch.

But the temptation to model human behaviour, and to recreate that in electronic form, is too hard to resist. The first steps have already been taken. According to their website :

“DeepMind is the world leader in artificial intelligence research and its application for positive impact.

We’re on a scientific mission to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how.

If we’re successful, we believe this will be one of the most important and widely beneficial scientific advances ever made, increasing our capacity to understand the mysteries of the universe and to tackle some of our most pressing real-world challenges. From climate change to the need for radically improved healthcare, too many problems suffer from painfully slow progress, their complexity overwhelming our ability to find solutions. With AI as a multiplier for human ingenuity, those solutions will come into reach.”

In a fascinating paper entitled “Multi-agent Reinforcement Learning in Sequential Social Dilemmas“, the researchers analysed “the dynamics of policies learned by multiple self-interested independent learning agents, each using its own deep Qnetwork, on two Markov games we introduce here: 1. a fruit Gathering game and 2. a Wolfpack hunting game. [They studied] how learned behavior in each domain changes as a function of environmental factors including resource abundance.” Videos of the games in action, along with a fuller discussion, can be found here: http://www.sciencealert.com/google-s-new-ai-has-learned-to-become-highly-aggressive-in-stressful-situations

The paper “…noted that the policies learned in environments with low abundance or high conflict-cost were highly aggressive while the policies learned with high abundance or low conflictcost were less aggressive. That is, the Gathering game predicts that conflict may emerge from competition for scarce resources, but is less likely to emerge when resources are plentiful.” In other words, when the fruit is scarce, it is best to zap your opposition.

While these are simple games, litigation is sometimes described as a game. The rules are complex, but the objective is to win. How long before the sometimes friendly, sometimes aggressive fruit pickers turn to the litigation game?