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Author Sieuwert van Otterloo

Author: Sieuwert van Otterloo
Dr. Sieuwert van Otterloo is a court-certified IT expert with interests in agile, security, software research and IT-contracts. He is a also an ISO 27001 and NEN 7510 auditor and AI researcher.

The ICTI list of influential computer scientists

Computer, science, AI and privacy-law are often described as new fields of research. This maybe was the case in 1990, but as of now these fields are old: The solutions to most current problems in society are already invented years ago, but not well-remembered. To help ourselves and other people remember all the work, we…

Sieuwert van Otterloo

Technology risk assessment 2023: what programming language (versions) to use

It is important for companies to choose future proof technology: if not you may have to switch technology at great cost, or run security risks. In our technology reviews, we therefore assess the risk of all modern software languages and frameworks. In this article we explain what we look at and provide a summary of the…

Sieuwert van Otterloo

A checklist for auditing AI systems

As the use of AI increases, the potential impact of using wrong AI system increases as well. It is therefore recommended and often required to audit AI systems. We have talked to several IT auditors and privacy experts to make a checklist on what should be considered when auditing an AI system.

Sieuwert van Otterloo

The Kickstarter video game dataset

The development of new videogame projects is often financed through crowdfunding. Unfortunately not all financed projects are delivered successfully. Jasser Bakridi compiled a dataset of 100 videogame projects that started as a kickstarter projects. The dataset not only contains data from the kickstarter campaign page but also the delivery status: whether the game has been…

Sieuwert van Otterloo

The Utrecht housing dataset – example dataset for prediction

The Utrecht housing dataset is a freely available dataset that can be used by students to learn about data science and machine learning. It is suitable for multiple techniques, including decision trees, linear regression, logistic regression and neural networks. Note: the dataset was updated in 2025, see a detailed description of the latest 2025 version…

Sieuwert van Otterloo