Geplaatst door Over the last couple of years, I’ve been exploring in what direction I want to continue my career. Or, more precisely: what I want to spend my time on. I’ve posted on LinkedIn about this process regularly. My approach has been to look for topics, technologies, and people that inspire me. My posts here, or rather your responses, have been one of the sources of inspiration. So, another post, this time about various topics I have explored (they’re all a bit ‘researchy’):
👉🏽 Digital Cultural Heritage. I enjoy learning about history: cities, countries, famous people and scientists, etc. Additionally, this field is rich in (linked) data and has a thriving and open community. I have several ideas for projects I can do, but they are a bit IT-heavy (I definitely want to avoid too much software engineering).
👉🏽 Adoption of technologies. I’ve seen my share of emergent technologies over the past few years. Big Data, No SQL, Low Code, Data Science, and now AI. It’s my impression that technology develops faster than its adoption-rate, and I wonder if that is true – and why – and under what circumstances. If so, what are the consequences of this for e.g. education and government institutions? What kind of leadership is required, and how do these adoptions affect culture at a company? And I wonder whether there is a process underlying technological adoption that we can explain, visualize, and guide (I’m thinking along the lines of Technology Readiness Levels). I’d like to research this academically, but in close cooperation with organizations going through these changes.
👉🏽 Decision-taking under uncertainty. We do a lot of machine learning these days, and algorithms are everywhere. Many are inherently uncertain, and I wonder what effect this uncertainty will have on our lives. Suppose an AI writes my e-mails for me and requires me to sign off on the result. How long will it be before I trust it, and just start clicking yes? Will I lose the ability to communicate in writing? What if my electronic lock, the temperature setting on my thermostat, the groceries I need, and the appointments I make – what if they all have a level of uncertainty but gain my trust over time? Is this a bad thing or not? At the moment, I use Google Maps all the time, I have no idea how it works, and I completely trust it. Well, as you see, I have not figured out what my central question here is. I merely feel that something fundamental is changing here.
👉🏽 Explainable AI. Perhaps this belongs under the previous category. I like the idea that algorithms have to be explained to us humans, but I don’t really know what ‘explainable’ means. To whom should it be explained? And what should be explained (construction, decisions, people involved, …)? And to what level? And how often? What if reality changed since training of the algorithm – do I get a new explanation? Plus, an ‘explanation’ can never take away the inherent uncertainty in the algorithm, so it will still make mistakes. ‘Explainable’ and ‘Faultless’ are not the same thing. My gut feeling here (not based on anything else tbh) is that ‘explainability’ is about creating trust, and a large part of that trust is explaining how it deals with mistakes. Like before, I’m not really clear on the direction I want to take in this topic.
👉🏽 Privacy Enhancing Technology. This field has grown a lot since I first encountered it 4-5 years ago. I like the field, because there is so much potential for applications, and I think the technology is still growing (i.e. I still get surprised now and then). At the same time, it’s very math-heavy in some cases, and I definitely don’t want to go too deep there. Also, my level of knowledge may not be sufficient to judge whether this career-topic is suitable for me. But perhaps a role as an advisor on the topic, close to applications, is an option.
👉🏽 Data & Machines. I have great respect for technical people who can create physical machines that work. Pumps, fans, engines, production lines … fascinating stuff. I’ve tried to get an analytics-related research job in this field, but without success. It’s on hold, but not forgotten.
As I write this, I realize that the list is long – and it’s not even finished. So why am I not working in one of these fields? The harsh reality is that competition is fierce, and without sufficient prior experience, my chances are slim. At the moment, I have a nice job in a nice team, and I’m cherishing that. Starting next May/June, I will have more time on my hands, and I’ll start working on one of these topics in my spare time. Let’s see what happens 🙂