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

Feel and Touch: A Haptic Mobile Game to Assess Tactile Processing

Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children from 3 to 6 years old, shows that children accept vibrations and are able to use the proposed vibrotactile patterns. However, it is still necessary to work on the instructions to make the game dynamic clearer and rewards to keep the attention of children. We close this article by discussing future work and conclusions

Examining the Impact of Provenance-Enabled Media on Trust and Accuracy Perceptions

In recent years, industry leaders and researchers have proposed to use technical provenance standards to address visual misinformation spread through digitally altered media. By adding immutable and secure provenance information such as authorship and edit date to media metadata, social media users could potentially better assess the validity of the media they encounter. However, it is unclear how end users would respond to provenance information, or how to best design provenance indicators to be understandable to laypeople. We conducted an online experiment with 595 participants from the US and UK to investigate how provenance information altered users' accuracy perceptions and trust in visual content shared on social media. We found that provenance information often lowered trust and caused users to doubt deceptive media, particularly when it revealed that the media was composited. We additionally tested conditions where the provenance information itself was shown to be incomplete or invalid, and found that these states have a significant impact on participants' accuracy perceptions and trust in media, leading them, in some cases, to disbelieve honest media. Our findings show that provenance, although enlightening, is still not a concept well-understood by users, who confuse media credibility with the orthogonal (albeit related) concept of provenance credibility. We discuss how design choices may contribute to provenance (mis)understanding, and conclude with implications for usable provenance systems, including clearer interfaces and user education.Comment: Accepted to CSCW 202

Designing for Nurse-AI Collaboration in Triage

The Local Emergency Medical Communication Centers (LEMCs) play a crucial role in the Norwegian healthcare system by receiving calls for immediate medical assistance. Registered nurses operate the phone calls, and their task is to assess the situation and triage the caller into appropriate triage levels indicating when and how help should be provided. Telephone triage poses challenges due to the limitations of audio communication, time sensitivity, and complex decision-making. Additionally, nurses often face the burden of managing clinical tools across multiple interfaces. This thesis explored how to design a system to support nurses in telephone triage and how we can facilitate nurse-AI collaboration in the process. A Research through Design (RtD) methodology was employed, and an iterative design approach was utilized. The research investigated the design aspects of AI-based suggestions and the use of natural language when creating semi-structured documentation. Four prototype iterations were developed throughout the study, and researchers from RE-AIMED and telephone operators conducted evaluations of the prototypes. Designing a tool for telephone triage requires understanding the user's needs and workflow. It is, therefore, crucial to involve telephone operators in the design process. The prototype demonstrated how we could design for incorporating AI in the triage process, and this thesis explores the various considerations when designing for nurse-AI collaboration. One notable finding was the importance of enabling documentation in natural language, as relying solely on structured documentation may fail to capture the caller's specific situation. Additionally, it is important to design a system that facilitates documentation of patient-initiated information and questions initiated by the nurses or the system.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Identifying Engagement in Children's Interaction whilst Composing Digital Music at Home

Identifying points of engagement from a person’s interaction with computers could be used to assess their experience and to adapt user interfaces in real-time. However, it is difficult to identify points of engagement unobtrusively; HCI studies typically use retrospective protocols or rely on cumbersome sensors for real-time analysis. We present a case study on how children compose digital music at home in which we remotely identify points of engagement from patterns of interaction with a musical interface. A mixed-methods approach is contributed in which video recordings of children’s interactions whilst composing are labelled for engagement and linked to i) interaction logs from the interface to identify indicators of engagement in interaction, and ii) interview data gathered using a remote video-cued recall technique to understand the experiential qualities of engaging interactions directly from users. We conclude by speculating on how the suggested indicators of engagement inform the design of adaptive music systems

Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations in the area. Here, we explore Java 8 default methods, which allow interfaces to contain (instance) method implementations. Default methods can ease interface evolution, make certain ubiquitous design patterns redundant, and improve both modularity and maintainability. A focus of this work is to discover, through a scientific approach and a novel technique, situations where developers found these constructs useful and where they did not, and the reasons for each. Although several studies center around assessing new language features, to the best of our knowledge, this kind of construct has not been previously considered. Despite their benefits, we found that developers did not adopt default methods in all situations. Our study consisted of submitting pull requests introducing the language feature to 19 real-world, open source Java projects without altering original program semantics. This novel assessment technique is proactive in that the adoption was driven by an automatic refactoring approach rather than waiting for developers to discover and integrate the feature themselves. In this way, we set forth best practices and patterns of using the language feature effectively earlier rather than later and are able to possibly guide (near) future language evolution. We foresee this technique to be useful in assessing other new language features, design patterns, and other programming idioms

Software Reference Architecture for CubeSats – A Direct Approach

Ever since the first CubeSat mission was launched, the concept and complexity of CubeSat missions has evolved at a pace that current operational system/doctrine cannot match. In an increasingly dynamic space economy, where small businesses have become the norm, innovative solutions that abstract away complexity and increase autonomy are fundamental to reduce operational costs. It is within this frame that the current study is presented. To address the need for a standardized software architecture of NewSpace companies, we first assess the European small satellite market needs through a survey with key players in the space sector. From this survey, we derive the high-level requirements, functionalities, and interfaces of a software architecture for CubeSats, the preferred platform due to its lower cost when compared with traditional platforms. Finally, we report the implementation results of a set of these components and show how they reflect design drivers

Is Evaluating Visual Search Interfaces in Digital Libraries Still an Issue?

Although various visual interfaces for digital libraries have been developed in prototypical systems, very few of these visual approaches have been integrated into today's digital libraries. In this position paper we argue that this is most likely due to the fact that the evaluation results of most visual systems lack comparability. There is no fix standard on how to evaluate visual interactive user interfaces. Therefore it is not possible to identify which approach is more suitable for a certain context. We feel that the comparability of evaluation results could be improved by building a common evaluation setup consisting of a reference system, based on a standardized corpus with fixed tasks and a panel for possible participants.Comment: 10 pages, 2 figures, LWA Workshop 201

Reputation Agent: Prompting Fair Reviews in Gig Markets

Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.Comment: 12 pages, 5 figures, The Web Conference 2020, ACM WWW 202