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Maybe you feel like you are being inclusive and warmhearted for praising soft skill vs 'teh codez skillz', but please also consider that tech and programming j

Maybe you feel like you are being inclusive and warmhearted for praising soft skill vs 'teh codez skillz', but please also consider that tech and programming jobs is like the last refuge for people with high technical aptitude and perhaps less social soft skills regarding the meta political and expectation games, eg people somewhere on the autism spectrum. Perhaps such interviews are overused but if the interview is purely soft, and about "sell yourself to me", you will also be biased towards some people. I mean of course it's important to be able to work together in a pleasant way, but when someone's main strengths are in the technical aspects, they may like to be able to showcase that too. And yes of course in the age of high level frameworks and glued CRUD pruducts, some programming jobs are more social than technical. But not necessarily all. And I'm seeing lots of this sentiment nowadays on social media, that all "allegedly" merit based nerdy "gatekeeping" is merely about white male privilege and hence not inclusive.

whatshisface 6y ago
Nobody complains about puzzles in tech interviews. People care about uncreative "did you read this book about interview questions" questions. If you want to test tech knowledge in tech interviews, ask a question that isn't in any book. That takes a lot more skill as an interviewer to pull off, but if you're a hiring manager, surely you can find someone on your team qualified to design a puzzle.
- bidirectional 6y ago
  Google's policy is to extensively discuss interview questions internally, and blacklist any that are leaked. They are still complained about near-constantly on any tangentially related HN thread.
  - deleted 6y ago
    [deleted]
  - bonoboTP 6y ago
    The attitude is often quite strange. Like on Twitter I saw a few days ago that many were riled up about the fact that a prof would ask how to solve Ax=b (linear algebra) for a deep learning / computer vision PhD position. People were calling this unnecessary gatekeeping... I'm like that's just a warm-up question to get comfortable... But apparently the loud online hive mind opinion is that all that should count is soft skills and that everyone is equally able. People are even calling out professors on Twitter (who then engage, for some reason) for saying they are looking for "outstanding" PhD candidates. Because this is apparently too exclusionary language, everyone is equally outstanding or something...
    - ravi-delia 6y ago
      Except solving linear functions has a clear role in any field that makes use of linear algebra. Interviews that require memorizing volumes of pointless trivia unrelated to the work at hand are completely different.
      - bonoboTP 6y ago
        Yes, in practice this interview style now achieves exactly the opposite goal that it was created for. That is, originally people wanted to base hiring on general problem solving skill, mapping out a problem domain with relevant questions, proposing solutions, identifying tradeoffs, reacting to a change in problem statement, etc. based on a pure computer science foundation, independent of ever changing software frameworks, libraries, APIs etc. Precisely because memorizing the specific steps of creating a CRUD mobile app in today's workflow is not useful later on. The problem is, Goodhart's law kicked in and performance in such puzzles became the target to optimize for, so it stopped being a good measure, because now people have to explicitly study for it from books and online courses and practice sites and so now it measures more of the effort you're willing to put in to jump hoops instead of actual problem solving aptitude. An alternative could be to ask about a recent real-world project of the applicant, but that's also easier to rehearse.
    - whatshisface 6y ago
      To be fair, you would not actually need to know how numpy.linalg.solve works to use pytorch. Solving linear equations is an extremely deep subject on its own, featuring a lot of difficult and sophisticated issues related to numeric stability. Entire books have been written about how to solve Ax=b with awareness of the nature of floating point arithmetic. Machine learning researchers are generally unconcerned with those topics.

whatshisface 6y ago

Nobody complains about puzzles in tech interviews. People care about uncreative "did you read this book about interview questions" questions. If you want to test tech knowledge in tech interviews, ask a question that isn't in any book. That takes a lot more skill as an interviewer to pull off, but if you're a hiring manager, surely you can find someone on your team qualified to design a puzzle.

bidirectional 6y ago
Google's policy is to extensively discuss interview questions internally, and blacklist any that are leaked. They are still complained about near-constantly on any tangentially related HN thread.
- deleted 6y ago
  [deleted]
- bonoboTP 6y ago
  The attitude is often quite strange. Like on Twitter I saw a few days ago that many were riled up about the fact that a prof would ask how to solve Ax=b (linear algebra) for a deep learning / computer vision PhD position. People were calling this unnecessary gatekeeping... I'm like that's just a warm-up question to get comfortable... But apparently the loud online hive mind opinion is that all that should count is soft skills and that everyone is equally able. People are even calling out professors on Twitter (who then engage, for some reason) for saying they are looking for "outstanding" PhD candidates. Because this is apparently too exclusionary language, everyone is equally outstanding or something...
  - ravi-delia 6y ago
    Except solving linear functions has a clear role in any field that makes use of linear algebra. Interviews that require memorizing volumes of pointless trivia unrelated to the work at hand are completely different.
    - bonoboTP 6y ago
      Yes, in practice this interview style now achieves exactly the opposite goal that it was created for. That is, originally people wanted to base hiring on general problem solving skill, mapping out a problem domain with relevant questions, proposing solutions, identifying tradeoffs, reacting to a change in problem statement, etc. based on a pure computer science foundation, independent of ever changing software frameworks, libraries, APIs etc. Precisely because memorizing the specific steps of creating a CRUD mobile app in today's workflow is not useful later on. The problem is, Goodhart's law kicked in and performance in such puzzles became the target to optimize for, so it stopped being a good measure, because now people have to explicitly study for it from books and online courses and practice sites and so now it measures more of the effort you're willing to put in to jump hoops instead of actual problem solving aptitude. An alternative could be to ask about a recent real-world project of the applicant, but that's also easier to rehearse.
  - whatshisface 6y ago
    To be fair, you would not actually need to know how numpy.linalg.solve works to use pytorch. Solving linear equations is an extremely deep subject on its own, featuring a lot of difficult and sophisticated issues related to numeric stability. Entire books have been written about how to solve Ax=b with awareness of the nature of floating point arithmetic. Machine learning researchers are generally unconcerned with those topics.