Bridget Burns
speaker
389 appearances
6 recordings
1 series
first heard Dec 2024
last heard May 2025
Bridget Burns’s voice in public audio — every appearance, attributed to the second.
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Appearances
Yeah, invite your people into the problem that you need to solve. People love to solve problems. People love to be helpful. But what they don't want to be is a cog in a wheel told to do X or Y. And they also literally work in that area. They might have some ideas. Listen, I know that you can have employees that you're like, they're just not going to want it.
All I'm saying is that the resistance is justified. And if you are so out of touch with your people that you can't understand that, then you've been at it too long. And you need to give yourself a micro dose of a empathy sprint to go out and remember why you started doing this work. Remember why you cared about the people. Remember why you chose to be a leader. Because...
I get dismissing people because I feel like people who work in any industry, my observation is there's a lot of people walking around with broken hearts because they've had a leader who's betrayed them. They've had a thing that they worked on for 10 years that got shelved at the last minute. And they remember that they showed up, that they missed dinner with their kids to build that thing.
And you're just going to turn it off. You're just getting rid of it. There's all these people who are carrying around these stories of bad experiences from change. And then there are leaders who are carrying around this mythology about people being lazy or people not wanting to do stuff. And I just, it doesn't serve us. And it is not, it's not reality.
And we are not our best selves when all we're doing is living out a story we're telling ourselves about change. Other people. And so you just got to you got to tap in. Curiosity is going to be your best friend.
And if you don't if you don't have it right now, you've got to give yourself you got to pull back out of the work and get back to caring about people and remembering they all have a reason to feel the way they do.
So I think the thing that is going to get in the way are things that are very human. The first thing I'm observing is that we have this natural tendency to compete with each other. There's like an arms race usually when something's new, and that's what's happening with AI.
So what you have is thousands of people across higher ed, different institutions, who are all trying to figure something out simultaneously. And what a waste that we are not finding a way to work together, that we are not teaming up on the shared objective that you just put forward.
Because this is a space that's hyper-competitive and we will batten the hatches and not share anything with anyone and students will be worse for it. Because you need the people who are in the classroom and people who are outside the classroom finding ways to collaborate with peers, not just at their institution, but do it in a way that...
advances the entire agenda forward for everyone, which is we have big questions around learning that we need to address. We need to figure out how to make it so that any person can learn. We need to figure out how to make it more sustainable for every person to have access to personalized learning at scale.
We need to figure out the efficacy and the safety issues that are definitely going to happen and are popping up already. And instead, what you're having is A bunch of people who are working individually with their head down, separated, all figuring out what problem they want, how they want to use AI or whether they don't. And then there's a large swath of higher ed that is more risk averse.
And so they may or may not be using it at all. And so you're going to see a new like version of the haves and have nots. And for me, what I just always I'm predisposed to notice the big picture and to be a systems thinker on this. And so I just I see really big sector problems that affect community colleges, every type of institute, every type of university. And it's really about the students.
It's about how we can weaponize this for good. How do we make it so that. The people who work at a university who are, you know, front office that are being overwhelmed by repetitive questions or repetitive issues, how do they use AI so they can actually not have to do that and instead can provide more hands-on support for students? Now, we're seeing that with chatbots as such.
And how do administrators be more effective and efficient so that they can actually get through their days and be able to produce more things, to be able to accelerate speed? Because that's a real challenge for us. And for faculty, just like it's learning, it's, you know, how do you use this ethically when you're trying to one of the biggest impediments for your time is grading?
How do you use it from a, like, pedagogical perspective to make it so that what you're doing is better? These are big questions that are not particularly unique. These are, I've given you what, it's like three problems. Those are sector problems. And so... It's just sad when we only focus on my institution wants to be first. So University of Michigan, go get them or Arizona State.
They're definitely out front on AI. But I just think that there are very clearly like same problems, like same team. And we have to find a way that we are going to collaborate together. in an effort to make our use of AI safe, effective, efficient, and trustworthy, and going to be able to, again, I think at the end of the day, it's about personalized learning at scale.
And also make sure that what we're teaching today is not out of date because the future of work and how AI is disrupting the workforce and going to disrupt the workforce, that means that the things we're teaching now in certain classrooms today is no longer relevant. And there is I have little confidence that individual disciplines are going to be in real time keeping up with that.
And if they are, it's one dean or it's one chair or faculty member. It's not the whole discipline working together to figure out, OK, so I can see that the role of paralegal is going to be changing rapidly right now because of chat GBT. fundamentally, you can conduct a lit review with a well-trained model super effectively.
And what does that mean for how we can... I just think there's a lot that's happening so fast. So then... If you're training people in the legal profession or anything related right now, you should have a part of your curriculum about AI. You should be thinking about how the role of paralegal is changing rapidly now because of that. And so therefore, it's like...
We've always had a problem with our connection with workforce. And now it's like it's on steroids and steroids are AI. And so, again, every one of these is a sector wide problem.
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