LAYER 1.1 Strategies
The impact of AI on ideation processes affects architecture on multiple levels. Consequently, architects of today must address contemporary complexities with new tools and methods to identify possible requirements, contexts, obstacles and potentials for a digital and contemporary architecture. This research has been an exploration with unforeseen outcomes, resulting in an exciting expedition into unknown territory. Hence, this work including its varying methods, was adjusted and modified on the go. But to face today's realities, it turns things around and sticks to the industry-mentality first by “doing it like we always do” tackling this research with a typical Site Analysis. To visually explain how this work is further organized the illustration (Fig. 11) below should support understanding its structure. The following mixed-methods approach was accomplished in the period of four months, from January to May 2025 and unfolds on five different levels.
Figure 11: Research strategies
LAYER 1.2 Historical Character
Inventions have always required people to adapt and rebalance their relationship to a new kind of technology. Today, rapidly evolving, global digital economies are transforming individual lifestyles and societies faster and more extensively than ever. They redefine how we produce, commute, plan, and communicate. In the past, innovations primarily affected local environments and spread slowly over time, taking years to unfold their impact as people shared knowledge as they moved. Today, however, new inventions manage to reach 1 million users worldwide within five days.(14) In addition to major paradigm shifts, the field of architecture currently faces challenges, such as advancing urbanization, climate change, and labor shortages, among other complex matters. Sustainability issues are taking up significant parts of daily work and steadily rising bureaucracy slows down processes, effectively reducing conceptual “creative spaces”. They confront the industry and all its individuals to come up with practical solutions from a standing start. However, known for being a slow adopter, the building industry traditionally lags behind necessary transformations connected to emerging challenges.(15)
Moreover, digital technologies fundamentally change how architects think, work, construct, and manage resources. Step into an architecture office and you will likely find everyone sitting behind a screen, as most of the tasks accomplished by today's architects include using a computer. Adjusting a wall slightly is promised to be done easier, faster, and more efficiently digitally than being drawn by hand. From start to finish and beyond, architects spend most of their day interacting with computers to communicate, execute data-driven workflows, or develop digital design approaches. The digitalization of architecture compared to its history is still in its infancy, but it is transforming the field at remarkable speed.(16)
Before the broad implementation of computers, most architects' work was done manually, characterized by hands-on methods and physical model building. The first drawings to visualize three-dimensional buildings date as far back as 4.000 years ago in Mesopotamia.(17) Architects (or however they called themselves at the time) typically used two-dimensional methods to communicate three-dimensional concepts. Coal, pencils, or ink were used to visualize first ideas on clay panels or papyrus, later than on paper, assisted by rulers and T-squares (Fig. 05). Usually, errors or mistakes were hardly excusable and needed careful treatment and skill to avoid destroying the hours and hours of work spent, often resulting in higher project costs or delays. There was a clear distinction between the roles of architects, engineers, and builders with an emphasis on craftsmanship.
Figure 05: Offices before digital drawing tools
To clarify what has brought the current architectural reality into consideration, this analysis of the site to be investigated examines relevant historical stepping stones. Researched from an architect’s perspective, the first example selected roughly traces the evolution of information back to the year 1440.(19) The following divisions do not represent rigid boundaries of evolutionary steps as every development builds on previously achieved knowledge, creating interlinked relations between advancements. In addition, all of the “architectural milestones” are connected to inventions and technological advances in information technologies, which have facilitated the architectural practice’s digitalization. These relations are only touched upon due to the scope of this work.
