{"id":734778,"date":"2024-04-05T08:30:56","date_gmt":"2024-04-05T07:30:56","guid":{"rendered":"https:\/\/www.architectsjournal.co.uk\/?p=734778"},"modified":"2024-04-05T08:42:13","modified_gmt":"2024-04-05T07:42:13","slug":"learn-the-ai-lessons-from-the-early-adopters-needs-link-to-ai-survey-where-indicated","status":"publish","type":"post","link":"https:\/\/www.architectsjournal.co.uk\/news\/learn-the-ai-lessons-from-the-early-adopters-needs-link-to-ai-survey-where-indicated","title":{"rendered":"Lessons in AI, from architecture\u2019s early adopters"},"content":{"rendered":"

Myth vs<\/i> experience\u00a0<\/span><\/span><\/h3>\n

When I was studying, \u2018parametricism\u2019 was the big buzzword. Despite the hype at the time, working with computational fluid geometry was mainly the preserve of the starchitect elite and a small band of niche experimental practices which also taught diploma units in London.\u00a0<\/span><\/span><\/p>\n

In the 2000s, some people began to identify as exclusively \u2018parametric\u2019 architects while others, like myself, who tended to draw with straighter lines, carried on as they were. The technological shift allowed by modelling software such as Grasshopper had become tethered to a style dogma and was largely ignored by mainstream practices. Labels that end with \u2018ism\u2019 usually tend to divide opinion.<\/span><\/p>\n

However, the application of generative design and AI tools is showing all the signs of becoming far more transformative for the way architects will work. It\u2019s not hyperbole to state that the physical environment of our future cities will be moulded largely by the work of computer scientists and the algorithms they\u2019ll write in the next few years.\u00a0<\/span><\/span><\/p>\n

With this as a backdrop, our best architects and placemakers must be more than part of the new conversation, they must also become active in the development of this consequential, software-driven shift.<\/span><\/p>\n

Some fears need to be allayed, because, despite what you see on social media, generative AI is agnostic when it comes to style. It\u2019s a general-purpose technology with very wide application, from administrative tasks to provocative conceptual design. It is available to everyone, often at low cost, and it spans the spectra of 3D, text and image.<\/span><\/p>\n

I\u2019ve both seen how it is being used and have been given an insight into how it might be used better. The following observations are taken from the many meetings, training workshops and deep discussions I\u2019ve had with practices around Europe since founding Arka Works six months ago.<\/span><\/p>\n

Lesson: AI is not the next style war; it\u2019s for everyone<\/b><\/span><\/p>\n

\"\"

Arka Works AI in Practice workshop at GPAD Architects\u2019 office<\/p>\n\t

<\/p><\/p><\/div>\n

Horizontal vs <\/i>vertical change<\/span><\/h3>\n

\u00a0<\/span>AI is often compared to the invention of CAD or BIM. This is largely wrong. AI will most likely bring horizontal change to your organisation. Namely, it will, in some way, touch every department of the business. In this way it is fundamentally different from CAD or BIM, which are more vertically managed phenomena.<\/span><\/p>\n

Think of AI as a broad, horizontal umbrella covering all parts of the business \u2013 projects, support, bids, communications and so on. Yes, you need technical expertise at the core of your approach, but mainly you need your designers and project leaders leading the conversation and doing actual testing on live projects to decide what is useful to their method, or not.\u00a0<\/span><\/span><\/p>\n

A common approach is for practices to view AI as a new, purely software-based problem and put it into their IT departments, which then research and ponder which apps, if any, they should direct budget towards. This is a misstep.\u00a0<\/span><\/span><\/p>\n

Yes, those tech specialists need to be closely involved, but this isn\u2019t purely a \u2018software stack\u2019 question; it\u2019s more a culture of practice and working behaviour question. Once you\u2019ve decided on the desired scope and depth of adoption, forming a working group is usually the first step.<\/span><\/p>\n

Lesson: Set up a working group led by your best designers<\/b><\/span><\/p>\n

\"\"

Lido concept image by Arka Works produced through text and image prompting using Midjourney (generative AI)<\/p>\n\t

<\/p><\/p><\/div>\n

Adoption<\/span><\/h3>\n

\u00a0<\/span>The first step on the road to adoption is deciding to take action. Our brains try to protect us from the risks of the unknown. We often fear change. People largely ignore new phenomena for several months until, on the seventh or eighth nudge, they decide to act. I\u2019m seeing many practices make this step now.\u00a0<\/span><\/span><\/p>\n

The AJ survey results<\/a> show that more than half of respondents are already on some kind of adoption journey and the \u2018early adopters and innovators\u2019 cohort (those using AI regularly) make up 15 per cent of the overall total. This figure maps closely onto the classical distribution predicted by the Diffusion of Innovation Theory model by EM Rogers in the 1960s \u2013 a bell-curve diagram that is applicable to any new transformative technology.<\/span><\/p>\n

