Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops

Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.

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Understanding the Design Elements Affecting User Acceptance of Intelligent Agents: Past, Present and Future

Elshan

Zierau

Engel

et al. 2022

Inf Syst Front

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Intelligent agents (IAs) are permeating both business and society. However, interacting with IAs poses challenges moving beyond technological limitations towards the human-computer interface. Thus, the knowledgebase related to interaction with IAs has grown exponentially but remains segregated and impedes the advancement of the field. Therefore, we conduct a systematic literature review to integrate empirical knowledge on user interaction with IAs. This is the first paper to examine 107 Information Systems and Human-Computer Interaction papers and identified 389 relationships between design elements and user acceptance of IAs. Along the independent and dependent variables of these relationships, we span a research space model encompassing empirical research on designing for IA user acceptance. Further we contribute to theory, by presenting a research agenda along the dimensions of the research space, which shall be useful to both researchers and practitioners. This complements the past and present knowledge on designing for IA user acceptance with potential pathways into the future of IAs.

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Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops

Cited by 4 publications

References 31 publications

Towards Effective Conversational Agents: A Prototype-Based Approach for Facilitating Their Evaluation and Improvement

Towards Effective Conversational Agents: A Prototype-Based Approach for Facilitating Their Evaluation and Improvement

How mature is requirements engineering for AI-based systems? A systematic mapping study on practices, challenges, and future research directions

Understanding the Design Elements Affecting User Acceptance of Intelligent Agents: Past, Present and Future

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