Model Visualization: A Misguided Obsession?

Model visualization is having its moment in the sun. Researchers are racing to make sense of complex models through visuals. But are they barking up the wrong tree? Most visualizations are obsessed with outcomes, leaving the inner workings of models shrouded in mystery.

The Two-Stage Framework

The model-centric, two-stage framework presented in recent research offers a fresh perspective. By employing abstract listeners, it captures both spatial and temporal behaviors of models. The data is then linked to the traditional InfoVis pipeline. This sounds promising on paper, but the execution reveals an industry overextended on visual output.

The researchers collected and analyzed 128 ModelVis papers, sifting through 331 coded figures. Their findings? A fixation on result-centric priorities. Visualization efforts are skewed towards model outcomes, quantitative data, and performance evaluation. The funding rate is lying to you again. Everyone's enamored with results, but at what cost?

Impact of Neglected Mechanisms

Here's where it gets interesting. Studies focusing on model mechanisms, though less frequent, punch above their weight in impact. These few studies dig into what models actually do rather than what they spit out. Despite their significance, interest in these insights wanes. Bullish on hopium. Bearish on math.

Why should you care? Because understanding mechanisms offers real insight. It's like reading the novel instead of just the summary. Zoom out. No, further. See it now?

Future Direction or Dead End?

Is this fixation on outcomes a dead end? The current framework might guide future designs, but it's built on shaky foundations. Are we truly advancing our understanding of AI, or just making pretty pictures? The question isn't whether we can visualize models, but whether we're asking the right questions about them.

As the interest in model visualization grows, let's not lose sight of what truly matters. It's not just about seeing. It's about understanding. Otherwise, we're just painting over cracks.