Since 1936, when Alan Turing first theorised an a-machine (automatic), our world has been meshed with ‘intelligent’ devices. They process information and perform complex tasks that either cannot be achieved by humans or where most people, relying only on natural intelligence (NI), simply are not effective. The implications for architecture and design education seem immense and imminent.

Probably the most sophisticated and familiar examples of AI are the mission-critical computer systems which fly us around the world. Before 1914, when Lawrence Sperry demonstrated the world’s first autopilot mechanism (using four gyroscopes to stabilise a plane in flight), pioneer aviators frequently crashed. Today’s aeroplane control systems, when programmed with a flight plan, automate the take-off, ascent, level flying, descent and landing phases of flights. Also, they constantly detect the positioning and behaviour of aircraft in space: adjusting altitude, latitude, longitude, pitch, roll and yaw. Similar electronic systems now automatically supervise many essential operations of buildings which never leave the ground.

Autopilot systems control passenger drones— flying taxis—which herald the huge new urban planning challenge of how to manage cities like vast airports. The Ehang 184, made in China, flies with eight propellers on its four arms and a host of sensors streaming real-time data, and includes ‘failsafe’ backup systems in case of emergencies. Flights are monitored by squads of technicians watching giant screens in remote control rooms. The only task to be performed 
by a ‘pilot’ is to key the destination on a smartphone app before automated take-off. Drone taxis—coming soon from Uber, etc.— revivify H.G. Wells’ Victorian flying machine stories, which must have inspired the Wright Brothers before their first flight in 1903.

Arrays of sensors also feed performance data to America’s Cup sailors and cyclors flying hydrofoil catamarans; to managers of public surveillance, transport and emergency services operations, and to technicians maintaining ‘smart’ city buildings and precincts.

Architects now can be conveyed to their terrestrial sites in self-driving Teslas. But back in their studios – seriously, could machines really auto-generate building designs and city plans? Not independently (or not yet) from the mammalian architects and engineers who program the algorithms and supervise/select from the outlines of forms that they generate.

Yet there are some plausible progenitors  of creative appliances toiling in future ateliers of design. For example, French inventor Patrick Tresset has built a troupe of robosketch artists whose electro-mechanical arms rapidly scribble portraits via their cameras and facial recognition software.

Each has a ‘personal’ drawing style, which Tresset has programmed—like architects guide their drafting staff to follow ‘house’ drawing styles and specifications. The robots, all named Paul, are best compared after they have clustered around a single sitter, scrawling jets of ink across paper on old-school wooden desks,  just like humans in life-drawing classes.

One of AI’s most promising uses is for robots to replace humans in performing extremely dangerous tasks: such as shimmying along narrow cavities to replace damaged wiring or record material stresses. Czech writer Karel Čapek first coined the term robot in his 1921 play R.U.R: Rossum’s Universal Robots – and today’s humanoid versions, such as Boston Dynamics’ Atlas and Honda’s Asimo, are astonishingly agile and sophisticated.

Non-humanoid robots, swivelling from fixed bases or traversing across gantries, are already printing small dwellings in masonry or powder-resins, or assembling timberwork as adroitly as a master carpenter. Artificial intelligence was ignored by most built environment professionals until satellite-enabled telecoms caused widespread apprehensions during the 1990s, systemic disruption during the 2000s, and now inevitably, new ways of understanding and doing things.

Today AI brings another wave of unfamiliar technologies and terms – including augmented intelligence, where machines are intended to improve human abilities to decide and perform. This seems less threatening than artificial intelligence, where machines increasingly replace humans, to a tipping point known as the Singularity (the term popularised by Ray Kurzweil).

All intelligence, artificial or natural, flows from competent processing of information. Most AI researchers have abandoned their early reliance on pre-programmed rules to solve problems. Instead they are evolving machine learning, where computers use algorithms to learn how to better display or interpret lakes of streaming data. The more data that computers are fed, the more capably they seem to crush complex tasks; partly through their suprahuman powers of pattern recognition.


Pictured: Tianjin Library, China. Photography by Ossip van Duivenbode

The full article is available in the July-September issue of Architecture & Design.