In today’s educational landscape, artificial intelligence is more than mere technology. It is also a subject that calls for critical engagement from students, faculty, and staff alike. Recent advancements in generative artificial intelligence automate the creation of content including text, images, music, and more. Scholars are now wrestling with profound methodological, pedagogical, ethical, and epistemological questions.
This toolkit offers guidelines and resources to help instructors support students as we all learn to navigate a world increasingly awash in AI. It also builds upon the work of colleagues at CUNY and elsewhere who have been closely following developments in artificial intelligence.
The toolkit opens below with critical provocations for instructors to pose to students. It then provides an FAQ on AI terms and concepts, followed by guidelines for how to approach questions of course policy and how to redesign assignments and activities with AI tools in mind. The toolkit then concludes with a resource hub containing links, articles, references, tools, and other relevant resources on AI’s role in education.
Critical Provocations for CUNY Students
As a starting point, instructors might pose the following provocations to their students to initiate critical dialogue on AI and its place in and beyond educational settings.
- How much do students know about the history of artificial intelligence?
AI history is marked by boom-and-bust periods that can inform how students understand recent advancements in AI technology and critically assess the ethical concerns that AI poses for the future.
- How much do students know about the role of human data in training AI?
Students should understand that AI systems are trained using large datasets of human-generated text or image, and that the value systems embedded in these datasets directly influence how AI systems behave.
- How much do students know about AI’s inherent biases?
AI systems can reproduce and amplify societal biases found in their training data, and students should be able to recognize and question these biases in AI’s representations of race, sex, gender, language, and culture.
- How much do students know about AI’s lack of self-awareness?
AI systems operate without understanding the meaning of their actions or the content they generate. Understanding this distinction is key for students to discern AI’s capabilities and the need for human oversight.
- How much do students know about the significance of their engagement with AI?
Students should understand that the framing they use to prompt generative AI influences the probability of yielding relevant and credible responses from these tools.
Toolkit Contents
About AI surveys basic AI concepts and principles with a focus on recent advancements in generative AI technology, such as large language models (LLMs) like ChatGPT and image generation tools like Midjourney.
Course Policy offers ethical guidelines and recommended policies for framing and deploying AI tools in educational settings. It provides reusable syllabus language for CUNY teachers and considers how self-advocacy and accountability can inform course policies on the use of generative AI tools in and outside the classroom.
Assignment Makeovers offers help with how to redesign assignments in ways that consider the wide availability of generative AI tools today. This includes suggestions for how to take an “activity inventory” of an assignment, and how to iteratively design that assignment with process-based, visible learning in mind.
Sample Activities surveys different kinds of AI-related activities for instructors to reuse in their classes. These activities are designed to foster critical thinking skills that prepare students to negotiate a world increasingly mediated by AI systems.
Learn More includes the following pages:
- Campus resources and support across the CUNY System
- Resource hub with crowdsourced directories of links, articles, references, tools, and other relevant resources on AI in education.
- TLC Assignment Library links to the growing collection of assignments designed for CUNY, which will over time expand to include assignments about working with artificial intelligence.
