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Augmented Reality: Enabling Learning Through Rich Context

This article is more than 8 years old.

By John Hagel and John Seely Brown

In his 1992 novel “Snow Crash,” Neal Stephenson envisioned the Metaverse: a three-dimensional manifestation of the Internet in which people interact and collaborate via digitally-constructed avatars. In the decades since, technology has advanced to the point where such a place no longer seems like science fiction.

Stephenson’s Metaverse is a virtual reality space, a completely immersive computer-generated experience whose users have minimal ability to interact with the real world. In contrast to this fictional vision is today’s burgeoning field of augmented reality (AR), a technology that superimposes visual information or other data in front of one’s view of the real world.

One of the most well-known AR technologies, Google Glass, projects data onto the upper right corner of the wearer’s glasses lens, creating a relatively seamless interaction between that information and reality. Today, such technologies tend to get noticed for either their novelty value or their role in privacy concerns. In the longer term, they can have tremendous potential to change the way we interact with our technology and with each other.

When Google Glass was first released, many analysts focused on its potential to change the way media was created and consumed, viewing it essentially as a head-mounted smart phone. Since then, some people have reacted negatively to use of a device that can constantly film one’s surroundings or relay social media to the wearer in the middle of a conversation. When the devices were used in ways deemed intrusive, users sometimes received negative reactions from others. While the circumstances surrounding these instances of intrusive use may be considered controversial, they seem to have contributed to limiting AR’s potential as an integrated social media tool, at least for the time being.

Perhaps in reaction, the focus on AR has shifted to its role in business—its ability to supplement workers’ perceptive abilities, enhancing efficiency. AR-enabled headsets have shown promise as real-time data translation tools, which can reduce the need for offsite data recording and tabulation. DAQRI Industrial 4D, for example, has developed an AR-integrated hard hat that can superimpose data across the wearer’s field of view for a variety of industrial applications. (DAQRI presented their technology at Techonomy 2014.) Workers can view instructions or maintenance/performance records for a particular piece of equipment, without having to process or reference the information on a separate device. By presenting data in context and in real time, AR has helped make data use less an actuarial process and more a source of immediately actionable information—a kind of conversation.

Generally, the conversational aspect of AR is a fairly recent focus. Many of the use cases exploring the technology’s potential value have to do with streamlining repetitive actions. Improving supply chain processes, reducing waste, and increasing operational efficiency are priorities for most organizations, and AR can help give some companies a substantial edge. From real-time inventory management to maintenance records, AR technologies provide greater detail and more supporting data, which can improve both efficiency and accuracy.

But efficiency is only one component of business competitiveness. Many roles that AR might supplement may soon be usurped by advanced robotics and other forms of automation. What is the value of AR when the people it is supposed to enhance are no longer needed to do the job? More fundamentally, in an increasingly complex and unpredictable world, many people consider increased efficiency secondary to the ability to collectively digest and act on rapid changes—in essence, the ability to learn.

In this scenario, AR is in a position to gain value. Collaboration is the bedrock of innovation, and AR enables us to learn faster by working together. To do so, we typically rely on fundamentally human capabilities—imagination, creativity, genuine insight, and emotional and moral intelligence—that are difficult or impossible to automate. In the same way that AR enables us to use data more deeply, it has the potential to help us communicate more deeply and meaningfully with each other.

Recent developments in AR have improved its ability to help us learn and communicate. Perhaps the most pertinent examples are systems that let users share context remotely. For example, while today’s online learning spaces can connect individuals on a massive scale, they can also limit context. Text, pictures, and video are helpful, but face-to-face interaction is often best at conveying meaning. Recent entrants such as Microsoft’s Hololens and MagicLeap (where author Stephenson serves as “Chief Futurist”) show potential to share more information across greater distances, in a richer context. Hololens, for example, allows people to convene in a remote space by layering holograms over their current reality. By projecting data and 3D object models, and using advanced avatars, two individuals on two different continents could, in theory, discuss how to repair a piece of equipment on Mars as if they were both standing on its surface. As this kind of AR technology reaches maturity, many AR systems will combine the networked capabilities of existing online communication with the rich context of in-person meetings. This is an example of the true value of AR.

This is not to say that AR can’t also be a powerful tool for increasing worker efficiency, or providing effective, context-rich social media interfaces. All of these potential outcomes are complementary benefits of the same mature capabilities. As we pursue more capable, less obtrusive technologies, AR has the ability to greatly change both our work experience and the ways we communicate. More fundamentally, however, as much of the world shifts its emphasis from economic efficiency to effective learning, it’s likely that the utility of AR will follow suit.

John Hagel III, director at Deloitte Consulting LLP, is the co-chairman of the Deloitte Center for the Edge based in Silicon Valley. John Seely Brown is the independent co-chairman of the Deloitte Center for the Edge.

Original article published at Techonomy.com.