Bringing Software Engineering Discipline to the Development of AI-Enabled Systems

Engineering AI Software systems is starting to evolve from the pure development of machine learning (ML) models to a more structured discipline that treats ML components as part of much larger software systems. As such, more structured principles are required for their development, such as established design principles, established development models, and safeguards for deployed ML models. This column focuses on papers presented at the Third International Conference on AI Engineering—Software Engineering for AI (CAIN 2024). The selected papers reflect the current development of the field of AI systems engineering and AI software development, taking it to the next level of maturity. Feedback or suggestions are welcome. In addition, if you try or adopt any of the practices included in the column, please send us and the authors of the paper(s) a note about your experiences.