140 - AI Is Getting Cheaper. Judgment Is Getting Pricier

I know we are on a time crunch today, but we didn't build in, and we should, a quick debrief from IXAI.

yeah well let me tell you it was yeah um amazing i won't spend too much time it was an amazing two days it was it was it was packed with um packed with learning to the point where i really i don't always when it's a virtual event i don't always just like sit kind of listening the way i was and like watching the slides but this time it really was i was It's hard not to multitask when you're at a virtual event.

And there is a little bit of that that happens over time because it's hard to sit and focus, I think, for so many hours.

But there was a lot that I really just sit and focused and listened to.

It was really amazing.

So high level, I think there were some really big themes coming out of this one, which... which is different than what I've been hearing before.

Yes, there were case studies.

Yes, there were methods.

So I encourage everybody to watch on demand, catch up on case studies, catch up on all there is to learn about AI moderation and synthetic data and the way people are using AI.

And yes, ethics and governance.

But there was a bigger story, a higher-arching story, which is really in three parts.

One, I wrote this down, so it's going to sound a little bit like written down because it is.

Accountability doesn't transfer to whatever machine you're using, whatever AI you're using, right? AI can produce the output, but the person, the researcher still owns that decision.

You are accountable for whatever the AI is doing.

Remember that and own it.

Remember, you are accountable as the professional, not the AI.

That was a very loud and clear theme that we have to stay mindful of as professionals.

That is what's going to ensure our professional credibility, let's not lose it.

Let's not lose our professional credibility to AI.

That was a really important theme.

Another theme was that, and this is related, our job is shifting, our job as insights professionals, shifting from kind of checking the work, which we have to do, but to checking the thinking about how we're using the work.

Pam Forbus at Mondelez spoke first thing yesterday morning, and she said, remember, we are AI's teachers, not AI's users.

which was really, really like a very, like one of those soundbites that you're like, yes, we are teaching AI.

And then at the end of the day, Lisa Cordaid from Organon joined us, one of our oldest fans, which is really fun to have her on.

Always awesome.