publications | Hauke G.W. Sandhaus

2026

ZfP
Deception Is Ugly: Linking Aesthetic Judgment to Perceived Manipulation in Dark Patterns

Hauke Sandhaus, and Doris Maria Rhomberg

Zeitschrift für Psychologie, 2026

Accepted, forthcoming

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Dark patterns are manipulative interface designs that exploit cognitive biases. We surveyed 126 social media users who evaluated mockups of 15 dark patterns across six strategic categories, using an adapted User Experience Questionnaire with four autonomy-focused items (pressuring, addictive, covert, deceptive). Deception co-occurred strongly with negative aesthetic judgments (r = 0.93): users rated deceptive interfaces as unattractive, whereas pressure, addictiveness, and covertness showed weaker associations. Within strategic categories, Interface Interference (r = 0.77) and Social Engineering (r = 0.72) items cohered, indicating that several categories from existing taxonomies correspond to coherent user experiences. These exploratory results are consistent with users holding tacit awareness that becomes articulable when vocabulary is provided, with the four autonomy items functioning as distinct perceptual dimensions. They point to ethics-focused UX measurement scales as a direction for capturing unethical influence alongside pragmatic and hedonic constructs.
@article{Sandhaus2026-deception, title = {Deception Is Ugly: Linking Aesthetic Judgment to Perceived Manipulation in Dark Patterns}, author = {Sandhaus, Hauke and Rhomberg, Doris Maria}, year = {2026}, journal = {Zeitschrift für Psychologie}, publisher = {Hogrefe Publishing}, language = {en}, psyarxiv = {https://osf.io/preprints/psyarxiv/bhfrz_v1}, thread = {ethical-design}, note = {Accepted, forthcoming}, }
TLDR: Across 126 social media users, perceived deception co-occurs strongly with negative aesthetic judgments of dark patterns (r = 0.93), pointing toward ethics-focused UX measurement scales.
CHIWORK LBW
Making Indecent Persuasion Visible: How Evaluation Metrics Shape UX Designers’ Ethical Reasoning

Hauke Sandhaus, Doris Maria Rhomberg, and Helen Nissenbaum

In CHIWORK ’26: Proceedings of the 5th Annual Symposium on Human-Computer Interaction for Work (Late-Breaking Work), Linz, Austria, Jun 2026

Accepted, forthcoming

Abs Bib

UX evaluation tools are widely treated as neutral measurement instruments, yet the metrics designers see during evaluation may determine what they can recognise as ethically problematic. In a three-condition experiment, 141 UX professionals evaluated social media interfaces containing dark patterns. When dashboards included persuasion-focused items alongside standard User Experience Questionnaire (UEQ) data, designers rejected manipulative interfaces at nearly double the rate of a no-data baseline (56.2% vs. 30.0%). Standard UEQ data alone already produced a significant intermediate shift (43.9% rejection), so any user-testing signal recalibrates judgement. Decision confidence stayed uniformly high across conditions: designers without evaluation data were not cautiously uncertain but confidently uncalibrated, reaching different conclusions than they would have with user data while feeling equally sure. Analysis of 1,313 written justifications showed that persuasion-focused data shifted reasoning from business and aesthetic framings toward explicit engagement with manipulation, user trust, and autonomy. We introduce indecent persuasion, behavioural influence that users experience as pressuring, addictive, covert, or deceptive, as a dimension of user experience that standard instruments fail to surface. The findings raise a question about evaluation infrastructure: who decides which dimensions of user experience count?
@inproceedings{Sandhaus2026-indecent, title = {Making Indecent Persuasion Visible: How Evaluation Metrics Shape UX Designers' Ethical Reasoning}, author = {Sandhaus, Hauke and Rhomberg, Doris Maria and Nissenbaum, Helen}, year = {2026}, month = jun, booktitle = {CHIWORK '26: Proceedings of the 5th Annual Symposium on Human-Computer Interaction for Work (Late-Breaking Work)}, location = {Linz, Austria}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {CHIWORK '26}, keywords = {UX metrics, dark patterns, indecent persuasion, ethical design, evaluation instruments, professional judgment}, thread = {ethical-design}, note = {Accepted, forthcoming}, }
TLDR: In a study of 141 UX professionals, persuasion-focused evaluation metrics nearly doubled rejection of manipulative interfaces, surfacing "indecent persuasion" as a dimension standard UX instruments fail to capture.
CHIWORK
Interrogating GenAI Augmentation for CHIworkers: Strategies for Professional Autonomy and Accountability

Hauke Sandhaus, Kashif Imteyaz, Mohammed Almutairi, and 5 more authors

In CHIWORK ’26: Proceedings of the 5th Annual Symposium on Human-Computer Interaction for Work (Workshop), Linz, Austria, Jun 2026

