arXiv subjects

Arianna Rossi

Publications and source records attributed to Arianna Rossi.

5 recordsLinked to original sources

arXiv2026

"What I'm Interested in is Something that Violates the Law": Regulatory Practitioner Views on Automated Detection of Deceptive Design Patterns

Although deceptive design patterns are subject to growing regulatory oversight, enforcement races to keep up with the scale of the problem. One promising solution is automated detection tools, many of which are developed within academia. We interviewed nine experienced practitioners working within or alongside regulatory bodies to understand their work against deceptive design patterns, including the use of supporting tools and the prospect of automation. Computing technologies have their place in regulatory practice, but not as envisioned in research. For example, investigations require utmost transparency and accountability in all the activities we identify as accompanying dark pattern detection, which many existing tools cannot provide. Moreover, tools need to map interfaces to legal violations to be of use. We thus recommend conducting user requirement research to maximize research impact, supporting ancillary activities beyond detection, and establishing practical tech adoption pathways that account for the needs of both scientific and regulatory activities.

cs.HC↗

arXiv2025

Acceptability of AI Assistants for Privacy: Perceptions of Experts and Users on Personalized Privacy Assistants

Individuals increasingly face an overwhelming number of tasks and decisions. To cope with the new reality, there is growing research interest in developing intelligent agents that can effectively assist people across various aspects of daily life in a tailored manner, with privacy emerging as a particular area of application. Artificial intelligence (AI) assistants for privacy, such as personalized privacy assistants (PPAs), have the potential to automatically execute privacy decisions based on users' pre-defined privacy preferences, sparing them the mental effort and time usually spent on each privacy decision. This helps ensure that, even when users feel overwhelmed or resigned about privacy, the decisions made by PPAs still align with their true preferences and best interests. While research has explored possible designs of such agents, user and expert perspectives on the acceptability of such AI-driven solutions remain largely unexplored. In this study, we conducted five focus groups with domain experts (n = 11) and potential users (n = 26) to uncover key themes shaping the acceptance of PPAs. Factors influencing the acceptability of AI assistants for privacy include design elements (such as information sources used by the agent), external conditions (such as regulation and literacy education), and systemic conditions (e.g., public or market providers and the need to avoid monopoly) to PPAs. These findings provide theoretical extensions to technology acceptance models measuring PPAs, insights on design, and policy implications for PPAs, as well as broader implications for the design of AI assistants.

cs.HC↗

arXiv2021

Cookie Banners, What's the Purpose? Analyzing Cookie Banner Text Through a Legal Lens

A cookie banner pops up when a user visits a website for the first time, requesting consent to the use of cookies and other trackers for a variety of purposes. Unlike prior work that has focused on evaluating the user interface (UI) design of cookie banners, this paper presents an in-depth analysis of what cookie banners say to users to get their consent. We took an interdisciplinary approach to determining what cookie banners should say. Following the legal requirements of the ePrivacy Directive (ePD) and the General Data Protection Regulation (GDPR), we manually annotated around 400 cookie banners presented on the most popular English-speaking websites visited by users residing in the EU. We focused on analyzing the purposes of cookie banners and how these purposes were expressed (e.g., any misleading or vague language, any use of jargon). We found that 89% of cookie banners violated applicable laws. In particular, 61% of banners violated the purpose specificity requirement by mentioning vague purposes, including "user experience enhancement". Further, 30% of banners used positive framing, breaching the freely given and informed consent requirements. Based on these findings, we provide recommendations that regulators can find useful. We also describe future research directions.

cs.HC↗

arXiv2021

I am Definitely Manipulated, Even When I am Aware of it. It s Ridiculous! -- Dark Patterns from the End-User Perspective

Online services pervasively employ manipulative designs (i.e., dark patterns) to influence users to purchase goods and subscriptions, spend more time on-site, or mindlessly accept the harvesting of their personal data. To protect users from the lure of such designs, we asked: are users aware of the presence of dark patterns? If so, are they able to resist them? By surveying 406 individuals, we found that they are generally aware of the influence that manipulative designs can exert on their online behaviour. However, being aware does not equip users with the ability to oppose such influence. We further find that respondents, especially younger ones, often recognise the "darkness" of certain designs, but remain unsure of the actual harm they may suffer. Finally, we discuss a set of interventions (e.g., bright patterns, design frictions, training games, applications to expedite legal enforcement) in the light of our findings.

cs.HC↗

arXiv2021

All in one stroke? Intervention Spaces for Dark Patterns

This position paper draws from the complexity of dark patterns to develop arguments for differentiated interventions. We propose a matrix of interventions with a \textit{measure axis} (from user-directed to environment-directed) and a \textit{scope axis} (from general to specific). We furthermore discuss a set of interventions situated in different fields of the intervention spaces. The discussions at the 2021 CHI workshop "What can CHI do about dark patterns?" should help hone the matrix structure and fill its fields with specific intervention proposals.

cs.HC↗