The term “algorithm” has a futuristic buzz, hence it seems like an intelligent thing. We have been personifying them as “algorithm design buildings”, “algorithms generate”, and “algorithms predicted”. But Data [and so algorithms] are dumb, as Judea Pearl says. Algorithms, by definition, are a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. It is a specific way in which a programmer implements functions.
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Algorithmic design
Algorithmic design is the process of using algorithms to create a product or a building. Explicit design is when a designer has an idea in his/her head and draws it. Algorithmic design is when he states the goals of a problem and lets the computer generate iterations. In an algorithmic design, a designer begins by defining the set of rules- for example, the amount of sunlight a building should receive, or the energy consumption of the building, which is optimized with the criteria (set by the designer), presenting an array of definite patterns. The algorithmic design consists of two major tasks:
1. the task of getting to the mathematical core of a problem, and then
2. the task of identifying the appropriate algorithm design techniques based on the structure of the problem. Identifying the design techniques becomes comfortable when the formulations of the problems are recognized. Algorithmic design not just provides solutions to the problems, but forms the language that lets us express the underlying questions.
Algorithms in Buildings
In this era of sustainability, people are mindful of the environment and the next generation of users. Therefore, there is a need for the buildings to be cleverly designed to later function efficiently. Using algorithms in building design enhances the efficiency of architects from just addressing the issues of structural, thermal, and electrical performance to optimize them with the highest reliability.
The application of algorithms in architecture includes the recent work of the Passion facade in Sagrada Familia by Burry. The whole facade has emerged as a parametric model built by Burry mathematically conceptualized such that every single component is inextricably linked dimensionally to its neighbors. The columns have an individually unique angle towards the center of the composition and the building.
Potential for Algorithm design in Buildings
A simple example of understanding the potential of algorithms is the functioning of traffic lights. Our first response to traffic lights would be, “Why should I wait on an empty road just that the signal shows red?” Now, with better sensors and algorithms, we can design better traffic lights that handle the traffic flow more intelligently with the data under different conditions that may vary on a minute-by-minute scale.
At a basic level, algorithms can be a powerful tool for providing exhaustive information for the design, construction, and planning of a city or a building. It can refine, reform, and even create new designs (given the rules). Algorithms can work out the layout of rooms, construct buildings and even change them according to human needs. As a whole, algorithms can be a new toolbox for architects in the information age to realize and improve their ideas.
Limitations of algorithmic design
Though computer-generated algorithms help design structurally and energy-efficient buildings, many other factors differ according to human needs at different times and in different places. This is stated by an example of Istanbul stadium by Micheal Arbib, a computational neuroscientist. After the match between Liverpool and Juventus, the hotel near the stadium (in the street) becomes the place for the enjoyment of the Liverpool fans and it bothers the hotel guests. He says that algorithms or AI won’t be able to make both the fans and the guests content, taking into account that different streets might have been closed and each one prepared to intelligently meet diverse sets of human needs.
He also asks, if the street is a major traffic artery, how does the street damp down the traffic noises. The resolution of the problem would be using noise-reducing earphones (individual) or encouraging the use of electric vehicles and public transport (political). But in both cases, the solution involves the awareness of the designer and the people and not the intelligence of algorithms. Thus, algorithms cannot design future cities. With the use of algorithms, a designer could design buildings that respond to the users of the space, rather than designing spaces that are themselves intelligent and aware of the users and surroundings.
Humans and Algorithms
As said earlier, data are dumb, and algorithms too. But humans are not. The statement holds even when the data are big and the algorithms are fancy. The intelligence of humans toward big data and machine learning leads the path to the realization of future cities and buildings. The intelligence of humans can be expressed in two ways, according to Arbib.
1. The ability of humans to interpret various domains forms the information infrastructure.
2. The potential of the public to interact with the subsystems to update their needs either through direct communication or through sensors that measure according to the currently set criteria.
Steward Brand in his book, “How buildings learn: What happens after they’re built” Steward Brand clarifies the misconceptions about machine learning in architecture. He focuses on how people adapt to the buildings they built decades ago. But he does not state buildings that change according to human needs. He addresses the fact that when people renovate a building, there is no accumulation of the history of the building. Rather, they renovate to seek their current needs.
He says that with the data collected (through algorithms) from the past, we shall be able to renovate the building better, learning the history. Above all, it is not only the transmission of data but if the analysis of the data is transferred to the next generation, we would be able to bring specific solutions to new problems concerning the context and the time at which it is built.
Hence, to make sense of the information age, we should understand the role of humans and the limits of data and algorithms. Rather than replacing designers (as many have predicted), algorithms are becoming an efficient tool for designers. The version of the future where algorithms are designers becomes a dystopian ring.