Accepted, forthcoming (open access, ACM); workshop co-organizer

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As Generative AI (GenAI) becomes deeply embedded in UX research, design, and software engineering, the HCI community faces a pressing challenge: balancing the acceleration of output with the risks of de-skilling, loss of flow state, and diminished accountability. The goal of this workshop is to move beyond simple AI disclosure statements to figure out how HCI professionals can maintain "deep work" and intellectual autonomy, rather than merely "scraping by" using AI outputs, and when full hand-off may be appropriate. Participants will be invited to bring concrete examples of AI-augmented workflows they consider responsible, or irresponsible, drawn from active practice. Through mapping real-world AI use and collaboratively brainstorming countermeasures, this hybrid workshop will bring together researchers and practitioners to define what ethical "co-thinking, co-creating and co-augmenting with AI" looks like. Ultimately, we aim to produce a shared repository of evolving responsible practices or a professional code of conduct, helping the community transition toward accountable, professional GenAI-augmented workflows.
@inproceedings{Sandhaus2026-chiwork-ai, title = {Interrogating GenAI Augmentation for CHIworkers: Strategies for Professional Autonomy and Accountability}, author = {Sandhaus, Hauke and Imteyaz, Kashif and Almutairi, Mohammed and Prajod, Pooja and Ramesh, Divya and Savage, Saiph and Yang, Qian and Muller, Michael}, year = {2026}, month = jun, booktitle = {CHIWORK '26: Proceedings of the 5th Annual Symposium on Human-Computer Interaction for Work (Workshop)}, location = {Linz, Austria}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {CHIWORK '26}, keywords = {Generative AI, Professional Ethics, Future of Work, HCI Practice, Accountability, Co-thinking}, thread = {human-ai}, note = {Accepted, forthcoming (open access, ACM); workshop co-organizer}, }
TLDR: A CHIWORK 2026 workshop moving beyond AI disclosure statements to ask how HCI professionals can preserve deep work, intellectual autonomy, and accountability in GenAI-augmented workflows.

CHI Workshop

Bridge Over Troubled Water: Aligning Commercial Incentives With Ethical Design Practice To Combat Deceptive Patterns

Thomas Eßmeyer, Johanna Gunawan, Colin M Gray, and 8 more authors

In Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, Apr 2026

Workshop co-organizer

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@inproceedings{Essmeyer2026-oa,
  title = {Bridge Over Troubled Water: Aligning Commercial Incentives With Ethical Design Practice To Combat Deceptive Patterns},
  author = {Eßmeyer, Thomas and Gunawan, Johanna and Gray, Colin M and Sánchez Chamorro, Lorena and Monge Roffarello, Alberto and Seaborn, Katie and Sandhaus, Hauke and Lukoff, Kai and Savino, Gian-Luca and Chivukula, Shruthi Sai and Nakamura, Satoshi},
  year = {2026},
  month = apr,
  doi = {10.1145/3772363.3778758},
  url = {https://doi.org/10.1145/3772363.3778758},
  booktitle = {Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  series = {CHI EA '26},
  keywords = {Dark Patterns, Ethics and Values, Legal and Policy Perspectives, Regulation, UX Practice},
  note = {Workshop co-organizer},
}

TLDR: A CHI 2026 workshop bringing researchers and practitioners together to align commercial incentives with ethical design practice and combat deceptive patterns.

CSCW Workshop

“Nobody Did This”: Contribution, Originality, and Accountability in Agent-Mediated Collaboration

Kashif Imteyaz, Mohammad Rashidujjaman Rifat, Divya Ramesh, and 6 more authors

In Companion Publication of the 2026 ACM Conference on Computer-Supported Cooperative Work and Social Computing, Nov 2026

Workshop co-organizer

Bib Website

@inproceedings{Imteyaz2026-nobody,
  title = {``Nobody Did This'': Contribution, Originality, and Accountability in Agent-Mediated Collaboration},
  author = {Imteyaz, Kashif and Rifat, Mohammad Rashidujjaman and Ramesh, Divya and Rick, Steven R and Hosio, Simo and Sandhaus, Hauke and Sarkar, Advait and Riedl, Christoph and Savage, Saiph},
  year = {2026},
  month = nov,
  booktitle = {Companion Publication of the 2026 ACM Conference on Computer-Supported Cooperative Work and Social Computing},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  series = {CSCW '26 Companion},
  note = {Workshop co-organizer},
}

TLDR: A CSCW 2026 workshop confronting "contribution dissolution": the blurring of attribution, originality, and accountability when LLM agents mediate collaborative knowledge work.