With the invention of the printing press, Johannes Gutenberg (~1400-1468) sparked the printing revolution by automating the production of texts at low costs, spreading knowledge and empowering common people. This technological advancement put them into the position of knowing their rights and liberties to no longer be governed by way of oppression.(20) The picture of the world started getting cracks more and more during the Renaissance.(21) Efforts to overcome established ideas, rules and traditions in different fields like politics, art, science or architecture resulted in profound social change confronting people with a major shift of paradigm. Paying attention to the term “Re-naissance” itself, it indicates that much of the developments were based on formerly achieved knowledge.(22)
Shifting realities during the Industrial Revolution (~1760-1840) introduced machines like the steam engine, railroads and telegraphs, effectively lowering transport costs and enabling a faster flow of information. Standardization and global trade networks made the international economy grow. The following period, known as the “Machine Age” (~1880-1945) increased global income inequality, putting industrialized countries in a position of power. In 1854, English mathematician and philosopher George Boole (1815-1864) published a framework for Boolean algebra, using binary values (0 and 1) to establish a system to represent logical relationships mathematically.(24) His work laid the foundation for how modern computers handle information. Some years later, in 1936 and building on the research from Boole, Alan Turing (1912-1954) invented the A-machine (Automation machine), also known as the Universal Turing machine, which was the theoretical model for today's computers using an algorithm, representing the prototype for all modern computation.(25) It processes one information entity and transforms it into another by implementing a mathematical function, effectively representing computation. In 1950, Turing proposed the Turing Test to assess machine intelligence. A method to evaluate a machine’s capability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.(26) Rather than creating machines that can really think, it was about mimicking human behaviour in an undistinguishable way. Furthermore, industrial standardization and modularity required architecture to adapt to new standards and methods and to incorporate new materials in construction and design (Fig. 06-07). The combination of simplifying and streamlining architectural processes and the availability of industrialized materials and knowledge offered new principles implemented in the creative discourse. Overall, the contemporary and rigorous follow-the-grid mentality and rational mindset ”Less is more” from German-American architect Ludwig Mies van der Rohe (1886-1969) or the Bauhaus movement (namely Walter Gropius and Le Corbusier (Fig. 06)) led to quasi-gamification of a LEGO-like conception of architecture (Fig. 07).
Figure 06: The Modulor by Le Corbusier - Attempts of standardization
Figure 07: Moshe Safdi (1938), Habitat ‘67 - Standardized units
After World War II, the global backlash was overcome by technological advancements such as the availability of new building materials and political frameworks like the Bretton Woods System(28), establishing global monetary systems and supply chains. Globalization gained momentum as digital information technologies started to be widely implemented. The invention of the digital computer, followed by the implementation of the internet's predecessor in the 1960s, accelerated global communication, effectively “shrinking” global distances. As computing costs decreased, technological advancements sparked, such as the computer program PRONTO(29) released in 1959 by Patrick Hanratty. A prototype of Computer Aided Design (CAD) software automating engineering processes. CAD tools allow for rigorous geometry control impacting the whole design process, aiming to enhance feasibility. Allowing for human-machine interaction, the Sketchpad (1962) was invented (Fig. 08). With the architectural mentality changing, American architect Robert Venturi (1925-2018) stated in 1966 “Less is a bore” showcasing shifting paradigms. Parametric design, only defined by algorithms and highly adjustable through parameter changes, enabled the creation of new spatial constructs and processes previously impossible.
“The goal is to create a system that would be flexible enough to encourage the engineer to easily consider a variety of designs. And the cost of making design changes ought to be as close to zero as possible.“
Samuel Geisberg, Founder of the Parametric Technology Corporation (PTC)
The first, innovative steps were predominantly done by engineers and other sectors, with architects later extending software solutions in their favor with the help of Computer Aided Architectural Design (CAAD). Softwares namingly AutoCAD (1982, later Revit Autodesk), ArchiCAD (1987), Rhino 3D (2001)(Fig. 09), including its extension “Grasshopper Plugin” (2003) broadened the spectrum of digital tools in architectural communication. Famous architect Zaha Hadid (1950-2016) embodied the architectural style of parametricism in her work (Fig. 10). The advancing change led to vivid discussions about the soul of architecture with all its traditions, methods, and tasks. Applications that aim to make the architecture industry more efficient and potential risks more calculable were already widely implemented. Referring back to changing architectural mentalities, the Danish architect Bjarke Ingels continued in 1999 with his stance “Yes is more”.
