open call for recruiting best practices in the current AI era? (take-home exercises, AI policy during/before interview, screen-sharing, etc.)
[Original Reddit post](https://www.reddit.com/r/ArtificialInteligence/comments/1tg2okj/open_call_for_recruiting_best_practices_in_the/)
Looking for feedback from either recruiting leaders at AI native companies or hiring managers (ideally of larger AI native teams). am about to open up a few new roles on my team at a series C AI native company in the bay area (~150 ppl). we historically have had very informal recruiting processes (e.g. heavily biased toward referrals and just hire fast and hope for the best). Have managed small teams since 2019 but am used to big company processes like at Google with a hiring panel and criteria for assessing candidates consistently and transparently. but also AI has advanced so much since I last hired someone. if mods consider this irrelevant I'll post in
r/recruiting
or
r/askmanagers
but I already searched those subs and found nothing relevant from the last few months. am looking for thoughts to the following questions:
are take-home assignments still worthwhile? is it better to validate that AI was used appropriately for take-home assignment with a live debrief or is it enough to ask candidates to record a ~10min loom video walking you through their final output and "showing their work" with a link to their various Claude/ChatGPT conversation threads?
for remote-video interviews, do you ask candidates to not use AI during the interview and/or require screen-sharing to (try) to enforce it? seems impossible to verify as ppl can have infinite screens up.
do you still stick with a consistent set of questions across candidates for ease of calibration (legacy best practice), or do you intentionally mix up questions so that it's harder for questions to end up on glass door or blind and become less useful over time?
if in-person is really the only way to ensure candidate aren't "cheating", is there more appetite for paying to fly candidates out for in-person interviews? historically my past companies only did that for senior leadership (people managers of people managers), but seems not crazy to pay $3-6k in travel expenses to help you hire the best of 3 viable candidates for a given role.
how about AI policies in general? what I think I've seen consensus around is that whatever the AI policy will be for the role, you should expect candidates to have access to the same tools as they would when they're actually doing the job?
TY in advance!
submitted by
/u/mtns_of_magic
Originally posted by u/mtns_of_magic on r/ArtificialInteligence
Looking for feedback from either recruiting leaders at AI native companies or hiring managers (ideally of larger AI native teams). am about to open up a few new roles on my team at a series C AI native company in the bay area (~150 ppl). we historically have had very informal recruiting processes (e.g. heavily biased toward referrals and just hire fast and hope for the best). Have managed small teams since 2019 but am used to big company processes like at Google with a hiring panel and criteria for assessing candidates consistently and transparently. but also AI has advanced so much since I last hired someone. if mods consider this irrelevant I'll post in
r/recruiting
or
r/askmanagers
but I already searched those subs and found nothing relevant from the last few months. am looking for thoughts to the following questions:
are take-home assignments still worthwhile? is it better to validate that AI was used appropriately for take-home assignment with a live debrief or is it enough to ask candidates to record a ~10min loom video walking you through their final output and "showing their work" with a link to their various Claude/ChatGPT conversation threads?
for remote-video interviews, do you ask candidates to not use AI during the interview and/or require screen-sharing to (try) to enforce it? seems impossible to verify as ppl can have infinite screens up.
do you still stick with a consistent set of questions across candidates for ease of calibration (legacy best practice), or do you intentionally mix up questions so that it's harder for questions to end up on glass door or blind and become less useful over time?
if in-person is really the only way to ensure candidate aren't "cheating", is there more appetite for paying to fly candidates out for in-person interviews? historically my past companies only did that for senior leadership (people managers of people managers), but seems not crazy to pay $3-6k in travel expenses to help you hire the best of 3 viable candidates for a given role.
how about AI policies in general? what I think I've seen consensus around is that whatever the AI policy will be for the role, you should expect candidates to have access to the same tools as they would when they're actually doing the job?
TY in advance!
submitted by
/u/mtns_of_magic
Originally posted by u/mtns_of_magic on r/ArtificialInteligence