To understand the concept of “Desire Line” or “Desire Path“, consider what the following have in common:
- Urban planners in Finland,
- Virginia Tech, and UC Berkeley,
- The stretches of New Orleans streetcars
- Broadway in New York,
These several entities all contribute to recognising and using natural, user-driven paths.
In Finland, planners study snow-covered desire routes to help with urban planning.
Urban planners enjoy a unique winter tradition in Finland’s crisp, snow-covered parks. After a fresh snowfall blankets the ground, obscuring existing pathways, they keenly observe the fresh footprints left by pedestrians. These tracks in the snow reveal natural desire lines – paths intuitively chosen by people moving through the space. The planners then use the insights. The footprints were etched in snow. They used it to guide the design of new, permanent walkways, ensuring they align perfectly with the natural flow of pedestrian traffic. This approach beautifully marries practical urban planning with the organic patterns of human movement.
Virginia Tech and UC Berkeley permitted people to stroll on the grass and only built the roadways after determining the pathways they used between the buildings. The intended trail was built using the spontaneous campus paths.
The streetcars of New Orleans illustrate historical urban planning based on preferred routes; since one of the streetcar lines that was called “Desire”, the concept “Desire Line” has been adopted.
The probably most renowned desire line in the world, Broadway in Manhattan, follows a diagonal path across Manhattan’s otherwise squarish system of avenues and streets because it was the original road that, in turn, follows an old Indian path – Wecquaesgeek. These different instances demonstrate the need to match infrastructure with human behaviour.
Desire line philosophy
As far as I have found, there is no one origin of the “Desire Line” concept; instead, the idea seems to pop up on different occasions. But, this observation of natural human behaviour sparked a revolution in design, underscoring the need to adapt to organic user preferences.
The ‘Desire line’ philosophy emphasises observation and adaptability to natural behaviour, a principle that has found applications beyond physical environments, extending into software development and artificial intelligence.
The old Greeks
Desire line, those spontaneous trails carved by repeated use, symbolises a fundamental philosophical divergence between Aristotle’s empiricism and Plato’s idealism.
Where Plato sought truth in unchanging, ideal forms, Aristotle emphasized the value of empirical observation and the tangible world.
Desire line embody the Aristotelian principle. They arise naturally from the practical decisions of individuals. This contrasts with conforming to a Platonic ideal, where the leaders should plan, and the people follow.
These paths capture the wisdom gained through lived experience. They also reflect the changeable nature of reality. These paths show how daily human actions can gently contest and reshape philosophical ideas.
Wisdom of crowds
Desire line are similar to the “wisdom of crowds” concept. They show the collective intelligence and decisions of many people. This contrasts with the decisions of a single planner or authority. The wisdom of crowds is based on a key idea. It suggests that a group’s combined choices are often better than one person’s decision.
Desire line form similarly. They result from many people making independent choices. Each person chooses the most direct or convenient route. This creates a physical example of crowd wisdom. The combined choices of individuals lead to a path. This path is often more functional and practical than initially planned routes. Both concepts underscore the power of collective decision-making, revealing how decentralized choices can lead to practical, efficient solutions.
User-Centred Design in Software
User-centred design (UCD) plays a pivotal role in modern software development. It’s all about acknowledging that users often find their own, perhaps unexpected, paths to achieving their goals within a software application. E.g. Desire paths!
Designers use heatmaps that show how the users have navigated through the application, and the combined effort of different users form “desire lines”.
This phenomenon can be likened to the unplanned paths people create when walking through a park. Software developers keenly observe these user behaviours and pathways to gain valuable insights into how their software is used in the real world.
Agile Methodology
The Agile development methodology mirrors the ‘Desire line’ concept. Like these user-made paths, Agile supports a flexible approach to software development. It advocates for iterative development. This means software evolves step-by-step.
User feedback continuously guides this process. This iterative approach is similar to natural pathways forming in software. Agile is about making a small effort and testing it against reality as quickly as possible.
Small early failures are welcome since they reduce the overall risk of failure. It lets the most convenient and desired paths emerge within the application. This ensures the software meets users’ needs and expectations perfectly.
In the world of software development, user interactions and feedback are invaluable. They serve as the compass, directing developers to enhance and refine popular features while reevaluating those less used.
This continuous process mirrors the “Desire line” evolution in urban planning. As well-worn paths are paved and improved for more straightforward navigation, software features are polished and optimised to create a seamless user experience.
Data-Driven Design Decisions
Data is the cornerstone of modern software development, much like it is for urban planners. Like skilled architects, software developers rely on data analytics to gain insights into user behaviour.
This data-driven approach empowers developers to make informed decisions regarding design and functionality. Like a city planner would use traffic data to optimise road networks, software developers leverage user data to enhance the software’s usability, efficiency, and overall user experience.
Neural Networks and Deep Learning
In reality, a lot of artificial intelligence or machine learning is a kind of ‘Desire line’ philosophy that appears in a digital context. This is especially true in neural networks and deep learning. These AI systems adapt by identifying patterns in large datasets.
This process is similar to how people create paths in a physical environment. Essentially, it’s about paving efficient and natural paths for the AI. Doing so optimises the AI’s functionality.
This learning principle applies in various areas, like image recognition, language processing, and autonomous decision-making. The revolution we are currently experiencing within Generative AI, such as ChatGPT, etc., is entirely built on this principle. Using an enormous amount of text material, the training algorithm creates vectors to predict the best next word based on the previous text. This is, for all practical purposes, the desired lines in the total text mass used for the training.
All human learning
In a way, all human learning can be likened to finding the desired path in the textbooks and learning material we use to learn. We learn through repetition. Learning complex subjects in school was like exploring uncharted territory. Just as people create well-worn trails through a park for convenience, we followed familiar routes to understanding.
For instance, when learning multiplication tables or mathematical theorems, we repeated reading, note-taking, and problem-solving until we knew them thoroughly. These intellectual “desire lines” represent our efficient route to mastering new subjects, shaped by our curiosity and determination.
Conclusion
The ‘Desire line’ philosophy, originating from natural pathways, teaches the importance of adapting to natural patterns. In software development and artificial intelligence, this translates to a user-centric and data-driven approach. From the early observations of a campus landscape to the complex algorithms of modern AI, this philosophy continues to guide innovative design and development strategies.
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