The future of AI in learning: what we learned from Microsoft at NextSteps 2018

NextSteps, NetDimensions’ global users conference, gave us the chance to hear from Nigel Willson, Global Strategist at Microsoft. He told us about the vast potential of AI in learning.

A photo of Nigel Willson, of Microsoft, talking about AI in learning at NetDimensions' NextSteps 2018 event

The rapid rate of change in business and technologies is exponential. When you use technology, the level of acceleration increases even more – leading to unprecedented change.

In the transportation industry, to name one of the sectors witnessing a learning revolution, new technologies such as self-driving vehicles and piloting assistance are transforming business, products and training.

So how can Artificial Intelligence (AI) help us to find learning solutions and work more effectively? In a fascinating and wide-ranging talk at NetDimensions’ NextSteps 2018 conference in London, Microsoft Global Strategist Nigel Willson outlined a few of the ways AI will profoundly change the future of learning.

Here are a few things we learned from his exciting insights.

Where are we on the AI journey?

As many people who have experienced AI know, we are only really at an early stage of developing the technology around AI in learning.

However, when we look back and think about what didn’t exist ten years ago, such as iPhones and Uber, we can reflect on seismic progress in AI and broader technologies.

Nigel has seen a huge amount change in his 20 years at Microsoft, but little compares to the pace of new technologies emerging and advancing during the past three or four years.

This is demonstrated by Microsoft’s investments in areas such as the Internet of Things – the name given to the Internet-powered network of computing devices embedded in everyday objects.

A photo of a human eye as part of AI in learning

AI’s powerful recognition capabilities

Nigel’s opening question, asking how his audience members were enjoying their day, would usually be taken rhetorically.

AI’s photo recognition capabilities, though, could genuinely have allowed him to ascertain how people in the room were feeling.

As well as reading faces, AI’s recognition capabilities offer all sorts of potential, even being able to tell the age of those in attendance.

And it doesn’t stop there. Some of the other capabilities of AI in learning include:

  • Language translation
  • Speech recognition
  • Gesture recognition
  • Speech synthesis and transcription

With a success rate above 95%, technology is now more accurate at recognizing human speech than people are. Bearing that in mind, it’s understandable that inventions such as Amazon’s virtual assistant, Alexa, have proved so successful.

It’s also unsurprising that AI is permeating our smartphones, technologies and everyday services and products.

As further impressive examples, you could use your voice to tell your computer to save a Powerpoint deck in another language, or deploy AI to translate a speech while the speaker is talking.

Another intriguing aside is the ways in which AI can work when recognizing people in videos. When it sees a well-known person, for example, AI can automatically create a biography based on Internet pages, as well as adding a timestamp to show where that person appears in the video.

A photo of a network of constellations as part of AI in learning

How will AI in learning affect jobs?

Despite high-profile stories about how robots will replace workers, the truth for organizations and employees is likely to be rather less intimidating.

The most notable change, if there is to be one, will probably see people who don’t embrace technology and AI in learning replaced by those who do.

Continual learning has a crucial role to play in this – working with technologies such as AI requires a new approach in which learning becomes a lifelong process, rather than something we do only when we are studying or in a new job.

This is a mindset Satya Nadella, who became CEO of Microsoft in 2014, emphasized in shifting the company from a ‘knowing’ to a ‘learning’ organisation.

Technology will also create jobs that don’t exist yet. For example, quantum engineers are likely to be in high demand from companies within the next five or 10 years.

A photo of a FitBit used for AI in learning

AI in learning offers dazzling possibilities

Whether we’re working, keeping active or resting, we all exude data. The amount of data now available is creating more personalized experiences than ever before.

FitBit trackers, for example, were used to carry out analysis of six million nights’ worth of sleep. With this data, they were able to analyze different states and work out the optimal time to wake up users based on their sleep patterns.

Together with this, the power of cloud services allows information to be collected about who learners are, what they’re connected to and their preferences.

In a working environment, this could allow employee’s calendars to be analyzed in order to decide whether they have sufficient time in the month to carry out a piece of learning.

If AI shows that they don’t, the amount of time allocated for the training could be increased, leading to higher completion rates.

Personalized learning can greatly improve training programs. Research has shown that learners who receive personalized instruction outperform 98% of those who don’t [1].

The cloud, meanwhile, provides organizations with highly cost-effective data storage and constantly updated functionality.

A photo of Nigel Willson, of Microsoft, talking about AI in learning at NetDimensions' NextSteps 2018 event

AI in learning: from the shock of the new to an everyday asset

From data stored on synthetic DNA to a suit you can wear that allows you to feel sensations from an online game, AI has already led to some incredible developments.

As the technology becomes faster and more accurate, the pace of change will quicken. Rather than being something we buy, AI will simply become part and parcel of organizational learning.

Making the most of this opportunity, as Nigel adroitly showed our NextSteps 2018 guests, offers huge potential for organizations on the path to successful learning.

Excited by the potential of innovative technologies? Contact us today to find out about NetDimensions’ connected learning solutions.

Additional source:
[1] Benjamin S Bloom (June 1984), ‘The 2 sigma problem: the search for methods of group instruction as effective as one-to-one tutoring’. Educational Researcher, volume 13 (6).

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