The notion of ‘genius loci’ refers to the spirit of a place or the idea that no two sites are equal even if they share adjacency. That every site has its own unique fingerprint which cannot be duplicated any place else is the main driving principle behind the theory of genius loci. The idea of genius loci originated in Roman mythology and alluded to the protective spirit of a place. This phenomenon mirrors Asian architecture where territorial spirits are acknowledged in outdoor spirit houses and in indoor shrines.

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Throughout the history of architecture and the history of the incorporation of the idea of a genius loci within the thought processes of architecture and design, many students, educators, and practitioners only considered the notion of genius loci in qualitative terms until recent advancements in computer and data science offered a new empirical lens through which the concept of genius loci can be viewed, understood, and utilized.

Before a new understanding led to a quantitative appreciation of the essence of place, design professionals would simply visit a site to savor its qualitative spirit during initial site visits or take stock of their feelings and emotions throughout their analysis of the site and harness that as inspiration or the main driving force behind the crafting of a built artifact.

Advancement in architectural thinking, computer technology and data science particularly, created opportunities for a quantitative understanding of the principle behind the notion of the spirit of a place. Since no two places are alike, different sites will not generate the same scientific data, irrespective of their proximity. The principle of genius loci can now be quantified by studying and observing various data sets of a particular site, mapping and documenting the results to create a unique data fingerprint that cannot be duplicated any place else. Site phenomena such as site densities at various times, site striations, pixels, chiaroscuro, climatic data and more, can be harvested over time with particular attention paid to observed distinctiveness, common trends, and repetitive patterns.

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Generative design and Artificial Intelligence (AI) create unique opportunities to collate data harvested from the site, extract distinctive attributes, transform that data into 3-dimensional form; and use that form as an initial concept model for further analysis and translation of what will ultimately become the final built outcome after exhaustively analyzing serial iterations of an initial concept model. Generative design, like artificial intelligence, designs components by inputting data which grants opportunity for an algorithm to suggest optimized solutions that may or may not meet the needs and expectations of the designer. Through recalibrating parameters, other solutions can be obtained without straying too far away from the unique characteristics of the scientific data extracted from the site.

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By focusing on microclimate conditions of a site, data derived from mapping climatic conditions at various times can be used to obtain 3-dimensional forms that would establish the basis for further design exploration.

Context in architecture is often misunderstood to mean adjacent buildings only. Yet, context in architecture should be at the discretion of the designer to make the determination regarding the expanse of area around the site that would be inclusive in their contextual analysis. Attempts at achieving a more effective design solution are elevated with the right combination of site data mining, collation, analysis, generation of an initial form and using it as a basis for serial translations until an optimized solution is found bearing in mind that a larger context would yield more intriguing phenomena.

The lines between generative design, artificial intelligence and sustainable design can be blurred when all these tools and methodologies are implemented at their appropriate temperament. It cannot be overemphasized that artificial intelligence is not an existential threat to architecture or architects, instead it is one of many tools that architects can use in implementing optimized design solutions. Better analysis and collation of scientific information obtained from the site, paired with stronger generative design tools and artificially intelligent models would lead to buildings that are energy efficient and have a low carbon footprint where the built artefact becomes a palimpsest of the rich layers that constitutes its quantitative genius loci, where the building flourishes as a true native of the site.

CONCEPT MODEL DESIGNED BY RUDI SOMUAH ARCHITECT MNAL MAA