Before practices begin to adopt new tools, they should have an open discussion about how this technology aligns with their core mission and values and, therefore, what their adoption journey will look like. This will be different for different practices.<\/span><\/p>\n

Setting a trajectory will mean trying some new things out for yourself, before forming a rigid opinion. It\u2019s very important that board-level design leaders are part of the testing. It is also best done in parallel to support real-world project work, so that actual and practical value can be assessed. Leadership needs to come from the top. Your direction must be design-based, because these techniques may begin to fundamentally impact the way you create. Ultimately, that is the single most important thing in any architecture practice.\u00a0<\/span><\/span><\/p>\n

Lesson: Don\u2019t run hypothetical \u2018research\u2019; start small and apply the new techniques\u00a0 <\/span>to real-world problems<\/b><\/span><\/p>\n

\"\"

Sketch-to-render-in-context demonstration image by Arka Works using Stable Diffusion<\/p>\n\t

<\/p><\/p><\/div>\n

Guardrails<\/span><\/h3>\n

Only 8 per cent of respondents to the AJ survey report any kind of controls being put in place around AI use. People are experimenting, which is great. But there are risks. We are in the Wild West and opportunities and pitfalls abound. If you are using a basic subscription on ChatGPT or Midjourney, then the images, PDFs and words you upload are likely being harvested and will be part of future model-training material.\u00a0<\/span><\/span><\/p>\n

It is possible to host and run your own private models using open-source models, or to pay extra for privacy. But, if you haven\u2019t taken a position, you may be in breach of an NDA or data policy and you may be allowing commercial or GDPR-sensitive data to leave the business.\u00a0 <\/span>Conversely, simply banning things probably isn\u2019t going to work either. That may put you on the back foot while competitors progress at pace.<\/span><\/p>\n

An adaptive approach that is permissive but cautious will reduce confusion about which tools are \u2013 or are not \u2013 endorsed officially by the practice. You must also allow yourself to change your mind when new information suggests a shift in strategy is needed. Many other guardrail issues should be considered, including bias, detecting errors, intellectual property and copyright, environmental impact and costs.<\/span><\/p>\n

Lesson: Scope things out and build a policy framework for responsible use<\/b><\/span><\/p>\n

\"\"

Hand-sketch by Nick Elias for a project by Haptic and Oslo Works<\/p>\n\t

<\/p><\/p><\/div>\n

\"\"

Masterplan concept image for the Haptic and Oslo Works proposal, based on the hand-drawn sketch by Elias \u2013 the image was produced using Stable Diffusion (generative AI) directly from the sketch<\/p>\n\t

<\/p><\/p><\/div>\n

All roads lead to customisation<\/span><\/h3>\n

Clients don\u2019t want \u2018vanilla\u2019 and generic solutions. But this is the likely outcome of using closed-source, \u2018black box\u2019 generalised AI tools. The solution? Don\u2019t use general tools. Pick them up and customise them, pull your own IP into them, get answers no one else can get (Heatherwick Studio has trained its own in-house image models, for example).<\/span><\/p>\n

All technological breakthroughs lead to unintended consequences, so we need to keep a proactive eye on change and engage it head-on. Let\u2019s not just let it happen to us. While practice leaders are wondering whether they should look into this AI thing, the next cohort of architects are graduating, and they are already using it every day.<\/span><\/p>\n

Some respondents to the AJ survey expressed concern that AI will lead to a lazy design culture and shorter collective attention span. Others have pondered what the point is in practice if we begin to dilute our core value proposition. I would agree with the sentiment on both points. However, as long as we are working with humans on behalf of other humans, then our human empathy, unique, experience-based insights and ability to communicate ideas with our clients is the most important service we offer, so we should lean into it.<\/span><\/p>\n

Conclusion: We shape our tools and then they shape us\u00a0<\/span><\/b><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Myth vs experience\u00a0 When I was studying, \u2018parametricism\u2019 was the big buzzword. Despite the hype at the time, working with computational fluid geometry was mainly the preserve of the starchitect elite and a small band of niche experimental practices which also taught diploma units in London.\u00a0 In the 2000s, some people began to identify as …<\/p>\n","protected":false},"author":17071,"featured_media":734786,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_oasis_is_in_workflow":0,"_oasis_original":0,"ep_exclude_from_search":false},"categories":[681],"tags":[100464,93810],"yoast_head":"\nLessons in AI, from architecture\u2019s early adopters<\/title>\n<meta name=\"description\" content=\"Architect and AI expert Keir Regan-Alexander, founder of Arka Works, reports from the architectural frontlines on how practices are experimenting with emerging technologies\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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