I've been so looking forward to this because I've been meaning to ask you. You saw the survey results. I read through them. You heard me give my assessment. But what do you think when you see these numbers? Yeah. By the way, the coffee is better in Melbourne.
As of the And so it begins. And so the debate universities, by the way, Rachel. But that's for another another time. Them fighting words here in Sydney. Well, first of it's so good to be here talking about Graham's and my book rather than than disruption and then combining the two.
So when I was looking at the stats Yeah. You talked a lot about that strategy gap. You know, do we have a strategy? Are we ready? The interesting thing about strategy when you're facing adaptive challenges and AI morphing about every adaptive challenge, Rachel. Very much so. So it's no wonder, you know, humans are prewired to go defensive in the face of ambiguity and uncertainty, sort of why toilet paper sold out within forty eight hours when the pandemic hit.
I mean, I'm still eating sausages from the bottom of the chest freezer from '21. But because we're sort of pre wired to go defensive, the real challenge for universities, for schools, for colleges, private providers is we love to think of these challenges as being in nice, neat, little linear ways as Heifetz and Linsky would talk about it. But they're not. They require experimenting. They require making mistakes because that's where the learning is.
And so strategy in this context is not about having everything figured out, but it is about being able to to say that's main intent. That's what we're going after. That's what AI is going to be for our institutions. You know, you and I have both read Alice in Wonderland. Yes.
Lewis Carroll. One of my favorite quotes. If you don't know where you're going, every road will get you there. Yeah. And I think that's what's going on right now.
Because there isn't that clear intent about where our institution, our school wants to go, everybody's just trying to do their best. And so to your point, that strategy gap, I think, is because everybody's trying to figure everything out and you can't, not in the face of an adaptive challenge. You know, it's interesting you say that. You know? And I think too, some people react very defensive, right? Because AI, let's be honest, for many educators it's still perceived as a threat. There's identity involved and this and that.
And so I think what, in your experience, what separates institutions that see it as a threat, which is I think where intent comes back in, like how do we lead more with confidence and with intent? What distinguishes universities that treat it more as a threat versus those that see it as an advantage to leap forward? Yeah. So do you want to know my danger signals? Yeah. So when I walk into any institution around the world and we start talking about it, the first is, are they trying to control it or are they actually open to experimenting with it? Getting started, empowering their people to try different things. Right? Almost expecting mistakes because that's where the learning is. So the first thing I I I get a read on is, is the institution truly willing within appropriate boundaries to experiment and learn and adapt? Because that's the only way forward with something like AI.
The second danger signal is is silence versus voice. In other words yeah. And it is because you again, unless you actually relax people in the organization, let them know that you want them to speak up. You want them to share. The latest LinkedIn data I said saw, Rachel, said fifty four percent of professional workers are reluctant to tell their manager that they're using AI at work for their most important tasks.
So you can see why. Because people are worried that if I try it, if I use it, I might be doing something wrong or I might make a mistake. We've got to liberate people from that, Rachel. It's interesting. Know, I think that's a big thing that's in the way of confidence.
You know, when I talk to universities and I met with a leader not too long ago that put together an incredibly thoughtful strategy and shared it with me, wanted to get my thoughts and again, compare to what other universities were doing. And one of the things she said was, hey, I'm very excited about what we're writing, but I don't think at the end of the day educators actually feel empowered to make decisions in the classroom around AI. Like how do translate that strategy? And I think part of it may be around what you're talking about, governance, right? Is there clear government's empowerment giving folks permission To do this experimentation? Yeah. Which is sort of my third, which is they're trapped in perfection over learning. Ironic for learning institutions.
Right? They keep thinking everything's gotta be buttoned down. All the policies need to be right. All the rules need to be right. Every contingent has to be right. Instead of saying, nope.
It's about learning. It's about experimenting, expecting mistakes. And provided we learn from those mistakes and we adapt and evolve, we'll be in great shape. But we will not we will not successfully lead through it if we're trying to lead in linear ways, Rachel. So what do you think I mean, just to make that really practical for the folks here, you know, what do you think leaders really need to do? So I think first and foremost, we need to realise that if if would we even dream of teaching English literacy or any language literacy with a course? No.
