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Publications (10 of 14) Show all publications
Angenius, M. & Ghajargar, M. (2023). Design Principles for Interactive and Reflective Journaling with AI. In: Kohei Arai (Ed.), Intelligent Computing: Proceedings of the 2023 Computing Conference, Volume 2. Paper presented at SAI 2023 Computing Conference, 13-14 July London, United Kingdom (pp. 62-81).
Open this publication in new window or tab >>Design Principles for Interactive and Reflective Journaling with AI
2023 (English)In: Intelligent Computing: Proceedings of the 2023 Computing Conference, Volume 2 / [ed] Kohei Arai, 2023, p. 62-81Conference paper, Published paper (Refereed)
Abstract [en]

Designing for reflection and journaling have been prominent research areas in HCI and Interaction Design. However, designing for the experience of journaling that is supported by conversations with AI–Conversational Agent (CA)–to foster reflection seems to be a relatively unexplored area. Furthermore, while there are an abundant number of general guidelines and design principles for designing human-AI interactions, a set of guidelines for designing an interactive and reflective journaling experience with AI is lacking. This paper is a first attempt to address that need. We present the result of a qualitative user study on interactive and reflective journaling. We were interested in attending to our participants’ experiences and finding out their needs regarding the interactive journaling experience with CA. The user needs then were translated to design requirements and thereafter to themes or design principles. Some of our findings suggest that one of the important factors in journaling is the personal aesthetics of writing, by using carefully selected personal tools, specific materiality and interactions. Further, the flow of writing is considered sacred, hence it is almost like an untouchable, reflective ritualistic flow. Reflecting on the findings, we believe the outcome of this study can create opportunities for designing for human-AI interactions that are generative and reflective for activities that require such qualities, such as journaling or creativity.

Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 739
Keywords
Journaling, Reflection, Interaction Design, Human-AI Interaction, Conversational Design
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:mau:diva-64252 (URN)10.1007/978-3-031-37963-5_6 (DOI)2-s2.0-85172268760 (Scopus ID)978-3-031-37962-8 (ISBN)978-3-031-37963-5 (ISBN)
Conference
SAI 2023 Computing Conference, 13-14 July London, United Kingdom
Available from: 2023-12-11 Created: 2023-12-11 Last updated: 2023-12-11Bibliographically approved
Angenius, M. & Ghajargar, M. (2023). Interactive Journaling with AI: Probing into Words and Language as Interaction Design Materials. In: Chatbot Research and Design: 6th International Workshop, CONVERSATIONS 2022, Amsterdam, The Netherlands, November 22–23, 2022, Revised Selected Papers. Paper presented at 6th International Workshop, CONVERSATIONS 2022, Amsterdam, The Netherlands, November 22–23, 2022 (pp. 150-170). Springer
Open this publication in new window or tab >>Interactive Journaling with AI: Probing into Words and Language as Interaction Design Materials
2023 (English)In: Chatbot Research and Design: 6th International Workshop, CONVERSATIONS 2022, Amsterdam, The Netherlands, November 22–23, 2022, Revised Selected Papers, Springer, 2023, p. 150-170Conference paper, Published paper (Refereed)
Abstract [en]

Conversational Agents (CAs) are making human-computer interaction more collaborative and conversational through using natural language. The HCI and interaction design communities, have been experimenting with and exploring the area of designing conversational interactions. Furthermore, interaction designers may need to acquire new skills for designing, prototyping, and evaluating artifacts that embody AI technologies in general, and CAs in particular. This paper builds upon a previous study on principles of designing interactive journaling experiences with CA and explores the practice of designing such experiences, using words, language, and conversations as design materials. We present a prototype for interactive and reflective journaling interaction with CA and the result of a Wizard of Oz experiment. Our findings suggest that designing interactions with CA challenges designers to use materials with inherently different natures and qualities. Despite this challenge, words appear to have unique characteristics to support designers to externalize and iterate on ideas, e.g., tone and intent. Hence, we suggest considering words, language, and conversations as the primary design materials, and the AI’s predictability, adaptivity, and agency as secondary materials, while designing human interactions with Conversational Agents.

