Prediction Accuracy and Autonomy

TL;DR

This paper critically examines recommender systems' impact on individual autonomy, analyzing research objectives and proposing design improvements, with a focus on YouTube, to better align system behavior with users' autonomy rights.

Contribution

It provides a nuanced literature survey on recommender systems' objectives and offers specific design recommendations to enhance user autonomy, especially in the context of YouTube.

Findings

Recommender systems may undermine user autonomy.

Aligning system objectives with user goals is complex.

Design changes can improve autonomy in recommender systems.

Abstract

The tech industry has been criticised for designing applications that undermine individuals' autonomy. Recommender systems, in particular, have been identified as a suspected culprit that might exercise unwanted control over peoples' lives. In this article we try to assess the objectives of recommender system research and offer a nuanced discussion of how these objectives can align with users' goals. This discussion employs a qualitative literature survey connecting the dots between relevant research within the fields of psychology, design ethics, interaction design and recommender systems. Finally, we focus on the specific use-case of YouTube's recommender system and propose design changes that will better align with individuals' autonomy. Based on our analysis we offer directions for future research that will help secure rights to digital autonomy in the attention economy.