  In this paper, we build on the 1971 memo "Twenty Things to Do With a
Computer" by Seymour Papert and Cynthia Solomon and propose twenty
constructionist things to do with artificial intelligence and machine learning.
Several proposals build on ideas developed in the original memo while others
are new and address topics in science, mathematics, and the arts. In reviewing
the big themes, we notice a renewed interest in children's engagement not just
for technical proficiency but also to cultivate a deeper understanding of their
own cognitive processes. Furthermore, the ideas stress the importance of
designing personally relevant AI/ML applications, moving beyond isolated models
and off-the-shelf datasets disconnected from their interests. We also
acknowledge the social aspects of data production involved in making AI/ML
applications. Finally, we highlight the critical dimensions necessary to
address potential harmful algorithmic biases and consequences of AI/ML
applications.