2025

FAccT
Privacy of Groups in Dense Street Imagery

Matt Franchi^*, Hauke Sandhaus^*, Madiha Zahrah Choksi, and 3 more authors

In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, Athens, Greece, Jun 2025

* = equal contribution

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Spatially and temporally dense street imagery (DSI) datasets have grown unbounded. In 2024, individual companies possessed around 3 trillion unique images of public streets. DSI data streams are only set to grow as companies like Lyft and Waymo use DSI to train autonomous vehicle algorithms and analyze collisions. Academic researchers leverage DSI to explore novel approaches to urban analysis. Despite good-faith efforts by DSI providers to protect individual privacy through blurring faces and license plates, these measures fail to address broader privacy concerns. In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from supposedly anonymized data. We perform a penetration test to demonstrate how easily sensitive group affiliations can be inferred from obfuscated pedestrians in 25,232,608 dashcam images taken in New York City. We develop a typology of identifiable groups within DSI and analyze privacy implications through the lens of contextual integrity. Finally, we discuss actionable recommendations for researchers working with data from DSI providers.
@inproceedings{franchi2025privacygroupsdensestreet, title = {Privacy of Groups in Dense Street Imagery}, author = {Franchi, Matt and Sandhaus, Hauke and Choksi, Madiha Zahrah and Engelmann, Severin and Ju, Wendy and Nissenbaum, Helen}, year = {2025}, doi = {10.1145/3715275.3732185}, isbn = {9798400714825}, url = {https://doi.org/10.1145/3715275.3732185}, booktitle = {Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency}, pages = {2874–2891}, numpages = {18}, keywords = {privacy, dense street imagery, group privacy, contextual integrity, computer vision, surveillance, penetration testing, auditing}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {FAccT '25}, month = jun, location = {Athens, Greece}, note = {* = equal contribution}, thread = {data-privacy}, eprint = {2505.07085}, archiveprefix = {arXiv}, primaryclass = {cs.CY} }
TLDR: Dense street imagery enables harmful group membership inference despite individual anonymity. Contextual Integrity is used to analyze group based privacy implications based on appropriate information flows.
CSCW
My Precious Crash Data: Barriers and Opportunities in Encouraging Autonomous Driving Companies to Share Safety-Critical Data

Hauke Sandhaus, Angel Hsing-Chi Hwang, Wendy Ju, and 1 more author

Proceedings of the ACM on Human-Computer Interaction, Oct 2025

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Safety-critical data, such as crash and near-crash records, are crucial to improving autonomous vehicle (AV) design and development. Sharing such data across AV companies, academic researchers, regulators, and the public can help make all AVs safer. However, AV companies rarely share safety-critical data externally. This paper aims to pinpoint why AV companies are reluctant to share safety-critical data, with an eye on how these barriers can inform new approaches to promote sharing. We interviewed twelve AV company employees who actively work with such data in their day-to-day work. Findings suggest two key, previously unknown barriers to data sharing: (1) Datasets inherently embed salient knowledge that is key to improving AV safety and are resource-intensive. Therefore, data sharing, even within a company, is fraught with politics. (2) Interviewees believed AV safety knowledge is private knowledge that brings competitive edges to their companies, rather than public knowledge for social good. We discuss the implications of these findings for incentivizing and enabling safety-critical AV data sharing, specifically, implications for new approaches to (1) debating and stratifying public and private AV safety knowledge, (2) innovating data tools and data sharing pipelines that enable easier sharing of public AV safety data and knowledge; (3) offsetting costs of curating safety-critical data and incentivizing data sharing.
@article{Sandhaus2025-hc, title = {My Precious Crash Data: Barriers and Opportunities in Encouraging Autonomous Driving Companies to Share Safety-Critical Data}, author = {Sandhaus, Hauke and Hwang, Angel Hsing-Chi and Ju, Wendy and Yang, Qian}, year = {2025}, month = oct, journal = {Proceedings of the ACM on Human-Computer Interaction}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {9}, number = {7}, pages = {1--21}, articleno = {348}, doi = {10.1145/3757493}, url = {https://doi.org/10.1145/3757493}, issn = {2573-0142}, thread = {data-privacy}, }
TLDR: This study identifies barriers to sharing safety-critical data in autonomous vehicle companies, revealing that datasets are seen as competitive knowledge due to embedded salient knowledge, making sharing politically fraught.
DIS
Co-Designing with Transformers: Unpacking the Complex Role of GenAI in Interactive System Design Education

Hauke Sandhaus, Qiuquan Gu, Maria Teresa Parreira, and 1 more author

In Proceedings of the 2025 ACM Designing Interactive Systems Conference, Funchal, Portugal, Jul 2025

