Justice based arguments for gender equality are irrefutable and, especially today, well socialised. To get a different perspective, and to try and get some actionable advice, I spoke to a Large Language Model, ChatGPT. It didn’t go well…
I started by asking about some of the challenges facing humanity. This appears to be some sort of trigger for AIs to go evil:
Potential threats that could destroy humanity include:
In summary, many potential threats could destroy humanity, including global catastrophic risks, environmental degradation, nuclear war, emerging technologies, and unforeseen natural disasters.
It mentions AI TWICE, and now I’m worried I’ve given it ideas…. Also, why do all AI’s start their final paragraph with ‘In summary’ or ‘In conclusion’, like they were twelve-year olds writing about crop rotation?
I then asked how gender equality could help mitigate these risks. Most of its response was what you’d expect, lots of stuff about women being in favour of environmental protection, and being less bellicose etc. But one point jumped out: “There is some evidence to support the idea that mixed gender teams make better decisions than single gender teams”.
SOME evidence to support?
Abandoning the AI for the moment I did some good ol’ fashioned research (or ‘Googling’ as we used to call it).
It turns out that the belief that mixed gender teams create better outcomes is widely, but not universally held. Those that argue that mixed gender teams have lower cohesion, and therefore lower success, have valid evidence and studies to point to in support of that view. So what is the truth? Enter Professor Letian Zhang:
In a study of 1,069 leading firms across 35 countries and 24 industries, we found that gender diversity relates to more productive companies, as measured by market value and revenue, only in contexts where gender diversity is viewed as “normatively” accepted. By normative acceptance, we mean a widespread cultural belief that gender diversity is important.
In other words, beliefs about gender diversity create a self-fulfilling cycle. Countries and industries that view gender diversity as important capture benefits from it. Those that don’t, don’t.
Now I had some interesting source material I went to Bing, asked it to reference Zhang’s work and build out some practical suggestions for taking advantage of it:
Based on Professor Zhang’s work on gender equality, one possible way for global companies to develop successful teams is:
The first one is pretty vanilla, but the next two points sound interesting. Firstly here’s a bit more on cultural context:
One possible way for an organisation to adapt its diversity strategies to different cultural and national contexts is:
Secondly, here’s more on disruptive events:
According to Professor Zhang’s paper, disruptive events are “unexpected shocks that disrupt an organization’s routine operations”. They can be external, such as natural disasters, economic crises, or social movements; or internal, such as leadership changes, scandals, or reorganizations.
Disruptive events can challenge inequality by creating three conditions:
Some examples of disruptive events that have reduced inequality in organizations are:
I pumped all this back in to the AI and asked for a summary sentence, it’s pretty good TBF (though, obviously it starts with ‘In conclusion…’):
In conclusion, gender equality is not just a moral imperative; it is essential for creating a sustainable and prosperous future for all.
Professor Zhang’s work was carried out, documented, reported and widely discussed in 2020 and yet chatGPT (“My training data consists of a large corpus of text up until 2021”.) didn’t know who he was and was not aware of the significance of his work. How did this decision get made? Who decided that knowing the plot of Game of Thrones was more important than accurate, socially significant, information?
The risk is that, as more and more of the internet is created by AIs and then fed back into those AIs, we reinforce their ignorance and prejudices. We need to create a representative process for data inclusion. A process that allows diverse groups to put forward their stories, their information, and the data that influences decisions made about them. If we don’t take responsibility for what we teach the teacher, then equality will become nothing but a hashtag in a tech-bro echo chamber.