Figure 08: Sketchpad developed by Ivan E. Sutherland
Figure 09: McNeels’ Rhino 3D - User Interface (own illustration)
Figure 10: Main building of the Heydar Aliyev Center in Baku, Azerbaijan (2013)by Zaha Hadid Architects
This era known as Information Age (starting ~1950s), is characterized by information technologies, digital platforms, Big Data and cloud services. Infiltrating our lives by establishing networks through the Internet of Things (IoT) as we evolve into digital humans, once more needing to leave behind traditions and ways of doing things. Implemented in the systems in which we live and work, rooted in the structures surrounding us, each monitor, each smartphone conceptually turns into a digital portal, with some spending most of their day in virtuality than in reality. The amount of data continues to reach new heights forming a vast digital mass that co-exists in our presence. This phase of digitizing realities is forcing people to adapt to new circumstances daily. To find a possible response to constantly increasing requirements in the world of multi-layered planning, the process of Building Information Modeling gets more and more established. The digital support of building processes solves structuring intricate operations and streamlines the understanding of new projects. And all of that is possible in real time. Dutch architect Rem Koolhaas (1944) built further on the architectural theme by declaring “More is more” in 2001 pointing to the abundance of possibilities at the time given. The complexity of new realities lead to a major change of the often romanticised role of the architect (whether it is the individual or the team/office) away from the virtuous craftsman of space or creative mastermind that draws stunning ideas on paper and brings them (with the help of others) into reality. Overall, technological developments compete with traditional practices offering architects unlimited opportunities to discover new processes in a constant flux of change. CAAD tools and BIM processes transfer traditional practices into the digital, fundamentally changing big parts of what it means to work as an architect. They enable digital design methods, seamless collaboration, and implement data-driven approaches at all scales of projects to potentially create more innovative, more efficient, and sustainable building solutions than ever before. Smart city frameworks scale innovations, using the IoT to optimize building performance within larger urban networks, connecting the physical and digital worlds. The relationship of spaces now emphasizes fluid boundaries rather than rigid segregation. The clear distinction between the physical and digital realm vanishes, erasing individuality, with architects finding themselves in the middle of a significant (r-)evolution. This transition of the architectural field into the virtual, entails an inevitable impact on core values of architecture by fundamentally changing its practice. Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR) are entering the stage, extending the three-dimensional world, making traditional realities disappear. As digital technologies evolve, the notion of reality consequently needs a recalibration.
In November 2022, ChatGPT entered the global stage, enabling the broad and tangible accessibility of AI with the help of Large Language Models (LLMs). Again, a technological advancement disrupts everyday certainties. So far, human intervention has been core to initiating machine operations (input command), with individuals or organizations bearing responsibility for the outcomes of these actions. Human supervision has traditionally guided this process to ensure that machines perform their tasks correctly. Humanity has now entered a stage of evolution in which machines effortlessly can do this on their own based on provided information (input data), requiring no human being in the loop. In today's context, it is crucial to differentiate between traditional algorithms and AI. Algorithms, represent a set of rules or instructions for solving problems, have long been used to automate tasks but still require human input and supervision. In contrast, AI systems, particularly those employing Machine Learning (ML), can autonomously make decisions and learn from data, potentially reducing the demand for constant human intervention. However, the ethical and legal responsibility for the actions and outcomes of both algorithms and AI systems remains a critical area of debate and regulation.
Across all industries, from finance to healthcare—AI impact is undeniable. The broadly accessibility of AI technologies for everyone is expected to be among the most disruptive technologies during the next few years. With the ever-advancing digitization and an increase in both hours spent online and the number of internet users, the expected influence of AI-technologies on our surroundings is tremendous and consequently resulting in a new era. On a daily basis, new AI featured applications are getting launched, making it hard to stay up to date forcing some people to feel left behind or eventually resign. The strict boundaries of expertise from the last centuries are getting blurred by the fact that much of what we are doing or dealing with is intangible.
