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Let’s be honest, being a student today is tough. Study, work, side jobs and keeping up with your social life, it requires a lot to catch up on. Finding time to cook healthy meals or a meal in general after a long day is the last thing you have the energy for. The rising food prices aren’t making anything easier. It’s no wonder that so many students end up living on instant noodles. This is exactly where student-smart meals comes in. A GenAI powered meal app designed by students, for students. 

Most of the students in the Netherlands work alongside their studies, which leaves little to no room for eating a healthy meal at home. While studies show that gen Z cares more about being healthy and sustainable, they are being held back by lack of time, rising living costs and limited cooking availabilities (McKinsey & Company, 2024). So, we asked ourselves: what if AI could generate an affordable, quick, and nutritious meal for you using supermarket discounts in real time? 

That’s where Generative AI (GenAI) comes in. the platform that again is going to help us with everyday problems and food is no exception in this. Our platform uses AI to create personalized recipes and meal plans based on your budget, diet, cooking tools and even how much time you have. We aim to make every meal doable in just 20 minutes. What makes this app a distinction from other prep-meal platforms is that we are integrating real-time supermarket data. The app analyzes current discounts on the ingredients you need for your AI-generated recipes. Basically, it’s going to be your new smart kitchen buddy that makes sure you eat well, without spending hours scrolling for recipes or exceeding your grocery budget. 

Personalization and sustainability can go hand in hand. The app doesn’t just make meal planning easier, it also helps students make smarter choices. Each recipe strives to a healthy, affordable and minimized waste use by reusing ingredients over the week, which directly supports UN Sustainable Development Goal 12, promoting responsible consumption. To keep the platform sustainable, we decided to use a freemium model. The basic version of the app is free for everyone but with ad-use, while a premium plan unlocks advanced features like detailed nutrition tracking and ad-free use.  For users, the impact is clear: less time planning, more money savings, and healthier eating habits. The app also reduces “decision fatigue”, the feeling of not knowing what to eat and replaces it with simple, affordable options that fit any schedule. GenAI, once again, proves that it can be a solution to everyday problems. By combining smart technology with real student needs, we created something that saves time, money, and energy, all while promoting healthier and more sustainable living.

In short, Student-Smart Meals shows what’s possible when technology meets real life difficulties. Because eating healthy shouldn’t be a privilege, it should be part of student life.

McKinsey. (2024, August 28). What Is Gen Z? McKinsey & Company. https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-gen-z

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Figure 1: 21 years old vs. 80 years old (Homiwork, 2025)

Nowadays, modern AI tools have the ability create human-like images that look incredibly real. With just a few clicks, you can see how you might look at 80 years old or even generate a picture of you and your favorite celebrity ‘together’. At first, it feels crazy that technology is able to do this and that it came this far, while it seems very normal to Gen Z. To be honest, the more I explore it, the more I realize it’s both exciting and strange how AI can blur the line between what’s real and what’s fake. 

AI image generators use models that are trained on massive datasets of human faces to create realistic images (Fotor, z.d.). They’ve become popular because they tap into something deeply human, our curiosity about ourselves and others. We love seeing ‘what ifs’: What if I had a beard? What if my partner and I were older? What if we had kids together? In a way, these images are a new form of digital storytelling. They let us play with identity, fantasy, and imagination in a way that photography never could.

But it also makes me think about how personal and emotional these AI-generated images can become. When you see a picture that looks exactly like you with someone you were never actually with, it can make you feel things that aren’t even real. It’s a reminder that AI isn’t just about logic, it can also touch our emotions, sometimes in unexpected ways.

Rather than seeing this as purely dangerous, I see it as a creative opportunity with responsibility. Artists are already using these tools to explore ideas of memory, time, and relationships, creating portraits that show how technology can expand what it means to be human. At the same time, we should remember that with every powerful tool comes a need for awareness. AI doesn’t just reflect reality, it can reimagine it.

So maybe the real challenge isn’t whether these tools are ‘good’ or ‘bad,’ but how we use them. If we combine creativity with mindfulness, AI-generated images can become more than tricks of the eye, they can be windows into our imagination.

Fotor. (z.d.). AI Face Generator: Create unique human faces using AI | Fotor. https://www.fotor.com/features/ai-face-generator/

Homework (2024). AI Age Progression: How Will You Look at 18 or Older. https://homiwork.com/en/app/pictures/create/age-transformation

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The concept of network effects is easy to describe: the more people use a service, the more valuable it becomes (Banton, 2024). This is why they play a significant role in the growth of products and services. What most people don’t realize is that these algorithms play a dominant role in determining what people get to see on their screens. Content doesn’t ‘just appear’ on screens.

Algorithms are designed to push popular or highly engaging content onto more feeds and ensure visibility. While this mechanism helps platforms grow, it also carries a darker side. The danger lies in the fact that algorithms don’t distinguish between positive and negative content. Engagement-driven algorithms prioritize strong emotional reaction above objective news articles. This means that fake news or misinformation spreads faster than accurate information (Vosoughi et al.,2018). As awareness of misinformation grows, public trust in platforms declines. Instead of reinforcing network effects, this process creates negative network effects, where the products or services become less valuable as more people use it.  Feed algorithms classify user preferences by collecting behavioral data and matches users with precise and continuous information. This creates powerful driving forces for group polarization, which highly contributes to the formation of echo chambers. Thus, echo chambers are fueled by algorithms. Recent studies show that these echo chambers can promote the spread of misleading information, fake news and rumors (Gao et al.,). For example, Youtube’s recommendation system has been criticized for pushing viewers toward increasingly radical content. The algorithms seem to consistently recommend more extreme versions of things users are watching, just like if you start watching running videos, you end up with videos about ultramarathons. 

Algorithms have a significant impact on the formation of negative network effects by prioritizing engagement-driven data over objective data, the risks of algorithms can cause a harmful loop that damages trust and spreads misinformation.

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References

Banton, C. (2024, 22 augustus). What Is the Network Effect? Investopedia. https://www.investopedia.com/terms/n/network-effect.asp

Gao, Y., Liu, F., & Gao, L. (2023). Echo chamber effects on short video platforms. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-33370-1

Tufekci, Z. (2018, 10 maart). YouTube, the great radicalizer. The New York Times. https://www.nytimes.com/2018/03/10/opinion/sunday/youtube-politics-radical.html

Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559