Continuous experimentation on artificial intelligence software : a research agenda
Nguyen-Duc, A., & Abrahamsson, P. (2020). Continuous experimentation on artificial intelligence software : a research agenda. In P. Devanbu, M. Cohen, & T. Zimmermann (Eds.), ESEC/FSE 2020: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 1513-1516). ACM. https://doi.org/10.1145/3368089.3417039
Date
2020Copyright
© 2020 the Authors and ACM
Moving from experiments to industrial level AI software development requires a shift from understanding AI/ ML model attributes as a standalone experiment to know-how integrating and operating AI models in a large-scale software system. It is a growing demand for adopting state-of-the-art software engineering paradigms into AI development, so that the development efforts can be aligned with business strategies in a lean and fast-paced manner. We describe AI development as an “unknown unknown” problem where both business needs and AI models evolve over time. We describe a holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requirements and Minimum Viable Products. From this, five areas of challenges are presented with the focus on experimentation. In the end, we propose a research agenda with seven questions for future studies.
Publisher
ACMParent publication ISBN
978-1-4503-7043-1Conference
ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software EngineeringIs part of publication
ESEC/FSE 2020: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software EngineeringKeywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/46991595
Metadata
Show full item recordCollections
License
Related items
Showing items with similar title or keywords.
-
A Multiple Case Study of Artificial Intelligent System Development in Industry
Nguyen-Duc, Anh; Sundbø, Ingrid; Nascimento, Elizamary; Conte, Tayana; Ahmed, Iftekhar; Abrahamsson, Pekka (ACM, 2020)There is a rapidly increasing amount of Artificial Intelligence (AI) systems developed in recent years, with much expectation on its capacity of innovation and business value generation. However, the promised value ... -
“This is Just a Prototype” : How Ethics Are Ignored in Software Startup-Like Environments
Vakkuri, V.; Kemell, K. K.; Jantunen, M., Abrahamsson, P. (Springer, 2020)Artificial Intelligence (AI) solutions are becoming increasingly common in software development endeavors, and consequently exert a growing societal influence as well. Due to their unique nature, AI based systems influence ... -
Implementing Ethics in AI : Initial Results of an Industrial Multiple Case Study
Vakkuri, Ville; Kemell, Kai-Kristian; Abrahamsson, Pekka (Springer, 2019)Artificial intelligence (AI) is becoming increasingly widespread in system development endeavors. As AI systems affect various stakeholders due to their unique nature, the growing influence of these systems calls for ethical ... -
The Current State of Industrial Practice in Artificial Intelligence Ethics
Vakkuri, Ville; Kemell, Kai-Kristian; Kultanen, Joni; Abrahamsson, Pekka (IEEE, 2020)As Artificial Intelligence (AI) systems become increasingly widespread, we have begun to witness various failures highlighting issues in these systems. These incidents have sparked public discussion related to AI ethics ... -
AI Ethics in Industry : A Research Framework
Vakkuri, Ville; Kemell, Kai-Kristian; Abrahamsson, Pekka (RWTH Aachen University, 2019)Artificial Intelligence (AI) systems exert a growing influence on our society. As they become more ubiquitous, their potential negative impacts also become evident through various real-world incidents. Following such early ...