-
humanpropensity robinberjon Zuboff argues the methods of data capitalization encourage users to render their own data in this way. And data that was once exhaust (incidental) becomes surplus to harvest. That creates incentives to alter the system towards manipulation which one must labor to negotiate...Permalink On twitter.com
❤️ 2 Favorites
Mood +1 🙂
-
humanpropensity robinberjon A quick example here: I would argue that this process does indeed turn going to lunch as labor. You now must order lunch for pickup on an app, then you use Google maps to get there, then you pay using a specialized loyalty system, you check in on Foursquare, and so on...Permalink On twitter.com
❤️ 1 Favorite
Mood +2 🙂
-
humanpropensity robinberjon Zuboff's useful analysis here is that as the companies involved begin to profit not just by providing you the service but also by packaging your data up for use in predictive targeting, they become incentivized to force your actions to more closely adhere to their predictions...On twitter.com
❤️ 1 Favorite
Mood +4 🙂
-
humanpropensity robinberjon So, even if it doesn't *feel* like friction, what is presented as simplification of these systems is actually added difficulty of negotiation towards getting what you really want. I would absolutely count that new negotiation with the tech as labor...Permalink On twitter.com
❤️ 1 Favorite
Mood +3 🙂
-
humanpropensity robinberjon So the labor is not picking up lunch, but negotiating these systems to decide, find and retrieve lunch while unlocking the additional value they can provide through participation. A good lunch example for this: ...Permalink On twitter.com
❤️ 1 Favorite
Mood +3 🙂
-
humanpropensity robinberjon What if an algorithm predicts you prefer Italian & presents a preference-filtered feed but today you want Greek food? You must actively labor around the UIs of almost all those systems to render *more* data to the involved systems to help increase their accuracy and profit.Permalink On twitter.com
❤️ 1 Favorite
Mood +6 🙂