Sam Altman, the now controversial but undisputed leader in artificial intelligence (AI), had been fired.
There were shock waves throughout the tech world and Silicon Valley was all abuzz.
Despite what happened, Sam is back... with a new board.
That board, however, is... well... white.
All white men.
All of them.
What does this have to do with AI, you might ask?
What we're calling AI today is a large-language model -- a simple task- and merit-based algorithm that just repeats and (supposedly) represents a reflection of humanity.
Let's go back to how AI is trained: Essentially, data comes from a whole host of locations but most notably it comes through readily available texts via the internet and through folks who are known as AI Trainers, people who are tasked with helping AI systems understand how humans think through consistent interactions with the models.
Let's take the first part: the internet. We all know that the internet is... well, the internet.
As a result, many of the texts, images, and publications available are created and geared towards that audience.
Now the second part: AI Trainers. I would fathom a guess that most people in this field will mimic the wider tech field and be mostly white, male, and - again - economically stable.
However, with both, you might get the occasional outsourced "pennies on the dollar" deal where people who can do something that amounts to a more sophisticated data entry job will do so much more work for so much less.
But besides all this, it's known to me and many others who come from marginalized communities: if it's outsourceable, they'll do it to people who are also from marginalized and oppressed communities. If it's still internal to a first-world country like this one, it'll primarily be white and/or Asian community members making the bulk of the decisions. Mostly male-identified. Mostly from upper-middle or rich families. And they'll make sure that they're compensated accordingly.
So what do I think about all this?
It is what it is.
My bigger worry is about the people making the decisions at the top.
Time and time again, I've gone to websites to check out their board of directors and senior management.
To not many's surprise, a lot of them are white, male-appearing, and came from privileged backgrounds.
So, guess what decisions they're making and for whom?
Now, do I think they have some diabolical plan to go out and wipe out the human race of anyone who doesn't look like them or support their interests?
But do I think ALL of those people have done the work to decolonize their patriarchal mindsets to be more intentionally inclusive? Absolutely not.
DEI positions in high levels of management are already being sliced and discontinued from a variety of companies.
No DEI accountability, no motivation to do inclusive work.
But what these companies and organizations are overwhelmingly forgetting is that, at least in the United States, the majority of the buying populous is becoming less and less white (with mainly the world itself already not being mostly white).
So with Sam Altman and ChatGPT's future at a powerful standstill, I worry that there aren't enough marginalized people making the important decisions to be able to see how this future can be harmful.
I think of the forcing out of AI Ethics aficionados like Timnit Gebru and how her signaling of the early instances of AI going off the rails was met with criticism and disdain.
I think of the documentary "Coded Bias" and how it highlighted the various issues many individuals have faced with accurately identifying nonwhite individuals by AI models trained on seeing mainly white people.
And I think of the research I did to create the Data-Driven Diversity course and presentation that spells out how many instances of a lack of inclusion have cost companies more than if they just implemented the changes, to begin with.
The only problem I see is that without a substantial board and AI ethic oversight, OpenAI and many other similar companies are just going to go down a biased path, discriminating (either inadvertently or purposely) against its largest customer base, and then blame it on ignorance and pledge to "do better."
No need to pledge, just do better now.