Place, publisher, year, edition, pages
Springer, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13815
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:mau:diva-64306 (URN)10.1007/978-3-031-25581-6_10 (DOI)2-s2.0-85148688905 (Scopus ID)978-3-031-25580-9 (ISBN)978-3-031-25581-6 (ISBN)
Conference
6th International Workshop, CONVERSATIONS 2022, Amsterdam, The Netherlands, November 22–23, 2022
Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2023-12-12Bibliographically approved
Ghajargar, M., Bardzell, J. & Lagerkvist, L. (2022). A Redhead Walks into a Bar: Experiences of Writing Fiction with Artificial Intelligence. In: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference: . Paper presented at Academic Mindtrek 2022: 25th International Academic Mindtrek conference, Tampere Finland, November 16 - 18, 2022 (pp. 230-241). ACM Digital Library
Open this publication in new window or tab >>A Redhead Walks into a Bar: Experiences of Writing Fiction with Artificial Intelligence
2022 (English)In: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference, ACM Digital Library, 2022, p. 230-241Conference paper, Published paper (Refereed)
Abstract [en]

Human creativity has been often aided and supported by artificial tools, spanning traditional tools such as ideation cards, pens, and paper, to computed and software. Tools for creativity are increasingly using artificial intelligence to not only support the creative process, but also to act upon the creation with a higher level of agency. This paper focuses on writing fiction as a creative activity and explores human-AI co-writing through a research product, which employs a natural language processing model, the Generative Pre-trained Transformer 3 (GPT-3), to assist the co-authoring of narrative fiction. We report on two progressive – not comparative – autoethnographic studies to attain our own creative practices in light of our engagement with the research product: (1) a co-writing activity initiated by basic textual prompts using basic elements of narrative and (2) a co-writing activity initiated by more advanced textual prompts using elements of narrative, including dialects and metaphors undertaken by one of the authors of this paper who has doctoral training in literature. In both studies, we quickly came up against the limitations of the system; then, we repositioned our goals and practices to maximize our chances of success. As a result, we discovered not only limitations but also hidden capabilities, which not only altered our creative practices and outcomes, but which began to change the ways we were relating to the AI as collaborator.  

 

Place, publisher, year, edition, pages
ACM Digital Library, 2022
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-56499 (URN)10.1145/3569219.3569418 (DOI)2-s2.0-85142667157 (Scopus ID)978-1-4503-9955-5 (ISBN)
Conference
Academic Mindtrek 2022: 25th International Academic Mindtrek conference, Tampere Finland, November 16 - 18, 2022
Available from: 2022-12-07 Created: 2022-12-07 Last updated: 2024-02-05Bibliographically approved
Ghajargar, M., Bardzell, J., Alison, S.-R., Höök, K. & Gall Krogh, P. (2022). Graspable AI: Physical Forms as Explanation Modality for Explainable AI. In: TEI '22: Proceedings of the Sixteenth International Conference on Tangible, Embedded, and Embodied Interaction. Paper presented at TEI '22: Sixteenth International Conference on Tangible, Embedded,and Embodied Interaction Daejeon Republic of Korea, February 13 - 16, 2022 (pp. 1-4). New York, USA: Association for Computing Machinery (ACM), 53
Open this publication in new window or tab >>Graspable AI: Physical Forms as Explanation Modality for Explainable AI
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2022 (English)In: TEI '22: Proceedings of the Sixteenth International Conference on Tangible, Embedded, and Embodied Interaction, New York, USA: Association for Computing Machinery (ACM), 2022, Vol. 53, p. 1-4Conference paper, Published paper (Refereed)
Abstract [en]

Explainable AI (XAI) seeks to disclose how an AI system arrives at its outcomes. But the nature of the disclosure depends in part on who needs to understand the AI and the available explanation modalities (e.g., verbal and visual). Users’ preferences regarding explanation modalities might differ, as some might prefer spoken explanations compared to visual ones. However, we argue for broadening the explanation modalities, to consider also tangible and physical forms. In traditional product design, physical forms have mediated people’s interactions with objects; more recently interacting with physical forms has become prominent with IoT and smart devices, such as smart lighting and robotic vacuum cleaners. But how tangible interaction can support AI explanations is not yet well understood.

In this second studio proposal on Graspable AI (GAI) we seek to explore design qualities of physical forms as an explanation modality for XAI. We anticipate that the design qualities of physical forms and their tangible interactivity can not only contribute to the explainability of AI through facilitating dialogue, relationships and human empowerment, but they can also contribute to critical and reflective discourses on AI. Therefore, this proposal contributes to design agendas that expand explainable AI into tangible modalities, supporting a more diverse range of users in their understanding of how a given AI works and the meanings of its outcomes.