In December 2024, Google launched its new quantum computing chip “Willow” which is a big step towards industrial quantum computing entering new heights of computational power. Merging AI and quantum computing and showing promising results, the emerging field of “Quantum Intelligence” might be worth keeping an eye on. Having this development in our minds, hardware is soon no longer a big issue for most of our everyday tasks, but the immense amount of electrical energy is.
On the downside, advancing globalization poses major questions to the human species. Within the next generation the UN is expecting humanity to grow up to 10.3 billion by 2080, as it has to tackle major challenges facing geo-political instabilities (e.g. democratic concerns, the atomic bomb, etc.), global crises (e.g. wars, poverty, food shortages, etc.) and climate change (e.g. global warming, loss of biodiversity, pollution, etc.). Global trade agreements are collapsing, financial crises, supply chain disruptions or worldwide pandemics challenge us to relate to global circumstances never experienced before. Well-established concepts such as laws and rules are falling short or adapt to slow and structures like borders or business premises simply get overruled. Caused by the effect of global connectivity, this state of “polycrisis” is impacting us all.(53) Meanwhile, all of that is well documented by the news and shared on social media platforms, getting liked, commented, and shared by millions exposing everybody to everything everywhere, competing for our attention. The rise of the “Attention Industry" directly competing with monetary systems, led to reality where “Attention Companies” and content creators strive to capture and retain our attention, possibly being monetized through advertising, data collection, and user engagement. Whoever gets the most attention entails the power to guide digital streams into wanted directions. In architecture to its current state, humanity has created a “Junkspace” as current generations have built more than all previous in common. It is a “global mess”.
Expectations were high as the implementation of the internet promised to provide access to information for everyone, connect every single person globally and potentially narrow the gap between rich and poor. The vision of a digital, decentralized and progressive space of freedom. In retrospect, the internet does provide information to everyone by democratizing knowledge, but global inequality is still an issue, if not more so than ever. Online accessibility makes it almost impossible to cope with this constant stream of information, resulting in an overwhelming flood in which it is hard not to get lost. It is a great noise. The resulting feeling of powerlessness or disorientation is pointing to the rising complexity of the world, often drawing apocalyptical images of the future. Some re-orientate themselves towards traditional methods (e.g. “Tradwives” or the rise of conservatives, Classicism) trying to find a hold in this rapidly changing reality.
The rapid flow of information renewed the rise of false information making it increasingly challenging to distinguish between what seems to be right or wrong. Fundamental questions of what to believe in arise, as anything to be seen on a digital screen could be artificial. Lifting our heads in public makes us realize that an endless stream of information enters our lives through smartphones, TV screens, or advertisements exposing us to everything, creating an information overload we need to cope with whether we like it or not. It vanishes the distinction between “true” and “false” and, from an architects’ point of view, “public” and “private” as personal lives at home and outside the house become visible and accessible through third-party participation. This evolving transparency happens sometimes with and often without permission.
“After three thousand years of explosion, by means of fragmentary and mechanical technologies, the Western world is imploding. During the mechanical ages we had extended our bodies in space. Today, after more than a century of electric technology, we have extended our central nervous system itself in a global embrace, abolishing both space and time as far as our planet is concerned. Rapidly, we approach the final phase of the extensions of man the technological simulation of consciousness, when the creative process of knowing will be collectively and corporately extended to the whole of human society, much as we have already extended our senses and our nerves by the various media. Whether the extension of consciousness, so long sought by advertisers for specific products, will be ‘a good thing’ is a question that admits of a wide solution. There is little possibility of answering such questions about the extensions of man without considering all of them together. Any extension, whether of skin, hand, or foot, affects the whole psychic and social complex.”
