A review by epochellipse
The Glass Cage: How Our Computers Are Changing Us, by Nicholas Carr
3.0
Decent read.
My main takeaway is about automation's changes to the workforce. While it increases productivity, it concentrates the monetary benefits on that productivity to those who own the automation. Think loss of middle class factory jobs, while increase in jobs is primarily in the service sector. Or gig economy work such as driving Uber/Doordash, selling on Etsy, etc driving much more significant profits to the clearinghouse.
This dovetails well with the quote towards the end of the book: "It strains credulity to imagine today’s technology moguls, with their libertarian leanings and impatience with government, agreeing to the kind of vast wealth-redistribution scheme that would be necessary to fund the self-actualizing leisure-time pursuits of the jobless multitudes."
The notes on automation in Electronic Medical Records was also SUPER interesting, so definitely going to look into that more. Basically that automation can promise higher quality of care IF it's interoperable. But because it's not open source (because proprietary programs and forcing brand loyalty), it greatly increases spending, while not increasing quality of care. Not to mention that automation can disrupt workflows and alter processes in ways that have adverse effects for patient outcomes.
As a UX researcher, I was also interested that automation for software onboarding can decrease task time in the short term, but *increase* task time in the long term due to decreased learning. This has a lot of implications for onboarding processes based on expected frequency of use.
Main drawback: The author clearly lacks understanding on the cognitive and neural side of things. There are are a number of non-explanations (pretty much any time he mentions "neurons"), as well as points where he's straight-up wrong. Example: purporting that novices do not have mental models until they gain expertise, and that those mental models are explicitly "dedicated assemblies of neurons." Which means... absolutely nothing. Like even a novice has a mental model of the task they're trying to achieve, it changes as they gain experience or more information. It's a top level process, and referring to it as "assemblies of neurons" gives it the (wrong) impression of being inherently bottom up.
I also really think he should read up on some of the topics that he was trying to touch on, but was not getting there. Such as optimal arousal theory (really ties into aspects of flow) and heuristics (necessary for talking about novice vs expert task learning).
My main takeaway is about automation's changes to the workforce. While it increases productivity, it concentrates the monetary benefits on that productivity to those who own the automation. Think loss of middle class factory jobs, while increase in jobs is primarily in the service sector. Or gig economy work such as driving Uber/Doordash, selling on Etsy, etc driving much more significant profits to the clearinghouse.
This dovetails well with the quote towards the end of the book: "It strains credulity to imagine today’s technology moguls, with their libertarian leanings and impatience with government, agreeing to the kind of vast wealth-redistribution scheme that would be necessary to fund the self-actualizing leisure-time pursuits of the jobless multitudes."
The notes on automation in Electronic Medical Records was also SUPER interesting, so definitely going to look into that more. Basically that automation can promise higher quality of care IF it's interoperable. But because it's not open source (because proprietary programs and forcing brand loyalty), it greatly increases spending, while not increasing quality of care. Not to mention that automation can disrupt workflows and alter processes in ways that have adverse effects for patient outcomes.
As a UX researcher, I was also interested that automation for software onboarding can decrease task time in the short term, but *increase* task time in the long term due to decreased learning. This has a lot of implications for onboarding processes based on expected frequency of use.
Main drawback: The author clearly lacks understanding on the cognitive and neural side of things. There are are a number of non-explanations (pretty much any time he mentions "neurons"), as well as points where he's straight-up wrong. Example: purporting that novices do not have mental models until they gain expertise, and that those mental models are explicitly "dedicated assemblies of neurons." Which means... absolutely nothing. Like even a novice has a mental model of the task they're trying to achieve, it changes as they gain experience or more information. It's a top level process, and referring to it as "assemblies of neurons" gives it the (wrong) impression of being inherently bottom up.
I also really think he should read up on some of the topics that he was trying to touch on, but was not getting there. Such as optimal arousal theory (really ties into aspects of flow) and heuristics (necessary for talking about novice vs expert task learning).