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International Postdoctoral Fellowship (GFF-IPF)
Type
fundamental research project
Start Date
01 October 2020
End Date
30 September 2023
Acronym
GFF-IPF
Status
ongoing
Keywords
Smart Personal Assistants
Affordances
Configurational Analysis
Description
Based on recent technological advancements in the field of Artificial Intelligence (AI), it is predicted that Smart Personal Assistants (SPAs) such as Amazon`s Alexa, Google`s Google Assistant, and Apple`s Siri will run on 870 million devices by 2022. This significantly increases the exposure of many to this technology in both B2B and B2C settings, especially when taking the ubiquitous chatbots into account. These Information Systems (IS) provide assistance by engaging with users especially via natural language and have been promised to fundamentally change the ways how we perform tasks, consume services and products, and interact with our environment. However, SPAs face problems in terms of user acceptance and affordance actualization. SPAs represent a novel class of IS that are characterized by high degrees of interaction and intelligence. These capabilities may fundamentally affect how people interact with SPAs as for instance users perceive them as increasingly human and, at the same time, less predictable. Thus, we need to generate insights on how to actualize the affordances offered by SPAs and realize their potential to avoid disuse that would lead to unrealized potential due to the rejection of SPAs. In specific, there is a lack of knowledge concerning the affordances that SPAs provide and how they may contribute to the actual outcomes of SPAs.
Based on these gaps in research, the aim of this project is to reveal which affordances contribute to SPA outcomes and how we leverage affordance actualization. In particular, a configurational, as well as a dynamic approach, is needed for understanding better, how this novel class of AI-based systems is appropriated as a technology-in-use. Therefore, I am providing a conceptual approach for studying SPA affordances, empirical insights on how SPA affordances actualization contributes to SPA outcomes and how companies can manage successful affordance actualization.
To achieve these goals, the proposed Basic Research Fund project first aims to shed light on which affordances are actually offered by this novel class of AI-based systems. For the affordance identification, I intend to review an interdisciplinary body of knowledge to provide a better theoretical understanding concerning the affordances offered and how they relate to the material properties of SPAs. In addition, a series of focus groups are conducted to complement this theoretical perspective with a practical view. On this basis, the project aims to provide a configurational and dynamic account for SPA affordances and their relationship to SPA outcomes. For this purpose, a series of empirical studies are conducted. First, a condition-oriented study aiming to provide empirical insights on relevant SPA affordance configurations to achieve SPA outcomes such as satisfaction and effective use. Second, a case-oriented diary study is conducted to provide insights about the dynamics of SPA affordance configurations and their patterns over time. These empirical insights finally enable to organize affordance actualization of SPAs and to contribute to a successful SPA implementation. Taken together, this project contributes to the body of knowledge by developing a conceptual approach for studying SPA affordances and generating insights on SPA affordance configurations and dynamics of affordances over time. Moreover, the project contributes to theory and practice by providing design principles for SPAs that will be used.
Based on these gaps in research, the aim of this project is to reveal which affordances contribute to SPA outcomes and how we leverage affordance actualization. In particular, a configurational, as well as a dynamic approach, is needed for understanding better, how this novel class of AI-based systems is appropriated as a technology-in-use. Therefore, I am providing a conceptual approach for studying SPA affordances, empirical insights on how SPA affordances actualization contributes to SPA outcomes and how companies can manage successful affordance actualization.
To achieve these goals, the proposed Basic Research Fund project first aims to shed light on which affordances are actually offered by this novel class of AI-based systems. For the affordance identification, I intend to review an interdisciplinary body of knowledge to provide a better theoretical understanding concerning the affordances offered and how they relate to the material properties of SPAs. In addition, a series of focus groups are conducted to complement this theoretical perspective with a practical view. On this basis, the project aims to provide a configurational and dynamic account for SPA affordances and their relationship to SPA outcomes. For this purpose, a series of empirical studies are conducted. First, a condition-oriented study aiming to provide empirical insights on relevant SPA affordance configurations to achieve SPA outcomes such as satisfaction and effective use. Second, a case-oriented diary study is conducted to provide insights about the dynamics of SPA affordance configurations and their patterns over time. These empirical insights finally enable to organize affordance actualization of SPAs and to contribute to a successful SPA implementation. Taken together, this project contributes to the body of knowledge by developing a conceptual approach for studying SPA affordances and generating insights on SPA affordance configurations and dynamics of affordances over time. Moreover, the project contributes to theory and practice by providing design principles for SPAs that will be used.
