Open-source learning: A bargaining approach

AI systems are much more transparent to one another than humans are to other humans; they can share information about the reward functions that drive their actions. Jesse Clifton, a PhD candidate in statistics at North Carolina State University, presents a framework for using “open-source learning algorithms” — which, thanks to this transparency, can make bargains to achieve mutually beneficial outcomes.