Traditional software engineering methods have been designed and optimized to help (teams of) developers to build high-quality software in a controlled and cost-effective manner. When building software systems that include Machine Learning (ML) components, those traditional software engineering method are challenged by three distinctive characteristics: Inherent uncertainty: ML components insert…

On the gap between theory and practice and how to close it — By Alex Serban and Joost Visser While research on the Ethics of AI increased significantly in recent years, practitioners tend to neglect the risks coming from inequity or unfairness of their ML components. This is one of the insights of the annual State of AI report for 2020 recently published…

On the relevance of Software Engineering for the development of ML-based software systems — We are studying the emerging discipline of Machine Learning Engineering by investigating best practices for developing software systems that include ML components. In this article, we share the research motivation and approach, some initial results, and an invitation to help us by taking our 7-minute online survey on ML Engineering…

On regulation of algorithms — And I don’t mean in the obvious way that the adjective “artificial” leads to philosophical thought and debate about the essence of intelligence and therefore the essence of human nature. No news there. Just ask Daniel Dennett, or any philosopher of the mind. I mean that AI made us think…

An awesome 😎 reading list — An ever-increasing number of organizations are developing applications that involve machine learning components. The complexity and diversity of these applications calls for software engineering techniques to ensure that they are built in a robust and future-proof manner. Do traditional software engineering practices apply equally to the development of applications with…

Product development starts with building a product roadmap, I was told. But what is the right way to do that? Here’s what I discovered about product roadmaps when building one. — I just delivered a Product Roadmap. I was appointed Chief Product Officer at SIG last September and gathered a small Product team. Mostly first-timers at this game, including myself. Our mission: provide the functional design of a new platform to propel our organisation into a new level of growth.

Our benchmark of development best practices shows piece-meal improvement — Deployment automation is quickly gaining ground. Backlog grooming is being perfected further. Code quality control and automated testing are improving, but still not fully adopted by most teams. These are just 3 of the lessons we learned from the yearly re-calibration of our development best practices benchmark. Read on for…

These hackathon teams prove it can be done — Last weekend 63 teams gathered in the old Sugar Factory in the Dutch city of Groningen for the world’s largest Blockchain hackathon. Here is what we learned from these teams about writing high-quality code under time pressure. Quality under pressure? Anyone can code. There are no formal entry criteria. An…

A different code quality philosophy — Should you measure and control code quality? According to a poll conducted by O’Reilly Media and my colleagues at the Software Improvement Group, virtually all developers say YES! Here’s a number of compelling reasons: Happiness: Better code and happy developers go together. It’s more fun to work on code that…