{"title":"Algorithm Literacy as a Subset of Media and Information Literacy: Competences and Design Considerations","authors":"D. Frau-Meigs","doi":"10.3390/digital4020026","DOIUrl":null,"url":null,"abstract":"Algorithms, indispensable to understand Artificial Intelligence (AI), are omnipresent in social media, but users’ understanding of these computational processes and the way they impact their consumption of information is often limited. There is a need for Media and Information Literacy (MIL) research investigating (a) how MIL can support algorithm literacy (AL) as a subset of competences and with what working definition, (b) what competences users need in order to evaluate algorithms critically and interact with them effectively, and (c) how to design learner-centred interventions that foster increased user understanding of algorithms and better response to disinformation spread by such processes. Based on Crossover project research, this paper looks at four scenarios used by journalists, developers and MIL experts that mirror users’ daily interactions with social media. The results suggest several steps towards integrating AL within MIL goals, while providing a concrete definition of algorithm literacy that is experience-based. The competences and design considerations are organised in a conceptual framework thematically derived from the experimentation. This contribution can support AI developers and MIL educators in their co-design of algorithm-literacy interventions and guide future research on AL as part of a set of nested AI literacies within MIL.","PeriodicalId":512971,"journal":{"name":"Digital","volume":"121 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/digital4020026","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
Algorithms, indispensable to understand Artificial Intelligence (AI), are omnipresent in social media, but users’ understanding of these computational processes and the way they impact their consumption of information is often limited. There is a need for Media and Information Literacy (MIL) research investigating (a) how MIL can support algorithm literacy (AL) as a subset of competences and with what working definition, (b) what competences users need in order to evaluate algorithms critically and interact with them effectively, and (c) how to design learner-centred interventions that foster increased user understanding of algorithms and better response to disinformation spread by such processes. Based on Crossover project research, this paper looks at four scenarios used by journalists, developers and MIL experts that mirror users’ daily interactions with social media. The results suggest several steps towards integrating AL within MIL goals, while providing a concrete definition of algorithm literacy that is experience-based. The competences and design considerations are organised in a conceptual framework thematically derived from the experimentation. This contribution can support AI developers and MIL educators in their co-design of algorithm-literacy interventions and guide future research on AL as part of a set of nested AI literacies within MIL.
算法是理解人工智能(AI)所不可或缺的,在社交媒体中无处不在,但用户对这些计算过程及其对信息消费的影响的理解往往有限。有必要开展媒体与信息素养(MIL)研究,调查:(a)媒体与信息素养如何支持算法素养(AL),将其作为能力的一个子集,并给出工作定义;(b)用户需要哪些能力才能批判性地评估算法并与之有效互动;以及(c)如何设计以学习者为中心的干预措施,促进用户加深对算法的理解,并更好地应对此类过程传播的虚假信息。基于交叉项目的研究,本文探讨了记者、开发人员和 MIL 专家使用的四种情景,这些情景反映了用户与社交媒体的日常互动。研究结果提出了将 AL 纳入 MIL 目标的几个步骤,同时提供了基于经验的算法素养的具体定义。这些能力和设计考虑因素被归纳到一个概念框架中,该框架以实验为主题。这一贡献可以支持人工智能开发人员和智能语言教育工作者共同设计算法素养干预措施,并指导未来对作为智能语言中嵌套人工智能素养一部分的 AL 的研究。