AI lifecycle models need to be revised An exploratory study in Fintech

Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components. Thus, the same development processes and standards in software engineering ought to be complied in artificial intellige...

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Vydáno v:Empirical software engineering : an international journal Ročník 26; číslo 5
Hlavní autoři: Haakman, Mark, Cruz, Luís, Huijgens, Hennie, van Deursen, Arie
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2021
Témata:
Compilers
Computer Science
Interpreters
Programming Languages
Software Engineering/Programming and Operating Systems
Case study
AI engineering
AI lifecycle
SE4AI
Machine learning
ISSN:1382-3256, 1573-7616
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Popis
Shrnutí:Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components. Thus, the same development processes and standards in software engineering ought to be complied in artificial intelligence systems. This study aims to understand the processes by which artificial intelligence-based systems are developed and how state-of-the-art lifecycle models fit the current needs of the industry. We conducted an exploratory case study at ING, a global bank with a strong European base. We interviewed 17 people with different roles and from different departments within the organization. We have found that the following stages have been overlooked by previous lifecycle models: data collection , feasibility study , documentation , model monitoring , and model risk assessment . Our work shows that the real challenges of applying Machine Learning go much beyond sophisticated learning algorithms – more focus is needed on the entire lifecycle. In particular, regardless of the existing development tools for Machine Learning, we observe that they are still not meeting the particularities of this field.
ISSN:1382-3256
1573-7616
DOI:10.1007/s10664-021-09993-1