A Seat At The Table
Reflections on AI builders, Hamilton, and being misgendered by ChatGPT
“160+ AI builders packed the room in Seattle on Monday night …”
Sounds like the beginning of a joke, right? 😉
No such luck. It was a very real LinkedIn post I saw the other day—alongside a picture of the happy gathering.
And my heart sank a little bit. Care to guess why?
Go ahead … I’ll wait ….
Who’s in the room?
I love me a good musical, and there’s none quite like Hamilton.
In it, Aaron Burr sings about the Compromise of 1790 and his desire to be in the inner circle and at the table when deals get struck:
“No one really knows how the game is played
The art of the trade
How the sausage gets made
We just assume that it happens
But no one else is in the room where it happens”
If you’re not at the table, how do you know how decisions get made? How can you be assured that your interests are represented?
You don’t. You can’t. And they’re most likely not.
So back to the 160 AI builders. Who do you suppose was in that room?
I wasn't there, so I can't say for certain. But judging from the photo, the room appeared to be overwhelmingly made up of White and South Asian men.
Anyone see a problem with this?
We can’t assume …
We assume that the people designing products and systems understand the people they're designing for. We assume that our interests are being served.
But we’ve seen time and time again what happens when the people who use products and systems are not part of the teams that build them.
I experience a small version of this every single day as a left-handed person. Turns out, the entire world is built for right-handers—something you don’t think about unless you happen to be left-handed.
Don’t believe me? Check out this fun little piece about all the challenges left-handers have with door handles, scissors, watches, kitchen utensils … the list goes on.
This is a minor annoyance I’ve had to navigate my entire life, but the outcome can be so much more insidious than just inconvenience:
Automated soap dispensers that don’t work for people with dark skin
Cars that are considerably more dangerous for women than men
AI that offers disparate salary advice to women and people of color
Facial recognition systems that lead to wrongful arrests
So, umm, yeah … really bad shit happens when we’re not in the room.
Representation matters
Just the other day, I was editing a post with ChatGPT. I have a project set up for SGNR that includes a year's worth of blog posts and historical chats to create an AI editor that knows me, my writing, and my voice so that it can recommend edits accordingly.
And yet, during an exchange about how I phrased one section, ChatGPT said readers may think to themselves: “Wait, is he arguing against AI?”
Read that again if you missed it.
A year’s worth of conversations. It’s read all my posts. About being out and proud. Taking PTO time with my wife. Reclaiming our power as women.
And it still misgendered me.
Because the dudes building ChatGPT inevitably bring their own experiences and assumptions with them. They likely don't mean to build a biased or exclusionary product—they simply can't see what they're missing.
They assume the world is exactly as they experience it.
We can fix this
As leaders, we have the power to change this. And the responsibility to.
We need to pay attention to whose voice isn’t being represented—whether on a specific project or within your leadership team.
As company leaders, our responsibility is even greater. It extends beyond our own internal teams to ensuring we truly understand and represent the people and industries we serve.
When I was a CIO, there was nothing more irritating than being sold to by a bunch of tech bros who hadn’t spent a single day in a campus role—but were going to “fix” education. 🙄
No matter how smart they are or how good their idea is, they don't know what they don't know. That's why you need people with lived experience in the room.
So the next time you convene 160 builders—or even 16—ask yourself: Who’s not in the room that should be?
Bonus read: When AI isn’t being unintentionally biased it does have the power to accelerate our work. But it requires experience to make it truly useful.
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