Innovation with data and AI requires more than just safeguarding privacy risks. Especially when things become complex—where ethics, human rights, and compliance intersect—it is essential that the right people come together and engage in meaningful dialogue. A DPIAMA combines a DPIA and an IAMA, bringing business, development teams, and compliance together at one table.
In our High on AI-podcast, we talk through the real world stories and use cases of business and organizations successfully introducing AI into their everyday work lives, to do all the things AI promises to do, can do and more.
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.
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?
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?
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.
Highberg digital transformation has assisted the municipality of Rotterdam in the responsible use of algorithms and transparency about these algorithms. In this project our experts managed the algorithm registry and executed the processes in the algorithm governance. During the project our experts provided concrete improvement suggestions and implemented these improvements in practice.