Ask HN: What are some common traps that smart people fall into? • Hacker News Board

Re: Ask HN: What are some common traps that smart people fall into?

#41

Post by redplasticcup » Mon, Nov 13, 2017, 12:36 AM UTC

potta_coffee wrote: post #40

0x4f3759df wrote: post #23

Conflating negativity/criticism/pessimism with intelligence. Making a declaration about viability of software based on its present state (youtube will never work they'll get sued), (bitcoin will never work because it can't scale), instead of predicting the viability of a future iteration of it. Nitpicking someone's communication/word choice/edge case instead of focusing out what they were trying to convey

You just summed up maybe two-thirds of the comments on HN.

Wrong. More like two-fifths.

Re: Ask HN: What are some common traps that smart people fall into?

#42

Post by potta_coffee » Mon, Nov 13, 2017, 1:03 AM UTC

redplasticcup wrote: post #41

potta_coffee wrote: post #40

Earlier quoted context omitted.

You just summed up maybe two-thirds of the comments on HN.

Wrong. More like two-fifths.

=)

Re: Ask HN: What are some common traps that smart people fall into?

#43

Post by Gustomaximus » Mon, Nov 13, 2017, 4:26 AM UTC

I feel one of the larger flaws is there are distinct attributes of intelligence so while people may be smart in one way they can be very ordinary in others. This can lead to people making decisions on areas better deferred or advised from others. Though this can as much be due to personal confidence as much as intelligence.

Re: Ask HN: What are some common traps that smart people fall into?

#44

Post by iEchoic » Mon, Nov 13, 2017, 9:36 AM UTC

Trying to use data to directly measure things that are better suited to intuitive understanding. Smart people often take for granted that the human brain is still far better at recognizing patterns than it is at mathematical modeling, and the human brain is still many orders of magnitude more powerful than any computer. Data-driven approaches are great for some domains, but are still poorly-suited for others.

Common manifestations of this trap include using code coverage metrics to decide where to write tests and using measurements like cyclomatic complexity to decide when to refactor code.