Responsible Prompting Recommendation: Fostering Responsible AI Practices in Prompting-Time

Human-Computer Interaction practitioners have been proposing best practices in user interface design for decades. However, generative Artificial Intelligence (GenAI) brings additional design considerations and currently lacks sufficient user guidance regarding affordances, inputs, and outputs. In this context, we developed a recommender system to promote responsible AI (RAI) practices while people prompt GenAI systems. We detail 10 interviews with IT professionals, the resulting recommender system developed, and 20 user sessions with IT professionals interacting with our prompt recommendations. Results indicate that responsible prompting recommendations have the potential to support novice prompt engineers and raise awareness about RAI in prompting-time. They also suggest that recommendations should simultaneously maximize both a prompt’s similarity to a user’s input as well as a diversity of associated social values provided. These findings contribute to RAI by offering practical ways to provide user guidance and enrich human-GenAI interaction via prompt recommendations.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713365
Citations
3
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
7.10
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article

Responsible Prompting Recommendation: Fostering Responsible AI Practices in Prompting-Time

Cassia Sampaio Sanctos, Sara Berger, Vagner Figuerêdo de Santana, Tianyu Su et al.
3 citations
Ethics and Social Impacts of AI
7.10
article

Responsible Prompting Recommendation: Fostering Responsible AI Practices in Prompting-Time

Cassia Sampaio Sanctos, Sara Berger, Vagner Figuerêdo de Santana, Tianyu Su, Heloísa Candello, L. S. Williams, Tiago Machado
article en
3 citations

Abstract

Human-Computer Interaction practitioners have been proposing best practices in user interface design for decades. However, generative Artificial Intelligence (GenAI) brings additional design considerations and currently lacks sufficient user guidance regarding affordances, inputs, and outputs. In this context, we developed a recommender system to promote responsible AI (RAI) practices while people prompt GenAI systems. We detail 10 interviews with IT professionals, the resulting recommender system developed, and 20 user sessions with IT professionals interacting with our prompt recommendations. Results indicate that responsible prompting recommendations have the potential to support novice prompt engineers and raise awareness about RAI in prompting-time. They also suggest that recommendations should simultaneously maximize both a prompt’s similarity to a user’s input as well as a diversity of associated social values provided. These findings contribute to RAI by offering practical ways to provide user guidance and enrich human-GenAI interaction via prompt recommendations.

Harvard University Press (US), Alliance for Safe Kids (US), IBM Research - Brazil (BR), Virginia Tech (US)
Openalex Percentile: Top 4%
Ethics and Social Impacts of AI
7.10
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