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In 1991, researchers at the center for the Learning Sciences of Carnegie Mellon University were confronted with the confusing question of “where is AI?” from users, who were interacting with artificial intelligence (AI) but did not realize it. After three decades of research, we are still facing the same issue with the unclear understanding of AI among people. The lack of mutual understanding and expectations among AI users and designers and the ineffective interactions with AI that result raises the question of “how AI is generally perceived today?” To address this gap, we conducted 50 semi-structured interviews on perception and expectations of AI. Our results revealed that for most, AI is a dazzling concept that ranges from a simple automated device up to a full controlling agent and a self-learning superpower. We explain how these folk concepts shape users’ expectations when interacting with AI and envisioning its current and future state.

This paper reflects on a case study of a user-centred concept development process for a Machine Learning (ML) based design tool, conducted at an industry partner. The resulting concept uses ML to match graphical user interface elements in sketches on paper to their digital counterparts to create consistent wireframes. A user study (N=20) with a working prototype shows that this concept is preferred by designers, compared to the previous manual procedure. Reflecting on our process and findings we discuss lessons learned for developing ML tools that respect practitioners’ needs and practices.

The development of artificial intelligence, e. g. for Computer Vision, through supervised learning requires the input of large amounts of annotated or labeled data objects as training data. Usually, the creation of high-quality training data is done manually which can be repetitive and tiring. Gamification , the use of game elements in a non-game context, is one method to make such tedious tasks more interesting. We propose a multi-step process for gamifying the manual creation of training data for machine learning purposes. In this article, we give an overview of related concepts and existing implementations and present a user-centered approach for a real-life use case. Based on a survey within the target user group we identified annotation use cases and dominant player characteristics. The results served as a foundation for designing the gamification concepts which were then discussed with the participants. The final concept includes levels of increasing difficulty, tutorials, progress indicators and a narrative built around a robot character which at the same time is a user assistant. The implemented prototype is an extension of an existing annotation tool at an AI product company and serves as a basis for further observations.

Current interaction modalities for mobile Augmented Reality (AR) are tedious and lack expressiveness. To overcome these prevalent limitations, we developed and evaluated a multimodal interaction concept by pairing a smartphone as an input and output modality for mobile AR. In a user study (n = 24), we investigated the effects on interaction speed, accuracy, and task load for (1) virtual object manipulation as well as (2) interaction with established graphical user interfaces (GUIs). Our findings show that a smartphone-based AR controller results in significantly faster and more accurate object manipulation with reduced task load than state-of-art mid-air gestures. Our results also indicate a significant enhancement for using the physical touchscreen as a modality compared to mid-air gestures for GUI interaction. We conclude that interaction in mobile AR environments can be improved by utilizing a smartphone as an omnipresent controller. Additionally, we discuss how future AR systems can benefit from tangible touchscreens as an additional and complementary interaction modality.

This study compares the use of a marker-based AR instruction with a paper instruction commonly used in manual assembly. Hypotheses were tested as to whether the instruction type affects assembly time, number of errors, usability, and employee strain. Instead of student participants and artificial assembly tasks (e. g. Lego assemblies), the study was conducted with 16 trainees in a real workplace for the assembly of emergency door release handles in rail vehicles. Five assembly runs were performed. Assembly times and assembly errors were determined from recorded videos. Usability (SUS) and strain (NASA-TLX) were recorded with questionnaires. After a slower assembly at the beginning, the AR group assembled significantly faster in the fifth run. The comparable number of errors, usability and strain make marker-based AR applications interesting for knowledge transfer in manual assembly, especially due to the easy entrance and low costs.

With an ever-increasing need of skilled healthcare workers, efficient learning methods like Virtual Reality (VR) are becoming increasingly important. We developed and tested a VR simulation for endotracheal suctioning. The aim of this pilot study was to examine the VR simulation’s acceptance and increase of knowledge among participants. Furthermore, the effects of presence on acceptance and increase of knowledge were investigated. A total of 51 students participated in the pilot study, using a quasi-experimental pre-post-test design. A modified Unified Theory of Acceptance and Use of Technology (UTAUT) and the Igroup Presence Questionnaire (IPQ) were used. Correlation and regression analyses were performed. Pre- and post-tests showed a significant increase of knowledge (p < 0.001). The correlation between presence and behavioural intention was highly positive (r = 0.52, p < 0.001). Performance and effort expectancy are dominant effects on behavioural intention of using the VR simulation as an educational tool. The results indicate that a simulation which conveys a higher sense of presence is more likely to be accepted by learners. Regarding outcomes of presence on increase of knowledge, we found no significant correlation. Based on our study, we propose a design for a future mixed reality simulation with haptic elements and a plan on how to assess skills improvement.

Funding bodies in Western societies increasingly require researchers to address gender in their proposals – though often exclusively framed around binary notions. With oppressive power structures being prevalent and persuasive, these seep into current practices of Computer Science and Human-Computer Interaction (HCI) research. However, current curricula rarely provide actors in this space with grounded guidance on gender issues tied to their inquiries. Hence, developing an increased awareness of our societal responsibility towards equity can be challenging without an appropriate starting point. Drawing on a close reading of select literature discussing gender sensitivity in HCI research, we derived practical guidance in the form of recommendations for the design, proposal, conduct and presentation of research. Based on these recommendations, we then present the design of a card deck and initial tests thereof at ditact women’s IT summer university. Our analysis offers a starting point for HCI students and interested researchers to explore questions and issues around gender and to identify how gender relates to their research. This sensitisation may aid them in further reflecting on how they might better account for gendered implications of their work.

Usability and user experience maturity models are used to evaluate the capabilities of an organization in order to provide an assessment of their ability to develop usable products. But, as the main focus of such models is on an all-encompassing organizational level, they are difficult to implement in more complex organizations with a wide range of diverse and interlinked projects. This paper presents a project related UX maturity model, which was developed at DB Systel to address this issue: the PUXMM. It takes into account the nested internal customer relationships between departments and subcontractors and applies a human-centered design approach. There are two practical application scenarios for the PUXMM. It can be used to determine the UX maturity level of an ongoing project and as checklist to align a project to a desired maturity level from the outset.

In today’s e-commerce industry, conversion rate optimization is often considered essentially the same as user experience optimization. In addition, there is a strong focus on quantitative experimentation, which some deem a jack-of-all-trades solution, often at the expense of qualitative user experience research. Both are worrying developments. This essay elaborates on why it is harmful to consider conversion rate optimization and user experience optimization to be the same thing in the context of growth marketing, and how the three concepts are interrelated.