Thank you for taking the time to publish this. It’s kind of sad to see companies painting a picture of some kind of internal intellectual vibrancy or freedom or something when in fact it’s more of a recruiting or morale gimmick, or is just dominated in practice by performance demands. I have the sense that utilization numbers are low because it’s actually quite hard to formulate something compelling to work on for oneself, even absent any demands for justification or approval, and one of the reasons that people work at companies is to be given something compelling to work on (though this often isn’t what actually happens).
Your post triggered the following thoughts in me:
At best you might hope that 20% time would harvest insights from “line-level” employees about (1) what tools could be built to improve their own productivity, (2) what features customers would like (especially when the line-level employees are a representative sample of customer base itself), and (3) what super cool things could be built that are just hard to understand unless you’ve pondered it over and over for years. Companies attempt to harvest and filter such insights (to whatever extent they really exist) through the ordinary reporting structure, but there are going to be some such insights that good but systematically fail to make it through, especially in category (3).
So we have employees who are doing a job that gives them, as a byproduct, some kind of insight that we want to get access to. This is really a lot like the problem of eliciting latent knowledge, in which we have some powerful machine learning system that has demonstrated competence in some domain (e.g. predicting the sensor-visible consequences of plans) and due to its competence in that domain we suspect that it has an internal understanding of something that would be useful to us (e.g. knowing whether its own sensors have been tampered with). This really seems like a non-vacuous connection to me. Interesting.
Thank you for taking the time to publish this. It’s kind of sad to see companies painting a picture of some kind of internal intellectual vibrancy or freedom or something when in fact it’s more of a recruiting or morale gimmick, or is just dominated in practice by performance demands. I have the sense that utilization numbers are low because it’s actually quite hard to formulate something compelling to work on for oneself, even absent any demands for justification or approval, and one of the reasons that people work at companies is to be given something compelling to work on (though this often isn’t what actually happens).
Your post triggered the following thoughts in me:
At best you might hope that 20% time would harvest insights from “line-level” employees about (1) what tools could be built to improve their own productivity, (2) what features customers would like (especially when the line-level employees are a representative sample of customer base itself), and (3) what super cool things could be built that are just hard to understand unless you’ve pondered it over and over for years. Companies attempt to harvest and filter such insights (to whatever extent they really exist) through the ordinary reporting structure, but there are going to be some such insights that good but systematically fail to make it through, especially in category (3).
So we have employees who are doing a job that gives them, as a byproduct, some kind of insight that we want to get access to. This is really a lot like the problem of eliciting latent knowledge, in which we have some powerful machine learning system that has demonstrated competence in some domain (e.g. predicting the sensor-visible consequences of plans) and due to its competence in that domain we suspect that it has an internal understanding of something that would be useful to us (e.g. knowing whether its own sensors have been tampered with). This really seems like a non-vacuous connection to me. Interesting.