Language is inherently imprecise, as demonstrated by a primary school math problem that revealed the difference between '2 times more than' and '2 times as many'.
Expertise can create blind spots, where years of formal training prevent individuals from understanding how certain phrases function in everyday language.
Translation gaps between human intention and machine execution can lead to semantic breakdowns, causing project failures in technology.
Improving translation capabilities in technology work involves restating requirements, establishing precise definitions, using multiple representations, considering different perspectives, and creating processes to resolve ambiguities.