Marshall McLuhan, Understanding Media: The Extensions of Man (Gingko Press, 1964).
In the final analysis of outlined circumstances and with today’s world changing at a speed that structures, systems and cultures which were set up over the last century are unable to keep track of. Doomed to face the current issues and develop new strategies and approaches to tackle future challenges, this work is specifically interested in how AI can enhance the act of coming up with innovative ideas through the lens of an architect. The acquired insights justify the focus of this work on the early stages of architectural processes, where the creative spaces are the biggest, but well-founded knowledge about projects first needs to be required. Another beautiful side of ideation processes is that when ideateing, real-life problems and everyday constraints are absent, opening up a gigantic conceptual solution space wanting to be explored. From Gutenberg's printing press and the steam engine to computers connected by the World Wide Web and Artificial Intelligence—disruptive technologies always lead to economic, political and social changes, shifting certainties and as a consequence forced people to rebalance their relation to reality. AI affects core values in architecture, yet, following the established insights, it is easy to see, that much of what happens digitally would lack any architectural meaning, excluding the physical world completely, but:
“What is architecture, when computers can do what we think architecture is?”
Ludger Hovestadt, CAAD ETH
Subsequently, what does it mean to be an architect today? With artificial intelligent tools and augmented workflows available to generate fantastic architectural concepts, why can not everybody be an architect then? What is architectural reality, when talking about systems with more than three dimensions? And what does that mean for future architects? Moreover, how to handle all of that junk? How to figure out what information is right or wrong and how to proceed with the one found? Who owns it and who is setting up the rules? Immediately it gets intimidating with issues, skills and competences involved, deeply rooted in one's personality and privacy.
LAYER 1.3 Current Character
Supporting the historical site analysis with current research data, this section highlights key studies aiming to draw a general picture of how AI technologies are currently utilized across creative industries and how they potentially benefit ideation processes as we speak. The use of AI in architectural design has the potential to revolutionize the field by enhancing creativity, efficiency, and innovation. Overall, approaches can be categorized into stimuli-based or interaction-based practices. Starting this research by searching for keywords like “AI” and “architectural ideation” or subsequent synonyms it was noticeable that the number of entries covering the topic in other industries (e.g. product design or general design tasks), were often of a higher number than within the architectural context.
Beginning the analysis with a review aiming to understand the benefits of AI as an external source of stimulation (e.g. pictures, videos, text, ect) or assisting creative endeavours, assuming that this could provide major benefits for future designers. The work considers “human-in-the-loop” approaches, where AI is not substituting the creative rather boosting their skill sets and effectiveness. Taking this approach further into consideration, most of the reviewed research was focusing on augmenting creatives rather than replacing them. Additionally, and in relation to others the study suggests a clear ethical framework, what AI should and should not do. Further studies address the impact of assistive AI-based stimuli on humans during ideation, showing an increasing effectiveness when solving creative design tasks. In common, they examine participants' possibilities to engage with AI-based inspiration potentially uplifting their creative approaches. With one study covering a representative sample of 55 participants, the other one lacks statistical power due to a small sample size of only seven participants. Both studies are covering the challenge of solving a general design problem but miss out the specific characteristics required in architecture. Other works include the architectural context focusing on already built projects from a broader point of view, analyzing how AI has been put to use by architecture offices to potentially uplift their overall design, but specifically miss the potential of early-stage AI implication during the ideation phase. Questioning traditional considerations about the domain of “being innovative” only to humans, companies start to research the possibilities of using AI applications to support or replace this labour intensive task. Analyzing big companies (Airbnb & Netflix), other works investigating how they try to foster innovative idea creation, potentially establishing new design workflows. It researches the questions of how AI is likely to change the principles of design and innovation and which decisions are going to be automated, arguing that the influence of AI will be likely to reinforce design principles of being people-centered, abductive, and iterative, while removing limitations in scale and scope. Creatives want collaborative AI tools to maintain a certain freedom, gain trust in the system and offer them different variations to explore possibilities in the solution space of a given task. Reviewing the topic from a computational point of view, studies propose a new, collaborative human-machine workflow, based on the technical challenges of evaluating good or bad results with AI. They highlight difficulties in understanding a purely generated design (flatness) and the challenge of introducing prior expert knowledge (e.g. rules) to machines, especially in content generation.
