I decided to challenge myself and explore existing and emerging technologies in order to estimate what could we achieve during the next 30 years. The question is considered in terms of an ever-evolving process of change and improvement within the Construction Industry. I do not believe that we can consider improvement as a finite process. The continuous improvement and change of technology, in general, will drive further changes which will not only improve the standards but will also change the way we design, work and live.
We only need to look back ten years to see examples of technology development: smartphones, social networking, Wi-Fi and IoT, tablets, e-commerce, wearable technology, and augmented reality. Ten years ago, the following products did not exist iPad, Google Chrome, Airbnb, Spotify, Uber, Oculus, Instagram, Kickstarter, 4G and many more.
According to Bill Allen CEO, President of EvolveLAB LLC in the next two decades, we will primarily use to design software agnostic tools, and we will be able to generate control, and capture data irrespective of what software the geometry was created in. Allen also predicts that computers will be able to execute tasks, rules, and processes autonomously and more efficiently than humans. Allen forecasts that in 20 years, algorithms will be able to design buildings and robots will build them.[1]
In Collins Dictionary, ‘Foresight‘ is defined as the ability to see what is likely to happen in the future and to take appropriate action. Although we do not know the future, the fact should not keep us from trying to see ahead.
Let’s explore existing technology in general, and construction-related design processes and techniques, and attempt to assess the possible near future of the Construction Industry.
Standardisation process
A standard can be linked to an algorithm in light of Allen’s suggestion. According to the Cambridge Dictionary standardisation mean a process of making things of the same type all have the same basic features.[2] This is very close to the definition of an algorithm which is nothing else like step by step method of solving a problem, this in turn no more than the Standard method and Procedure (SMP) described in ISO 19650-0; 2019 as …’ Combination of information standard and information production method and procedure’…[3]
Educational institutions include in their curriculum programming as early as in primary school. This is due to the almost limitless demand for coders suggested by Thompson[4] We can assume that some of these individuals once graduated, will move onto management and construction. More and more people have at least basic coding skills, which allows for workflow improvement and automation. Similarly, the development of new SMPs based on analysis, which will enable the development of an algorithms to automate or perform the majority of the current design processes.
Existing broad-spectrum Technology – algorithms
In the 1980s people believed that computers would never beat humans at chess, on February 1996, IBM’s Deep Blue defeated world chess champion, Garry Kasparov, bringing to an end the particular claim for human pre-eminence[5]
February 2015, a program developed by Google DeepMind learned by itself how to play forty-nine classic Atari games. It then played most of them as well as or better than human players.[6]
In 2016 Google AlphaGo software taught itself how to play Go, an ancient Chinese strategy board game significantly more complex than chess, and defeated South Korean Go champion Lee Sedol 4-1[7]
Low-budget Baseball team Oakland Alethic become the first team in American League history to win 20 consecutive games with the team of human overlooked and undervalued players selected by algorithms.[8]
Thanks to powerful algorithms, Uber can manage millions of taxi drivers with only a handful of humans
In May 2014, Deep Knowledge Ventures – a Hong Kong venture-capital firm specialising in regenerative medicine hired an algorithm named Vital to its board. Like the other five board members, VITAL gets to vote on whether or not the firm invests in a specific company making use of analysis of vast amounts of data.[9]
OncoFinder algorithm used by Pathway Pharmaceuticals is used to select and rate personalised cancer therapies[10]
David Cope, a musicology professor, created a number of programmes with best one named Annie, a machine learning composer, which is not only able to compose music but also poetry, 2011 Cope published ‘Comes the Fiery Night: 2,000 Haiku by Man and Machine’ where some of the poems were written by Annie and the rest by human poets. The result is mind-blowing no one can tell the difference between human or machine creativity.[11]
Existing Technology – Construction
Researchers from eight professorships at ETH Zurich, within the framework of the National Centre of Competence in Research (NCCR) “Digital Fabrication”, in collaboration with industrial partners, have for the first time transferred several new digital construction technologies from the laboratory into real-world and have built primarily digitally the DFAB HOUSE unit, with the help of robots and 3D printers[12]
Mariana Popescu developed a new method to create a low-cost, lightweight and more sustainable formwork system for concrete structures. Popescu working with her colleagues discovered how using a machine-knitted technical formwork can be tensioned with steel cables to create a strong geometric shape that can be coated with a concrete paste. Compared with traditional rigid formwork, the “KnitCrete” method allows complex structures to be built cheaply, quickly and with a much smaller carbon footprint[13]
A real estate giant WeWork is using AI-driven machine learning to predict how potential occupants might use co-working and shared spaces and to assist its design partners in making more optimal choices.
