Accenture’s Ryan Shanks outlines how AR and VR are transforming the workplace, and how we can tackle the challenges faced by human-machine collaboration.
Ryan Shanks is director of The Dock, Accenture’s global R&D and innovation centre, which is based in Dublin’s Silicon Docks.
Here, he discusses The Dock’s constant experimentation as a workspace, and why immersive technologies are now moving from hype to reality.
Is there a forward-thinking approach to the workplace in The Dock? If so, how have you achieved this?
There is. It’s not because we have followed any number of trends but because we are constantly experimenting. Collaboration, for example, is crucial for us at The Dock. And yes, if you walk in here, it’s a very open, vibrant environment. It facilitates those collisions with people from different teams and groups so that ideas and connections manifest themselves as they go.
But what we are also seeing is that one person’s collisions and vibrancies are another person’s distractions. There is a need for people to have quiet space. This notion of a constant open plan is actually a challenge. We have meeting rooms, there’s demand for project space that’s walled off and we are constantly looking at how we reconfigure the building.
There was initially an assumption that people would move around the building and change desks quite often but I think, with human behaviours, that’s not how it is playing out, particularly on a day-to-day basis. People do sit in different parts of the building depending on what projects they are working on, but there is also a sense of team identity. We have more than 300 people in the building and what I’ve noticed is that each of those teams, although they identity as being part of The Dock, they also identify as being part of their individual teams.
There is a natural tension between collaboration and individuals moving around. People often get a sense of identity in a common purpose with a group of people that endures past one particular project. So, it’s about striking the balance between these.
As well as having a progressive workspace of your own, Accenture’s research teams are known to test and develop future workforce technologies, which they roll out to other organisations and industries. What are the technologies and solutions you’re most excited about, particularly from a Dock perspective, in the next year?
One area that is growing and is exciting is our work in extended reality or augmented (AR) and virtual reality (VR). For a while, this has been something that people have largely seen as novel or as a game. We are now seeing it being used as a learning tool and as augmentation in how people do their work.
For example, our teams are working on a project we call BioVR, which is a VR tool that helps train people to handle highly volatile or biological materials in controlled environments. We showcased this to a major retailer in the UK and they have now invited us to go into their warehouses and see how VR and AR can work in their supply chain and logistics centres. So, VR and AR are on the horizon as becoming mainstream in the workplace – that’s something that is moving from hype to actual application.
What is the biggest challenge in achieving a vision of human-machine collaboration at work?
There is too much focus on the machine. In human-machine collaboration, the human is primary, and the machine is a tool. The question is, what needs do humans have that machines can fulfil? We shouldn’t be too tech-centric – the vision lies in the hands of the humans, not the machines.
The challenge is in the approach. If we understand what challenges workers and employees face, and then look at how emerging technologies can help them to do their work better, you get ‘use cases’ that work. If you have a piece of tech that you are excited about and you want people to use, and you go in search of a problem, the likelihood of it being adopted is low.
How cautious do you have to be about preventing negative outcomes (such as biased algorithms) at the early development stage before these technologies rapidly roll into the workforce?
Bias is certainly one. We’ve seen one example with a facial recognition software that works quite well for white males but struggles with people of a different gender or ethnicity. Diversity needs to be considered at an early stage to ensure the solutions we create are fit for purpose.
And, in so many areas of emerging technology, we need to continuously respect privacy. There are plenty of effective ways that people’s data can be used for their benefit, but we need to always be conscious that users are aware of what that data is being used for, and they need to have control over it.