In today’s hyper-connected world, recommendation algorithms have quietly become our everyday guides. They influence the music we listen to, the news we read, the things we buy, and even the people we connect with. These systems help us navigate an overwhelming amount of information by offering content that seems relevant and convenient. Using powerful AI and machine learning, they learn from our behavior—often without us realizing—and use techniques like collaborative or content-based filtering to guess what we might want next.

However, this convenience comes with hidden costs. Are these “neutral” systems really neutral? What kinds of biases are built into them? And how does being constantly nudged toward certain choices shape our tastes, opinions, and how we see the world? The idea behind the “nudge” theory is that people often react to their environment without much thought. Recommendation systems work in a similar way—gently steering our behavior through design and personalization. In their drive to keep us engaged, they often repeat what we already know or like, which can limit discovery, trap us in echo chambers, and make culture feel more uniform. Ironically, having too many suggestions can also make it harder to choose, leading us to passively go along with whatever the algorithm serves up.

Presented at the Pavillon Sicli in Geneva, 404 looks beneath the surface of these powerful technologies. The exhibition features new student projects alongside work by invited artists and designers, all exploring the promises and problems of recommendation systems. Rather than simply accepting technology as a useful tool, the artists featured in the exhibition ask tough questions and offer alternative perspectives. They aim to:

1 Unveil the Mechanics – Making the invisible processes behind recommendation systems more understandable by exposing how they work, what they rely on, and what assumptions they carry. For example, Higher Resolution by Caroline Sanders reveals the hidden data structures behind algorithmic personalization, showing how they shape our online experiences.

2 Challenge the Bias – Examining how these systems can reflect and even amplify existing biases—whether based on demographics, popularity, or commercial interests. Jake Elwes’ The Zizi Show confronts these issues by playfully critiquing how AI handles gender and identity, using deepfake drag performances as both critique and celebration.

3 Explore the Effects – Looking at how algorithm-driven content impacts personal choice, cultural diversity, and the experience of stumbling upon something new. Trevor Paglen’s works like Echo Chamber and ImageNet Roulette highlight how AI systems classify and interpret the world, and the unexpected consequences that can follow.

4 Imagine Alternatives – Asking what other ways of navigating information might look like—systems that encourage exploration, diversity, and user control instead of just predicting our next click. A guest lecture by Tera Brain invites visitors to think about post-algorithmic futures, where curiosity and ambiguity play a larger role in how we interact with technology.

Through interactive installations, speculative designs, data visualizations, and critical objects, 404 invites visitors to reflect on their own relationship with recommendation algorithms. It opens up space for discussion about how these systems shape our digital lives, what we trade in exchange for personalized content, and how we might find a better balance between efficiency and meaningful human experience. In a world increasingly shaped by algorithms, how can we take back control and shape our own paths?