Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
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2024
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| author | Kafai, Yasmin Morales-Navarro, Luis |
| author_facet | Kafai, Yasmin Morales-Navarro, Luis |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_06775 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning Kafai, Yasmin Morales-Navarro, Luis Computers and Society K.3.2 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. |
| title | Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning |
| topic | Computers and Society K.3.2 |
| url | https://arxiv.org/abs/2402.06775 |