arXiv subjects

Thomas Mildner

Publications and source records attributed to Thomas Mildner.

14 recordsLinked to original sources

arXiv2025

A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social Media

Dark patterns are deceptive strategies that recent work in human-computer interaction (HCI) has captured throughout digital domains, including social networking sites (SNSs). While research has identified difficulties among people to recognise dark patterns effectively, few studies consider vulnerable populations and their experience in this regard, including people with attention deficit hyperactivity disorder (ADHD), who may be especially susceptible to attention-grabbing tricks. Based on an interactive web study with 135 participants, we investigate SNS users' ability to recognise and avoid dark patterns by comparing results from participants with and without ADHD. In line with prior work, we noticed overall low recognition of dark patterns with no significant differences between the two groups. Yet, ADHD individuals were able to avoid specific dark patterns more often. Our results advance previous work by understanding dark patterns in a realistic environment and offer insights into their effect on vulnerable populations.

cs.HC↗

arXiv2025

Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities

The emergence of Large Language Models (LLMs) has revolutionized Conversational User Interfaces (CUIs), enabling more dynamic, context-aware, and human-like interactions across diverse domains, from social sciences to healthcare. However, the rapid adoption of LLM-based personas raises critical ethical and practical concerns, including bias, manipulation, and unforeseen social consequences. Unlike traditional CUIs, where personas are carefully designed with clear intent, LLM-based personas generate responses dynamically from vast datasets, making their behavior less predictable and harder to govern. This workshop aims to bridge the gap between CUI and broader AI communities by fostering a cross-disciplinary dialogue on the responsible design and evaluation of LLM-based personas. Bringing together researchers, designers, and practitioners, we will explore best practices, develop ethical guidelines, and promote frameworks that ensure transparency, inclusivity, and user-centered interactions. By addressing these challenges collaboratively, we seek to shape the future of LLM-driven CUIs in ways that align with societal values and expectations.

cs.HC↗

arXiv2024

Level Up or Game Over: Exploring How Dark Patterns Shape Mobile Games

This study explores the prevalence of dark patterns in mobile games that exploit players through temporal, monetary, social, and psychological means. Recognizing the ethical concerns and potential harm surrounding these manipulative strategies, we analyze user-generated data of 1496 games to identify relationships between the deployment of dark patterns within "dark" and "healthy" games. Our findings reveal that dark patterns are not only widespread in games typically seen as problematic but are also present in games that may be perceived as benign. This research contributes needed quantitative support to the broader understanding of dark patterns in games. With an emphasis on ethical design, our study highlights current problems of revenue models that can be particularly harmful to vulnerable populations. To this end, we discuss the relevance of community-based approaches to surface harmful design and the necessity for collaboration among players/users and practitioners to promote healthier gaming experiences.

cs.HC↗

arXiv2024

Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design

In the rapidly evolving field of artificial intelligence (AI) agents, designing the agent's characteristics is crucial for shaping user experience. This workshop aims to establish a research community focused on AI agent persona design for various contexts, such as in-car assistants, educational tools, and smart home environments. We will explore critical aspects of persona design, such as voice, embodiment, and demographics, and their impact on user satisfaction and engagement. Through discussions and hands-on activities, we aim to propose practices and standards that enhance the ecological validity of agent personas. Topics include the design of conversational interfaces, the influence of agent personas on user experience, and approaches for creating contextually appropriate AI agents. This workshop will provide a platform for building a community dedicated to developing AI agent personas that better fit diverse, everyday interactions.

cs.HC↗

arXiv2024

Finding a Way Through the Social Media Labyrinth: Guiding Design Through User Expectations

