Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms

TL;DR

This paper introduces a formal framework to measure users' ability to control their attention and influence others on digital platforms, considering recent AI advances and platform design.

Contribution

It presents a novel formal framework for quantifying attentional agency, encompassing both personal attention control and influence over others on digital platforms.

Findings

Framework clarifies how platforms extend and limit attentional control.

Implications of AI and generative models for attentional agency are analyzed.

Strategies for enhancing online attentional agency are proposed.

Abstract

We propose a framework for measuring attentional agency, which we define as a user's ability to allocate attention according to their own desires, goals, and intentions on digital platforms that use statistical learning to prioritize informational content. Such platforms extend people's limited powers of attention by extrapolating their preferences to large collections of previously unconsidered informational objects. However, platforms typically also allow users to influence the attention of other users in various ways. We introduce a formal framework for measuring how much a given platform empowers each user to both pull information into their own attention and push information into the attention of others. We also use these definitions to clarify the implications of generative foundation models and other recent advances in AI for the structure and efficiency of digital platforms. We conclude with a set of possible strategies for better understanding and reshaping attentional agency online.