An Industry in Dire Need of Disruption

The building construction industry faces an existential crisis. It is one of the least digitized industries and the world’s leading producer of C02 emissions. With rising temperatures around the globe and mass migration to urban centers, there is a dire need for a digital disruption that will enable more sustainable ways of working.

We as architects can learn from other fields that have made rapid strides in developing synergistic human-machine systems which exploit the positive aspects of human and AI-generated reasoning.

Over the past year, a number of AI tools have been developed that provide new insights into the environmental impact and performance of a design. Despite their great potential, several barriers to widespread adoption exist:

Significant expertise is required to take advantage of their capabilities AI and other computational methods require narrowly defined design goals For clients — the ones financing the projects — the outputs of these tools remain opaque and not understandable.

At Digital Blue Foam (DBF) we develop new solutions to accelerate the world’s transition to better and more sustainable cities. We are designers and technologists with a strong sense of responsibility to drive a desperately needed revolution in architecture, engineering and construction (AEC) industries towards carbon-negative projects.

At the dawn of a new age of design, several fundamental questions remain:

How do we develop tools that give designers greater agency to promote sustainable designs?

What does the next generation of user interactions look like?

How do we connect the strengths of both human and machine intelligence in a design tool?

AI Makes No (Common) Sense

2019 was a prolific year for new Machine Learning (ML) applications . ML, the machine’s ability to infer outputs from structured, or, in the case of Deep Learning, unstructured data, has garnered massive hype and hysteria. This has led to the common misconception that if we collect and process enough data using the latest algorithms and computing power, intelligence will simply emerge. This is simply not the case.

Using a strategy of correlation rather than causation, ML identifies patterns incredibly fast, especially when the input data is well-structured. This is why it is so effective at playing video games like Flappy Bird. In most video games, rules and goals are consistent; unlike the real world, where the pattern will always stay the same. But what happens when the situation changes?

‘Causal’ intelligence is the basis of human smarts. While humans recognize patterns comparatively poorly, we excel at reapplying our past knowledge to new situations. So when Flappy Bird 2 gets released, we know it will have mostly the same rules and goals as the original, and we adapt quickly. Our AI, on the other hand, did not understand anything; it only followed a pattern. When the pattern is altered, the AI becomes useless.

Interfaces for Augmented Intelligence

Digital Blue Foam has developed a tool that can steer the AEC industry around a major bottleneck. Architects spend a lot of time learning and using inefficient drafting tools that actually distract them from their essential role of creating and experimenting with design options that cater to the plethora of needs of the site and project, be they social, environmental, or economic. Our tool uses augmented intelligence to free architects from this hassle and aid them in generating design, through the augmentation of the time-tested method of sketching.

We at DBF are major proponents of augmented intelligence’ as opposed to black-box AI. In this paradigm, AI becomes a tool to enhance human intelligence rather than replace it. While sophisticated AI systems are able to make decisions after analyzing patterns in ‘big data,’ they are only as good as the data humans give them.

Augmented Intelligence is the hybridization of Human and Machine Intelligence

Augmented intelligence is already embedded within many well-known products. It is particularly evident in word-processing applications: MS Word’s spell-checker, the Hemmingway Editor, and Grammarly (an online grammar checker) are a few everyday examples of augmented intelligence. The ‘design ideas’ feature in Powerpoint, which uses augmented intelligence to help non-designers improve their layouts, is another example.

In our software, the user designs with the computer, using a pen interface. What ensues is something others have described as human-in-the-loop augmented intelligence with human-computer collaboration (Zheng, 2017).