Place, publisher, year, edition, pages
New York, USA: Association for Computing Machinery (ACM), 2022
Keywords
Tangible Interaction, Explainable AI, Human-Centered AI
National Category
Computer Sciences Human Aspects of ICT Design
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-50373 (URN)10.1145/3490149.3503666 (DOI)000940778800053 ()2-s2.0-85124973762 (Scopus ID)978-1-4503-9147-4 (ISBN)
Conference
TEI '22: Sixteenth International Conference on Tangible, Embedded,and Embodied Interaction Daejeon Republic of Korea, February 13 - 16, 2022
Available from: 2022-02-28 Created: 2022-02-28 Last updated: 2023-12-13Bibliographically approved
Ghajargar, M. & Bardzell, J. (2022). Learning About Plant Intelligence from a Flying Plum Tree: Music Recommenders and Posthuman User Experiences. In: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference: . Paper presented at Academic Mindtrek 2022: 25th International Academic Mindtrek conference, Tampere Finland, November 16 - 18, 2022 (pp. 343-346). ACM Digital Library
Open this publication in new window or tab >>Learning About Plant Intelligence from a Flying Plum Tree: Music Recommenders and Posthuman User Experiences
2022 (English)In: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference, ACM Digital Library, 2022, p. 343-346Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Recommender Systems (RS) are used in many different applications such as ecommerce and for media streaming, including music. Recommenders not only help users discover new music, but they also help to create assemblages of songs into playlists. Intentionally or otherwise, playlists often manifest themes, that is, universal ideas that are expressed in particular songs, lyrics, or passages. In this paper we were interested to explore the capabilities of AI to introduce themes through generated playlists, them-selves seeded by the theme of plants. Taking a self-reflexive and user experience approach, we collaborated with AI to create four Plant Music playlists to subject ourselves to what came to refer to as a posthuman user experience.  

 

Place, publisher, year, edition, pages
ACM Digital Library, 2022
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-56500 (URN)10.1145/3569219.3569388 (DOI)2-s2.0-85142633909 (Scopus ID)978-1-4503-9955-5 (ISBN)
Conference
Academic Mindtrek 2022: 25th International Academic Mindtrek conference, Tampere Finland, November 16 - 18, 2022
Available from: 2022-12-07 Created: 2022-12-07 Last updated: 2024-02-05Bibliographically approved
Ghajargar, M. & Bardzell, J. (2022). Making AI Understandable by Making it Tangible: Exploring the Design Space with Ten Concept Cards. In: Sweetser, Penny ; Lawrence Taylor, Jennyfer (Ed.), OzCHI '22: Proceedings of the 34th Australian Conference on Human-Computer Interaction. Paper presented at The 34th Australian Conference on Human-Computer Interaction (OzCHI'22) Canberra, Australia 29 November -2 December. 2022 (pp. 74-80). New York: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Making AI Understandable by Making it Tangible: Exploring the Design Space with Ten Concept Cards
2022 (English)In: OzCHI '22: Proceedings of the 34th Australian Conference on Human-Computer Interaction / [ed] Sweetser, Penny ; Lawrence Taylor, Jennyfer, New York: Association for Computing Machinery (ACM), 2022, p. 74-80Conference paper, Published paper (Refereed)
Abstract [en]

The embodiment of Artificial Intelligence (AI) in everyday use products is raising challenges and opportunities for HCI and design research, such as human understandings of AI’s functions and states, passing back and forth of control, AI ethics, and user experi-ence, among others. There has been progress in those areas, such as works on explainable AI (XAI); fairness, accountability, and transparency (FAccT); human-centered AI; and the development of guidelines for Human-AI interaction design. Similarly, the in-terest in studying interaction modalities and their contributions to understandable and transparent AI has been also growing. How-ever, the tangible and embodied modality of interaction and more broadly studies of the forms of such everyday use products are relatively underexplored. This paper builds upon a larger project on designing graspable AI and it introduces a series of concept cards that aim to aid design researchers’ creative exploration of tangible and understandable AI. We conducted a user study in two parts of online sessions and semi-structured interviews and found out that to envision physicality and tangible interaction with AI felt challenging and “too abstract”. Even so, the act of creative exploration of that space not only supported our participants to gain new design perspectives of AI, but also supported them to go beyond anthropomorphic forms of AI.

