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  • 1.
    Ghajargar, Maliheh
    et al.
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).
    Bardzell, Jaffrey
    Pennsylvania State University.
    Making AI Understandable by Making it Tangible: Exploring the Design Space with Ten Concept Cards2022Ingår i: 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, s. 74-80Konferensbidrag (Refereegranskat)
    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.

    Ladda ner fulltext (pdf)
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  • 2.
    Ghajargar, Maliheh
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    Bardzell, Jeffrey
    Pennsylvania State University, United States.
    Learning About Plant Intelligence from a Flying Plum Tree: Music Recommenders and Posthuman User Experiences2022Ingår i: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference, ACM Digital Library, 2022, s. 343-346Konferensbidrag (Övrigt vetenskapligt)
    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.  

     

  • 3.
    Ghajargar, Maliheh
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    Bardzell, Jeffrey
    Pennsylvania State University, USA.
    Alison, Smith-Renner
    Dataminr, USA.
    Höök, Kristina
    KTH Royal Institute of Technology.
    Gall Krogh, Peter
    Aarhus University, Denmark.
    Graspable AI: Physical Forms as Explanation Modality for Explainable AI2022Ingår i: 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, s. 1-4Konferensbidrag (Refereegranskat)
    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.

    Ladda ner fulltext (pdf)
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  • 4.
    Ghajargar, Maliheh
    et al.
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).
    Bardzell, Jeffrey
    IST, Pennsylvania State University, United States.
    Lagerkvist, Love
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    A Redhead Walks into a Bar: Experiences of Writing Fiction with Artificial Intelligence2022Ingår i: Academic Mindtrek '22: Proceedings of the 25th International Academic Mindtrek Conference, ACM Digital Library, 2022, s. 230-241Konferensbidrag (Refereegranskat)
    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.  

     

    Ladda ner fulltext (pdf)
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  • 5.
    Ghajargar, Maliheh
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    Bardzell, Jeffrey
    Indiana University Bloomingtonm,USA.
    Smith-Renner, Alison
    Dataminr, USA.
    Höök, Kristina
    Royal Institute of Technology (KTH).
    Gall Krogh, Peter
    Aarhus University, Denmark.
    Wiberg, Mikael
    Umeå University.
    Tangible XAI2022Övrigt (Övrig (populärvetenskap, debatt, mm))
    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.

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