4 ms·

I don't think most companies want to relinquish that kind of control to a third party, due to the potential for abuse

komali2 7y ago
I'm not sure if it's abuse so much as just generally, a hiring manager, i.e. a team lead or senior engineer, can't confidently say "I know how to interview people well." I say this because I think the skillset required to "choose a good engineer among thousands of applicants" is quite different from "lead a team of engineers to develop a product." Some are better than others, but point being, if one can't say "based on research, this is a good way to interview," why would you risk changing what seems to work? Why would you risk offloading your "good enough" strategy onto another company that, to you, probably is just guessing as much as you are?
- stcredzero 7y ago
  a hiring manager, i.e. a team lead or senior engineer, can't confidently say "I know how to interview people well." Isn't data a potential solution to this? One issue is that the best data would have to be gathered on timescales of years, and not just a few years.
  - yomly 7y ago
    Call me old fashioned but I'm unconvinced about data's role in defining "good candidate" although if anyone could do it, Google is the perfect storm of data know how and applicant pool scale. Fundamentally it is a human evaluating another human. Process and rubric can assist in eliminating bias but as human interaction is complex, a bit of pattern matching and whooly experience is going to go a long way and excels in these domains. Let's also not forget that things that interpret data are subject to bias as they are built by humans too - see Amazon's case where filtering was accidentally sexist
    - JamesBarney 7y ago
      There are mountains of data on interviewing and hiring(see industrial psychology), and none of it shows that human evaluation is the gold standard. In fact the research shows that pretty much anything you do to reduce the "je ne sais quoi" of hiring is going to improve results.

I'm not sure if it's abuse so much as just generally, a hiring manager, i.e. a team lead or senior engineer, can't confidently say "I know how to interview people well." I say this because I think the skillset required to "choose a good engineer among thousands of applicants" is quite different from "lead a team of engineers to develop a product." Some are better than others, but point being, if one can't say "based on research, this is a good way to interview," why would you risk changing what seems to work? Why would you risk offloading your "good enough" strategy onto another company that, to you, probably is just guessing as much as you are?

stcredzero 7y ago
a hiring manager, i.e. a team lead or senior engineer, can't confidently say "I know how to interview people well." Isn't data a potential solution to this? One issue is that the best data would have to be gathered on timescales of years, and not just a few years.
- yomly 7y ago
  Call me old fashioned but I'm unconvinced about data's role in defining "good candidate" although if anyone could do it, Google is the perfect storm of data know how and applicant pool scale. Fundamentally it is a human evaluating another human. Process and rubric can assist in eliminating bias but as human interaction is complex, a bit of pattern matching and whooly experience is going to go a long way and excels in these domains. Let's also not forget that things that interpret data are subject to bias as they are built by humans too - see Amazon's case where filtering was accidentally sexist
  - JamesBarney 7y ago
    There are mountains of data on interviewing and hiring(see industrial psychology), and none of it shows that human evaluation is the gold standard. In fact the research shows that pretty much anything you do to reduce the "je ne sais quoi" of hiring is going to improve results.