Getting Trapped in Amazon's "Iliad Flow": A Foundation for the Temporal Analysis of Dark Patterns

Research Background and Issues

• What problems or challenges did the authors identify?
  The authors pointed out that contemporary research on analyzing dark patterns in digital systems primarily focuses on static images or isolated patterns, lacking a comprehensive temporal analysis of dark patterns across the user journey. This gap prevents a full understanding of the role of dark patterns in the overall user experience and their potential cumulative effects.

• Why is this issue important?
  Dark patterns have the potential to manipulate, deceive, or restrict users, directly impacting their decision-making and autonomy. More critically, these patterns are often embedded in complex user journeys (especially in e-commerce platforms and subscription services like Amazon Prime), where their prolonged effects can cause significant economic and psychological harm. Existing regulations (e.g., the U.S. Federal Trade Commission and the EU Digital Services Act) and design ethics require systematic analytical methods to identify these patterns.

• Research Motivation and Related Work
  This study builds upon and extends prior classifications of dark patterns (e.g., the hierarchical and ontological models established by Gray et al.) and references research on dark patterns in specific domains (e.g., e-commerce, gaming, social media, mobile applications). Responding to academic demands, the study explores the temporal dimension of dark patterns—how these patterns interact and amplify each other across different stages of the user journey.

Proposed Solution

• What methods or solutions did the authors propose?
  The authors proposed the "Temporal Analysis of Dark Patterns" (TADP) methodology, illustrated through a detailed case study of Amazon Prime's cancellation process, known as the "Iliad Flow," to demonstrate how to identify, map, and visualize these patterns over time.

• What are the innovative aspects of this solution?

  1. Temporal Dimension Framework: For the first time, dark patterns are analyzed beyond single pages to encompass user journeys and system-level interactions, constructing a temporal analysis framework at the intra-page (single page), inter-page (multi-page), and system levels.
  2. Interaction Analysis Between Patterns: The study introduces two key mechanisms—co-occurrence and amplification—to reveal the synergistic effects of different dark patterns.
  3. Methodological Visualization Tools: The methodology employs UX visualization techniques such as user journey maps and service blueprints to illustrate and quantify the long-term impact of dark patterns on users from both experiential and design perspectives.

• What are the implementation steps and key techniques used?

  1. Identifying Dark Patterns: Utilizing the high-/mid-/low-level dark patterns ontology proposed by Gray et al. to define the dark patterns present in pages and interactions.
  2. Mapping Interface Elements: Identifying specific interface elements containing dark patterns and analyzing their potential impact on user experience.
  3. Analyzing Pattern Interactions: Describing the co-occurrence and cumulative amplification effects of different dark patterns, exploring their synergistic relationships over time.
  4. Visual Representation: Integrating all temporal dimensions of dark patterns using analytical tools such as annotated wireframes, task flows, and service blueprints.

Research Findings

• What specific findings were achieved?

  1. Conducted a systematic coding analysis of Amazon Prime's "Iliad Flow" cancellation process, uncovering the multi-layered design intentions and strategies behind the dark patterns.
  2. Established the Temporal Analysis of Dark Patterns (TADP) methodology, including clear steps and a visualization framework, providing actionable guidelines for scholars and regulators.

• What advantages does it have compared to existing solutions?

  1. Comprehensiveness: Unlike existing methods that focus solely on static analysis, TADP offers an integrated perspective across multiple user interaction steps.
  2. Support for Legal and Policy Needs: Through precise case analyses (e.g., the FTC's complaint against Amazon), the methodology aligns directly with current regulatory requirements, supporting legal actions and policy reforms.
  3. Evidence-Based Analysis: Provides a more rigorous evaluation framework for the user experience design and HCI research communities, offering evidence to support future design ethics and legal interventions.

• What were the experimental or evaluation results?
  By analyzing Amazon's Iliad Flow, the authors revealed how the process employs multiple dark patterns (including social engineering, interface interference, and forced actions) to create obstacles and limit users' ability to cancel services. Specific findings include:

  • Single-Page Analysis: Demonstrated how each page uses manipulative design elements (e.g., "visually prominent" buttons that distract users from cancellation options).
  • Multi-Page Analysis: Illustrated how dark patterns across multiple pages construct a "maze-like" user experience.
  • System-Level Analysis: Using service blueprints, the study revealed Amazon's overarching strategy in designing subscription and cancellation services, showing that dark patterns are integral to its business strategy.

• Limitations and Future Directions

  1. Limitations:
     • Relies on complete information such as interface screenshots and interaction traces; partial evidence may limit analytical precision.
     • Time-intensive analysis process, making large-scale automated detection of dark patterns challenging.
  2. Future Directions:
     • Develop semi-automated or automated tools to enhance efficiency when combined with the TADP methodology.
     • Expand research to study the impact on vulnerable user groups, particularly those disproportionately burdened by dark patterns.
     • Explore cross-disciplinary approaches from design intervention to legal enforcement to support the governance of dark patterns.

Conclusion

Through case analysis and methodological development, this paper extends the analysis of dark patterns to multi-level temporal dimensions, proposing an actionable framework (TADP). This contribution addresses the gap in existing research regarding temporal complexity and opens new research pathways for academia, design, and legal fields.