Lessons Learned from Designing and Evaluating CLAICA: A Continuously Learning AI Cognitive Assistant

Freire, Samuel Kernan; Niforatos, Evangelos; Wang, Chaofan; Ruiz-Arenas, Santiago; Foosherian, Mina; Wellsandt, Stefan; Bozzon, Alessandro

doi:10.1145/3581641.3584042

Cited by 3 publications

(1 citation statement)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The development of the IA for systematic refection was carried out in close collaboration with factory partners; It builds on several existing features such as collecting issue descriptions and providing recommendations as described in previous literature [20,21]. The development involved conducting semi-structured interviews, collecting requirements from workers and management, observation, user evaluations, and integrating the IA with the factory's IT systems.…”

Section: Systematic Reflection Supported By An Intelligent Assistant ...mentioning

confidence: 99%

Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant

Freire

Wang

Ruiz-Arenas

et al. 2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

Many industries face the challenge of capturing workers' knowledge to share it, particularly tacit knowledge. The operation of complex systems such as a manufacturing line is knowledge-intensive. Considering this knowledge's breadth and dynamic nature, existing knowledge-sharing solutions are inefcient and resource intensive. Conversational user interfaces are an efcient way to convey information that mimics how humans share knowledge; however, we know little about how to design them specifcally for knowledge sharing, especially regarding tacit knowledge. In this work, we present an intelligent assistant that we have developed to support the elicitation of tacit knowledge from workers through systematic refection. The system can interact with workers by voice or text and generate visualizations of shop foor data to support refective prompts. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; Interactive systems and tools; Natural language interfaces.

show abstract

Section: Systematic Reflection Supported By An Intelligent Assistant ...mentioning

confidence: 99%

Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant

Freire

Wang

Ruiz-Arenas

et al. 2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

show abstract

A review of digital assistants in production and logistics: applications, benefits, and challenges

Zheng,

Grosse,

Morana

et al. 2024

International Journal of Production Research

View full text Add to dashboard Cite

A Systematic Mapping Study about Technologies for Hedonic Aspects Evaluation in Text-based Chatbots

Mariano,

Souza,

Guerino

et al. 2024

JIS

View full text Add to dashboard Cite

Many studies present and evaluate daily-use systems ranging from information to conversational systems. Chatbots, either text-based or voice-based, have attracted the attention of researchers. In particular, User eXperience (UX) has been pointed out as one of the chatbot's leading aspects of evaluation involving pragmatic and hedonic aspects. Pragmatic aspects deal with the usability and efficiency of the system, while hedonic aspects consider aspects related to the originality, innovation, beauty of the system, and the user's psychological well-being. Even with existing research on usability evaluation and human-computer interaction within conversational systems, there is a clear shortfall in studies specifically addressing the hedonic aspects of user experience in chatbots. Therefore, this paper presents a Systematic Mapping Study that investigates various UX evaluation technologies (questionnaires, methods, techniques, and models, among others), focusing on the hedonic aspect of chatbots. We focused on studies with chatbots that are activated by text, although they may be able to display click interactions, videos, and images in addition to the text modality. We discovered 69 technologies to evaluate hedonic aspects of UX in chatbots, and the most frequent aspect found is the General UX . Our study provides relevant data on the research topic, addressing the specific characteristics of human-chatbot interaction, such as identity and social interaction. Moreover, we highlight gaps in the hedonic aspect evaluation in chatbots, such as a few works investigating the assessment of user emotional state.

show abstract

Lessons Learned from Designing and Evaluating CLAICA: A Continuously Learning AI Cognitive Assistant

Cited by 3 publications

References 45 publications

Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant

Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant

A review of digital assistants in production and logistics: applications, benefits, and challenges

A Systematic Mapping Study about Technologies for Hedonic Aspects Evaluation in Text-based Chatbots

Contact Info

Product

Resources

About