When quantum computing gains widespread adoption in the future, general knowledge about quantum computing — and skills for using quantum-enabled applications — must also become widespread. We can all recognize the importance of modern (classical) computer literacy today — in the workforce and in our recreational lives. So too, will we one day recognize the importance of quantum computing literacy?
In a post-quantum world, basic knowledge and competency with quantum computing will become critical, even if they do not reach the same level of importance as classical computing. In addition, specialized skills will also be needed. Today, an accountant, for example, needs to be well versed in specific specialized software and have general computer skills, but they do not need to understand how the CPU on their laptop works. Similarly, the future accountant may require specialized training in quantum-enabled technologies and general skills with quantum platforms. Still, they won’t need to understand exactly how the underlying quantum processors put qubits into superposition.
Let’s take a selective look at the history of classical computing to see where we came from and where we are today.
What are some differences between early and modern computers?
Many people over many years contributed to the creation of computing as we know it today. The early development of classical computing involved a small number of experts. Early computers were enormously expensive and had minimal functionality (they could perform simple calculations, but they weren’t solving complex systems of partial differential equations). In the 1960s, computers were difficult to use, requiring exceptional skills and knowledge to operate. Before the advent of second-generation programming languages (assembly languages), programmers were limited to writing in binary machine code (i.e., 0’s and 1’s). As a result, there were high barriers to the use and adoption of early computers, such as skill and economic obstacles.
Nowadays, classical computers are ubiquitous, and essentially anyone can use one with little training. Modern computers have as many applications as there are stars in the sky. Third- and fourth-generation programming languages, user-friendly development environments, and cloud-based learning platforms allow novices to create and run programs without understanding how the programs actually “work.” Indeed, much has changed.
If modern computers were still prohibitively expensive and required deep expertise to operate, they would still be a niche technology and not the world-changing powerhouses that they are today.
Likewise, if large-scale quantum computing is going to see widespread use, quantum devices and applications will need to have low skill and economic barriers for their adoption. Otherwise, they will remain niche and for specialized purposes only.
Who even truly understands computers, anyway?
What does understanding computers mean? Does it mean that you have deep knowledge of computer hardware design? That you’re an expert in software development? That you can write assembly code? Maybe it means that you’re well-versed in the OSI and TCP/IP layers and various protocols that go with them. Perhaps it means that you broadly understand how bits can be processed to achieve computation. Or maybe it means that you’re capable of using a computer to perform any number of daily tasks.
Regardless of how ridiculously complicated modern computers are, almost everybody can use a computer reasonably well for various purposes. Even if you don’t truly understand computers, you can still do your job and live your life. Nearly every modern business utilizes computers and requires a workforce with varying skills and knowledge of computers.
Similarly, think of an automobile. Modern vehicles can have hundreds of millions of lines of computer code, more components from more suppliers than you can count, and are, in many ways, absolute marvels of engineering. (Have you ever looked into how differential braking works? It’s incredible!) Yet, teenagers can operate these machines. Likewise, modern computers, like modern vehicles, are deeply complicated while, at the same time, they are relatively simple to operate. And as the technology improves over time, the machines become simpler and simpler to use — for example, autonomous driving or computers designed for infants.
Let’s consider the early days of computers and how many people “understood” or could competently use one. We don’t need to go as far back as Charles Baggage, Alan Turing, or the Antikythera mechanism to see that as the technology was developing, much fewer people understood it at all. Those who were developing the technology — at IBM, Microsoft, Apple, etc. — understood more of the body of knowledge at the time than someone working in the industry today has of the current body of knowledge. The modern body of knowledge is more extensive than it was even a few decades ago.
How did we go from a world where relatively few people understood anything about computers and where it took notable expertise to utilize a computer to a world where computers outnumber people, and very little expertise is required to use one?
Evolution. Over decades and decades, the technology, the knowledge, and the enabling peripheral industries, standards bodies, and supply chain ecosystems evolved from their nascent forms into what they are today. Consumers became increasingly aware of the utility computers could bring them (businesses certainly did). Over time, as the adoption of computers increased, the cost of purchasing and owning a computer decreased. It was a complicated process that simply took time.
Why should we care about how the complexity or accessibility of computers has evolved over the years? As we step back and look at the storied history of computing, we can take lessons learned and apply them to our future. These lessons can give us foresight into the future development of quantum computing and the goals we should set for ourselves moving forward.
What knowledge is required to build a quantum computer?
Here are highlights:
• Some understanding of quantum mechanics (which in turn requires an understanding of classical mechanics)
• The theory of quantum computation and quantum algorithms, and complexity
• The materials science for constructing physical qubits — and knowing the difference between a photonic, trapped-ion, superconducting, or topological qubit
• The engineering for entangling and controlling qubits
• The engineering to create stable environments for qubits to maintain coherence
• Specialized software for using the machines
• Quantum error correction codes
• And so much more
One of the bottlenecks often described by organizations working to build quantum computers is the lack of general expertise. While it is possible to find someone who is an expert in a handful of the above, there is a notable lack of a well-rounded understanding of what all is involved. And even if one person had a solid experience of everything required to build a quantum computer, more specialized knowledge would still be required to develop applications for the technology.
At the same time, nearly every organization involved in quantum computing will be quick to tell you of the future virtues of large-scale quantum computing (and rightly so); of how its future applications will be an unprecedented boon to humanity. But, for those applications to become widespread and usable by anyone other than a handful of world-class experts, the accessibility must increase, and the barriers (intellectual and economic) to using them must simultaneously decrease. This means then that for the much-heralded applications of quantum computing to become a reality, we must get to a point where the workforce will have enough knowledge and skills to competently use the future quantum computers.
If you are trying to sell a product that leverages quantum computing, you must have sufficient knowledge about quantum computing. If you’re developing a use case for a quantum computer, you’ll need a team with enough understanding to create and market your product. If today’s developers each required Ph.D.s and a decade of hands-on experience to make any meaningful software, then we’d have a lot less software available. Lowering barriers to developing excellent software is essential.
What’s next?
Companies producing quantum-related products and services will be well served to gradually make their wares more and more accessible to a broader number of people, geographies, and applications.
What will reduce the barriers? As was the case for classical computing: technological development, standardization, competition, incentives based on market needs, and experts able to communicate the concepts, applications, and their utility clearly to non-experts, including customers, partners, and the general public.
The more people and companies work on quantum-related technologies, the more that the technologies advance. As the technologies advance, more and more use cases will be discovered, more jobs will be created, and maybe even whole new industries will appear. As all of this happens, the barriers will slowly erode.