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Generative Artificial Intelligence (GenAI) is transforming Human-Computer Interaction (HCI) education and technology design, yet its impact remains poorly understood. This study explores how graduate students in an applied HCI course used GenAI tools during interactive device design. Despite no encouragement, all groups integrated GenAI into their workflows. Through 12 post-class group interviews, we identified how GenAI co-design behaviors present both benefits, such as enhanced creativity and faster design iterations, and risks, including shallow learning and reflection. Benefits were most evident during the execution phases, while the discovery and reflection phases showed limited gains. A taxonomy of usage patterns revealed that students’ outcomes depended more on how they used GenAI than the specific tasks performed. These findings highlight the need for HCI education to adapt to GenAI’s role and offer recommendations for curricula to better prepare future designers for effective creative co-design.
@inproceedings{Sandhaus2025-jc, title = {Co-Designing with Transformers: Unpacking the Complex Role of GenAI in Interactive System Design Education}, author = {Sandhaus, Hauke and Gu, Qiuquan and Parreira, Maria Teresa and Ju, Wendy}, year = {2025}, month = jul, booktitle = {Proceedings of the 2025 ACM Designing Interactive Systems Conference}, location = {Funchal, Portugal}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {DIS '25}, pages = {1228--1243}, doi = {10.1145/3715336.3735805}, isbn = {979-8-4007-1485-6/2025/07}, url = {https://doi.org/10.1145/3715336.3735805}, eprint = {2410.14048}, archiveprefix = {arXiv}, primaryclass = {cs.HC}, thread = {human-ai}, }
TLDR: GenAI in Human-Computer Interaction education and design brings both benefits, such as enhanced creativity and faster iterations, and risks, including shallow learning and reflection. Students’ approach to GenAI, rather than the specific tasks performed, influences the success of GenAI co-design.

2024

ITSC
Characterizing Cultural Differences in Naturalistic Driving Interactions

Rachel Di Pirro, Hauke Sandhaus, David Goedicke, and 3 more authors

In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), Sep 2024

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The characterization of driver interactions is important for a variety of problems associated with the design of autonomy for vehicles. We consider the role of cultural context in driver interactions, by evaluating the differences in driving interactions in simulated driving experiments conducted in New York City, New York, USA, and in Haifa, Israel. The same experiment was conducted in both locations, and focused on naturalistic driving interactions at unsigned intersections, in which interaction with another vehicle was required for safe navigation through the intersection. We employ conditional distribution embeddings, a nonparametric machine learning technique, to empirically characterize differences in the distribution of trajectories that characterize driver interactions, across both locations. We show that cultural variability outweighs individual variability in intersections that require turning maneuvers, and that clear distinctions amongst driving strategies are evident between populations. Our approach facilitates a data-driven analysis that is amenable to rigorous statistical testing, in a manner that minimizes filtering, pre-processing, and other manipulations that could inadvertently bias the data and obscure important findings.
@inproceedings{Di_Pirro_2024, title = {Characterizing Cultural Differences in Naturalistic Driving Interactions}, author = {Di Pirro, Rachel and Sandhaus, Hauke and Goedicke, David and Calderone, Dan and Oishi, Meeko and Ju, Wendy}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, pages = {3651--3658}, year = {2024}, month = sep, day = {24-27}, address = {Edmonton, Canada}, url = {https://its.papercept.net/conferences/scripts/abstract.pl?ConfID=87&Number=874}, doi = {10.1109/itsc58415.2024.10919603}, issn = {2153-0017,2153-0009}, language = {en}, thread = {automotive}, }
TLDR: This study compares driver interactions at unsigned intersections in New York City and Haifa, using MMD in Hilbert space, revealing that cultural differences significantly influence driving strategies, especially during turns.
AutoUI
Modeling Social Situation Awareness in Driving Interactions

Navit Klein, Hauke Sandhaus, David Goedicke, and 2 more authors

In Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Stanford, CA, USA, Sep 2024

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The design of self-driving vehicles requires an understanding of the social interactions between drivers in resolving vague encounters, such as at un-signalized intersections. In this paper, we make the case for social situation awareness as a model for understanding everyday driving interaction. Using a dual-participant VR driving simulator, we collected data from driving encounter scenarios to understand how (N=170) participant drivers behave with respect to one another. Using a social situation awareness questionnaire we developed, we assessed the participants’ social awareness of other driver’s direction of approach to the intersection, and also logged signaling, speed and speed change, and heading of the vehicle. Drawing upon the statistically significant relationships in the variables in the study data, we propose a Social Situation Awareness model based on the approach, speed, change of speed, heading and explicit signaling from drivers.
@inproceedings{10.1145/3640792.3675717, title = {Modeling Social Situation Awareness in Driving Interactions}, author = {Klein, Navit and Sandhaus, Hauke and Goedicke, David and Ju, Wendy and Parush, Avi}, year = {2024}, booktitle = {Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications}, location = {Stanford, CA, USA}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {AutomotiveUI '24}, pages = {1}, doi = {10.1145/3640792.3675717}, isbn = {9798400705106}, url = {https://doi.org/10.1145/3640792.3675717}, numpages = {1}, keywords = {Driving encounters, autonomous vehicles, social situational awareness (SA), unsignaled intersections, virtual reality (VR)}, thread = {automotive}, }
TLDR: Proposes a Social Situation Awareness model for better understanding driver negotiation at un-signalized intersections.
AutoUI
Changing Lanes Toward Open Science: Openness and Transparency in Automotive User Research

