In the 2009-2010 school year, the Bavarian State Office for Health ran an experiment in six German schools. Researchers tracked carbon dioxide levels across 20 classrooms and matched them against pupils’ test performance on the same days. In classrooms with good air, CO2 sat around 1,045 ppm. In classrooms with poor air, it climbed to 2,115 ppm. The children in the worse air were not slower overall. They made significantly more errors on the tests (Twardella et al., 2012, Indoor Air). Neither the pupils nor their teachers noticed a difference in the room.

That is the pattern I keep finding in this literature: a room changes what a mind can do, and nobody in the room feels it happen.

The Charité hospital in Berlin gives a second case, with higher stakes. In 2013 the architecture practice GRAFT rebuilt two intensive care rooms. They added a lighting system that simulated day and night, damped the ambient noise and moved medical equipment behind wall panels so patients no longer woke to the sight of it. Spies and colleagues later measured the result: delirium in the redesigned rooms ran at 46 percent, against 76 percent in the standard rooms nearby (Spies et al., 2024, Critical Care Medicine). ICU delirium extends hospital stays and adds substantial cost per case. A room redesign cut it by 30 percentage points.

A third case moves the same question into offices. Joseph Allen and colleagues ran the COGfx study on how ventilation shapes cognition at work. In well-ventilated buildings, cognitive test scores came out roughly double those measured in conventionally ventilated ones. Crisis response scored 131 percent higher, strategic thinking 288 percent higher (Allen et al., 2016, Environmental Health Perspectives). The air in a building was doing more to shape how people think than most of what gets debated in a design review.

None of this is new or isolated. In 1984, Roger Ulrich published a study in Science showing that surgical patients with a view of trees needed less pain medication and were discharged earlier than patients who looked at a wall. Later research has repeatedly supported the finding. The World Health Organization estimates that indoor dampness accounts for about 15 percent of new childhood asthma in Europe (WHO Housing and Health Guidelines, 2018). The evidence spans decades and hundreds of studies, across air, light, noise and materials.

Drawing on my experience with AI-based analysis in marketing and retail, I built a system that evaluates this research by building type and user group. Moving into an unfamiliar field was a fairly big stretch. AI tools and the coding tools built around them made the path less rocky than expected. The data itself was extensive, and because most of it was scientific, it was very consistent and easy to work with.

Working through it changed what I thought the actual problem was. I expected to find that the research was thin, or that nobody had worked out how to put it into terms a planner could use. Neither is true. What I found instead is that the research sits in separate disciplines that rarely meet: acoustics, lighting research, indoor climate and materials science each run their own studies, their own journals and their own conferences. Almost nobody in daily practice works through all four in parallel, so the picture stays split even when each piece of it is solid.

The decisions that set a room’s air, light, noise and outlook are made in the floor plan and the building’s mechanical systems, and mostly they cost nothing extra. Whether an ICU patient’s window frames trees or a firewall is fixed early, at the same price either way. Whether a classroom’s ventilation runs at 1,000 ppm or 2,000 ppm is an equipment setting, not a budget line. These decisions get made anyway, on some basis. Rarely is it the evidence that already exists.