Sabine Steenwinkel-den Daas

Sabine Steenwinkel-den Daas

Senior Consultant Digital Law & Ethics at Highberg

About Sabine
Sabine has ten years of experience in developing, implementing, validating, and assessing data and AI applications. She possesses a strong analytical and theoretical foundation to understand algorithms and AI deeply. With her background in data science, entrepreneurship, numerous IT project assignments, and certifications in privacy (CIPM) and data management (CDMP), Sabine comprehends the necessary prerequisites and control measures for successful AI implementations in great detail. She is also the substantive founder of the Highberg (c) assessment and standards framework for algorithms and has tested multiple AI systems in practice. Sabine is aware of the latest developments, such as the AI Act, and knows the ISO/IEC 42001 in detail. In her daily work, Sabine provides concrete advice on how to stay in control of data and algorithms in a responsible way, and she also enjoys sharing her knowledge through training sessions and webinars.

Want to know more? Connect with Sabine on LinkedIn.

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Article
5 min read
April 19, 2024
Break through in regulation of AI: The AI Act

This text is translated from Dutch with the help of AI - On December 8, 2023, the European Union reached a preliminary political agreement on the Artificial Intelligence Regulation (hereafter referred to as the AI Act). The final text is formally approved by the European Parliament. Twenty days after official publication the AI Act will enter into force. This landmark legislation marks the EU's first step towards regulating artificial intelligence, targeting developers, distributors, and users of AI systems, including those systems used for predictions, classifications, and analyses. The potential impact on governments and businesses deploying AI systems is significant. Key obligations, their effects on organizations, and proactive steps to ensure compliance are outlined below.

Article
11 min read
April 19, 2024
Bias in AI Explained

This text is translated from Dutch with the help of AI – "Tell me honestly, what's your biggest fear when it comes to algorithms and AI?" When I ask people this question, the response often is, "AI systems discriminate!" And of course, discriminating is far from desirable. But how do we ensure that algorithms don't discriminate? First and foremost, it's important to understand that algorithms themselves do not discriminate. However, algorithms can be developed in ways that lead to unwanted or undesired distinctions in representation of groups in the result. This is commonly referred to as "bias" in technical terms Essentially, if you have control over the bias within the algorithm, you also minimize discrimination. Here, how to achieve this is explained. Let's start by answering the question: What is bias?

Article
5 min read
April 19, 2024
In control of your AI systems

Have you ever heard or said within your organization, "We're working with data/algorithms/AI" or "We have plenty of data initiatives, but scaling within the organization is challenging"? These questions all boil down to one main question: How do you ensure that you apply the right algorithms in the right way?

Article
6 min read
April 19, 2024
Transparency with algorithm registry?

This article has been translated from Dutch with the help of AI: In an era where algorithms exert increasing influence on our daily lives, maintaining control over the latest developments and being transparent about them is more important than ever. This leads to a crucial question: when is the openness and transparency surrounding these algorithms sufficient? The answer is not simple, because transparency goes beyond just registering the algorithm. The steps needed to start working on transparent and responsible use of algorithms can be structured into five maturity levels.

Cases by Sabine Steenwinkel-den Daas

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