Artificial intelligence is increasingly perceived as a mechanism to revolutionize the work of designers and other professionals, posing a potential threat to alter and potentially dominate certain creative domains.
In the realm of layout, AI could potentially offer both a blessing and a strategic advantage, at the very least.
During the upcoming annual meeting of AIA Minnesota, the primary focus of discussion will revolve around this very subject. Phillip G. Bernstein, an associate professor and alternative doctor at Yale Architecture, renowned for his book “Machine Learning: Architecture in the Age of Artificial Intelligence,” is slated to deliver the keynote address.
Bernstein emphasizes the potential benefits of harnessing AI’s capabilities to enhance the predictability, cost-efficiency, sustainability, and inclusivity of design and construction within the job and building industry. Despite the advancements in AI post-publication of his book, he remains optimistic about its transformative impact.
Karen Lu, representing AIA Minnesota on the national Strategic Council and serving as the equate director of Snow-Kreilich, has been actively involved in exploring AI’s role in the future of architecture. Inspired by Bernstein’s book, she facilitated a session at the recent AI and architecture conference and also presented a keynote address.
According to Lu, Bernstein’s extensive experience spans various facets of structural education and technology, particularly in handling substantial and intricate projects. His tenure as a vice president at AutoDesk during the development of building information modeling (BIM) further underscores his expertise.
In preparation for the event, AIA Minnesota urged its members to delve into the realm of “machine learning” to foster insightful discussions and pose pertinent questions.
Lu expressed keen anticipation about the discourse surrounding the impact of AI on the future of the profession, acknowledging a blend of excitement and apprehension. The objective is to engage in a more profound and informed dialogue on the subject.
Bernstein’s book delves into three core sections: process, relationships, and results, encompassing expertise, tools and technologies, regulations, risk and safety, delivery methods, data generation, utilization and curation, value propositions, and business models.
While the integration of AI in infrastructure is still evolving, Bernstein notes a cautious approach among industry players who prefer a wait-and-see strategy.
According to Bernstein, the utilization of relational algorithms transcends mere text blocks from ChatGPT or captivating images from MidJourney. He advocates for leveraging relational algorithms to craft intricate and functional architectural designs, emphasizing the role of creativity and insight in producing optimal outcomes.
Nevertheless, Bernstein acknowledges potential risks such as job displacement, mundane machine-generated outputs, and the uncredited utilization of historical structural knowledge for AI training datasets. These socio-economic and political challenges necessitate resolution beyond the infrastructure domain.
Lu underscores the collective enthusiasm among builders, developers, clients, and architects to delve into the uncharted territory of AI.
She emphasizes the need for a cautious approach, highlighting the importance of vigilance against biases in data and the potential distortions induced by AI.
Lu concludes by emphasizing the transformative potential of AI to streamline routine tasks, enabling professionals to focus on critical issues like sustainability, climate action, and other complex challenges impacting the industry.