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2022
Keywords
Human-AI Interaction, Creativity Support Tools, Explainable AI, Product Design.
National Category
Design Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-56340 (URN)10.1145/3572921.3572942 (DOI)2-s2.0-85153363252 (Scopus ID)979-8-4007-0024-8 (ISBN)
Conference
The 34th Australian Conference on Human-Computer Interaction (OzCHI'22) Canberra, Australia 29 November -2 December. 2022
Available from: 2022-12-01 Created: 2022-12-01 Last updated: 2024-02-05Bibliographically approved
Ghajargar, M., Bardzell, J., Smith-Renner, A., Höök, K., Gall Krogh, P. & Wiberg, M. (2022). Tangible XAI. New York, USA: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Tangible XAI
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2022 (English)Other (Other (popular science, discussion, etc.))
Abstract [en]

Computational systems are becoming increasingly smart and automated. Artificial intelligence (AI) systems perceive things in the world, produce content, make decisions for and about us, and serve as emotional companions. From music recommendations to higher-stakes scenarios such as policy decisions, drone-based warfare, and automated driving directions, automated systems affect us all.

But researchers and other experts are asking, How well do we understand this alien intelligence? If even AI developers don’t fully understand how their own neural networks make decisions, what chance does the public have to understand AI outcomes? For example, AI systems decide whether a person should get a loan; so what should—what can—that person understand about how the decision was made? And if we can’t understand it, how can any of us trust AI?

The emerging area of explainable AI (XAI) addresses these issues by helping to disclose how an AI system arrives at its outcomes. But the nature of the disclosure depends in part on the audience, or who needs to understand the AI. A car, for example, can send warnings to consumers (“Tire Pressure Low”) and also send highly technical diagnostic codes that only trained mechanics can understand. Explanation modality is also important to consider. Some people might prefer spoken explanations compared to visual ones. Physical forms afford natural interaction with some smart systems, like vehicles and vacuums, but whether tangible interaction can support AI explanation has not yet been explored.

In the summer of 2020, a group of multidisciplinary researchers collaborated on a studio proposal for the 2021 ACM Tangible Embodied and Embedded (TEI) conference. The basic idea was to link conversations about tangible and embodied interaction and product semantics to XAI. Here, we first describe the background and motivation for the workshop and then report on its outcomes and offer some discussion points.

Place, publisher, year, pages
New York, USA: Association for Computing Machinery (ACM), 2022
Keywords
Explainable AI, Tangible Embodied Interaction, Human-Centred AI
National Category
Design Human Aspects of ICT Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-50374 (URN)
Note

TANGIBLE XAI Blogs Posted: Tue, February 15, 2022 

Available from: 2022-02-28 Created: 2022-02-28 Last updated: 2022-12-13Bibliographically approved
Ghajargar, M., Bardzell, J., Smith Renner, A., Gall Krogh, P., Höök, K., Cuartielles, D., . . . Mikael, W. (2021). From "Explainable AI" to "Graspable AI". In: Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’21): . Paper presented at ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI'21). New York: Association for Computing Machinery (ACM), Article ID 69.
Open this publication in new window or tab >>From "Explainable AI" to "Graspable AI"
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2021 (English)In: Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’21), New York: Association for Computing Machinery (ACM), 2021, article id 69Conference paper, Published paper (Refereed)
Abstract [en]

Since the advent of Artificial Intelligence (AI) and Machine Learning (ML), researchers have asked how intelligent computing systems could interact with and relate to their users and their surroundings, leading to debates around issues of biased AI systems, ML black-box, user trust, user’s perception of control over the system, and sys- tem’s transparency, to name a few. All of these issues are related to how humans interact with AI or ML systems, through an interface which uses different interaction modalities. Prior studies address these issues from a variety of perspectives, spanning from under- standing and framing the problems through ethics and Science and Technology Studies (STS) perspectives to finding effective technical solutions to the problems. But what is shared among almost all those efforts is an assumption that if systems can explain the how and why of their predictions, people will have a better perception of control and therefore will trust such systems more, and even can correct their shortcomings. This research field has been called Explainable AI (XAI). In this studio, we take stock on prior efforts in this area; however, we focus on using Tangible and Embodied Interaction (TEI) as an interaction modality for understanding ML. We note that the affordances of physical forms and their behaviors potentially can not only contribute to the explainability of ML sys- tems, but also can contribute to an open environment for criticism. This studio seeks to both critique explainable ML terminology and to map the opportunities that TEI can offer to the HCI for designing more sustainable, graspable and just intelligent systems.

