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Google Trends search for "artificial intelligence" and "literacy" tells us something important about our field's entrance into the age of AI: a long stretch of no measurable interest interrupted by a dramatic spike in late 2022, when OpenAI published ChatGPT. Since then, debates across diverse communities and domains-dinner table conversations, government reports, op-eds, podcasts, and journal special issues like this one-have worried over AI's impact on academic integrity, copyright law, the future of writing, and the very nature of authorship and humanity. At the same time, generative AI has begun to upend established pedagogical practices and approaches to assessment across levels and disciplines, leaving many educators grappling-and sometimes groping-with how to respond (Figure 1).Yet even as our community of scholars and educators scrambles to make sense of this disruption to literacy learning and living, it's worth remembering that the infrastructures that power AI were already everywhere in late 2022, operating well below the flat line and the lack of interest it reflects. Consider the Google Trends tool itself, for example. The clear, familiar-looking graph belies complex systems of data capture, storage, and retrieval-systems increasingly shaped by AI-powered computational techniques like machine learning, the same methods enabling chatbot platforms like ChatGPT. These techniques, which are often as opaque to their creators as they are to those of us outside the black boxes of the platform industry (Hassenfeld, 2023), have been quietly at work in our lives for years, sifting our email inboxes; recommending new music, television, and films to us; and gluing us to precision-guided, short-form video content on social media platforms. They have also been working on students as they learn to read and write-assessing their essays for plagiarism and grammar, personalizing their reading education experiences with adaptive algorithms, and mediating their access to the internet through school-based surveillance platforms. All to say, literacy studies had entered the age of AI long before many in our field became aware of it in late 2022.But to modify an old saying, if the best time to reckon with AI was 20 years ago, the second-best time is now. As we noted in the call for this special issue, "the practice of literacy-whether it be reading algorithmically-recommended books on an Amazon Kindle or composing with predictive text suggestions-is increasingly threaded to sociotechnical factors that are and will continue to shape the boundaries of literacy learning and living in the age of AI. " These factors are not limited to the computational techniques that constitute AI, but, as surfaced in recent literacy scholarship, extend to their entanglements with broader social and political economic forces (Nichols & Garcia, 2022). Studies have shown, for example, how automated writing platforms can encode normative assumptions about language that perpetuate racialized and gendered notions of "good writing" (Dixon-Román et a...
Google Trends search for "artificial intelligence" and "literacy" tells us something important about our field's entrance into the age of AI: a long stretch of no measurable interest interrupted by a dramatic spike in late 2022, when OpenAI published ChatGPT. Since then, debates across diverse communities and domains-dinner table conversations, government reports, op-eds, podcasts, and journal special issues like this one-have worried over AI's impact on academic integrity, copyright law, the future of writing, and the very nature of authorship and humanity. At the same time, generative AI has begun to upend established pedagogical practices and approaches to assessment across levels and disciplines, leaving many educators grappling-and sometimes groping-with how to respond (Figure 1).Yet even as our community of scholars and educators scrambles to make sense of this disruption to literacy learning and living, it's worth remembering that the infrastructures that power AI were already everywhere in late 2022, operating well below the flat line and the lack of interest it reflects. Consider the Google Trends tool itself, for example. The clear, familiar-looking graph belies complex systems of data capture, storage, and retrieval-systems increasingly shaped by AI-powered computational techniques like machine learning, the same methods enabling chatbot platforms like ChatGPT. These techniques, which are often as opaque to their creators as they are to those of us outside the black boxes of the platform industry (Hassenfeld, 2023), have been quietly at work in our lives for years, sifting our email inboxes; recommending new music, television, and films to us; and gluing us to precision-guided, short-form video content on social media platforms. They have also been working on students as they learn to read and write-assessing their essays for plagiarism and grammar, personalizing their reading education experiences with adaptive algorithms, and mediating their access to the internet through school-based surveillance platforms. All to say, literacy studies had entered the age of AI long before many in our field became aware of it in late 2022.But to modify an old saying, if the best time to reckon with AI was 20 years ago, the second-best time is now. As we noted in the call for this special issue, "the practice of literacy-whether it be reading algorithmically-recommended books on an Amazon Kindle or composing with predictive text suggestions-is increasingly threaded to sociotechnical factors that are and will continue to shape the boundaries of literacy learning and living in the age of AI. " These factors are not limited to the computational techniques that constitute AI, but, as surfaced in recent literacy scholarship, extend to their entanglements with broader social and political economic forces (Nichols & Garcia, 2022). Studies have shown, for example, how automated writing platforms can encode normative assumptions about language that perpetuate racialized and gendered notions of "good writing" (Dixon-Román et a...
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