Addressing the Distraction Crisis: a Cognitive Model of Allocation, Detraction, and Control

Objective

Even as you read this sentence, chances are you have already been interrupted twice - from social media, a newsfeed, or your operating system insisting that an update is needed. This highlights the problem: our digital world is designed to distract us, to capture our attention. Intuitively, we can understand that distractions have costs; but we don’t have a clear picture of why we get stuck scrolling and how we can break free from the hold of the algorithms. Part of the problem is that existing models ignore the important roles played by motivation and mental effort. This project, ARCADE, will address this pressing issue by delivering a neuro-computational model of attentional capture and task reconnection. It will be the first model of its kind to integrate multidimensional reward (the value of task progress vs new information) with task switching cost and effortful cognitive control. During the project I will build the model and validate it with a novel experimental task that contains realistic distraction, and uses eyetracking with pupillometry. ARCADE will achieve two key goals: 1) A predictive neuro-computational model that accounts for task re-engagement time with >15% accuracy than current approaches. 2) A powerful simulation tool that can be used to explain the consequences of attention capture on productivity, and increase understanding of the cognitive mechanisms that are involved. The impact of the project is significant. Scientifically I will contribute to the understanding of how attention and decision making interact during task selection. Societally, my findings will inform policies for healthier digital environments and align with UN SDG 3 (Good Health & Well-being). Economically, the project will ultimately contribute by guiding design of digital environments that can curb productivity losses to digital distractions.