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2021
Keywords
Explainable AI, XAI, Machine Learning, Artificial Intelligence, Tan- gible Embodied Interaction, TEI, Interaction Design
National Category
Design Computer Systems
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-38983 (URN)10.1145/3430524.3442704 (DOI)2-s2.0-85102059863 (Scopus ID)978-1-4503-8213-7 (ISBN)
Conference
ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI'21)
Funder
Knowledge Foundation
Available from: 2021-01-05 Created: 2021-01-05 Last updated: 2024-04-04Bibliographically approved
Ghajargar, M. & Bardzell, J. (2021). Synthesis of Forms: Integrating Practical and Reflective Qualities in Design. In: CHI '21: CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, May 2021: . Paper presented at CHI '21: CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, May 2021. New York, NY, USA: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Synthesis of Forms: Integrating Practical and Reflective Qualities in Design
2021 (English)In: CHI '21: CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, May 2021, New York, NY, USA: Association for Computing Machinery (ACM), 2021Conference paper, Published paper (Refereed)
Abstract [en]

Synthesis, or the integration of hitherto separated elements, is a prominent concept in theories of design processes. Synthesis often happens when there is a need to make a decision, though it is often the result of a combination of different alternatives, instead of deciding in favor of one and eliminating another. In many design studies, synthesis has been investigated in the contexts of everyday design—bicycle frames, sewing machines, commercial architecture. We were interested in how it might apply in contexts of reflective design, whose pragmatics often depend on different interrelationships between users and technological products. In this paper, we argue that designing everyday use objects for reflection requires a synthesis of two apparently opposite forms: conventionally practical forms, since they are everyday use objects, and evocative forms, since they make users think. We provide two examples of everyday objects for reflection that we believe synthesize both conventionally practical and evocative forms, analyzing the design processes that led to these forms, and discussing how these reflective designs embody different forms of synthesis.

Place, publisher, year, edition, pages
New York, NY, USA: Association for Computing Machinery (ACM), 2021
Keywords
Formgiving, Design process, Research through Design, Design Theory
National Category
Design Interaction Technologies
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-41307 (URN)10.1145/3411764.3445232 (DOI)000758168002059 ()2-s2.0-85106679389 (Scopus ID)978-1-4503-8096-6 (ISBN)
Conference
CHI '21: CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, May 2021
Available from: 2021-03-16 Created: 2021-03-16 Last updated: 2024-02-05Bibliographically approved
Schröder, A. M. & Ghajargar, M. (2021). Unboxing the Algorithm: Designing an Understandable Algorithmic Experience in Music Recommender Systems. In: Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021. co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021).: . Paper presented at 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, The Netherlands, September 25, 2021..
Open this publication in new window or tab >>Unboxing the Algorithm: Designing an Understandable Algorithmic Experience in Music Recommender Systems
2021 (English)In: Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021. co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021)., 2021Conference paper, Published paper (Refereed)
Abstract [en]

After decades of the existence of algorithms in everyday use technologies, users have developed an algorithmic awareness, but they still lack the confidence to grasp them. This study explores how understandability as a principle drawn from sociology, design, and computing can enhance the algorithmic experience in music recommendation systems. The preliminary results of this Research-Through-Design showed that users had limited mental models so far but had a curiosity to learn. Further, it confirmed that explanations as a dialogue could improve the algorithmic experience in music recommendation systems. Users could comprehend recommendations the best when they were easy to access and understand, directly related to user behavior, and when they allowed the user to correct the algorithm. To conclude, our study reconfirms that designing experiences that help users to understand the algorithmic workings will make authentic recommendations from intelligent systems more applicable in the long run.

Keywords
Human-centered computing, Interaction design, Empirical studies in interaction design, algorithmic experience, music recommendation systems, transparency, machine learning, explainable AI
National Category
Computer Systems Design Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-46098 (URN)
Conference
15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, The Netherlands, September 25, 2021.
Available from: 2021-09-25 Created: 2021-09-25 Last updated: 2023-03-13Bibliographically approved
Projects
Dynamic Intelligent Sensor Intensive Systems; Malmö University; Publications
Persson, J. A., Bugeja, J., Davidsson, P., Holmberg, J., Kebande, V. R., Mihailescu, R.-C., . . . Tegen, A. (2023). The Concept of Interactive Dynamic Intelligent Virtual Sensors (IDIVS): Bridging the Gap between Sensors, Services, and Users through Machine Learning. Applied Sciences, 13(11), Article ID 6516.
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1852-3937