Continuing my 3-week series on the Governance Frameworks for AI, this is part 6 of a much larger series on Ethical, Governance, Data Governance, and Societal concerns related to AI. There will be ...

Artificial Intelligence (AI) is revolutionizing industries across the globe, enhancing productivity, efficiency, and innovation. However, with these advancements comes a growing concern: job ...

There once was a project manager that pitted departments against each other. The Business Analysts were rated on their requirements defects. The testers were rated based on could not reproduce defects ...

I am writing a series on Emerging Trends in Data Governance. I will be breaking down multiple aspects of these trends and diving deeper into each of the major subject areas I’ve covered in my first ...

In the age of digital transformation, data is an organization’s most valuable asset. However, with the sheer volume, variety, and velocity of data generated, managing it effectively requires a robust ...

In the Netherlands, we are intimately familiar with the concept of managing complex systems. The intricate network of canals and polders that shape our landscape is a testament to our ability to ...

Continuing my blog series on the Ethical Implications of AI, this is part 4 of a much larger series on Ethical, Governance, Data Governance, and Societal concerns related to AI. There will be about 15 ...

Data is often referred to as the new oil, a critical asset that fuels the development of cutting-edge technologies, especially Artificial Intelligence (AI). At the heart of this is the concept of data ...

The concept of Vibe Coding can be explained as an approach that emphasizes the ability to define what needs to be programmed, rather than knowing how to develop software. This concept was introduced ...

The recent announcement of Google [link] has gained a lot of attention [1]. Google Quantum AI announced their new quantum chip Willow, which demonstrates notable improvements in reliability and speed.

Attended bots are useful when the entire end-to-end process can’t be automated, typically targeted toward front-office activities. RPA bots can work alongside humans to deliver attended automation.

Machine learning models often perform impressively in the lab but struggle in the real world. The main culprit? Domain shift: the difference between the data a model was trained on and the data it ...