It's not a course. It's actually gotta be a capability, Rachel. So the the first thing that every institution I work with, the first question I ask is, do you have a common understanding of AI literacy for every member of staff and every student? And are you teaching that on a on an ongoing repeatable basis where you are committing and funding literally tens of hours per year to make sure that your students and your staff are staying up to date? And the second thing is, are we building it into our work? In other words, are we seeing that, you know, understanding it or what many call literacy is off to the side, or are we legitimizing it in people using it in every one of their jobs in every way? And the final one is make learning a habit. So in the book, we talk about relentless debriefing. The really smart institutions are rolling out STEM to Stern for their staff and students, AI literacy programs establishing, you know, what is main intent? What are we going after? Are we all speaking the same language? But then what they're doing is they're capturing, they're harvesting the best practices and they're setting up peer to peer learning and double loop learning sessions.
And they're they're actually investing in the time for their people to learn on a consistent ongoing basis. It's not a one off, Rachel. It's gotta be a habit for life that we all move into. And that's why the curious are going to inherit the earth. I agree with that.
You do? Good I do. Yeah. I refer I'm a learn a lot, not a know a lot. Yeah. So I'm going to break the rules now, Rachel.
Okay. Mainly because they're sick of hearing from me. Going to ask you a So question you've talked so much around confidence sitting underneath the gaps that you you talked about. So where does that I mean, you talk to customers all around the world, folks just like us in ANZ. So where does that lack of confidence come from from your perspective? Yeah.
Well, it's a great question. And and like I mentioned, I think that it is really about lack of of empowerment and permission to fail or not really to fail but to experiment in that learn like you talked about and having the space. So I think it's about that governance factor that's having clarity on what you can and cannot do and to give folks the space to say, hey, look, it's okay to experiment. It's okay to make mistakes. It's okay to try and let's learn.
I don't know that that's really built. I think it comes back to governance in the confidence because let's be honest, I think we're all new at this. A lot of folks have trepidation and we want structure. Like I think when we're nervous and there's uncertainty, we crave structure. And I think that it's important that we give some guardrails so folks can not be paralyzed with inaction.
I think that's where that perceived lack of confidence comes in is really, really important. Yeah. So I mean, play that back to you is when you use the word governance in this context, you could also call it permissions, couldn't you? That you are committed to go try these things, to do these things. And if you do, you're Exactly. You're not going to be punished for this.
You're not going to be and we also have forums. Again, this is back to governance, but forums for the feedback to surface, have the space for the learnings to be shared, to be iterated on, etcetera. Right? And to do that you do have to have a culture that supports that level of transparency, call it learning, etcetera. I do think it's cultural to a certain degree as well. And no strategy is going to address that.
I mean, you have to kind of embody that from the beginning. And in the book we talk about the minute a human goes into a fear state, they go defensive. And what do they do when they're defensive? They resist. They resist change. And and we know of all the things that could go wrong, the worst strategy in the face of AI is to do nothing, is to just simply sit and wait.
And so that governance, that giving of permissions, that take away the fear, give people the opportunity to experiment, learn, and adapt has got to be the way forward. Is your is it your opinion then that because you keep coming back to that. Is it is in your experience, like when they say they have a strategy but it's not being put into use, is that your diagnosis of what's happening underneath? Or what else do you think is going on? I think the strategy is often pitched at the wrong level. So it's so high level. It's so generic.
We do this a lot particularly in university strategies. It's sort of you read one, you read them all. Know, we sort of stay at these sort of headline levels of we will implement AI ethically and responsibly. What do I do with that? Right? I mean, what do I do with that? Great. What does that mean? What direction does that give me? So I think really where it's going wrong is what we might think of as the clarity gap actually, Rachel.
There's nothing wrong with that high level, you know, pie statement as you would say in America. But still gotta try to figure that out actually. But anyway, that apple pie statement dropping that down into sort of, yeah, but what do I do with that? And so I I think actually discussing and certainly in an educational context, debating and agreeing the principles by which we will implement AI in the academic community, in the professional community, in the broader community, and then give the permissions and explicitly call that out so that people can go forward with with confidence. Well, and I think too, you touched on something there as well. It's like I think that the irony is people don't know what good looks like yet.
You could say you do, but you really don't. I mean, yes. And so in the learning is where you find out what good looks like. And I think back to this idea of perfectionism, I think there's this idea of waiting to be told what good looks like when actually it's the opposite. Yes, there's going to be, I mean to your point, the strategy is going to say at a very high level what the desired intent or outcomes are.
