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8 ideas (for PMs building machine learning products) — week of Feb 23
Trying something different this week!
Instead of covering eight unrelated ideas I learned this week, I’m sharing what I learned from a deep dive on how to be a product manager (PM) of machine learning (ML) products.
Note: I tried to stay away from PM basics (“solve a real problem for your users”) and ML basics (“this is the difference between supervised and unsupervised learning”) and focus more on the intersection of product and ML.
Other 8 ideas posts I’ve written:
Top 3 🏆
1. Build user trust with “seamful design”
Humans don’t take advice from sources they don’t trust.
ML models are usually black boxes. Their lack of transparency makes it hard for us to trust them and take action on their results.
Outside of getting good results in the first place, one of the biggest hurdles for ML products is presenting the results to the user in a way that he or she can trust them.
