In a preprint paper, researchers at Alphabet's DeepMind and the University of California, Berkeley propose a framework for comparing the ways children and AI learn about the world. The work, which was motivated by research suggesting children's learning supports behaviors later in life, could help close the gap between AI and humans when it comes to acquiring new abilities. For instance, it might lead to robots that can pick and pack millions of different kinds of products while avoiding various obstacles. Exploration is a key feature of human behavior, and recent evidence suggests children explore their surroundings more often than adults. This is thought to translate to more learning that enables powerful, abstract task generalization -- a type of generalization AI agents could tangibly benefit from.

On 6-7 May 2019, the World Economic Forum Centre for the Fourth Industrial Revolution and its partners UNICEF and the Canadian Institute for Advanced Research (CIFAR) hosted a workshop in San Francisco on the joint "Generation AI" initiative. This workshop identified deliverables in two key areas: 1) public policy guidelines that direct countries on creating new laws focused on children and 2) a corporate governance charter that guides companies leveraging AI to design their products and services with children in mind.