Social networking services (SNS) have become integral to modern life to create and maintain meaningful relationships. Nevertheless, their historic growth of features has led to labyrinthine user interfaces (UIs) that often result in frustration among users - for instance, when trying to control privacy-related settings. This paper aims to mitigate labyrinthine UIs by studying users' expectations (N=21) through an online card sorting exercise based on 58 common SNS UI features, teaching us about their expectations regarding the importance of specific UI features and the frequency with which they use them. Our findings offer a valuable understanding of the relationship between the importance and frequency of UI features and provide design considerations for six identified UI feature groups. Through these findings, we inform the design and development of user-centred alternatives to current SNS interfaces that enable users to successfully navigate SNS and feel in control over their data by meeting their expectations.

cs.HC↗

arXiv2024

Hell is Paved with Good Intentions: The Intricate Relationship Between Cognitive Biases and Dark Patterns

Throughout the past decade, research in HCI has identified numerous instances of dark patterns in digital interfaces. These efforts have led to a well-fostered typology describing harmful strategies users struggle to navigate. However, an in-depth understanding of the underlying mechanisms that deceive, coerce, or manipulate users is missing. We explore the interplay between cognitive biases and dark patterns to address this gap. To that end, we conducted four focus groups with experts (N=15) in psychology and dark pattern scholarship, inquiring how they conceptualise the relation between cognitive biases and dark patterns. Based on our results, we constructed the "Relationship Model of Cognitive Biases and Dark Patterns" which illustrates how cognitive bias and deceptive design patterns relate and identifies opportune moments for ethical reconsideration and user protection mechanisms. Our insights contribute to the current discourse by emphasising ethical design decisions and their implications in the field of HCI.

cs.HC↗

arXiv2024

Listening to the Voices: Describing Ethical Caveats of Conversational User Interfaces According to Experts and Frequent Users

Advances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits, they also yield risks that may exploit people's trust. Although research looking at unethical design deployed through graphical user interfaces (GUIs) established a thorough understanding of so-called dark patterns, there is a need to continue this discourse within the CUI community to understand potentially problematic interactions. Addressing this gap, we interviewed 27 participants from three cohorts: researchers, practitioners, and frequent users of CUIs. Applying thematic analysis, we construct five themes reflecting each cohort's insights about ethical design challenges and introduce the CUI Expectation Cycle, bridging system capabilities and user expectations while considering each theme's ethical caveats. This research aims to inform future development of CUIs to consider ethical constraints while adopting a human-centred approach.

cs.HC↗

arXiv2023

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

Dark patterns are ubiquitous in digital systems, impacting users throughout their journeys on many popular apps and websites. While substantial efforts from the research community in the last five years have led to consolidated taxonomies of dark patterns, including an emerging ontology, most applications of these descriptors have been focused on analysis of static images or as isolated pattern types. In this paper, we present a case study of Amazon Prime's "Iliad Flow" to illustrate the interplay of dark patterns across a user journey, grounded in insights from a US Federal Trade Commission complaint against the company. We use this case study to lay the groundwork for a methodology of Temporal Analysis of Dark Patterns (TADP), including considerations for characterization of individual dark patterns across a user journey, combinatorial effects of multiple dark patterns types, and implications for expert detection and automated detection.

cs.HC↗

arXiv2023

An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building

Deceptive and coercive design practices are increasingly used by companies to extract profit, harvest data, and limit consumer choice. Dark patterns represent the most common contemporary amalgamation of these problematic practices, connecting designers, technologists, scholars, regulators, and legal professionals in transdisciplinary dialogue. However, a lack of universally accepted definitions across the academic, legislative and regulatory space has likely limited the impact that scholarship on dark patterns might have in supporting sanctions and evolved design practices. In this paper, we seek to support the development of a shared language of dark patterns, harmonizing ten existing regulatory and academic taxonomies of dark patterns and proposing a three-level ontology with standardized definitions for 65 synthesized dark patterns types across low-, meso-, and high-level patterns. We illustrate how this ontology can support translational research and regulatory action, including pathways to extend our initial types through new empirical work and map across application domains.