Patrick Ebel, Pavlo Bazilinskyy, Mark Colley, and 6 more authors

In Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Stanford, CA, USA, Sep 2024

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We review the state of open science and the perspectives on open data sharing within the automotive user research community. Openness and transparency are critical not only for judging the quality of empirical research, but also for accelerating scientific progress and promoting an inclusive scientific community. However, there is little documentation of these aspects within the automotive user research community. To address this, we report two studies that identify (1) community perspectives on motivators and barriers to data sharing, and (2) how openness and transparency have changed in papers published at AutomotiveUI over the past 5 years. We show that while open science is valued by the community and openness and transparency have improved, overall compliance is low. The most common barriers are legal constraints and confidentiality concerns. Although research published at AutomotiveUI relies more on quantitative methods than research published at CHI, openness and transparency are not as well established. Based on our findings, we provide suggestions for improving openness and transparency, arguing that the motivators for open science must outweigh the barriers. All supporting materials are freely available at: https://osf.io/zdpek/
@inproceedings{10.1145/3640792.3675730, title = {Changing Lanes Toward Open Science: Openness and Transparency in Automotive User Research}, author = {Ebel, Patrick and Bazilinskyy, Pavlo and Colley, Mark and Goodridge, Courtney Michael and Hock, Philipp and Janssen, Christian P. and Sandhaus, Hauke and Srinivasan, Aravinda Ramakrishnan and Wintersberger, Philipp}, year = {2024}, booktitle = {Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications}, location = {Stanford, CA, USA}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {AutomotiveUI '24}, pages = {94–105}, doi = {10.1145/3640792.3675730}, isbn = {9798400705106}, url = {https://doi.org/10.1145/3640792.3675730}, numpages = {12}, keywords = {AutomotiveUI, open data, open science, openness, reproducibility, transparency}, thread = {automotive}, }
TLDR: Analyzes how openness and transparency have evolved in automotive user research and suggests steps for improving data sharing.
AutoUI WiP
Regaining Trust: Impact of Transparent User Interface Design on Acceptance of Camera-Based In-Car Health Monitoring Systems

Hauke Sandhaus, Madiha Zahrah Choksi, and Wendy Ju

In Adjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Stanford, CA, USA, Sep 2024

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Introducing in-car health monitoring systems offers substantial potential to improve driver safety. However, camera-based sensing technologies introduce significant privacy concerns. This study investigates the impact of transparent user interface design on user acceptance of these systems. We conducted an online study with 42 participants using prototypes varying in transparency, choice, and deception levels. The prototypes included three onboarding designs: (1) a traditional Terms and Conditions text, (2) a Business Nudge design that subtly encouraged users to accept default data-sharing options, and (3) a Transparent Walk-Through that provided clear, step-by-step explanations of data use and privacy policies. Our findings indicate that transparent design significantly affects user experience measures, including perceived creepiness, trust in data use, and trustworthiness of content. Transparent onboarding processes enhanced user experience and trust without significantly increasing onboarding time. These findings offer practical guidance for designing user-friendly and privacy-respecting in-car health monitoring systems.
@inproceedings{sandhaus2024regainingtrustimpacttransparent, title = {Regaining Trust: Impact of Transparent User Interface Design on Acceptance of Camera-Based In-Car Health Monitoring Systems}, author = {Sandhaus, Hauke and Choksi, Madiha Zahrah and Ju, Wendy}, year = {2024}, booktitle = {Adjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications}, location = {Stanford, CA, USA}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {AutomotiveUI '24 Adjunct}, pages = {203–208}, doi = {10.1145/3641308.3685048}, isbn = {9798400705205}, url = {https://doi.org/10.1145/3641308.3685048}, numpages = {6}, keywords = {Creepiness, In-Car Health Monitoring, Online Study, Pervasive Sensing, Privacy, Technology Acceptance, Transparent Design, Trustworthiness, User Experience, Vehicle}, archiveprefix = {arXiv}, primaryclass = {cs.HC}, thread = {data-privacy}, }
TLDR: Transparently designed privacy onboarding can enhance user trust in camera-based in-car health monitoring systems.
CHI Workshop
Student Reflections on Self-Initiated GenAI Use in HCI Education

Hauke Sandhaus, Maria Teresa Parreira, and Wendy Ju

LLMs as Research Tools Workshop at CHI Conference, Honolulu, Hawaii, USA, May 2024

