The Design Space of in-IDE Human-AI Experience
- URL: http://arxiv.org/abs/2410.08676v1
- Date: Fri, 11 Oct 2024 10:02:52 GMT
- Title: The Design Space of in-IDE Human-AI Experience
- Authors: Agnia Sergeyuk, Ekaterina Koshchenko, Ilya Zakharov, Timofey Bryksin, Maliheh Izadi,
- Abstract summary: Key findings stress the need for AI systems that are more personalized, proactive, and reliable.
Our findings show that while Adopters appreciate advanced features and non-interruptive integration, Churners emphasize the need for improved reliability and privacy.
Non-Users, in contrast, focus on skill development and ethical concerns as barriers to adoption.
- Score: 6.05260196829912
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Nowadays, integration of AI-driven tools within Integrated Development Environments (IDEs) is reshaping the software development lifecycle. Existing research highlights that users expect these tools to be efficient, context-aware, accurate, user-friendly, customizable, and secure. However, a major gap remains in understanding developers' needs and challenges, particularly when interacting with AI systems in IDEs and from the perspectives of different user groups. In this work, we address this gap through structured interviews with 35 developers from three different groups: Adopters, Churners, and Non-Users of AI in IDEs to create a comprehensive Design Space of in-IDE Human-AI Experience. Our results highlight key areas of Technology Improvement, Interaction, and Alignment in in-IDE AI systems, as well as Simplifying Skill Building and Programming Tasks. Our key findings stress the need for AI systems that are more personalized, proactive, and reliable. We also emphasize the importance of context-aware and privacy-focused solutions and better integration with existing workflows. Furthermore, our findings show that while Adopters appreciate advanced features and non-interruptive integration, Churners emphasize the need for improved reliability and privacy. Non-Users, in contrast, focus on skill development and ethical concerns as barriers to adoption. Lastly, we provide recommendations for industry practitioners aiming to enhance AI integration within developer workflows.
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