By Rhys Giles, Product Director, Fuse
We loved our tech talk session ‘Cracking the Content Blackbox’ with Learning Sharks’ Christopher Lind. Christopher inspired us to delve deeper into explaining just how smart the Fuse platform is, and how Fuse is using Machine Learning like no other L&D platform on the market today.
When it comes to AI and Machine Learning, there’s a lot of hype to sift through to get to useful and practical examples of how the technologies are saving enterprises time and money while introducing useful innovation.
Frustratingly, sometimes the two terms are used interchangeably, when in reality, AI should refer to intelligent technology that has the potential to simulate human thought processes and behaviour. Machine Learning on the other hand should always be looked at as a subset of AI that helps machines to learn from data.
The irony in the L&D world is that (for an industry entirely devoted to learning) few companies are actually using Machine Learning usefully, and even fewer still can demonstrate a machine’s ability to learn - that is, to use data and become more accurate over time in actions.
In L&D, most companies are still very much focused on how Machine Learning can aggregate content for individual learners. Fuse on the other hand is doing some truly innovative things with Machine Learning which are making a real difference to our customers.
If you’re asking yourself what Machine Learning has really done for you lately, and the answer is ‘not as much as it should have done,’ read on to hear about how we are innovating with Machine Learning to create real-world, every day impact for our customers.
Content Blackbox Versus the Corporate Brain
You can throw a search bar into any L&D platform, but if all that comes out of a search is just a list of information with no context or relevance, then your corporate learning initiatives won’t get very far in adding value to your business.
Chief Learning Officers, HR and learning directors, ask yourself: does your L&D system actually understand all of the content you’ve created or licensed? Or are you dealing with a content blackbox, where you have no transparency at all?
It’s time to move on from the content blackbox to embrace what Machine Learning can actually do for a business. We like to call it building your corporate brain, and it means that after all the AI tools we use to crawl, analyse and make sense of your content have done their thing, we can apply some serious Machine Learning in the form of our Knowledge Intelligence (KI) Engine.
A bit of KI goes a long way, and it can act as a learner experience layer to help provide the easiest and most relevant content, research and recommendations. The content blackbox quickly evolves into a corporate brain, which is not static, but rather an individualised body of knowledge that becomes more relevant and accurate over time as Machine Learning understands what is the most critical knowledge for an organisation.
Whereas a content blackbox simply gets added to like a library, a corporate brain is a living, breathing entity that is constantly learning. Think of Machine Learning as a master at identifying patterns, able to analyse things faster and more efficiently than a human ever could. Now think about that in terms of your digital estate of knowledge. Machine Learning is constantly learning from your content libraries, like LinkedIn Learning and others, and it’s learning from things added to Sharepoint or other third party integrated systems.
It’s a great example of how Machine Learning is helping real-world problems. Fundamentally, one of the biggest challenges many organisations face is that they don’t realise what knowledge they have. With Machine Learning-led Knowledge Intelligence, companies can overcome that challenge, while also making better use of their investment in content creation and content libraries.
What Productivity Crisis?
Between The Office for National Statistics and the BBC, we’re rarely without a story about the UK productivity crisis (luckily, the FT says the British productivity crisis is less acute than previously estimated.)
When dealing with a situation where experts in the workplace spend up to 30% of their time answering the same questions and skilled workers spend 20% of their time trying to find all sorts of questions in their job, learning seems an obvious place to start tackling the productivity conundrum. When looking for real-life, practical efficiencies that Machine Learning can introduce, productivity improvements are a go-to business use case.
We’ve already explained how Machine Learning-driven Knowledge Intelligence is making learning better and effective, but what we haven’t mentioned is the productivity gains this also introduces.
Think about it: all of the work the Knowledge Intelligence Engine does to crawl, tag and analyse knowledge is one thing. It makes sure you find the answer you want to the question you actually have. As Fuse founder Steve Dineen says, if you’re James Bond, you don’t have time to watch a whole thermonuclear video course. All you want to know is whether you need to cut the red wire or the blue one so that you can save the world. Our Knowledge Intelligence Engine and strategic search results give learners that simplicity, ease and convenience.
But Machine Learning is taking it one step further. It’s ‘understanding’ the informal, social part of learning that happens in Fuse. People ask questions within the platform, and others comment and answer them. The Machine Learning-led corporate brain knows that if someone with authority has answered a question and the answer is matched as correct, then it can rate that answer as high quality and use it above other answers.
It’s taking structured knowledge and unstructured knowledge together, and learning from both to improve its understanding and accuracy to pinpoint the best knowledge to serve up in answer to questions.
From a practical point of view, it means that experts within a business don’t have to spend all their time answering what are often the same questions - they can do it once, with Fuse. And learners can search for and successfully find the best answers they need to complete tasks within the flow of work, saving that 20% of their time for more useful endeavours.
Solving the productivity conundrum is just another example of how Machine Learning is helping with real business problems that can actually affect the bottom line in the enterprise. We’re looking forward to introducing you to others as we roll out more AI and Machine Learning based solutions.
To wrap up, we’d like to extend a big thank you to Christopher Lind for hosting us - as always, a great time was had by all, and we covered a lot of inspirational ground. Readers, if you liked what you saw, head over to Learning Sharks for many more great learning tech talks.
Beyond this, if you’d like to learn more about how a digital learning platform powered by AI can put your workforce ahead of the rest, download our latest ebook today: 4 Ways AI Can Power Up Digital Learning.
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