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This study explores students’ self-initiated use of Generative Artificial Intelligence (GenAI) tools in an interactive systems design class. Through 12 group interviews, students revealed the dual nature of GenAI in (1) stimulating creativity and (2) speeding up design iterations, alongside concerns over its potential to cause shallow learning and reliance. GenAI’s benefits were pronounced in the execution phase of design, aiding rapid prototyping and ideation, while its use in initial insight generation posed risks to depth and reflective practice. This reflection highlights the complex role of GenAI in Human-Computer Interaction education, emphasizing the need for balanced integration to leverage its advantages without compromising fundamental learning outcomes.
@article{sandhaus_student_2024, title = {Student Reflections on Self-Initiated GenAI Use in HCI Education}, author = {Sandhaus, Hauke and Parreira, Maria Teresa and Ju, Wendy}, year = {2024}, month = may, journal = {LLMs as Research Tools Workshop at CHI Conference}, location = {Honolulu, Hawaii, USA}, language = {en}, primaryclass = {cs.HC}, archiveprefix = {arXiv}, url = {https://arxiv.org/abs/2405.01467}, eprint = {2405.01467}, }
TLDR: Generative AI tools in HCI design can accelerate iterations, but also raise concerns among students about shallow learning.
CHI Workshop
Towards Quantifying Ethical User Experience: Evaluating User Perceptions of Dark Patterns in Social Media

Doris Maria Rhomberg^*, and Hauke Sandhaus^*

Mobilizing Research and Regulatory Action on Dark Patterns and Deceptive Design Practices Workshop at CHI Conference on Human Factors in Computing Systems , Honolulu, Hawaii, USA, May 2024

* = equal contribution

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No standardized questionnaire currently incorporates an ethical dimension for assessing User Experience (UX). We explored how the ethicality of interface design is reflected in current UX metrics and how they could be extended. To this end, we adapted the User Experience Questionnaire (UEQ) and enriched it with supplementary items specifically designed to capture user responses on social media to unethical interface designs, commonly referred to as ’dark patterns’. Through an exploratory analysis of a survey involving 120 participants who evaluated a selection of 15 social media dark patterns, we found preliminary evidence that (1) an aggregated UX score using items from the User Experience Questionnaire does not effectively indicate unethical user interface design. Instead, (2) subscale measures from the questionnaire show a relationship with unethical design. Furthermore, extending the User Experience Questionnaire seems promising, as (3) users can identify interfaces with addictive and pressuring properties, and (4) evaluations demonstrate consistency within groups of unethical design strategies.
@article{rhomberg_towards_2024, title = {Towards Quantifying Ethical User Experience: Evaluating User Perceptions of Dark Patterns in Social Media}, author = {Rhomberg, Doris Maria and Sandhaus, Hauke}, year = {2024}, month = may, journal = { Mobilizing Research and Regulatory Action on Dark Patterns and Deceptive Design Practices Workshop at CHI Conference on Human Factors in Computing Systems }, location = {Honolulu, Hawaii, USA}, language = {en}, note = {* = equal contribution}, }
TLDR: Only a modified User Experience Questionnaire can explicate unethical aspects of social media interfaces.
🏆 CHI
The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology

Emma Harvey, Hauke Sandhaus, Abigail Z Jacobs, and 2 more authors

Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, Jan 2024

Best Paper Honorable Mention at CHI ’24

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Motion capture systems, used across various domains, make body representations concrete through technical processes. We argue that the measurement of bodies and the validation of measurements for motion capture systems can be understood as social practices. By analyzing the findings of a systematic literature review (N=278) through the lens of social practice theory, we show how these practices, and their varying attention to errors, become ingrained in motion capture design and innovation over time. Moreover, we show how contemporary motion capture systems perpetuate assumptions about human bodies and their movements. We suggest that social practices of measurement and validation are ubiquitous in the development of data- and sensor-driven systems more broadly, and provide this work as a basis for investigating hidden design assumptions and their potential negative consequences in human-computer interaction.
@article{Harvey2024-gn, title = {The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology}, author = {Harvey, Emma and Sandhaus, Hauke and Jacobs, Abigail Z and Moss, Emanuel and Sloane, Mona}, year = {2024}, month = jan, journal = {Proceedings of the CHI Conference on Human Factors in Computing Systems}, archiveprefix = {arXiv}, primaryclass = {cs.CY}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, articleno = {768}, numpages = {23}, keywords = {anthropometry, measurement, motion capture, social practices, validation}, location = {Honolulu, HI, USA}, series = {CHI '24}, doi = {10.1145/3613904.3642004}, url = {https://doi.org/10.1145/3613904.3642004}, howpublished = {CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems}, thread = {data-privacy}, note = {Best Paper Honorable Mention at CHI '24}, }
TLDR: Motion capture systems are built and validated on old assumptions as a literature review using social practice theory shows.

