I’m strongly in support of this initiative, and hope to help out as my schedule permits.
I agree with Larks that the linked studies have poor methodology and don’t provide sufficient support for their claims. I wish that there was better empirical research on this topic, but I think that’s unlikely to happen for various reasons (specifying useful outcome metrics is extremely difficult, political and researcher bias pushes hard toward a particular conclusion, human studies are expensive, etc.).
In lieu of reliable large-scale data, I’m basing my opinion on personal experiences and observations from my 5 years as a full time (cis female) AIS researcher, as well as several years of advising junior and aspiring researchers. I want to be explicit that I’d like better data than this, but am using it because it’s the best I have available.
I see two distinct ways that this initiative could be valuable for AIS research:
It could help us to recruit and retain more promising researchers. As Lewis commented, we need all the help we can get. While this community tries hard to be meritocratic, and is much less overtly hostile to women than neighboring communities I’ve experienced, I have personally noticed and experienced unintentional-yet-systemic patterns of behavior that can make it particularly difficult to remain and advance in this field as a woman. I’d prefer not to get into an in-depth discussion of that on here, though I have written about a bit of it in a related comment.[1] I believe that a more gender-balanced environment, and particularly more accessible senior female researchers and mentors, would likely reduce this.
I also suspect that more balanced gender representation would make more people feel comfortable entering the field. I am often the only woman at lab meetings, research workshops, and other AIS events, and very often the only woman who isn’t married to a man who is also in attendance. This doesn’t bother me, but I think that’s just a random quirk of my personality. I think it’s totally reasonable and not uncommon for people to be reluctant to join a group where their demographics make them stand out, and we could be losing female entrants this way. (Though I have noticed much more gender diversity in AIS researchers who’ve joined in the past <2 years than in those who joined >=5 years ago, so it’s possible this problem is already going away!)
Women (or any member of an underrepresented group or background) could provide important perspective for some areas of AIS research. It’s important to distinguish between different research areas here, so I’m gonna messily put AIS topics on a spectrum between “fundamental” and “applied”. By “fundamental”, I mean topics like interpretability, decision theory, science of deep learning, etc — work to understand, predict, and figure out how to control AI behavior at all. By “applied”, I mean topics like practical implications of RLHF when teachers have differing preferences, or constructing meaningful evaluations for foundation models — work to understand, predict, and dictate how AI interacts with the real world and groups of humans.
On the “fundamental” end of the spectrum, I don’t think that diversity in researcher background and life experience really matters either way. But in topics further toward the “applied” end of the spectrum, it can help a whole lot. There’s plausibly-important safety work happening all along this spectrum, especially now that surprisingly powerful AI systems are deployed in the real world, so there are areas where researchers with diverse backgrounds can be particularly valuable.
Overall, I think that this is an excellent thing to dedicate some resources to on the margin.
A relevant excerpt: “most of these interactions were respectful, and grew to be a problem only because they happened so systematically—for a while, it felt like every senior researcher I tried to get project mentorship from tried to date me instead, then avoided me after I turned them down, which has had serious career consequences.”
I’m strongly in support of this initiative, and hope to help out as my schedule permits.
I agree with Larks that the linked studies have poor methodology and don’t provide sufficient support for their claims. I wish that there was better empirical research on this topic, but I think that’s unlikely to happen for various reasons (specifying useful outcome metrics is extremely difficult, political and researcher bias pushes hard toward a particular conclusion, human studies are expensive, etc.).
In lieu of reliable large-scale data, I’m basing my opinion on personal experiences and observations from my 5 years as a full time (cis female) AIS researcher, as well as several years of advising junior and aspiring researchers. I want to be explicit that I’d like better data than this, but am using it because it’s the best I have available.
I see two distinct ways that this initiative could be valuable for AIS research:
It could help us to recruit and retain more promising researchers. As Lewis commented, we need all the help we can get. While this community tries hard to be meritocratic, and is much less overtly hostile to women than neighboring communities I’ve experienced, I have personally noticed and experienced unintentional-yet-systemic patterns of behavior that can make it particularly difficult to remain and advance in this field as a woman. I’d prefer not to get into an in-depth discussion of that on here, though I have written about a bit of it in a related comment.[1] I believe that a more gender-balanced environment, and particularly more accessible senior female researchers and mentors, would likely reduce this.
I also suspect that more balanced gender representation would make more people feel comfortable entering the field. I am often the only woman at lab meetings, research workshops, and other AIS events, and very often the only woman who isn’t married to a man who is also in attendance. This doesn’t bother me, but I think that’s just a random quirk of my personality. I think it’s totally reasonable and not uncommon for people to be reluctant to join a group where their demographics make them stand out, and we could be losing female entrants this way. (Though I have noticed much more gender diversity in AIS researchers who’ve joined in the past <2 years than in those who joined >=5 years ago, so it’s possible this problem is already going away!)
Women (or any member of an underrepresented group or background) could provide important perspective for some areas of AIS research. It’s important to distinguish between different research areas here, so I’m gonna messily put AIS topics on a spectrum between “fundamental” and “applied”. By “fundamental”, I mean topics like interpretability, decision theory, science of deep learning, etc — work to understand, predict, and figure out how to control AI behavior at all. By “applied”, I mean topics like practical implications of RLHF when teachers have differing preferences, or constructing meaningful evaluations for foundation models — work to understand, predict, and dictate how AI interacts with the real world and groups of humans.
On the “fundamental” end of the spectrum, I don’t think that diversity in researcher background and life experience really matters either way. But in topics further toward the “applied” end of the spectrum, it can help a whole lot. There’s plausibly-important safety work happening all along this spectrum, especially now that surprisingly powerful AI systems are deployed in the real world, so there are areas where researchers with diverse backgrounds can be particularly valuable.
Overall, I think that this is an excellent thing to dedicate some resources to on the margin.
A relevant excerpt: “most of these interactions were respectful, and grew to be a problem only because they happened so systematically—for a while, it felt like every senior researcher I tried to get project mentorship from tried to date me instead, then avoided me after I turned them down, which has had serious career consequences.”