Yim Register, Joseph William Tan Garcia, Nayan Kaushal, Dev Wilder, Xiaobing Xu
{"title":"AI education matters","authors":"Yim Register, Joseph William Tan Garcia, Nayan Kaushal, Dev Wilder, Xiaobing Xu","doi":"10.1145/3557785.3557790","DOIUrl":null,"url":null,"abstract":"I always say to my students \"you are going to be the future data science leaders of the world\". Wherever they end up, I hope they apply critical (Cotter, 2020; Dasgupta & Hill, 2020) and human-centered (Xu, 2019) thinking to the AI decisions they make. As AI algorithms become ever more omnipresent in our lives - from newsfeed organization to product recommendations and beyond - it is our responsibility as educators to equip our students with the necessary tools to interrogate the impacts of AI technology. Luckily, there has been a large push for the integration of ethics into AI curricula. Whether this is in Model AI assignments (Furey & Martin, 2019) or entire conferences (such as FAccT), there is a demand for integrated and critical algorithmic literacies both in the classroom and outside of it. As a social media researcher and AI educator, my work regularly contends with two pillars: Joy and Justice. In this article I intend to outline ways of integrating both play and critical interrogation into AI education, with examples from AI education scholarship (Druga, Vu, Likhith, & Qiu, 2019; Ko et al., 2020) as well as a light experience report highlighting student work. My students join me on this article as they are the main inspiration for innovative joy and justice practices!","PeriodicalId":91445,"journal":{"name":"AI matters","volume":"8 1","pages":"22 - 24"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AI matters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3557785.3557790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
I always say to my students "you are going to be the future data science leaders of the world". Wherever they end up, I hope they apply critical (Cotter, 2020; Dasgupta & Hill, 2020) and human-centered (Xu, 2019) thinking to the AI decisions they make. As AI algorithms become ever more omnipresent in our lives - from newsfeed organization to product recommendations and beyond - it is our responsibility as educators to equip our students with the necessary tools to interrogate the impacts of AI technology. Luckily, there has been a large push for the integration of ethics into AI curricula. Whether this is in Model AI assignments (Furey & Martin, 2019) or entire conferences (such as FAccT), there is a demand for integrated and critical algorithmic literacies both in the classroom and outside of it. As a social media researcher and AI educator, my work regularly contends with two pillars: Joy and Justice. In this article I intend to outline ways of integrating both play and critical interrogation into AI education, with examples from AI education scholarship (Druga, Vu, Likhith, & Qiu, 2019; Ko et al., 2020) as well as a light experience report highlighting student work. My students join me on this article as they are the main inspiration for innovative joy and justice practices!
我总是对我的学生说“你们将成为未来世界数据科学的领导者”。无论他们最终走到哪里,我都希望他们将批判性思维(Cotter,2020;达斯古普塔和希尔,2020)和以人为中心的思维(Xu,2019)应用于他们做出的人工智能决策。随着人工智能算法在我们的生活中变得越来越普遍——从新闻推送组织到产品推荐等等——作为教育工作者,我们有责任为学生提供必要的工具,让他们了解人工智能技术的影响。幸运的是,人们大力推动将伦理纳入人工智能课程。无论是在模型人工智能作业中(Furey&Martin,2019)还是在整个会议中(如FAccT),课堂内外都需要综合和批判性的算法文本。作为一名社交媒体研究人员和人工智能教育家,我的工作经常与两大支柱争论:快乐和正义。在这篇文章中,我打算用人工智能教育奖学金的例子(Druga,Vu,Likhhit,&Qiu,2019;Ko et al.,2020)以及一份强调学生工作的轻松体验报告来概述将游戏和批判性审问融入人工智能教育的方法。我的学生们和我一起写这篇文章,因为他们是创新快乐和正义实践的主要灵感来源!