"With modern browsing habits and the amount of available online media, I suspect this post will be quickly passed over in favor of more interesting reading material. Before you immediately close this tab, I invite you to scroll down and read the conclusion, which hopefully can give you some food for thought along the way. If, however, you manage to read the whole thing, I applaud your impressive attention span."
"A common criticism of the use of large language models (LLMs) is that it can deprive us of cognitive skills. The typical argument is that outsourcing certain tasks can easily cause some kind of mental atrophy. To what extent this is true is an ongoing discussion among neuroscientists, psychologists and others, but to me, the understanding that with certain skills you have to "use it or lose it" seems intuitively and empirically sound."
"He compares this to the misconception that there is only a finite amount of work that needs to be done in an economy, which often is referred to as "the lump of labour fallacy". His viewpoint is that "thinking often leads to more things to think about", and therefore we shouldn't worry about letting machines do the thinking for us - we will simply be able to think about other things instead."
Outsourcing thinking to large language models raises concern about cognitive skill loss due to reduced practice. The 'use it or lose it' intuition suggests certain skills require active use to be maintained. The critical question is which uses of cognition are beneficial and which are detrimental when delegated to machines. The lump of cognition fallacy challenges the idea of a fixed amount of thinking, arguing that thinking generates more things to think about. Machines taking over some cognitive tasks can free humans to focus on different, potentially higher-level or creative problems without necessarily reducing overall cognitive engagement.
Read at Erikjohannes
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