Dreaming of a Quantum Workplace
With good reason, there are a lot of people talking about the future of work right now, although this mostly turns out to be a discussion about addressing the "now of work".
Having a real conversation about the future of work is difficult. There is no evidence that Henry Ford ever said: "If I had asked people what they wanted, they would have said faster horses." But my consulting experience tells me that if I ask people what they want in their future workplaces, their ideas are often grounded in today's thinking. That's why I use human centered design in my work to elicit needs and wants, rather than just requirements.
The other issue is reflected in Amara's law, which states that “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”
I think one of those long-term technology effects will be because of quantum computing. I know just enough about quantum computing to realise that it is a lot less Star Trek and more like the early days of computing, although a lot better looking.
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Recently I had the opportunity to talk with Anna Phan, a Research Scientist at IBM and explore the future impact of quantum computing on our workplaces.
When I look over the horizon thinking about the future of work, I am trying to understand beyond just the surface impact on the employee experience, like will we all be wearing virtual reality headsets? What's more important is thinking about how technology changes the type of jobs we do, how we do those jobs, and finally our relationship to work.
One of the obvious links between quantum computing and the workplace is that scientists often like to use a cup of coffee to explain how it works and possible applications. Here in Australia at least, we have a massive coffee culture and its one of the things I miss about working in an office. I asked Anna about this and was wondering if I should be expecting a better espresso or flat white thanks to quantum computing?
She explained that coffee is a familiar substance and conveniently the caffeine molecule is a good example where the number of 'bits' we might use to simulate it with software and the number of 'qubits' (the quantum computing equivalent) is more divergent than other molecules, like water. This makes it a good candidate to show off the potential for quantum chemistry. But she also said, "coffee, however, is pretty good already."
Quantum chemistry is just one example of how quantum computing might be used to build models to help simulate or analyse data that might otherwise be hard to achieve with traditional computing. This clearly has big implications for professionals that currently enjoy roles where they have to combine expertise with existing software tools to make decisions or make recommendations. In this context, there is a natural leap for me to think about the relationship between quantum computing and artificial intelligence.
Does this mean we could replace some roles with quantum computing?
Anna was quick to caution me as my imagination started to run away on this idea. Just like traditional computing, quantum computing is only as good as the data and the models we create. She said while it could improve machine learning, context is important.
"We need to understand the data going in. But it also might mean that we may not have to think about or frame the question so specifically. In general terms this might make it easier for non-experts to define the problem."
If you are familiar with Dan Pink's explanation of motivation based on autonomy, mastery, and purpose we can think about this as an opportunity to create a workplace that is augmented by quantum computing and empowers both experts and non-expert employees to do more. Experts can focus on what they do best building models, while non-experts have better access to the distilled knowledge contained in those models.
We can also think about how quantum computing might provide a new strategy for addressing the productivity paradox. In today's workplace, we spend a lot of time in non-productive work trying to integrate information and action, rather than collaboration and innovation. If quantum computing can help us to reduce uncertainty or miscommunication, it will improve productivity.
This shift is part of a much bigger story of transformation that, along with the pandemic, is changing the requirements of our workplaces and what we do at work.
I've written before (on my original blog) about the history of the first commercial computer system developed in the 1950s, the "Lyons Electronic Office". I'd argue that this is the first case study of digital transformation, but also reflect on the point that this example is from seventy years ago.
Looking at quantum computing, we are right at the beginning of another journey where trailblazers and forward-looking businesses are starting to experiment and imagine the possibilities. But the similarities between the evolution of traditional and quantum computing are likely to diverge at a much quicker pace.
The point of cross-over where the real-world application of quantum computing starts to overtake traditional computing could happen anytime in the next three to five years. Effective quantum computing might then appear within the decade. And unlike the early days of traditional computing, you don't need to build your own or have access to a university to start experimenting.
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Anna thinks it's good to see corporations partnering with IBM to start applying it to real-world problems, so they can learn where to apply it and increase their understanding of how to apply it. For example, Mercedes-Benz, a Daimler brand, is using IBM's quantum computing services to learn how the technology could help create advanced batteries for electric cars. But she would like to see more university students and business people learning how to use it.
"It would be exciting to see people using it accelerating certain complicated problems and using quantum computing to make the use of machine learning better."
If you are planning for the real future of work, now might be a good time to start testing and learning with quantum computing.
This post was sponsored by IBM.