aron
@aronshelton
aron
@aronshelton
If you want to be read in the future, make sure you would have been read in the past. We have no idea of what’s in the future, but we have some knowledge of what was in the past. So I make sure I would have been read both in the past and in the present time, that is by both the comtemporaries and the dead. So I speculated that books that would have been relevant twenty years in the past (conditional of course of being relevant today) would be interesting twenty years in the future.
Artificial Intelligence and Humans In The Loop
Real thinking is to an AI like waves are to a lattidue line.
In an AI, there is genuinely no one home. It’s all model. No reality.
the map is not the territory; but neither is the model
metalabels and
PDF | This paper considers some of the limitations and possibilities of computational models in the context of environmental inquiry, specifically... | Find, read and cite all the research you need on ResearchGate
researchgate.netprovocations and
Data-driven research methods necessitate the collection of huge quantities of data and in doing so, they dismantle opportunities for paying close specific attention to the world. These methods also tend to obscure the many other ways of building understanding. Also, perhaps intentionally, data collection increasingly acts to maintain the status quo. We use data to study problems that would be more effectively addressed through simple political action. The impetus to “study the problem” ad nauseam gives the appearance of addressing an issue while perfectly maintaining the present state of affairs.
Despite the presumption that we're each in our own algorithmic bubbles, served up bespoke content — when something strikes a nerve, our networked lives ensure the signal travels instantaneously. It reaches all. Sometimes: the good. Often: the bad. And most likely of all: the ugly.