3 ms·
Going by this: https://www.aeaweb.org/conference/2025/program/paper/3Y3SD8TZ https://www.aeaweb.org/conference/2025/program/paper/3Y3SD8T... which states “… fou
by mk_chan 1y ago
Going by this: https://www.aeaweb.org/conference/2025/program/paper/3Y3SD8TZ https://www.aeaweb.org/conference/2025/program/paper/3Y3SD8T... which states “… founding teams comprised of all men are most common (75% in 2022)…”
it might actually make sense that the LLM is reflecting real world data because by the point a company begins to use an LLM over personal network-based hiring, they are beginning to produce a more gender-balanced workforce.
- darkwater 1y agoThe bias found by this research is towards females.
- xenocratus 1y agoAnd the comment says that, since companies start out with more males, it presumably makes sense to favour females to steer towards gender balance.
- Saline9515 1y agoIf this reveals true this is an interesting case of an AI going rogue and starting to implement its own political agenda.
- Scarblac 1y agoAIs can do no such thing of course, they're a pile of coefficients computed from training data. Any bias found must be a result of either the training data or the exact algorithm (in case of bias based on position in the prompt, for example).
- philipallstar 1y agoI imagine this is not rogue at all. James Damore was fired almost 10 years ago from Google for saying that aiming for equal hiring from non-equal-sized groups was a bad idea.
- apwell23 1y agoI thought google tried that and got laughed out of the room.
- billyp-rva 1y agoIf this were true, the LLMs would favor male candidates in female-dominated professions.
- mk_chan 1y agoThat should happen if the training dataset (which is presumably based on the real world) reflects that happening.
- giantg2 1y agoAiming for a gender balanced workforce might be biased if the candidate pool isn't gender balanced as well.
- mk_chan 1y agoFollowing the paper, if you end up with a gender balanced workforce, it implies there is surely a bias in one of the variables - the candidate pool (like you say) or the evaluation of a candidate or other related things. However the bias must also reverse to equalize once the balance tips the other way or actually disappear once the desired ratio is achieved. Edit: it should go without saying that once you hire enough people to dwarf the starting population of the startup + consider employee churn, the bias should disappear within the error margin in the real world. This just follows the original posted results and the paper.
- gitremote 1y agoAn LLM doesn't have any concept of math or statistics. There is no need to defend using a black box like generative AI in hiring decisions.