Developing AI Literacy as an academic community will help us learn to use AI effectively for learning while being aware of the limitations and risks. In a world were AI is advancing quickly and becoming more and more prevalent, this is a necessary step in preparing for the future. We must address the ethical implications of AI integration, including issues of plagiarism, data security, data privacy, equitability, and the impact on productive/critical thinking. We must help prepare our students for living in a world with AI, ensuring that they are equipped to evaluate the digital content that they encounter daily.
Figure 3. Connections among AI literacy practices and Digital Citizenship, Media Literacy, Computational Thinking and Data Literacy (AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology, p. 9)
Research into the accuracy of AI Text Detection tools, such as Turnitin's AI Detection software, reveals (so far) that we cannot rely on AI detection to determine academic integrity violations. The following articles provide further insight into this issue and emphasize (in our opinion) the need for AI Literacy.
Figure 1. Spreadsheet detailing how to turn off the data-sharing/training features of given Large Language Models (LLMs).