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Hanna Schraffenberger

Publications and source records attributed to Hanna Schraffenberger.

7 recordsLinked to original sources

Friction in AI-Assisted Clinical Decision-Making: A Case Study on The Role of Questions and 'What-if' Scenarios

Clinical decision-making is augmented by decision-support systems (DSSs). To counter overreliance on DSSs, several methods have been proposed that create friction in order to promote cognitive engagement and reflection. In this paper, we investigate how two such forms of friction, namely data-driven questions and `what-if' analysis, are perceived by medical experts. For a real-world decision task, we replicated a DSS used in clinical practice and gathered clinicians' feedback on a prototype through in-situ interviews (n=7). Our findings suggest that while the questions were perceived as unhelpful for reflective thinking, they could serve as reminders to consider relevant information. Furthermore, inspecting `what-if' hypotheticals was found useful for potentially improving patient care. Clinicians saw our prototype as a promising training tool for novice clinicians. From the clinicians' feedback, we make recommendations for designing friction in work practices. Our work contributes to human-AI interaction research, which aims to encourage reflection to mitigate AI overreliance.

cs.HC↗

Supporting Reflection and Forward-Looking Reasoning With Data-Driven Questions

Many generative AI systems as well as decision-support systems (DSSs) provide operators with predictions or recommendations. Various studies show, however, that people can mistakenly adopt the erroneous results presented by those systems. Hence, it is crucial to promote critical thinking and reflection during interaction. One approach we are focusing on involves encouraging reflection during machine-assisted decision-making by presenting decision-makers with data-driven questions. In this short paper, we provide a brief overview of our work in that regard, namely: 1) the development of a question taxonomy, 2) the development of a prototype in the medical domain and the feedback received from clinicians, 3) a method for generating questions using a large language model, and 4) a proposed scale for measuring cognitive engagement in human-AI decision-making. In doing so, we contribute to the discussion about the design, development, and evaluation of tools for thought, i.e., AI systems that provoke critical thinking and enable novel ways of sense-making.

cs.HC↗

Dark and Bright Patterns in Cookie Consent Requests

Dark patterns are (evil) design nudges that steer people's behaviour through persuasive interface design. Increasingly found in cookie consent requests, they possibly undermine principles of EU privacy law. In two preregistered online experiments we investigated the effects of three common design nudges (default, aesthetic manipulation, obstruction) on users' consent decisions and their perception of control over their personal data in these situations. In the first experiment (N = 228) we explored the effects of design nudges towards the privacy-unfriendly option (dark patterns). The experiment revealed that most participants agreed to all consent requests regardless of dark design nudges. Unexpectedly, despite generally low levels of perceived control, obstructing the privacy-friendly option led to more rather than less perceived control. In the second experiment (N = 255) we reversed the direction of the design nudges towards the privacy-friendly option, which we title "bright patterns". This time the obstruction and default nudges swayed people effectively towards the privacy-friendly option, while the result regarding perceived control stayed the same compared to Experiment 1. Overall, our findings suggest that many current implementations of cookie consent requests do not enable meaningful choices by internet users, and are thus not in line with the intention of the EU policymakers. We also explore how policymakers could address the problem.

cs.CY↗

A Taxonomy of Questions for Critical Reflection in Machine-Assisted Decision-Making

Decision-makers run the risk of relying too much on machine recommendations, which is associated with lower cognitive engagement. Reflection has been shown to increase cognitive engagement and improve critical thinking and therefore decision-making. Questions are a means to stimulate reflection, but there is a research gap regarding the systematic creation and use of relevant questions for machine-assisted decision-making. We therefore present a taxonomy of questions aimed at promoting reflection and cognitive engagement in order to stimulate a deliberate decision-making process. Our taxonomy builds on the Socratic questioning method and a question bank for explainable AI. As a starting point, we focus on clinical decision-making. Brief discussions with two medical and three educational researchers provide feedback on the relevance and expected benefits of our taxonomy. Our work contributes to research on mitigating overreliance in human-AI interactions and aims to support effective human oversight as required by the European AI Act.

cs.HC↗

Digital Dotted Lines: Design and Evaluation of a Prototype for Digitally Signing Documents Using Identity Wallets

Documents are largely stored and shared digitally. Yet, digital documents are still commonly signed using (copies of) handwritten signatures, which are sensitive to fraud. Though secure, cryptography-based signature solutions exist, they are hardly used due to usability issues. This paper proposes to use digital identity wallets for securely and intuitively signing digital documents with verified personal data. Using expert feedback, we implemented this vision in an interactive prototype. The prototype was assessed in a moderated usability test (N = 15) and a subsequent unmoderated remote usability test (N = 99). While participants generally expressed satisfaction with the system, they also misunderstood how to interpret the signature information displayed by the prototype. Specifically, signed documents were also trusted when the document was signed with irrelevant personal data of the signer. We conclude that such unwarranted trust forms a threat to usable digital signatures and requires attention by the usable security community.

cs.HC↗

Staying at the Roach Motel: Cross-Country Analysis of Manipulative Subscription and Cancellation Flows

Subscribing to online services is typically a straightforward process, but cancelling them can be arduous and confusing -- causing many to resign and continue paying for services they no longer use. Making the cancellation intentionally difficult is recognized as a dark pattern called Roach Motel. This paper characterizes the subscription and cancellation flows of popular news websites from four different countries, and discusses them in the context of recent regulatory changes. We study the design features that make it difficult to cancel a subscription and find several cancellation flows that feature intentional barriers, such as forcing users to type in a phrase or call a representative. Further, we find many subscription flows that do not adequately inform users about recurring charges. Our results point to a growing need for effective regulation of designs that trick, coerce, or manipulate users into paying for subscriptions they do not want.

cs.HC↗

One-press control: a tactile input method for pressure-sensitive computer keyboards

This work presents One-press control, a tactile input method for pressure-sensitive keyboards based on the detection and classification of pressing movements on the already held-down key. To seamlessly integrate the added control input with existing practices for ordinary computer keyboards, the redefined notion of virtual modifier keys is introduced. A number of application examples are given, especially to point out a potential for simplifying existing interactions by replacing modifier key combinations with single key presses. Also, a new class of interaction scenarios employing the technique is proposed, based on an interaction model named "What You Touch Is What You Get (WYTIWYG)". Here, the proposed tactile input method is used to navigate interaction options, get full previews of potential outcomes, and then either commit to one or abort altogether - all in the space of one key depress / release cycle. The results of user testing indicate some remaining implementation issues, as well as that the technique can be learned within about a quarter of an hour of hands-on operating practice time.

cs.HC↗