cs.HC↗

arXiv2023

Defending Against the Dark Arts: Recognising Dark Patterns in Social Media

Interest in unethical user interfaces has grown in HCI over recent years, with researchers identifying malicious design strategies referred to as ''dark patterns''. While such strategies have been described in numerous domains, we lack a thorough understanding of how they operate in social networking services (SNSs). Pivoting towards regulations against such practices, we address this gap by offering novel insights into the types of dark patterns deployed in SNSs and people's ability to recognise them across four widely used mobile SNS applications. Following a cognitive walkthrough, experts (N=6) could identify instances of dark patterns in all four SNSs, including co-occurrences. Based on the results, we designed a novel rating procedure for evaluating the malice of interfaces. Our evaluation shows that regular users (N=193) could differentiate between interfaces featuring dark patterns and those without. Such rating procedures could support policymakers' current moves to regulate deceptive and manipulative designs in online interfaces.

cs.HC↗

arXiv2023

About Engaging and Governing Strategies: A Thematic Analysis of Dark Patterns in Social Networking Services

Research in HCI has shown a growing interest in unethical design practices across numerous domains, often referred to as ``dark patterns''. There is, however, a gap in related literature regarding social networking services (SNSs). In this context, studies emphasise a lack of users' self-determination regarding control over personal data and time spent on SNSs. We collected over 16 hours of screen recordings from Facebook's, Instagram's, TikTok's, and Twitter's mobile applications to understand how dark patterns manifest in these SNSs. For this task, we turned towards HCI experts to mitigate possible difficulties of non-expert participants in recognising dark patterns, as prior studies have noticed. Supported by the recordings, two authors of this paper conducted a thematic analysis based on previously described taxonomies, manually classifying the recorded material while delivering two key findings: We observed which instances occur in SNSs and identified two strategies - engaging and governing - with five dark patterns undiscovered before.

cs.HC↗

arXiv2022

Rules Of Engagement: Levelling Up To Combat Unethical CUI Design

While a central goal of HCI has always been to create and develop interfaces that are easy to use, a deeper focus has been set more recently on designing interfaces more ethically. However, the exact meaning and measurement of ethical design has yet to be established both within the CUI community and among HCI researchers more broadly. In this provocation paper we propose a simplified methodology to assess interfaces based on five dimensions taken from prior research on so-called dark patterns. As a result, our approach offers a numeric score to its users representing the manipulative nature of evaluated interfaces. It is hoped that the approach - which draws a distinction between persuasion and manipulative design, and focuses on how the latter functions rather than how it manifests - will provide a viable way for quantifying instances of unethical interface design that will prove useful to researchers, regulators and potentially even users.

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arXiv2021

Ethical User Interfaces: Exploring the Effects of Dark Patterns on Facebook

Many researchers have been concerned with whether social media has a negative impact on the well-being of their audience. With the popularity of social networking sites (SNS) steadily increasing, psychological and social sciences have shown great interest in their effects and consequences on humans. In this work, we investigate Facebook using the tools of HCI to find connections between interface features and the concerns raised by these domains. Using an empirical design analysis, we identify interface interferences impacting users' online privacy. Through a subsequent survey (n=116), we find usage behaviour changes due to increased privacy concerns and report individual cases of addiction and mental health issues. These observations are the results of a rapidly changing SNS creating a gap of understanding between users' interactions with the platform and future consequences. We explore how HCI can help close this gap and work towards more ethical user interfaces in the future.

cs.HC↗

arXiv2021

How Social Are Social Media The Dark Patterns In Facebook's Interface

Many researchers have been concerned with social media and possible negative impacts on the well-being of their audience. With the popularity of social networking sites (SNS) steadily increasing, psychological and social sciences have shown great interest in their effects and consequences on humans. Unfortunately, it appears to be difficult to find correlations between SNS and the results of their works. We, therefore, investigate Facebook using the tools of HCI to find connections between interface features and the concerns raised by these domains. With a nod towards Dark Patterns, we use an empirical design analysis to identify interface interferences that impact users' online privacy. We further discuss how HCI can help to work towards more ethical user interfaces in the future.

cs.HC↗