How the Design of YouTube Influences User Sense of Agency
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Abstract (arXiv)
In the attention economy, video apps employ design mechanisms like autoplay that exploit psychological vulnerabilities to maximize watch time. Consequently, many people feel a lack of agency over their app use, which is linked to negative life effects such as loss of sleep. Prior design research has innovated external mechanisms that police multiple apps, such as lockout timers. In this work, we shift the focus to how the internal mechanisms of an app can support user agency, taking the popular YouTube mobile app as a test case. From a survey of 120 U.S. users, we find that autoplay and recommendations primarily undermine sense of agency, while search and playlists support it. From 13 co-design sessions, we find that when users have a specific intention for how they want to use YouTube they prefer interfaces that support greater agency. We discuss implications for how designers can help users reclaim a sense of agency over their media use.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jan 2021.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 2; 2025: 3; 2026: 4.
12 papers.
- 2023MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Interventioncited by 16
- 2024VRCopilot: Authoring 3D Layouts with Generative AI Models in VRcited by 10
- 2021Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachabilitycited by 8
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsingcited by 7
- 2024Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Interventioncited by 5
- 2025CTRL-Rec: Controlling Recommender Systems With Natural Languagecited by 4
- 2021Causal Inference Struggles with Agency on Online Platformscited by 2
- 2025State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Livingcited by 2
- 2026Privacy in Human-AI Romantic Relationships: Concerns, Boundaries, and Agencycited by 2
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holescited by 1
- 2026Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agentscited by 0
- 2026Compass: Continuously Aligning Social Media Feeds via In-Situ Reflectionscited by 0
- 2026Compass: Continuously Aligning Social Media Feeds via In-Situ Reflections4 Aug 2026
- 2026Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents15 Jul 2026
- 2026Privacy in Human-AI Romantic Relationships: Concerns, Boundaries, and Agency23 Jan 2026
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holes19 Jan 2026
- 2025State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Living16 Oct 2025
- 2025CTRL-Rec: Controlling Recommender Systems With Natural Language14 Oct 2025
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsing15 May 2025
- 2024VRCopilot: Authoring 3D Layouts with Generative AI Models in VR18 Aug 2024
- 2024Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention3 Mar 2024
- 2023MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention28 Sep 2023
- 2021Causal Inference Struggles with Agency on Online Platforms19 Jul 2021
- 2021Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability30 Jun 2021