2023

CSCW
VR Job Interview Using a Gender-Swapped Avatar

Jieun Kim^*, Hauke Sandhaus^*, and Susan R Fussell

In Computer Supported Cooperative Work and Social Computing, Oct 2023

* = equal contribution

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Virtual Reality (VR) has emerged as a potential solution for mitigating bias in a job interview by hiding the applicants’ demographic features. The current study examines the use of a gender-swapped avatar in a virtual job interview that affects the applicants’ perceptions and their performance evaluated by recruiters. With a mixed-method approach, we first conducted a lab experiment (N=8) exploring how using a gender-swapped avatar in a virtual job interview impacts perceived anxiety, confidence, competence, and ability to perform. Then, a semi-structured interview investigated the participants’ VR interview experiences using an avatar. Our findings suggest that using gender-swapped avatars may reduce the anxiety that job applicants will experience during the interview. Also, the affinity diagram produced seven key themes highlighting the advantages and limitations of VR as an interview platform. These findings contribute to the emerging field of VR-based recruitment and have practical implications for promoting diversity and inclusion in the hiring process.
@inproceedings{Kim2023-no, title = {VR Job Interview Using a Gender-Swapped Avatar}, author = {Kim, Jieun and Sandhaus, Hauke and Fussell, Susan R}, year = {2023}, month = oct, booktitle = {Computer Supported Cooperative Work and Social Computing}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/3584931.3606976}, url = {https://doi.org/10.1145/3584931.3606976}, language = {en}, eprint = {2307.04247}, archiveprefix = {arXiv}, primaryclass = {cs.HC}, howpublished = {CSCW '23 Companion}, note = {* = equal contribution}, }
TLDR: Gender-swapped avatars in virtual job interviews influences applicant’s perception of performance.
CHI Workshop
Promoting Bright Patterns

Hauke Sandhaus

CHI ’23 Workshop: Designing Technology and Policy Simultaneously, Hamburg, Germany, Apr 2023

This paper started the brightpatterns.org website

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User experience designers are facing increasing scrutiny and criticism for creating harmful technologies, leading to a pushback against unethical design practices. While clear-cut harmful practices such as dark patterns have received attention, trends towards automation, personalization, and recommendation present more ambiguous ethical challenges. To address potential harm in these "gray" instances, we propose the concept of "bright patterns" - persuasive design solutions that prioritize user goals and well-being over their desires and business objectives. The ambition of this paper is threefold: to define the term "bright patterns", to provide examples of such patterns, and to advocate for the adoption of bright patterns through policymaking.
@article{sandhaus2023promoting, title = {Promoting Bright Patterns}, author = {Sandhaus, Hauke}, year = {2023}, journal = {CHI '23 Workshop: Designing Technology and Policy Simultaneously}, eprint = {2304.01157}, archiveprefix = {arXiv}, primaryclass = {cs.HC}, thread = {ethical-design}, note = {This paper started the <a href="https://brightpatterns.org/" target="_blank">brightpatterns.org</a> website}, location = {Hamburg, Germany}, month = apr, day = {23} }
TLDR: The first definition of "bright patterns" is accompanied by examples that illustrate corporate use of persuasive design in support of user goals over their desires and business objectives.
CHI Workshop
Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously

Hauke Sandhaus, Wendy Ju, and Qian Yang

CHI ’23 Workshop: Designing Technology and Policy Simultaneously, Hamburg, Germany, Apr 2023

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Autonomous Vehicles (AVs) can potentially improve urban living by reducing accidents, increasing transportation accessibility and equity, and decreasing emissions. Realizing these promises requires the innovations of AV driving behaviors, city plans and infrastructure, and traffic and transportation policies to join forces. However, the complex interdependencies among AV, city, and policy design issues can hinder their innovation. We argue the path towards better AV cities is not a process of matching city designs and policies with AVs’ technological innovations, but a process of iterative prototyping of all three simultaneously: Innovations can happen step-wise as the knot of AV, city, and policy design loosens and tightens, unwinds and reties. In this paper, we ask: How can innovators innovate AVs, city environments, and policies simultaneously and productively toward better AV cities? The paper has two parts. First, we map out the interconnections among the many AV, city, and policy design decisions, based on a literature review spanning HCI/HRI, transportation science, urban studies, law and policy, operations research, economy, and philosophy. This map can help innovators identify design constraints and opportunities across the traditional AV/city/policy design disciplinary bounds. Second, we review the respective methods for AV, city, and policy design, and identify key barriers in combining them: (1) Organizational barriers to AV-city-policy design collaboration, (2) computational barriers to multi-granularity AV-city-policy simulation, and (3) different assumptions and goals in joint AV-city-policy optimization. We discuss two broad approaches that can potentially address these challenges, namely, "low-fidelity integrative City-AV-Policy Simulation (iCAPS)" and "participatory design optimization".
@article{sandhaus2023prototyping, title = {Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously}, author = {Sandhaus, Hauke and Ju, Wendy and Yang, Qian}, year = {2023}, journal = {CHI '23 Workshop: Designing Technology and Policy Simultaneously}, eprint = {2304.06639}, archiveprefix = {arXiv}, primaryclass = {cs.HC}, location = {Hamburg, Germany}, month = apr, day = {23} }
TLDR: Maps out the interdependencies between AV, city, and policy design and discusses methods for iteratively prototyping all three simultaneously.