Other interesting attempts explore the possibility of implementing AI not just as a personal assistant but as a collaborative partner supporting a design team, showing the various possibilities that this research could be applied to. Employing ChatGPT 4.0 as an independent player to compete against 5th year engineering students in a Hackathon, it proves that AI outputs are competitive. Even if vague and ambiguous descriptions often lead to errors with continuity and relevance in responses due to forgetting previous information. Recommendations to leverage LLMs in generating a broader spectrum of concepts during ideation with human guided oversight, guiding into the desired direction were proposed. Analyzing AI in the role of an assistive partner it was easy to see that until today, AI is unable to perform tasks that distinguish between good or bad designs, make adequate choices, communicate findings to third parties or transfer concepts into other contexts which a human can easily do.
Diving into the field of Generative AI (GenAI), recent findings show that the use of generative AI tools speeds up idea generation and broadens creative possibilities in architectural design processes, reshaping traditional workflows. Researching the effectiveness of generative AI outputs (visuals from DALL-E and Midjourney) on 40 first-year architecture students, researchers found that AI-generated stimuli might supplement digital image-based sources like Pinterest or Instagram. They highlight the rapid development of a richer design vocabulary, consequently resulting in the importance of prompt-crafting, to clearly articulate ideas or concepts given to AI. GenAI applications found on the market were further taken into closer consideration and collaborative use cases augmenting designers’ capabilities while maintaining human decision making was analyzed. Stating that internalising and externalising expert knowledge and iterating variations and selection might be the core for future “augmented designers” while AI at its current state cannot fully replace the human designer. Several generative AI approaches exploring deep learning to generate floor plans have been successfully accomplished. Explorations like ArchiGAN apply Generative Adversarial Networks (GANs) to generate new floor plans among others. Recognized architects like Refik Anadol and Daniel Blojan as well as architecture students utilize GANs in their work to showcase some use cases of generative AI. Following this further, offices like Coop Himmelb(l)au build their own deep learning model “Deep Himmelblau” based on earlier projects. Comparing approaches researching the application of GenAI-tools (text-to-text, text-to-image, image-to-image generators and GANs) during conceptual design, emphasizing the requirement for a balanced approach that combines human expertise with AI capabilities.
LAYER 1.4 Local Character
A preliminary analysis of approximately 200 master's projects in architecture realized at NTNU Trondheim over the past six years uncovered only three works (including this one) specifically exploring the topic of AI within the field. This investigation, while informal and lacking in methodological rigor, highlights a significant local gap in existing research. The limited number of projects suggests a significant demand for increased attention to how AI technologies are influencing architectural design, planning, and methodology. As AI continues to rapidly evolve, understanding its implications on architecture could lead to innovative practices and solutions, making it crucial for future studies.
LAYER 1.5 Focus
AI is fundamentally transforming ideation processes by influencing human and architectural creativity. At the same time, immense challenges are waiting to be answered, forcing creatives to come up with innovative methods and new tools to tackle the uncertain future. With AI able to conduct enormous amounts of information at an early stage, it provides the possibility of decision-making and problem-solving in a way that was not possible before. As AI technologies evolve, the first wave of deployment and exploitation mainly focuses on everyday tasks or applications, changing known models and concepts by introducing AI much in a way happening with the digital before. As a consequence, first intentions are only scraping on the surface of what is possible. Even though the early-stage phase is addressed, current research does not adequately cover the very first ideas and concepts. In general, the focus in current research is on how AI can push individually selected concepts rather than understanding and developing the initial functional and conceptual frameworks that professionals create in the earliest stages of design. Reviewed attempts tend to be too close to the matter by aiming to take the specific effects of one or multiple AI tools into consideration. Data-driven algorithms and machine learning techniques were often applied when project related data was already collected and structured in a way to be manageable with AI. So far, most of the research has been done focusing on later stages in creative processes, technical issues or covering other industries than architecture. To acquire subsequent knowledge, this work attempts to add new insights to the current conversation around the general influence of AI in ideation processes.
