As AI is becoming more commonplace and integrated into industry and everyday life, AI literacy is increasingly important. Its value in providing effective, efficient tools to support a variety of tasks is mitigated by the challenge that it carries bias, makes mistakes, and itself has no integrity, no orientation towards truth, and no sense of fairness or honesty.
Because of these limits, it is important for instructors and students alike to understand how it works, and to have the skills to evaluate any AI outputs and recommendations. In the same way that a mathematician must understand the concepts of calculus or hyperbolic geometry when using a calculator for computation, using AI effectively requires an understanding of underlying concepts and how the algorithm employs them.
Some Examples of Integrating AI Literacy into the Classroom
Modelling: Various means can be used to model AI literacy, including generating AI output, sharing it with students, and demonstrating processes of evaluation by articulating the strengths and weaknesses of that output. Another strategy might be discussing case examples where AI output has been used both successfully and unsuccessfully.
Assignments that require AI use: Many industries require knowledgeable use of AI, and so assessments that help students learn how to use it effectively can help them develop skills that will serve them well in the workplace. Examples might include permitting students to use AI as a companion for specific stages of an assessment; or perhaps drawing on AI for feedback or self-testing tools.
Caution: If requiring students to employ AI, it is important to consider the degree to which you may also be requiring students to hand over their intellectual property to the AI machine, as well as to provide free labour and effort to support its training. As AI does not have integrity, and is arguably itself a plagiarist, there are ethical dilemmas surrounding its use, and the expectation that others should use it – and because of this, students may not wish to participate.
Provide AI-generated materials for validation and critique: Instead of asking students to engage actively with AI, another approach might be to generate your own materials, and then have students work to validate and critique those materials. These types of fact-checking exercises can be constructed as formative assessments or as in-class activities and can help students see both the benefits and limitations of AI generated claims.
Brainstorming Tool: AI can be effectively used for brainstorming, jumpstarting ideas when confronted with a blank page, or perhaps even more potently, for encouraging students to think beyond superficial and commonplace answers to vexing problems (e.g. Karout & Harouni, 2023).
© Created by Allyson Skene, 2024
Consider sharing the Career Centre resource AI in the Workplace Series with your students to encourage them to learn more.