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This guide was created by participants of the Critical AI Literacy for Reading, Writing, and Languages Workshop, an initiative of the MLA-CCCC Task Force on Writing and AI. Ethical and effective use of GenAI technologies is emerging as an essential skill that students must develop in order to live, learn, and work. Yet GenAI comes with potential pitfalls for students–from the risk of being accused of academic misconduct to missing out on foundational skills in reading, writing, research, and learning. Developing literacy with a tool means becoming a more skilled and thoughtful user of that tool. For example, developing literacy in reading means being able to reread, tackle increasingly difficult texts, and do research in order to further build your capability as a reader. Literacy also assumes you have enough knowledge to question and evaluate what you are studying. Similarly, developing AI literacy requires that you learn certain basics about how GenAI works, how to use it, and how to evaluate its output. You should also learn when not to use it. Developing GenAI literacy should be your starting point for using this technology. When you build skills and habits for using GenAI ethically and effectively you will establish yourself as a thoughtful creator and consumer of GenAI content as technologies change over time.

From art to business, generative AI is making waves across the globe. It's set to fundamentally reshape our society. Here's a curated list of AI generators covering text, image, video, music, and code generation. Think of it as your go-to directory for exploring these emerging technologies.

Artificial intelligence (AI) is progressing rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI’s impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI (1), there is a lack of consensus about how to manage them. Society’s response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness and barely address autonomous systems. Drawing on lessons learned from other safety-critical technologies, we outline a comprehensive plan that combines technical research and development (R&D) with proactive, adaptive governance mechanisms for a more commensurate preparation.

Presentación de la nueva versión de GPT, GPT-4o.