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Trend 3: Adaptive Learning
Adaptive learning is a technology and technique within the larger AI (artificial intelligence) trend. The 20th-century educational model is radically disrupted now and will be even more in the near future. What Adaptive Learning does is modify learning content in real-time as a student is trying to master new knowledge and skills.
Technology like this is playing out in two areas—digital textbooks and online learning websites. In places like Pluralsight—one of the leading software training websites serving the software engineering, design, marketing, animation, 3D and CAD industries—algorithms provide real-time benchmarking of a student’s knowledge of a particular application or software area. The software can not only determine if you are a novice, expert, or merely proficient but can direct you to specific training programs.
In the CAD and 3D industries, sometimes pros have lopsided skillsets around one or more tools. Algorithms work during assessments to narrow in on what you know and don’t know about your software skills per application. Adaptive learning technology can greatly hone in what you need to learn next, what you don’t know, and what you truly know, to make training programs much more engaging.
Adaptive technology will affect one of the greatest barriers to more dynamic change in software in the AEC industries: unlearning. Mark Boncheck, author of Shift Thinking writes:
Unlearning is not about forgetting. It’s about the ability to choose an alternative mental model or paradigm.
It is unlearning that is principal to blame for the slow adoption of new methods, techniques, and technology in most industries, particularly risk adverse industries like building construction. Attacking the “unlearning barrier” with algorithmic-driven, highly engaging adaptive learning can loosen-up holds on outdated technology and methodologies, enabling the AEC industry to move a bit faster in technology adoptions—like the BIM movement—that will bring about progress in productivity gains, something lagging in the AEC industry for decades now.
Attacking the “unlearning barrier” with algorithmic-driven, highly engaging adaptive learning can loosen-up holds on outdated technology and methodologies, enabling the AEC industry to move a bit faster in technology adoptions—like the BIM movement—that will bring about progress in productivity gains, something lagging in the AEC industry for decades now.
Trend 4: Crowd Learning
You likely have heard of crowd sourcing or asking the public to contribute content or verify on-the-ground conditions. Crowd learning is querying the passive data from mobile phones, urban sensors, online activity, public records, and GPU data on the locations of people and their machines.
But how will these queries work?
They will work through software applications, on the web, desktop, and mobile. One app today is Waze which utilizes data from crowd sourcing. This interrelationship between crowd-sourced data and learning from the crowd will empower AEC professionals like urban planners, architects, and likely many of their clients (building owners) including major and minor urban cities. Queries can be made against the data to provide insight and decision support.
The biggest companies to watch for crowd learning will be Alphabet, Apple, Microsoft, government agencies and their websites, and news agencies. As for AEC companies? Again, unlearning appears to be getting in the way of learning to choose alternative mental models that orient practice in AEC fields. However, this is changing fast in the domains of city planning. Will architects learn to adapt? They must but how their methods evolve is highly debatable. (see, Architosh, “Phil Bernstein on the Changing Role of the 21st Century Architect—The Interview (Part 2),” 17 April 2016)
Trend 5: Smart City System
“Smart City” is a term you may not have heard before. Wikipedia’s definition is the following: “A smart city is an urban development vision to integrate multiple information and communication technology (ICT) and Internet of Things (IoT) solutions in a secure fashion to manage a city’s assets – the city’s assets include, but are not limited to, local departments’ information systems, schools, libraries, transportation systems, hospitals, power plants, water supply networks, waste management, law enforcement, and other community services.”
One goal of smart cities is to utilize urban informatics and technology to better improve the lives of a cities inhabitants, and this could mean wildlife and not just humans. The informatic infrastructure helps city stakeholders learn how a city is being used and how it is evolving. How a city is evolving is very important information for design and engineering professionals to access.
Currently, major smart city initiatives are underway, and a ton of money is being invested. The US Department of Transportation is awarding dozens of millions of dollars in federal grant money to upgrade urban transit systems as part of smart city initiatives. In Australia, the City of Melbourne launched a Smart City Office, which includes—and this part is relevant to AEC pros like architects, landscape architects, and urban planners—open data projects.
Melbourne’s system includes a 24-hour pedestrian counting system, among other things. The data from that can be immensely useable by architects and planners. So too is its data on its urban forests (see image 05 above) which will help determine increasing (or decreasing) tree canopy levels to help combat urban heat island effects. Decreasing the urban temperatures of a city, which can swing up to 7 degrees hotter than nearby green space, can help lower energy use for cool buildings.
But how will AEC pros gain access to this data?
A lot of access will come through websites and web applications. This is what is available currently. Others will deliver APIs for programmers to tap directly into. But what programs will tap into these APIs? This will be an emerging area within the global building design and delivery industries.
Helping this effort along is IBM with its Smart City Challenge and providing selected cities with access to Watson APIs to crunch on city data in ways useful to many constituents—like architects, urban designers, and planners.
These five trends are quite different than other leading edge innovations discussed before on Architosh. We didn’t mention VR, AR or mixed reality, though all three are going to impact environmental design professionals deeply as well. A related trend to those three worth mentioning now is holograms and the work that is going on at places like hologram technology startup LEIA.
Cognitive computing (e.g., IBM Watson), collaborative robots, VR marketing, IoT, and universal basic income (UBI) are also worth investigating regarding their impact on the future of AEC professionals and those trusted with shaping the future of our human environments.
The five trends above were chosen because they come at AEC industries more obliquely. The first trend will slowly change our landscape, as cars likely decrease in number for the first time since their invention. The second trend may affect our building heights but before that will be useful aids to various AEC professionals. The third trend will help us get past the unlearning road block that keeps AEC pros moving glacially. The fourth and fifth trends are linked in that they will empower stakeholders and citizens to see their communities and cities differently. These two may have the largest eventual impact on AEC professionals, particularly those charged with planning and designing our cities.