Machines and Megaprojects – AI Trajectory 2023+

We stand at the cusp of a new era: The impact of Artificial Intelligence and other disruptive technologies on megaprojects is both undeniable and inevitable. Already, we are seeing extensive use of Digital Twins in industries as diverse as automotive, manufacturing, construction, healthcare, and utilities.

SwissCognitive Guest Blogger: Dr. Thomas D. Zweifel and Vip Vyas – “Machines and Megaprojects”

“Any sufficiently advanced technology is indistinguishable from magic.”

— Arthur C. Clarke

For those unfamiliar with digital twins, think of them as a connector between the real and digital worlds. They work by creating virtual simulations or clones of existing physical assets, hence the term. Using sensors built into the physical assets, virtual simulators mine and analyze data, showing managers how various elements and processes in the physical device work together. This visibility is critical in helping design, build, operate and maintain physical assets that deliver higher performance at lower costs.

Zoom out from digital twins of individual products or assets, and we end up with entire cities. “Smart cities” gather big data through various electronic methods (sensors, voice activation, facial recognition, etc.) The data is then used to monitor, fix, and manage the city’s assets, resources and services more efficiently. Examples of applications include power plants, water supply systems, schools, sanitation, waste management, hospitals, more efficient public transportation, smoother mobility across the city, and ultimately solving social problems such as early crime detection, prevention, and increasing public awareness of safety.

Zooming out even further, several prominent technology companies have invested billions of dollars in the metaverse. This digital twin on a global level promises to build a virtual reality that mirrors in every way our reality. It’s a clone of the world. The metaverse is bound to be a greater disruption than the Internet was in the 1990s. If it comes into being, it might transform how we live, work, and play. But even without the metaverse, megaprojects already benefit from technological advancements:

AI makes project tracking easier through real-time project updates;
AI improves virtual collaboration between decentralized, globally dispersed teams;
AI improves efficiency and productivity through automation of time-consuming processes, and
AI enhances effective decision-making through Increased transparency and data visualization.

Figure 1 below shows the considerable variation in technology spending as a percentage of revenues between different industry sectors. Banking and Securities spend on average approximately 7 percent, compared to only 1.5 percent for the construction sector. In addition, there are also considerable differences in the benefits expected from these project investments.

A deeper look at construction, the lowest-investing sector, shows how technology investments primarily focus on improving business operations and efficiency. Very little is invested in innovation and top-line growth.

Figure 1: Technology Spending by Industry. Source: Deloitte, 2016-2017 Global CIO Survey

To build on these findings, Figure 2 below illustrates the potential contributions of disruptive technologies to projects. As a starting point, project boards could deploy artificial intelligence and machine learning in their decision-making. Visualization tools such as digital twins can assist in building the business case. The metaverse can allow for prototyping a virtual version of the final product. AI could also be used for estimates and schedules based on previous similar projects.

A blockchain can enhance effective management of the supply chain through smart contracts, which are computer programs (transaction protocols) stored on the blockchain and programmed to run when predetermined conditions are met. Smart contracts typically serve to automate the execution of a process so that all participants can be immediately sure of the outcome, without any involvement of an intermediary or any time loss. That’s why blockchains have been called “trust machines.” The trust between economic agents that was traditionally provided by banks or notaries or lawyers, or in retail commerce by centralized actors like Amazon, Airbnb or Uber, can now be ensured by the blockchain and smart contracts running on it. Hence smart contracts lower transaction costs.

Figure 2: The Flight Path in the Digital World. © 2022 Distinctive Performance

For example, say you have a shipment of rice that you want to transport from the Sichuan province in China to London via the Gulf of Aden, Suez, and Gibraltar. Traditionally you needed several dozen separate bills of lading, a separate contract for each port of call, with lawyers and notaries involved for each contract. Now, you can have a single blockchain, like a decentralized, transparent, and permanent ledger on which all transactions are recorded.

This creates trust. And that trust is not some temporary or psychological jargon. It produces actual savings. According to TradeLens, a company co-founded by shipping giant Maersk and IBM; and dedicated to digitizing the global shipping industry, some $18 trillion worth of goods trade worldwide each year. Of these, $12 trillion, two-thirds, are shipped in containers. The shipping industry has traditionally been a bit slow, to say it nicely. TradeLens says that inefficiencies in global supply chains, primarily facilitated by paper-based logistics, decrease system performance by 15 percent. Using the Blockchain allows shipping companies to manage international trade in the cloud and regain some or all of those 15 percent lost.

Similarly, in the world of megaprojects, smart contracts act as a “single source of truth.” They enable the project to track every single item and element used in the final product’s production. Such transparency can provide the project with up-to-the-minute status regarding sourcing items, production locations, completion status, risk identification, quality management, and immediate payment to vendors that make up the supply chain.

