Show, Don’t Tell. Reflections on the Design of Multi-modal Conversational Interfaces

Crovari, Pietro; Pidò, Sara; Garzotto, Franca; Ceri, Stefano

doi:10.1007/978-3-030-68288-0_5

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…Conversational interfaces, also called chatbots, support explainability of complex technical systems [16] and facilitate complex problem solving [11]. Multi-modal conversational interfaces have been explored in the bio-informatics domain [8] and fashion retail applications [20]. The authors in [8] formulate seven design principles for multi-modal conversational interfaces which we use for the design of our system.…”

Section: Multi-modal Conversational Interfacementioning

confidence: 99%

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What Does It Cost to Deploy an XAI System: A Case Study in Legacy Systems

Höhn

Faradouris²

2021

Explainable and Transparent AI and Multi-Agent Systems

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Enterprise Resource Planning (ERP) software is used by businesses and extended via customisation. Automated custom code analysis and migration is a critical issue at ERP release upgrade times. Despite research advances, automated code analysis and transformation require a huge amount of manual work related to parser adaptation, rule extension and post-processing. These operations become unmanageable if the frequency of updates increases from yearly to monthly intervals. This article describes how the process of custom code analysis to custom code transformation can be automated in an explainable way. We develop an aggregate taxonomy for explainability and analyse the requirements based on roles. We explain in which steps on the new code migration process machine learning is used. Further, we analyse additional effort needed to make the new way of code migration explainable to different stakeholders.

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Section: Multi-modal Conversational Interfacementioning

confidence: 99%

“…Multi-modal conversational interfaces have been explored in the bio-informatics domain [8] and fashion retail applications [20]. The authors in [8] formulate seven design principles for multi-modal conversational interfaces which we use for the design of our system. Figure 2 shows the current modalities.…”

Section: Multi-modal Conversational Interfacementioning

confidence: 99%

What Does It Cost to Deploy an XAI System: A Case Study in Legacy Systems

Höhn

Faradouris²

2021

Explainable and Transparent AI and Multi-Agent Systems

View full text Add to dashboard Cite

show abstract

“…When the complexity of the tasks arises, an effective troubleshooting could benefit from multi-modal assistance, juxtaposing the textual messages with visual hints on the graphical user interface [4,6,8]. For this reason, we propose MCTK, Multi-modal Conversational Troubleshooting Kit, a prototype system that allows to easily design and integrate a conversational agent into a web application.…”

Section: Introductionmentioning

confidence: 99%

MCTK: a Multi-modal Conversational Troubleshooting Kit for supporting users in web applications

Abbo

Crovari

Pidò

et al. 2022

Proceedings of the 2022 International Conference on Advanced Visual Interfaces

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Conversational Interfaces for user assistance are becoming persuasive. Today, though, most chatbots are not integrated into the application in which they are placed, but only superimposed, with no communication between the conversational and the graphical interface. We propose Multi-modal Conversational Troubleshooting Kit (MCTK), a Python package to easily integrate a conversational agent for troubleshooting in web applications. MCTK is multi-modal: once the system recognizes the problem the user is encountering, the textual solution in the chat is coupled with visual hints in the GUI. On top of that, MCTK is easy to configure and offers separation of concerns: dialogue designers can work on the conversation without the necessity of modifying the code, and vice versa.

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