But it's really about that empowerment to say, we're actually looking for you to tell us rather than waiting to be told. And I think that's the way we flip it because I think it's back to clarity, this waiting for being told exactly what good looks like, that's a fallacy. That's a fallacy because I think everyone's still trying to figure out what good looks like. Yeah. And I've got to tell you, going back to something that I said before, because everybody is coming up with incredible ways to use it to save time, be more effective, drive better learning outcomes, be more efficient in my role, to free the human up to do the higher value tasks.
That's really the goal that I I work with. What I'm not seeing enough of though is the harvesting of those learnings, Rachel. And and that's you know, if I could give some advice to everybody in the room, how are you in your institution, in your organization, making sure that you're constantly learning from what everybody else is doing and sharing that with others so that they can grab it and and run. I mean, had the great pleasure of joining you and your colleagues in a strategy session recently, Rachel. And what I loved is the two days were peppered with members of your most senior leaders getting up and sharing how they were using generative AI to make them and their teams more effective in what they do.
And I was like, textbook. Textbook. What they're doing is actually building it into the work. They're making it normal to be sharing best practice, to be sharing skills, sharing agents, sharing workflows so that others can grab them and adapt them and use them and and work with them. And and then, you know, so that's what we're talking about, really making it part of the work to be a consistently learning organization in the face of the greatest technological disruption we've ever seen that is moving it at a pace that we've never seen before.
Yeah. 100%. You know, I could talk we we could talk about this all day and I love this conversation. But, you know, before we wrap up, you know, as someone who and you you've really coached me, you know, like you mentioned with my own team, Someone who has seen disruption, who has written now about it, and through all your experience, whether it's at Microsoft or obviously your amazing academic experience, what is the biggest like when you think about disruption, what is the one lesson around readiness that you keep coming back to for this group? If you say, hey, look, if there's one lesson that I can impart to say, you know, what do leaders underestimate that you would want everyone to take away as we're all navigating disruption together? Yeah. And it of course, she gave me all the questions in advance.
We're meant to make it look like I didn't prep. But, anyway, we'll just so but this will kind of blow my cover a little bit, Rachel. But I went and looked for a quote. Many people will know who Amelia Earhart was. Yeah.
So she faced a pretty adaptive challenge in her life. Right? So I love this quote. The most difficult thing is the decision to act. The rest is merely tenacity. And I think that's the lesson I've learned in my career, Rachel, because I've always been at that intersection of education and technology.
And as a sector, probably more than most, I work with most of them now, we are sort of pre wired to overanalyze, go defensive, question, challenge, and it's a good thing. That's why we need institutions like the ones represented in this room. But the big thing that's changed this time is the pace, Rachel. It's the pace. It's relentless.
It's changing all the time. You know, today is the slowest day of the rest of our working lives. And I know you're already feeling worn out and change fatigue and you got another four changes out in front of you, but it is the reality. So, Rachel, I think the the greatest challenge is the courage of our convictions to get going, to start, to act, that decision to act as Amelia described it. But then it's gonna require a lot of tenaciousness to keep up.
Because the minute we pause, the minute we slow down, the minute we allow ourselves to go defensive in the face of ambiguity, we start to put our own careers, our institute at risk, our institutions at risk, and then sadly, by definition, our staff and students at risk because we will slip into a crisis of relevance. We will cease to be relative relevant in our societies and our communities, and and we're seeing the danger signs of that all over the world when we look at where funding for schools and colleges and universities are going. And we're looking at the talk track about us being yesterday's news and not keeping up, Rachel. So that that to me, in the face of this relentless pace, we need to have the courage to make that decision to act, and then we need to tenaciously stay at it. But do that with great care and humility and the right ethical lens because this is gonna put a lot of pressure, a lot of pressure on our staff, a lot of pressure on our students, a lot of pressure on our communities, which is why whenever I get engaged around AI, I always say, how can it be used to free up the time of humans to do what they wanna do and where they add the greater value for all of us as educators.
Thank you, Martin. You're very welcome. Well, with that, and I know speaking of communities and speaking of responsibilities, we've got a panel of students getting ready to come up here So as I love talking with you. Thank you so You're welcome. So very much.
And thanks for having me back. Take care, everybody. Thank you, everyone. Thank you.
