Hacker News Reader

Comment by BrenBarn | Hacker News Reader

The thing is that that's not a conflict between data and lived experience, it's just a conflict between different sets of data. If you measure wealth and then you measure wealth relative to housing costs, neither one of those is "lived experience". If you do a survey on people's sentiments about the economy, that's data too. I'm skeptical of the term "lived experience" precisely because people tend to use it in arguments of the form "let's disregard data in favor of my individual preferences". But when you aggregate the "lived experience" of many people, you get data, and that data can be just as valuable as more anodyne economic data.

View on HN

The problem with countering lived experience with data, is that whatever data you can provide, it's very unlikely to capture the exact sentiment you're addressing. That doesn't mean one shouldn't try, of course. But one should be very open to the possibility that things are happening outside of your specific data.

The most infuriating example, to me, is the overuse of GDP. As if that should tell us everything.

No, it shouldn't tell us everything, but if someone makes a very data-oriented claim ("millenials will be the first generation poorer than their parents") and you return with data that shows the opposite, you can make a claim that the data is poorly gathered, etc.

But pivoting to the "but it's not my lived experience, bro" is weak.

If you made the claim that "millenials have it harder than their parent" then we're talking something where experience can be more useful.

Yes, but I guess I'd say that we should not attempt to capture an exact sentiment in making policy decisions. The bigger the decision, the more people are involved and affected, and the more people, the greater the variation in their sentiments. It simply doesn't make sense to try to somehow please each individual to address something like housing affordability in the US (or California, or Los Angeles, or even Monterey). The only way to do that is to aggregate sentiments into data. In doing so you lose precision about those sentiments, but that's good, because some of that precision is measuring idiosyncratic stuff that shouldn't play a role in solving the problem in question.

Reply on news.ycombinator.com