Reconceptualizing AI Literacy: The Importance of Metacognitive Thinking in an Artificial Intelligence (AI)-Enabled Workforce
Sidra Sidra, Claire Mason
Abstract
We propose that metacognitive skills and metacognitive thinking will become increasingly important for effective use of AI (Artificial Intelligence) systems. As the collaborative capability of AI systems improves, humans will spend more of their time working with AI. This is expected to uniquely influence the human decision-making process. We identify four characteristics that differentiate human-AI interactions from human-human interaction, each of which is likely to affect our thinking and decisions. These are (1) the accuracy of our cognitive heuristics for predicting the behaviour of AI systems, (2) AI’s limited capability when dealing with novel and ill-defined problems, (3) the lack of a natural, reciprocal feedback mechanism in AI systems and (4) the inability of AI systems to engage in metacognition. Drawing upon the dual-process theory of human thought process, we argue that these characteristics will diminish the efficacy of the system one mode of human thinking, making metacognitive thinking skills important to ensure effective use of AI systems. We conclude by describing how this need can be addressed through training and AI design.