Moreover, with AI supported tools changing the way creatives develop ideas as of today, the impact of the overall development on the field of architecture remains unaddressed. The ability to rapidly analyze vast amounts of data brings AI to the core of early-stage design processes and increases its impact especially where former expert knowledge and experiences majorly influence the quality of the results. Although rigorous approaches to standardize architectural experiences (e.g. floor plan datasets), the broad knowledge about art, engineering, history, and even psychology plays a major role in architectural offices making them knowledge-based organizations, heavily relying on their individuals. As analyzed, multiple studies show that AI-assisted creatives are able to automate big parts of the idea generation tasks resulting in a new role of expertise, such as problem finding or evaluating good and bad outputs becoming core capabilities for designers. It has the power to generally increase the effectiveness of established approaches, similar to forcing us to rethink creative processes. In general, “creativity, and its derivative, innovation, are the key factors of wealth creation in the digital economy, and of meaning creation in the digital culture.” Unfortunately and in addition to the slow adoption of technologies in architecture, professionals tend to have lower competences in AI, which is why other disciplines are adopting new technologies faster, potentially inventing innovative solutions earlier, putting architects in the position of further losing impact on the built environment.
Considering these facts, there is a desperate need to better understand how AI affects the creative solution space in architecture. What happens, if architects suddenly have the power to analyze vast datasets already at the start of design processes to gain valuable insights and therefore increase the overall project outcome? How is hyperconnectivity affecting capabilities of being creative and therefore inventing? How might a LLM effectively support creative architectural explorations? As a consequence, “questions on the nature of architecture and AI are gaining enormous momentum, as the public interest in the methodology is steadily growing”. Founded in the laid out reasons, this work aims to better understand how architectural creativity can be supported by AI, additionally providing data to fill the scarcity of information during AI supported ideation processes. To research what future architects should be aware of, this work is guided by the following question:
How could architects successfully utilize the power of AI during ideation to fertilize human creativity and foster architectural projects of higher meaning?
To clarify upfront, this work slightly touches the “easy” problems of creativity (Fig. 11) as it is interested in how architects could use AI to support and enrich their work rather than understanding what architectural creativity is. To distinguish what might be the difference between architects or non-architects having a creative idea is not part of the scope.
Figure 11: Hierarchy of conscious-problems by Max Tegmark in Life 3.0
EXTENSION: Persona
Talking with the people on the third level, two communication channels were established to ensure effective information flow in both directions during the process of this research. From the very beginning, the experiment of a digital persona representing the soul of this work was established to regularly write posts on Instagram and Linkedin based on the development of this text. Taking on the general knowledge that architects have a preference for informing themselves in a visual manner, one account aims to address architects on Instagram, whereas the other one aims to reach for field-related professionals on Linkedin. Continuously drawing parallels with the theories of communication, the aim of this approach is to push resonance as extensively as possible, with regular posts on social media. By doing so, a more fulfilling dialogue with the field of creative processes in architecture was anticipated and it was possible to engage people in a richer, more nuanced discourse. The process of communicating a known quantity from one domain to another is taking a central role throughout this research. This work seeks to bridge the gap between different fields of knowledge, contributing to a future that advances both architectural practice and theory.
This work might serve as a contribution to enrich the depth of future architectural ideation, discovering new, unexplored fields of research, and hopefully fostering a more holistic understanding of the built environment. I think that “it is the right moment for a discussion about the impact of AI on the world of architecture.”
