17.3 Conclusion 315 e Physical: creative constructive play with objects — Example task: Ability to construct novel, interesting structures from blocks e Conceptual invention: concept formation — Example task: Given a new category of objects introduced into the lab (e.g. hats, or pets), the robot should create a new internal concept for the new category, and be able to make judgments about these categories (e.g. if Ben particularly likes pets, it should notice this after it has identified "pets" as a category) e Verbal invention — Example task: Ability to coin a new word or phrase to describe a new object (e.g. the way Alex the parrot coined “bad cherry" to refer to a tomato) e Social — Example task: If the robot wants to play a certain activity (say, practicing soccer), it should be able to gather others around to play with it 17.3 Conclusion In this chapter, we have sketched a roadmap for AGI development in the context of robot or virtual preschool scenarios, to a moderate but nowhere near complete level of detail. Completing the roadmap as sketched here is a tractable but significant project, involving creating more tasks comparable to those listed above and then precise metrics corresponding to each task. Such a roadmap does not give a highly rigorous, objective way of assessing the percentage of progress toward the end-goal of human-level AGI. However, it gives a much better sense of progress than one would have otherwise. For instance, if an AGI system performed well on diverse metrics corresponding to 50% of the competency areas listed above, one would seem justified in claiming to have made very substantial progress toward human-level AGI. If an AGI system performed well on diverse metrics corresponding to 90% of these competency areas, one would seem justified in claiming to be "almost there." Achieving, say, 25% of the metrics would give one a reasonable claim to "interesting AGI progress." This kind of qualitative assessment of progress is not the most on