Kaat Van Doren
Head of Talent & Culture
In this article, we delve into the mind of Kaat Van Doren, Head of Talent & Culture at ML6, as she explores the role of curiosity within the organization and her own professional life at a podcast sit down with Cevora.
ML6 focuses on artificial intelligence and machine learning, a rapidly growing field. As an individual, keeping up in this rapidly developing field is not easy, which is why consultants continuously feed the collective intelligence of ML6. For Kaat “the focus on learning and innovation to accelerate AI adoption” is what makes ML6 unique.
Knowledge is our product at ML6, and we strive to continuously learn to provide added value to our clients. As an individual, it is impossible to keep up with all the AI developments, but with a team of 100 people, we can build a huge collective intelligence that makes a difference. Our ML6 agents are therefore given time to learn and contribute to our collective intelligence.
Our company is organized around this collective intelligence, which is embedded in our processes, culture, and how we interact with each other and our clients. For example, we have a tool that tells us who has experience or expertise within AI or an insights tool to see who is working on which projects. This is crucial information for new employees, to quickly match clients with ML6 agents, and for our general way of working.
We also promote knowledge sharing to spread information throughout the organization. For example, if each engineer reads an article or paper, or follows a new release of a technology, and then shares the information with colleagues and feeds back to our clients, we win enormously. We have several initiatives for this, such as weekly meetings and conferences, to stay on top of the latest innovations as a team and for our clients. "It's fantastic to see the dynamic that arises with a new GPT release, colleagues immediately exchanging thoughts, sharing opinions, and starting to work on projects."
Also a broader network is something we actively invest in. We learn a lot from each other within the tech community. Open source is plays an important role within the AI and machine learning community - much information is publicly accessible. That means we can build on existing algorithms and make them even better, contributing to the positive snowball effect of the AI domain.
"Within AI and machine learning, a lot of information is publicly accessible, anyone can build on it. That snowball effect is the great strength of the AI domain, and we are happy to contribute to it."
When you're a team of 10, you brief each other spontaneously, and everyone is aware of everything. But with a team of 100, you facilitate that differently, and not everything is relevant to everyone. Thinking carefully about who needs what information is essential so that every ML6 agent has the right information.
That’s why we regularly organize different contact moments. Project teams can share knowledge about a completed project, and there are also many events for the entire team, which is important for creating a sense of teamwork and unity. For example, we meet four times a year for our own organized conference day, where we cover technical topics as well as strategic and HR themes. We then share that content with our external communities, such as schools and clients, as a thought leader.
You can always go deeper into a particular domain, but at some point, you no longer add value or make progress. That's the pitfall of curiosity. There is also the risk of too much information - it never stops. It can be very tiring to want to know everything continuously. Setting boundaries in a timely manner and focusing on creating added value is crucial.
Of course, you don't want to suppress curiosity, but you need to make people aware that they can't shoot at everything at once. As a team, you are stronger than alone. But it's not easy, and sometimes as a company and individual, you have to say no. This helps to maintain direction and focus, "choose your focus." For example, we have forums where senior engineers put topics on the agenda and thus influence those choices, or an incubation team (focused on long-term innovation) that helps prioritize projects.
"Furthermore, I strongly believe in learning from each other on the job. I learn a lot from my colleagues as well." This fits again within the core way of working at ML6. The focus on collaboration and teamwork is important and one of our strengths. People can learn a lot from each other and can also bring each other to a higher level.
For example, I'm not an AI expert myself, but I still want to be up-to-date with how AI works, trends within the field and the projects we do at ML6. It's important to know what the people at your company are doing, to focus on the important aspects in your HR strategy. This is also important for recruitment or to plan development paths.
In my field of expertise - HR - continuous learning is also crucial. Our HR team only consists of three people, so we also need to look outside of our own team sometimes. How do large HR teams tackle a certain problem? I actively seek out HR colleagues who are experiencing similar situations, whether they are in the same industry or not. But it's also enriching to spar with a colleague from a completely different industry or from abroad.
In addition to the strong internal knowledge we build at ML6, we also gladly enrich ourselves with knowledge from the broad AI domain or even other domains. We maintain good relationships with communities and in this way, we strengthen our knowledge. This also goes in both directions; we also share a lot of our own knowledge externally through blog posts, talks, etc.
In AI, everything is shifting, but HR is also a domain that is constantly evolving. You don't have to know everything, but curiosity is about asking questions and actively seeking information that can help you further or provide a new perspective."