At a recent panel of a state’s most widespread and prominent employers, all three of the participants stated that they would hire no college graduates, or no new hires at all, unless the applicants had relevant and practical generative AI experience. When one of the attendees, an instructor, noted that “you cannot really do that, students will have ethical concerns and will not want to use AI,” the panelists indicated that did not matter, that there were ethical ways to use AI, and they would use them, or would not be employed by those companies. In light of this conversation, and similar ones throughout the world, the instructional design, education, and workplace communities must facilitate a dialogue with each other and their students about WHEN and HOW to incorporate AI tools into teaching and learning experiences. This discussion must be contextualized with the expectations of the fields into which students will be entering when they leave instructional environments. Participants will discuss tools and resources,trends in the workplace regarding AI use, and then have the rest of the time for and open discussion about questions and issues raised during the first parts of the presentation. Artificial intelligence will eventually be used in many fields, even in ways that are currently inconceivable. This session will be a discussion on helping students develop human-centered patterns and perspectives NOW so they can rely on them when they move to the workplace. AI pervades the world whether or not we want it. It is in a variety of standalone products and is incorporated into previous “AI-free” products. We must acknowledge this reality and incorporate these tools where they are reliably productive. Centering work, school, or lives, on the other hand, on a tool that is relatively transitory and constantly updating means relying on something with variable access, which could drastically degrade in quality, or, worse, be completely shut down. In order to prepare for a workplace that has the most appropriate and usable tools, learners should practice with the same tools that they will use in the workplace. There will be little use learning on ChatGPT or Grok, for instance, if the student is going to use Claude or Perplexity during work. There is no use, furthermore, in learning exclusively how to use AI tools to search, OR research, when they do not have the capacity to learn how to control for the issues of these technologies. At the same time, there will be little use in learning an AI-free method of doing a task when employers will be looking for workers who know how to use AI. Instructional designers and educators are responsible for instructing students in the best practices of their fields, how to do things using their own skills, and then how to use technologies such as AI if those technologies have been prominently and solidly integrated into their fields' common practices. In an ideal, human-centered, AI-optional world, a learner would not use an AI tool to create something or produce something or carry out a task until they have MASTERED that skill. In academic terms, this would be three things, POSSIBLY four: 1. A master’s student 2. A college graduate 3. Someone with equivalent work experience 4. A student in their LAST SEMESTER of undergraduate experience More pragmatically, students should only use genAI tools in their course to produce something or follow a process until they have DONE THE TASK BY THEMSELVES, until they have learned ENOUGH about the process or product to be able to understand the theory and reasoning behind its existence, its nature. This connects to the concept put forth by Neil Postman in his book TECHNOPOLY that EVERY TEACHER should be a history teacher; students must learn how to do things manually, and the theories and debates and propositions about the relevant problems, processes, solutions, etc. in the field, before they use any technology, AI or otherwise, to do that task.