In projects where the final deliverables are hard, tangible outcomes (for example, designing and constructing buildings using manufacturing techniques), robotics and built-in sensors during production can yield real-time data for immediate updating of the project’s Gantt Chart. As one of our clients put it, “The impact of Covid is that we can’t travel to the production yards. Though not perfect, beaming real-time video from remote sites back to the head office does provide a little more reassurance of the status of key items.” This definitely sounds like the future.

The Rise of the Machines

Disruptive technologies like AI, blockchain or metaverse herald new value and wealth creation possibilities for many investors and technologists. But then there is a much larger subset of humanity, people for whom the ascendance of these new machines lives as an existential threat.

Might the housekeeping robot one day get fed up with serving the morning coffee and turn into a killer robot? From one day to the next, the robot’s owners become slaves. We are tongue-in-cheek here, but these are genuine concerns for many people. When it comes to our jobs, careers, and employment, the big questions at the back of our minds are, “Will my job become obsolete? Will I be terminated? Worse, will I be unemployable, a little pawn in a world run by a super-intelligence?” These are the ethical, moral, and practical questions in the background for which solutions have yet to be invented.

In their book, The Age of AI: And Our Human Future, authors Henry Kissinger (the former US secretary of state), Eric Schmidt (the ex-Google CEO), and Daniel Huttenlocher (a computer scientist) set out to tackle such dilemmas and describe three possible relationships we can have with disruptive technologies:

Confine the technology and its uses where there is a destructive potential for humanity, for example in military applications.
Partner with the technology, much like a symbiotic relationship, where humans and machines work more effectively side by side. The autopilot on a plane is an example of this.
Defer to technology where it’s a better performer than we are. For example, computers do much better than us in crunching through large volumes of data and detecting hidden patterns.

AI Has a Black Box Too

Such distinctions are helpful, but something more sinister, something hidden from our consciousness, also needs to be exposed. Peter Haas, Associate Director of Brown University’s Humanity Centered Robotics Initiative, and many others working at the cutting edge of disruptive tech have become increasingly vocal about the detrimental impact of human bias unknowingly (or knowingly?) being incorporated into our algorithms.^[i] These biases live as lines of code constituting fundamental decision rules.

What type of decisions are we talking about? Take an AI bias that automatically rejects your job application because you happen to be black (or white, or female, or male, or 50-plus, take your pick). Remember that a human initially programmed the machine. This means the source code reflects that person’s subconscious and unconscious beliefs, thought patterns, and blind spots—in short, their bias.

A hidden bias that disproportionately favors one racial or age or gender group over another in crucial decisions such as hiring individuals is one thing. More chillingly, consider the impact AI bias could have in determining whether someone should be prosecuted or sentenced to prison, and perhaps even the length of their sentence.

The bias may not even stem from the source code itself but already lives in the input data fed into the machine at the outset. Worse, few people might even see their own prejudices since programmers or app developers are rarely trained to detect bias.

So yes, new technologies have enormous potential, but without solid human oversight and leadership, they could do as much harm as good. Technology is like fire: It can be used to build, or to destroy. Keeping technology in perspective and maintaining a healthy skepticism without becoming cynical is the hallmark of an intelligent leader.

And remember: Leaders are not needed when everything is going well. Leaders emerge in uncertain times, when the waters are rough, when things get out of hand. As long as everything runs like clockwork, a manager or even an administrator can do the job quite well. But when crucial things are missing, when projects are deadlocked, when conditions are complex or chaotic, then you have to lead.

To use a picture from the football (or if you prefer, soccer) World Cup: The leader is whoever happens to have the ball. And leaders move the ball where it’s not (yet), where it’s missing. Or if you prefer an artistic metaphor: “You only painted what is!” the grumpy magician scolds the lad Chi Po-shih, who is destined to become the greatest Chinese painter of the 19^th century. “Anyone can paint what is. The real secret is to paint what is not!”

^[i] Peter Haas. 2017. “The Real Reason to be Afraid of Artificial Intelligence” TEDx Dirigo. https://www.youtube.com/watch?v=TRzBk_KuIaM

This article is based on Gorilla in the Cockpit: Breaking the Hidden Patterns of Project Failure and the System for Success, just out.

About the Authors:

Vip Vyas is the founder of Distinctive Performance, partnering organizations to catalyze new levels of performance. For 30 years, he has worked on megaprojects in places like the Niger Delta, the Middle East, the North Sea, and China. He is an Executive Consultant at the Said Business School, Oxford University and has written for INSEAD, Duke and Forbes India. He and his family live in Hong Kong. And no, he was not his school’s cricket captain. That was another guy called Vijay, not Vip.

Dr. Thomas D. Zweifel is the award-winning author of 10 books. The ex CEO of Swiss Consulting Group serves on several boards. For 20 years, he taught leadership at Columbia University and St. Gallen University. He ran the New York City Marathon in under 3 hours—in 2:59.58, to be exact (you have to be Swiss to pull that one off) and named “Fastest CEO in the NYC Marathon” by The Wall Street Journal. Thomas, his family and their dog Motek live in Zürich.