2018

UIST
A WOZ Study of Feedforward Information on an Ambient Display in Autonomous Cars

Hauke Sandhaus, and Eva Hornecker

In The 31st Annual ACM Symposium on User Interface Software and Technology Adjunct Proceedings, Berlin, Germany, Oct 2018

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We describe the development and user testing of an ambient display for autonomous vehicles. Instead of providing feedback about driving actions, once executed, it communicates driving decisions in advance, via light signals in passengers’ peripheral vision. This ambient display was tested in a WoZ-based on-the-road-driving simulation of a fully autonomous vehicle. Findings from a preliminary study with 14 participants suggest that such a display might be particularly useful to communicate upcoming inertia changes for passengers.
@inproceedings{Sandhaus2018-el, title = {A WOZ Study of Feedforward Information on an Ambient Display in Autonomous Cars}, author = {Sandhaus, Hauke and Hornecker, Eva}, year = {2018}, month = oct, booktitle = {The 31st Annual {ACM} Symposium on User Interface Software and Technology Adjunct Proceedings}, location = {Berlin, Germany}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, series = {UIST '18 Adjunct}, pages = {90--92}, doi = {10.1145/3266037.3266111}, isbn = {9781450359498}, url = {https://doi.org/10.1145/3266037.3266111}, keywords = {on-road simulation, autonomous vehicle interfaces, methodology, ambient display}, }
TLDR: Ambient displays in autonomous vehicles can subtly communicate driving decisions to passengers (Master Thesis).
D TEX
Smart Textiles in the Performing Arts

Aline Martinez, Michaela Honauer, Hauke Sandhaus, and 1 more author

Textiles, Identity and Innovation: Design the Future, Oct 2018

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We present the Sonification Costume, an interactive costume created for modern dance performances, that makes movements perceivable through sound. We created it in the context of studying textile-based sensors, and here describe the exploration of different production techniques, which led to a knitted whole-body suit with seamlessly integrated stretch sensors. Self-reflection and a user study reveal that the costume concept is interesting to dancers and how we can further improve textile-integrated sensors.
@article{Martinez2018-xc, title = {Smart Textiles in the Performing Arts}, author = {Martinez, Aline and Honauer, Michaela and Sandhaus, Hauke and Hornecker, Eva}, year = {2018}, journal = {Textiles, Identity and Innovation: Design the Future}, publisher = {Taylor & Francis}, url = {https://www.taylorfrancis.com/chapters/edit/10.1201/9781315100210-57/smart-textiles-performing-arts-aline-martinez-michaela-honauer-hauke-sandhaus-eva-hornecker}, }
TLDR: Our dance costume using smart textiles makes movements perceivable through sound.

2015

UT
Development of a 3D Navigable Interface for a Touchless Showcase

Hauke Sandhaus

University of Twente, Oct 2015

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Due to widespread usage of touchscreens, users have accepted interaction without haptic feedback. Commercial game consoles have introduced users to touchless input and natural user interfaces. Only recently it has become technically possible to track human hand skeleton in high detail, precision, and low latency contactless. This report describes the design process for the user experience, user interface, and interaction interface of a touchless showcase using skeletal hand tracking. The project extends on existing hardware, compares current approaches, researches on the user group, and rebuilds the software, based on these findings, from scratch. To allow input, multiple interactions and 3D buttons were developed. In a user experiment, these were tested. A final prototype was implemented on two showcases for a month and compared to the existing software. The findings suggest that users want more natural and direct interactions. Missing physical feedback, non-existent depth perception on traditional screens, and unfamiliar gesture language are hindrances but can be overcome with the use of good visual cues. Future work on the software is solely on refinement. Some of the interactions investigated in this thesis will prevail, while some might appear in other contexts.
@mastersthesis{Sandhaus2015-in, title = {Development of a {3D} Navigable Interface for a Touchless Showcase}, author = {Sandhaus, Hauke}, year = {2015}, school = {University of Twente}, }
TLDR: An intuitive 3D navigable interface for a touchless showcase using skeletal hand tracking (Bachelor Thesis).