Our daily digital interactions rely heavily on recommender systems. Netflix, Google, Amazon, Spotify, LinkedIn, etc… all watch what we do to some degree to learn about us. The data gathered is used to recommend the best fitting products, services, or persons. In effect, a recommender system simply delivers suggestions based on behavior or characteristics that have been tracked by the system. Why do companies do this? As the Spotify Research Team states “Users are overwhelmed by the choice of what to watch, buy, read, and listen to online”(1) even with the best, most helpful intentions, to some degree this leaves us feeling as though many decisions are being made for us.
If you would like to geek out a bit more on this recommender, algorithm concept, check out Spotify’s AI called BaRT (“Bandits for Recommendations as Treatments”) (2) below is an article written by a Spotify team… the title does not sound threatening at all (lol): “Explore, Exploit, and Explain: Personalizing Explainable Recommendations with Bandits.”
Recommendation systems have a place but where the LinkedIn recommender system suggests persons based on your network, working history, and interests, these may not be the people or groups you would choose for yourself. What does that leave a professional seeking growth to do? You can take control of this system by choosing to be part of a group of like minded people doing similar work with similar approaches. Our team at Ready Learner One and ChangeMaker are hard at work linking like minded people through our learning platforms. Interested in seeing if this is the right choice for you? Check us out:
Ready Learner One Innovations Beta Lab: https://readylearner.one/innovationsbetalab/
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Let’s Connect… I recommend it,
Micah (not a Bandit, a real human being reaching out)
- Marius, H. (2021, November 23). Uncovering How the Spotify Algorithm Works – Towards Data Science. Medium; Towards Data Science. https://email@example.com?p=4d3c021ebc0
- McInerney, J., Lacker, B., Hansen, S., Higley, K., Bouchard, H., Gruson, A., & Mehrotra, R. (2018). Explore, exploit, and explain. Proceedings of the 12th ACM Conference on Recommender Systems. https://doi.org/10.1145/3240323.3240354