_{By Matthew R. Versaggi – Head of Education, Quantum Strategy Institute}

The preparation of a quantum workforce for industry use is significantly different than the preparation of a workforce to create quantum hardware technology. There are stark differences in the stakeholders (technologists vs. managerial), the key spaces (security, algorithms/programming, specific domains like healthcare), and the pool of information leveraged to educate those various stakeholders. This publication explores those topics and highlights the key learnings from the quantum educational journey of a Fortune-5 Healthcare Organization.

Producers vs. Consumers Divide

Quantum Computing can be divided up into two camps, those whom produce the technology for industry to use, and those whom consume that technology to solve problems of note for organizations. The innate skills set (and corresponding educational requirements) are significantly different by default. The producers camp needs dense quantum physics, materials science, and opaque mathematics as skills, whereas the consumer camp needs professional consultancy skills along with software engineering. That skills/education gap that is yet to be fully recognized by the quantum computing industry as evidenced by the fact that 99% of the publicly available educational materials cater to the producer camp and less than 1% of those materials cater to the consumer camp. This situation is a significant impediment to the adoption of QC in enterprises that the quantum industry needs to solve for.

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Currently, QC producers have little reason to educate the QC consumers (or they don’t know they need to and/or are frustrated that they have to for adoption/socialization purposes).  Consequently , the near term finds a far larger producer group than consumer group. In time however, that situation will reverse (as we have witnessed with the democratization of AI), and the consumer group will eclipse the producer group.

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From a skills development perspective, the educational space for the consumer group is massively underserved and is easily overshadowed by that of the producer group.  This situation isn’t permanent however, and the consumer educational space will grow to critical mass just like it did in the history of the classical computer space, except at a different rate. The classical computer space was dominated by hardware engineers who toiled to make computation devices better until that hardware matured to the point where the software could then take over and mature on it’s own. Post that hardware epoch in history (computer engineers), computation moved from the lab to the office, and software engineers (computer science) grew in mass and importance as a group.  We can realistically expect to see the same pattern in QC, albeit with the rate of change being significantly different.

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Technical vs. Executive Education (AI Use-Case Lessons)

The use-case of Artificial Intelligence is an excellent case study of the adoption of cutting-edge technologies by industry and their educational undergirding. This experience has lessons which will inform us of the best practices which can be employed when it comes to quantum computing, albeit with a few very important twists.

Technical Education

The AI use-case has shown us that technical education (once matured) is a fairly pragmatic, methodical, reliable, scalable (through the modern online educational frameworks) approach that is replicable and produces consistent quality engineers of a respectable quality. The AI use-case has demonstrated that the technical education of software engineers at scale is possible, straightforward, and therefore is not a serious threat to the adoption of AI in industry. Generally speaking, we can reasonably expect that to also be the case (eventually) with the consumer side of quantum computing technical education.

There were a few interesting phenomena we observed from our experiences training software engineers in quantum programming, one in particular dealt with an individuals “transition vulnerability” and the resulting point of “Quiescence” when embarking on their quantum educational journey. 

We observed that students will panic for the first 8 weeks of the educational journey only to begin to settle down as week 12 approaches. The causes for this phenomenon are that QC is a completely new field, with unavailable adjacent concepts, experiences, metaphors to create intellectual foundations from that they can tether to for intellectual growth and progress. They are quite literally learning the majority of the domain from scratch, as opposed to it building on top of previous foundations they have developed earlier in their educational experiences. This creates a good deal of anxiety that educators would be wise to anticipate and move to mitigate, as this phenomenon appears to be common across many students in this space.

Executive Education

The AI use-case has also shown us that the education of business executives with an eye toward developing the key conceptual concepts and understanding which will undergird strategic thinking has proven to be  far more difficult, and is a legitimate impediment to the adoption of AI in industry. There are reasons for this phenomena that need to be understood if we are to develop an effective approach for educating business executives about the strategic value of quantum technology, which is conceptually much harder than AI is.

Business leaders parlay in conceptual models (and their corresponding linguistics) as their stock & trade – the accuracy of these mental models and the reliability of their organization’s behaviour per those intellectual models determines the leaders’ value (and influence) within their organization.

When new technology appears on the horizon, its adoption by business leaders tends to correspond (to some degree) to its ability to be understood, and that is closely linked to how closely it is related to something that is already well understood by those business leaders, such as the mobile phone and fax machines for examples.

Artificial Intelligence was not closely related to much of what typically understood in the executive community, and therefore it’s adoption lagged until enough executives were educated well enough to create a “pull effect” for the technology – this was a painful lesson, and an even harder, longer, more expensive fix.

Quantum computing as a domain makes the Artificial Intelligence experience look like kindergarten in comparison. There are literally no doppelgangers for nearly all of the critical quantum concepts in the classical world to tether to for understanding, and there are few concepts remotely adjacent that can be used as bridges to shepherd the executives mental models from the classical world to the quantum world with. As an example;  binary/digital concepts are black/white or 1’s and 0’s which is easy to understand in general, quantum on the other hand mimics nature and is probabilistic, which is much more difficult for humans to comprehend, much less articulate.

To those executives who live and die using human language as their primary vehicle to communicate precious concepts with accuracy and confidence to their organizational constituency, this is a big problem. To quantum producers who need to develop markets in which to sell their products, this is a much, much bigger problem.

In short, the executive education for QC will follow the typical patterns witnessed in the AI space, except that the adjacent concepts, experiences, metaphors, and allegories  to create intellectual foundations from (a space executives live their lives in) will be nonexistent. Because of this, the approach to effectively ‘reach’ the senior leader space must be very well thought out to engineer the narrative to the absolute nuance given where QC sits on the concepts path to executive adoption below.

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Why Roll Your Own QC Education?

Given that 99% of the QC educational materials in existence today are geared toward the “producers” camp (those making the tech), and less than 1% of the materials created in the wild are geared toward the “consumers” camp (those using the tech), then there are very few options available today to undergird an organization’s quantum journey unless they decide on rolling their own.

In our organization, we decided on rolling our own nine-month long program and will seek to open-source those resources in the future to benefit the industry at large, however, that was a 1.5+ year investment to produce educational materials of sufficient value to do the job properly. Without pre-curated materials readily available, organizations have little choice at this juncture at time but to create their own materials, or hire out to a big consulting firm who has pre-curated those educational materials.

Matthew R. Versaggi is Head of Education of the Quantum Strategy Institute and Senior Director of AI and Cognitive Technology at UnitedHealth Group, possessing a unique blend of business, technology, entrepreneurial, and academic
expertise

Copyright 2021 Matthew R. Versaggi