With each new change in process or technology, apprehension from users challenges the need to adapt their current methods and processes. When technology replaces an existing method or process, it is only sustainable if it offers something above and beyond what is currently in place. Some call this “disruption.”
According to Clayton Christensen who coined the phrase disruptive innovation (when a need is not satisfied by existing providers), disruption will happen when a new provider begins meeting the unserved or underserved need and uses the technology to expand exponentially, toppling market incumbents.1
However, that is not always the case; for instance, development of new technology may be irrelevant to an existing provider’s services, but once available, many derivatives of it can disrupt an existing provider’s services — especially in the fringes and unrelated markets (e.g., fax did it to mail, Uber did it to taxi service and food delivery, Toyota did it to General Motors). All of these innovations don’t have to satisfy the current wants, but they will need to address some of the needs that, when satisfied, will expand in the areas that were not known before. For example, Apple created an entire new ecosystem for app development by creating the iPhone and iPad. Everything came through inventions that are man-made, but their origin has always been in the nature.
Exploring the distinction between “man-made” and “natural” things prompts us to consider their origins. Regardless of the final product, the source of knowledge behind both is the same. Without delving into philosophical or religious realms, it’s essential to recognize that anything crafted or fabricated stems from human hands. Although the outcomes (positive and negative) can vary significantly, the origin of creation traces back to a non-artificial intelligence.
Artificial Intelligence
Artificial intelligence (AI) is the new buzzword trending in the news, research, books, and social media. It has caused debate, core questions, and incredible advancements in information transfer. But how will it impact construction?
Will ChatGPT send prefabricated assembly instructions to a 3D printer? Will robots fix the workforce shortage problem? The answer to these questions (and more) is possibly, but not without Agile Intelligence™. Having knowledge about work and the experience of using tools to build is strictly human.
Technology has always helped to move from one step to the next or increase the pace of evolution. To better understand how AI will impact construction, we can look at the industrialization of other industries such as agriculture and manufacturing to move faster toward the Industrialization of Construction®.2 This article explores the source of information as the crux, which has been coined as Agile Intelligence™.
Technology, Information Technology & AI
To better understand the role of technology, information technology (IT), and intelligence in the Industrialization of Construction®, Exhibit 1 explores the connection and distinction of these words that build on each other to get to the definition of AI.
If AI is meant to reflect human intelligence, then where does that intelligence come from? If it is based on knowledge, then what is the source? The knowledge is not artificial; it’s based on data.
Many companies have an abundance of data; however, it’s the progression from data to information to knowledge to wisdom (as coined by Dr. Perry Daneshgari) that helps an organization gain intelligence through learning and asking the right questions of the data.
Exhibit 2 shows how the intelligence and experience of those with wisdom can guide teams or individuals on how to collect data. Those with knowledge can help guide others on what to look for, where to collect the data, and who should collect the data.
This is essentially moving up the AI chain — recognizing how to assemble data, translating it to information and then to overall knowledge, and finally, recognizing what those with wisdom know from their experiences and knowledge.3 The result of this progression from data leads not to artificial intelligence, but rather to Agile Intelligence™, which is gained from experience and a human source that can be used to improve the system and organization.
Industrialization in Other Industries
Technology played a role in each of the five steps of industrialization.4 Once the techne — the art and skill — is understood and made explicit (through Steps 1 and 2), it can be improved upon with systematic treatment (e.g., technology).
In agriculture, advancements in understanding the techne started in the 18th century when universities and governments began studying what led to better yields based on what farmers did. Then they worked to develop a systematic approach using fertilizers, irrigation, crop rotation, and mechanization.
Eventually this technology became housed in machines that provided both physical and mental (decision-making)
aid to the farmer. Exhibit 3 shows this advancement in machines first using hardware technology to replace human/animal muscle power and then using software technology to enhance human decision-making and improve yield based on a systematic approach.5
In manufacturing, the technological advancement of computing (IT) has mostly replaced manual and human computing, which allowed manufacturing to go through industrialization in one-third of the time that it took for agriculture.6