Using GenAI the ENCOM Way

13

October

2025

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As a die-hard Tron fan, I recently went to watch Tron Ares in the cinema, and it stuck with me.  In the Tron world, ENCOM and Dillinger Systems are rival companies competing for control of the digital future. Without spoiling the whole story, I can say that the movie shows two paths for AI: the ENCOM path, where tech helps people and opens new possibilities to improve our lives, and the Dillinger path, where power and control come first. Seeing that contrast on a giant screen made me think about how I use generative AI in my own life and why my experience has been mostly positive.

Day-to-day, GenAI, mostly large language models (AI chatbots), feels like an ENCOM tool for me. I use it to give me medical advice, clean up emails and messages, translate conversations. It summarizes long articles when I’m short on time, helps me outline essays, drafts slides and talking points. When I’m coding with RStudio, it explains errors in simple terms. And when I’m planning a trip, it helps me think through checklists. It’s like an assistant that only wants the best for you.

Part of why this stays positive is the way these GenAI tools are set up. It tries to be friendly and helpful, and it puts safety first. Harmful or abusive requests get blocked or redirected. It won’t imitate a living person’s exact voice, won’t help with dangerous instructions, and pushes me toward responsible use. That doesn’t make misuse impossible, but it does make it harder.

Of course, the Dillinger path exists in the real world, too. We see AI being built into defense, border security, and large-scale surveillance systems. Companies like Palantir and Anduril are known for powerful analytics and autonomous sensing platforms. Facial recognition firms have scraped massive image datasets. These tools can centralize power in ways that can be worrying. It’s very much like the movie’s warning: when a few actors control the Grid, ordinary Users lose agency. I’m not saying these companies are “villains,” but the direction of travel still matters.

So I set myself a simple goal: keep my use of AI on the ENCOM path. Tron Ares should remind us that AI Programs can turn dangerously powerful in the future. If we give them good goals, they can light up the city. If we don’t, the same power can bite back, with the risk of even turning against us. Kind of like Skynet, but that’s a whole other franchise.

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Rotterdam’s Digital Twin: Fighting Climate Change with AI

25

September

2025

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Last week, Roland van der Heijden introduced us to Rotterdam’s Open Urban Platform (OUP) and its Digital Twin, a three-dimensional, real-time copy of the city. This platform is more than just a digital map. It is a shared system where data from sensors, companies, and citizens all come together. From traffic to air quality, everything can be shown in one common model.

But what if this digital version of Rotterdam could also help us prepare for climate change? The Netherlands is very vulnerable to rising sea levels and heavy rainfall. Imagine running flood simulations inside the Digital Twin: testing how storm surges move through neighbourhoods, where sewage systems might fail, and how well our infrastructure can cope.

The OUP already includes tools for flood analysis and heat-stress mapping. These tools can help city leaders explore worst-case scenarios before they happen. During a crisis, live data streams could update the model in real time, helping first responders and guiding evacuation plans.

This is where AI could make a big difference. Traditional flood simulations can take a lot of time, but AI can work like a “fast-forward” button. By learning from earlier simulations, AI can predict outcomes in seconds. This means decision-makers can test many more scenarios, explore different risks, and choose better responses.

The real power comes from the platform logic we discussed in class: the value grows as more people and organizations join. If municipalities, universities, businesses, and citizens all share their data, the OUP becomes not only a better tool for simulations but also a training ground for AI models. The more diverse and continuous the data, the smarter and more reliable these models become.

So here’s my question: could the Digital Twin, combined with AI, become our most powerful defense against climate risks? Not only predicting where floods might hit, but helping us design a safer future city together?

Sources:

  • Municipality of Rotterdam. (2024). Rotterdam in Transformation: Vision on the Digital City 1.0. Open & Agile Smart Cities. https://oascities.org/wp-content/uploads/2024/11/Rotterdam-in-tranformation-vision-on-the-digital-city-1.0.pdf
  • Future Insight. (2025, January 16). The future of Rotterdam starts today: the Open Urban Platform has been launched. Future Insight. https://www.futureinsight.nl/post/the-future-of-rotterdam-starts-today-the-open-urban-platform-has-been-launched?lang=en
  • Bagheri, S., Brandt, T., & van Oosterhout, M. (2021). Digital City Rotterdam: Open Urban Platform — Teaching Case. Erasmus University Rotterdam / ECDA RSM Case. https://ecda.eur.nl/wp-content/uploads/2021/10/Urban-platform-teaching-case-final_.pdf
  • Van der Heijden, R. (2025, September 18). Rotterdam Citiverse & Open Urban Platform [Guest lecture]. Rotterdam School of Management, Erasmus University Rotterdam.

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