Leader contributor(s)
Funder(s)
Topic(s)
Actualizing the Potential of Smart Personal Assistants – Investigating Affordance Configurations and their Dynamics for AI-based Systems
Method(s)
Survey
Qualitative Comparative Analysis
Diary Study
Focus Groups
Division(s)
Eprints ID
247948
24 results
Now showing
1 - 10 of 24
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PublicationTowards a Trust Reliance Paradox? Exploring the Gap Between Perceived Trust in and Reliance on Algorithmic Advice( 2021)Beyond AI-based systems’ potential to augment decision-making, reduce organizational resources, and counter human biases, unintended consequences of such systems have been largely neglected so far. Researchers are undecided on whether erroneous advice acts as an impediment to system use or is blindly relied upon. As part of an experimental study, we turn towards the impact of incorrect system advice and how to design for failure-prone AI. In an experiment with 156 subjects we find that, although incorrect algorithmic advice is trusted less, users adapt their answers to a system’s incorrect recommendations. While transparency on a system’s accuracy levels fosters trust and reliance in the context of incorrect advice, an opposite effect is found for users exposed to correct advice. Our findings point towards a paradoxical gap between stated trust and actual behavior. Furthermore, transparency mechanisms should be deployed with caution as their effectiveness is intertwined with system performance.Type: conference paperJournal: International Conference on Information Systems (ICIS)
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PublicationDisentangling Trust in Voice Assistants - A Configurational View on Conversational AI Ecosystems( 2023)Bevilacqua, TatjanaVoice assistants’ (VAs) increasingly nuanced and natural communication via artificial intelligence (AI) opens up new opportunities for the experience of users, providing task assistance and automation possibilities, and also offer an easy interface to digital services and ecosystems. However, VAs and according ecosystems face various problems, such as low adoption and satisfaction rates as well as other negative reactions from users. Companies, therefore, need to consider what contributes to user satisfaction of VAs and related conversational AI ecosystems. Key for conversational AI ecosystems is the consideration of trust due to their agentic and pervasive nature. Nonetheless, due to the complexity of conversational AI ecosystems and different trust sources involved, we argue that we need a more detailed understanding about trust. Thus, we propose a configurational view on conversational AI ecosystems that allows us to disentangle the complex and interrelated factors that contribute to trust in VAs. We examine with a configurational approach and a survey study, how different trust sources contribute to the outcomes of conversational AI ecosystems, i.e., in our case user satisfaction. The results of our study show four distinct patterns of trust source configurations. Vice versa, we show how trust sources contribute to the absence of the outcome, i.e., user satisfaction. The derived implications provide a configurative theoretical understanding for the role of trust sources for user satisfaction that provides practitioners useful guidance for more trustworthy conversational AI ecosystems.Type: conference paperJournal: Annual Meeting of the Academy of Management (AOM)
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Publication“I Will Follow You!” – How Recommendation Modality Impacts Processing Fluency and Purchase Intention( 2022-12-09)
;Schwede, Melanie ;Hammerschmidt, MaikAlthough conversational agents (CA) are increasingly used for providing purchase recommendations, important design questions remain. Across two experiments we examine with a novel fluency mechanism how recommendation modality (speech vs. text) shapes recommendation evaluation (persuasiveness and risk), the intention to follow the recommendation, and how modality interacts with the style of recommendation explanation (verbal vs. numerical). Findings provide robust evidence that text-based CAs outperform speech-based CAs in terms of processing fluency and consumer responses. They show that numerical explanations increase processing fluency and purchase intention of both recommendation modalities. The results underline the importance of processing fluency for the decision to follow a recommendation and highlight that processing fluency can be actively shaped through design decisions in terms of implementing the right modality and aligning it with the optimal explanation style. For practice, we offer actionable implications on how to make effective sales agents out of CAs.Type: conference paperJournal: International Conference on Information Systems (ICIS) -
PublicationType: conference paper
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PublicationAlexa, are you still there? Understanding the Habitual Use of AI-Based Voice Assistants( 2021-12)
;Grünenfelder, Janay IlyaVoice assistants are a novel class of information systems that fundamentally change human–computer interaction. Although these assistants are widespread, the utilization of these information systems is oftentimes only considered on a surface level by individuals. In addition, prior research has focused predominantly on initial use instead of looking deeper into post-adoption and habit formation. In consequence, this paper reviews how the notion of habit has been conceptualized in relation to biographical utilization of voice assistants and presents findings based on a qualitative study approach. From a perspective of post-adoption users, the study suggests that existing habits persist, and new habits hardly ever form in the context of voice assistant utilization. This paper outlines four key factors that help explain voice assistant utilization behavior and furthermore provides practical implications that help to ensure continued voice assistant use in the future.Type: conference paperJournal: International Conference on Information Systems (ICIS) -
