Архитекторы научились измерять человеческий опыт с помощью нейробиологии и искусственного интеллекта

We measure almost everything in buildings—except how people experience them. Buildings are designed for people, yet we often describe human experience through abstractions, relying largely on intuition. The lobby will feel welcoming, visitors will instinctively know where to go, and the space will encourage people to gather and connect. These are well-intentioned aspirations, but they are often difficult to validate or predict with confidence. At the same time, building and architectural sciences have developed a sophisticated and reliable set of performance metrics that tell us how a building will function at a systems level. From carbon emissions and energy consumption to thermal comfort and daylight performance, we can describe the performance of a building in remarkable detail. Yet the experience of the people for whom we design remains comparatively difficult to measure. Architecture has built a culture of performance measurement, but it has largely excluded its most important variable: human experience. The reason for this is clear: building sensors, simulation tools, and performance modelling platforms are readily available and deeply integrated into architectural practice. Human experience, by contrast, that is, the way people think, feel, and behave, has traditionally been far more difficult to quantify and is often treated as architecture’s dark matter: universally acknowledged to exist, profoundly influential, yet difficult to observe directly. Yet the tools and methods required to understand human experience are just as real as those used to measure energy consumption, thermal comfort, or daylight performance. Emerging advances in behavioural science, neuroscience, spatial analytics, and artificial intelligence present an opportunity to bring human experience into the same evidence-based framework that already guides so many aspects of design. In doing so, they allow us to move beyond intuition and begin speaking about the relationship between people and the built environment in measurable, testable, and ultimately more actionable terms. Human experience emerges from the interaction between a designed environment and the internal state of the person experiencing it. While these internal states can be described in many ways, one of the most useful frameworks is to consider how environments influence what people think, feel, and do. These dimensions are deeply interconnected, each shaping and reinforcing the others. A cognitively demanding environment, such as an airport or hospital, may be experienced as confusing or overwhelming, which can lead to feelings of stress or frustration and ultimately influence behaviour, causing users to hesitate, seek assistance, or leave altogether. Conversely, an environment that is easy to understand can foster confidence, calm, and purposeful action. Importantly, this framework aligns closely with how architects already describe design intent. We routinely make claims that a space will feel welcoming or inspiring, help people understand where they are and where they need to go, or encourage them to gather, explore, and connect. These are fundamentally statements about emotion, cognition, and behaviour. The difference is that emerging research methods now allow these aspirations to be measured, tested, and evaluated as performance outcomes rather than assumptions. The idea of measuring and understanding human experience has a long history. As early as the first century BCE, Vitruvius argued that architecture should balance firmitas, utilitas, and venustas (strength, function, and beauty), recognizing that the success of a building depends not only on its physical performance, but also on how it is perceived and experienced by people. Nearly two millennia later, the emergence of experimental psychology in the mid-19th century marked the first systematic effort to quantify human perception. Gustav Fechner’s pioneering work in psychophysics sought to transform concepts such as brightness, loudness, and intensity from subjective sensations into measurable phenomena, establishing a scientific foundation for the study of human experience. Today’s advances in neuroscience, behavioural science, and artificial intelligence extend this tradition, allowing designers to measure aspects of emotion, cognition, and behavior within the built environment itself. Our approach couples a range of research techniques intended to quantify three fundamental dimensions of human experience: how the built environment influences how people behave, think, and feel. Understanding Behaviour Space Syntax and pedestrian flow simulation help us understand how people move through space. These methods reveal how spatial configuration influences route choice, visibility, decision-making, congestion, and patterns of use, allowing designers to predict movement behaviour before a project is built. Understanding Cognition EntroAQ, a proprietary AI model, evaluates characteristics such as visual complexity, legibility, and hierarchy to predict how people are likely to perceive and interpret an environment. These insights can be validated through eye-tracking, which measures visual attention and gaze behaviour, and electroencephalography (EEG), a technique that measures brainwave activity. Together, these methods provide direct evidence of what people notice, how they process information, and the cognitive effort required to navigate and understand a space. Understanding Emotion Electrodermal activity (EDA), which measures physiological arousal through changes in skin conductance, helps identify moments of stress, engagement, and emotional activation. Combined with EEG and EntroAQ, these tools provide a deeper understanding of how environments influence comfort, confidence, and emotional response. Together, these methods allow designers to move beyond intuition alone, transforming experience from something that is merely described into something that can be measured, modelled, and improved. Crucially, these technologies can be applied throughout the design process. At the outset, they can be used to establish baseline conditions and understand how an existing environment influences movement, attention, stress, and decision-making. Later, as design solutions are developed, they can help validate decisions, demonstrate performance improvements, and refine interventions before implementation. The methods are also flexible, drawing from a wide range of data formats, including videos, photographs, and floor plans of existing environments, as well as renderings, walkthroughs, and floor plans of spaces that have yet to be built. This approach shifts the conversation around architectural experience in several important ways. First, it moves design from authorship toward accountability. Design becomes more than an expressive act; it becomes measurable, testable, and defensible. Second, it expands the definition of performance, encouraging us to consider how buildings perform from a human perspective, not only from a systems or environmental perspective. Third, it augments intuition with evidence. The objective is not to replace design judgment, but to sharpen it with meaningful data, allowing designers to better understand, test, and improve the experiences their work is intended to create. The consequences of design decisions are often hidden in plain sight. They appear as hesitation at a decision point, a missed appointment, a delayed connection, or a staff member interrupted to provide directions. The research methods described above allow these experiences to be understood in measurable terms. By quantifying how environments influence behaviour, cognition, and emotion, we can move beyond intuition and evaluate human experience with the same rigour traditionally applied to building performance. In doing so, experience becomes something that can be analysed, tested, and improved rather than simply observed after the fact. Vedran Dzebic is the research director at Entro, an experiential design firm, where he applies cognitive neuroscience to understand how people perceive, navigate, and emotionally engage with the built environment. His work explores the intersection of behavioural science and environmental design, using tools like AI, machine learning, eye-tracking, and user simulation to inform more intuitive, inclusive, and human-centred transit systems. His expertise spans spatial cognition, visual complexity, biophilic design, and accessible communication. He holds a PhD in Cognitive Neuroscience and has presented internationally at AIA, Academy of Neuroscience for Architecture (ANFA), Environmental Design Research Association (EDRA), the Biennial Conference on Environmental Psychology, and Intelligent Buildings International.