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.

翻译：本文以西摩尔·派普特与辛西娅·所罗门1971年提出的备忘录《计算机能做的二十件事》为基础，提出人工智能与机器学习领域的二十项建构主义实践。部分方案延续了原始备忘录的思想内核，另一些则针对科学、数学及艺术领域的新议题展开探讨。纵观宏观主题，我们注意到儿童参与的重心已不再局限于技术能力培养，而是转向对自身认知过程的深层理解。此外，这些理念强调设计具有个人相关性的AI/ML应用，突破孤立模型与脱离兴趣的现成数据集局限。我们同时承认AI/ML应用开发中数据生产所涉及的社会性要素。最后，本文将阐述应对潜在有害算法偏差及AI/ML应用后果所需的关键维度。