PublicationWhat do you mean? A Review on Recovery Strategies to Overcome Conversational Breakdowns of Conversational Agents( 2021-12)
;Benner, Dennis ;Schöbel, SofiaSince the emergence of conversational agents, this technology has seen continuous development and research. Today, advanced conversational agents are virtually omnipresent in our everyday lives. Albeit the numerous improvements in their conversational capabilities, breakdowns are still a persistent issue. Such breakdowns can result in a very unpleasant experience for users and impair the future success of conversational agents. This issue has been acknowledged by many researchers recently. However, the research on strategies to overcome conversational breakdowns is still inconclusive, and further research is needed. Therefore, we conduct a systematic literature analysis to derive conceptual conversational breakdown recovery strategies from literature and highlight future research avenues to address potential gaps. Thus, we contribute to theory of human-agent interaction by deriving and assessing recovery strategies and suggesting leads for novel recovery strategies.Type: conference paperJournal: International Conference on Information Systems (ICIS) -
PublicationMechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research( 2023-01-06)
;Tolzin, AntoniaHuman-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.Type: conference paperJournal: Hawaii International Conference on System Sciences (HICSS) -
PublicationDesigning for Conversational System Trustworthiness: The Impact of Model Transparency on Trust and Task Performance( 2022-06-24)Designing for system trustworthiness promises to address challenges of opaqueness and uncertainty introduced through Machine Learning (ML)-based systems by allowing users to understand and interpret systems’ underlying working mechanisms. However, empirical exploration of trustworthiness measures and their effectiveness is scarce and inconclusive. We investigated how varying model confidence (70% versus 90%) and making confidence levels transparent to the user (explanatory statement versus no explanatory statement) may influence perceptions of trust and performance in an information retrieval task assisted by a conversational system. In a field experiment with 104 users, our findings indicate that neither model confidence nor transparency seem to impact trust in the conversational system. However, users’ task performance is positively influenced by both transparency and trust in the system. While this study considers the complex interplay of system trustworthiness, trust, and subsequent behavioral outcomes, our results call into question the relation between system trustworthiness and user trust.Type: conference paperJournal: European Conference on Information Systems (ECIS)
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PublicationVoice as a Contemporary Frontier of Interaction Design( 2021)Voice assistants’ increasingly nuanced and natural communication bears new opportunities for user experiences and task automation, while challenging existing patterns of human-computer interaction. A fragmented research field, as well as constant technological advancements, impede a common apprehension of prevalent design features of voice-based interfaces. As part of this study, 86 papers across domains are systematically identified and analysed to arrive at a common understanding of voice assistants. The review highlights perceptual differences to other human-computer interfaces and points out relevant auditory cues. Key findings regarding those cues’ impact on user perception and behaviour are discussed along with the three design strategies 1) personification, 2) individualization and 3) contextualization. Avenues for future research are lastly deducted. Our results provide relevant opportunities to researchers and designers alike to advance the design and deployment of voice assistants.Type: conference paperJournal: European Conference on Information Systems (ECIS)
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PublicationA Review of the Empirical Literature on Conversational Agents and Future Research Directions( 2020)The knowledge base related to user interaction with conversational agents (CAs) has grown dramatically but remains segregated. In this paper, we conduct a systematic literature review to investigate user interaction with CAs. We examined 107 papers published in outlets related to IS and HCI research. Then, we coded for design elements and user interaction outcomes, and isolated 7 significant determinants of these outcomes, as well as 42 themes with inconsistent evidence, providing grounds for future research. Building upon the insights from the analysis, we propose a research agenda to guide future research surrounding user interaction with CAs. Ultimately, we aim to contribute to the body of knowledge of IS and HCI in general and user interaction with CA in particular by indicating how developed a research field is regarding the number and content of the respective contributions. Furthermore, practitioners benefit from a structured overview related to CA design effects.Type: conference paperJournal: International Conference on Information Systems (ICIS)
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