For this interview I spoke with Marc Zao-Sanders, CEO of Filtered, a platform that makes learning recommendations. In our daily life, we see recommendation engines in action all around us, such as Spotify and Netflix.
Recommendation engines and learning are a natural fit. The process of seeing patterns in what an organisation or an individual needs, and then finding the right learning experience, is a core function of L&D. This is something a recommendation engine can do.
Marc uses a bit of machine learning jargon at one stage: collaborative filtering. A basic description of a collaborative filter is that it’s a series of techniques that looks at a user’s past actions and interests, and how they relate to those of other users, and makes recommendations based on user behaviour interrelationships.