…or because of the group’s underrepresentation both in the training data and among system designers. Alleviating this problem by seeking to “equalize” representation merely co-opts designers in perfecting vast instruments of surveillance and classification.
…umptions about your skills. Other colleagues in technology assume you know everything data related. You know your way around Spark, Hadoop, Hive, Pig, SQL, Neo4J, MySQL, Python, R, Scala, Tensorflow, A/B Testing, NLP, anything machine learning (and anything else data related that you can think of — BTW if you see a job specification with all of these written on it, stay well clear. It reeks of a job spec from a company that has no idea what their data strategy is and they’ll hire anyone because they think that hiring any data person will fix all of their data problems).
I’ve seen companies implement OKRs across the whole organization, but reject team-level attempts to experiment with something like mobbing, eliminating story points, or foregoing Jira. That’s right: a broad blast radius mandate vs. local safe-to-fail experiments…and big-bang wins!