Date: 27 April 2022 | Speaker: Jack Furby
With humans and machines working ever closer together additional capabilities are required to aid the integration of the separate agents to make the overall team more productive. Humans are known to build mental models of their environment but current neural network solutions are not guaranteed to learn human-understandable solutions to tasks and due to their “black box” nature a human may face difficulties building an accurate mental model of the agent possibly resulting in unjustified trust. This talk will discuss a type of model which aims at improving human-machine interaction and if it can aid a human to create a mental model of the neural network based agent.
