Human and artificial cognition

Predictions of the timelines for when machines will be able to perform general cognitive activities that rival humans, or even the arrival of “super intelligence”, range from years to decades to never. For researchers in the education sector, the potential future state of AI, while provocative, is secondary to important shorter-term questions that influence how AI is integrated into learning and knowledge practices such as sensemaking and decision making. AI is not a future technology. It is already present in our daily lives, often shaping, behind the scenes, the types of information we encounter. It is, therefore, important to consider immediate questions surrounding the dynamics of human-machine interactions. In this paper, we focus on the relationship between human and artificial cognition and treat these as separate systems, each with distinct strengths and capabilities. We adopt a functional view (i.e., discrete tasks) of the activities that artificial cognition completes and those that are best handled by humans. This creates a foundation to then evaluate models for how these two cognitive systems interact and the mechanisms for coordination that are required. In doing so, we create a basis for future researchers to develop testable hypotheses regarding the impact of artificial cognition on knowledge processes such as learning, sensemaking, and decision making. Our evaluation provides insight for researchers regarding the optimal relationship between which cognitive activities should be handed off to the machine, which should remain the domain of human performance, and how these two should then be integrated when outputs are passed from one cognitive system (human or artificial) to the other.