Arup has made use of machine learning technology in the project in New Zealand, completed in 2016, where a joint venture of Arup and Jacobs developed a “neural network” that consolidated the utility data with information about the light rail’s asset features to create recommendation design for a proposed 18-mile Auckland Light Rail route with 24 stations. The design reduced the number of potential overall clashes to 443 from 5,183 and saved an estimated 790 engineering hours of work.[14]
To make it all fit together in the end
In terms of progress over the next 30 years, the construction industry has the potential to outperform our expectations. The change will most likely integrate construction with other industries; the rate of change will depend on many factors, which can accelerate or impede the process. One of the factors quoted in A Look Ahead: 2019 Foresight Survey report, with the potential to impede the change, is Political and Economic Uncertainty, quoted within the report Dave Gilmore, says: “geopolitical and geo-economic risks are deepening across the globe,” and that the tension between the globalization of the world economy and the growing nationalism of world politics is a deepening risk. Added to that were strained relationships in 2018 between many of the world’s powers related to trade and investment, as well as the growing nationalism in many countries.[15]
Will machines be able to design? I believe the question should be, not if, but to what extent within the given time frame. Artificial Intelligence and Machine Learning are widely used already with many examples shown above. According to Jeff Wald, the incentive is sufficient enough.
Employees believe countless aspects of their jobs to be repetitive, and industry leaders claim that substantial portions of their workdays are ideal fits for automation. According to WorkMarket’s 2020 In(Sight) Report quoted by Wald 53% of employees state that they can save up to 240 hours per year through automation, and 78% of industry leaders suggest that automation can free up to 360 work hours per year.[16]
[1] Allen, B., n.d. The Future of BIM Will Not Be BIM and It’s Coming Faster Than You Think | Autodesk University [WWW Document]. URL (accessed 11.18.19).
[2] STANDARDIZATION | meaning in the Cambridge English Dictionary [WWW Document], n.d. URL (accessed 11.19.19).
[3] British Standards Institution, 2019. Transition guidance to BS EN ISO 19650.
[4] THOMPSON, CLIVE., 2019. CODERS : who they are, what they think and how they are changing the world. PICADOR.
[5] Deep Blue computer beats world chess champion – archive, 1996 | Chess | The Guardian. (n.d.). Retrieved December 10, 2021,
[6] Google DeepMind AI outplays humans at video games | New Scientist. (n.d.). Retrieved December 10, 2021, from
[7] Google’s AlphaGo beats world’s best player in latest Go match | New Scientist [WWW Document], n.d. URL (accessed 11.19.19).
[8] Billy Beane’s revolutionary use of Statistical Analysis [WWW Document], n.d. URL (accessed 11.19.19).
[9] VITAL Named To Board – Business Insider [WWW Document], n.d. URL (accessed 11.19.19)
[10] Buzdin, A.A., Zhavoronkov, A.A., Korzinkin, M.B., Venkova, L.S., Zenin, A.A., Smirnov, P.Y., Borisov, N.M., 2014. Frontiers in Genetics 5.
[11] The Machine That Writes Haiku – Big Bang Poetry. (n.d.). Retrieved December 10, 2021, from https://www.bigbangpoetry.com/2017/11/the-machine-that-writes-haiku.html
[12] Knitting concrete for buildings | ETH Zurich [WWW Document], n.d. URL (accessed 11.19.19).
[13] Building digitally, living digitally | ETH Zurich [WWW Document], n.d. URL (accessed 11.19.19).
[14] Building Design + Construction, 2018. Tech Report 5.0: AI Arrives [WWW Document]. URL (accessed 11.19.19).
[15] DesignIntelligence, 2019. A Look Ahead: 2019 Foresight Survey. [16] Wald, J., 2017. How Automation Could Save Your Business $4 Million Annually [WWW Document]. URL (accessed 11.19.19).
