Will AI take architects’ jobs too, or will it make them much more fulfilling instead? asks Akos Pfemeter of Graphisoft
Although the field is not new at all – AI research started during the Dartmouth Summer Research Project in 1956 – it is only after a half-a-century-long “AI Winter” that with the unexpected breakthrough of OpenAI’s ChatGPT that reached 100 million users in just two months, AI is now all the rage in 2023 – and for a reason. AI now has human-level cognitive abilities making it capable of passing the US Uniform Bar Exam with a higher score than 90% of humans.
AI fairs well on the creative side, too: it can compose music, write poetry (helpful in creating lyrics for the music it just composed) and generate image representation of anything imaginable or rather “prompt” -able by the expression of natural human language. No wonder news headlines are full of “[BLANK] profession is in danger of losing jobs to AI” – feel free to fill in the blank with “journalists,” “marketeers,” “programmers,” “lawyers” or many other white collar job titles.
What does all this mean for the AEC industry? Will AI take architects’ and engineers’ jobs too? Or will it make them much more fulfilling instead? No one knows the future, and there are multiple scenarios for AI to unfold, but one thing is certain – our profession will be fundamentally different by the end of the decade. What follows is a discussion of the relevant points to help answer the questions stated, giving you a better overall understanding of the subject so that you can prepare.
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Let’s start with definitions: AI (artificial intelligence), ML (machine learning), and DL (deep learning) are used interchangeably in colloquial language, and while they are related, they are by far not the same thing.
AI is an umbrella term for machines that can do things beyond sheer automation – a robot vacuum cleaner that can clean rooms of any shape without specific instructions is already considered AI. Its “intelligence” comes from its software; simply put, the AI revolution is a software revolution.
In traditional software development, people (programmers) specify the instructions for the computer. AI uses a new programming paradigm called machine learning where computers aren’t given specific instructions. Instead, they are shown vast amounts of examples of input<>output pairs (e.g., input: a photo of a bus <> output: image label “bus”) from which they distill patterns that will become in this example an image recognition software. (Fun fact: with CAPTCHA tests you, the human, have been teaching the computer these patterns).
The AI breakthrough is the result of recent developments in GPU-based mass computing married with traditional “statistical” methods to find patterns in large datasets of images (photos, medical x-rays, video frames, and photos), sound (speech and music) or text (emails, websites, and books). The resulting software can be used to recognise similar patterns in new datasets (e.g., cancer diagnosis, voice recognition), and to generate new similar datasets (prompt-based image, text, and music generation).
You might wonder if it’s possible to train AI on large datasets of architectural plans or better still building information models and have AI design buildings by the design program as the system “prompt”? There are startups already offering promises very close to this vision but there are still more questions than answers today. Would you (your client) really like this approach to building design? Would you (your client) agree to contribute your existing design (asset) IPs to train the AI? Wouldn’t such an approach lead to too much uniformity?
The more relevant question is how AI can contribute to building design today? It most certainly “won’t design your next building”, but it can potentially contribute to it by augmenting your capabilities by making you a better, more efficient designer.
AI will undoubtedly have a lasting impact on our industry but probably even more so on humanity
You can already use generative AIs such as Stable Diffusion or MidJourney to help you with design ideas in the form of renderings based on your mass model. There are third party integrations with BIM software already available and native integrations (i.e., one from Graphisoft) are underway.
In the immediate future, we can expect further integrations with existing large AI models to make specific tasks easier/better/automated. The target range is extremely broad, including voice/natural text or even gesture control for BIM software (revamped “command line” anyone?), BIM integrated AI chatbot for personal training/support, and AI translated “lightweight” API for broad accessibility to a more democratised add-on development.
On the not-so-far-in-the-future-term model generation from drawings, images, point clouds or even from natural language-given prompts is a promising utilisation of AI. This will provide the key to unlocking vast reservoirs of dumb/analogue/proprietary information into intelligent/parametric/open formats, accelerating the digitisation of building-related data/content. A specific example of this model generation is when natural language prompts are used for parametric object scripting (GDL, anyone?).
But the highest yet achievable AI goal should be to free human designers from mundane tasks such as technical documentation. In this use case, the architect would focus on what s best in design. At the same time, the computer would carry out the laborious tasks of technical detailing and documentation (not to mention the multiple cycles of updates while the design is still changing). This is undoubtedly one of the more complex tasks for AI implementation, but still within our reach.
Whether AI will ever provide complete architectural services directly to clients is still an open question. One thing is for sure: future architectural and engineering practices will require a different type of workforce with different skillsets than today; “prompt engineering”, for example, is an emerging field where you learn how to ask the right questions of AI – a skill we will need to master to a degree, should we want to yield the benefits of existing and future AI systems.
AI will undoubtedly have a lasting impact on our industry but probably even more so on humanity. AI truly has the potential to turn society on its head, disrupting everything, including wealth distribution, political control, and how we live – similar to what the steam engine did to medieval Europe during the industrial revolution in the 18th century. A growing number of AI scientists go even further, demanding a six-month pause on all large AI model training so that we humans can catch up with the latest progress in AI.
Should we be optimistic about AI? If we survive singularity, we certainly will have a powerful ally to help solve our biggest problems, such as global warming, crime, poverty, pandemics, erosion, etc., but to get there, we need safeguards. We should not only worry about IP rights, AI alignment, and a new arms race but also ensure we don’t transmit our own human biases to the machines. If we succeed, AI will bring never before seen prosperity to humanity.