Building AI Literacy as a Core Competency  transcript

Welcome everybody.

I'm, we're very excited to be here for the future of learning live.

We're going to be talking today about building AI literacy as a core competency.

It's wonderful to have educators joining from across the entire world.

I was seeing in the chat, we've got Italy, I saw Egypt, I saw Texas, I saw Milan, all these places I want to go to.

So we're very excited to hear your perspectives and for you to hear what our panel has to say.

Today.

We talk so much about preparing students to live, to learn, and to work alongside AI.

But moving from that ambition to practice really raises some challenging questions.

So what does genuine AI literacy look like?

Who owns it?

How do we equip educators to teach it?

And how do we build something meaningful enough to work across different disciplines, contexts, and future roles?

So that's what we're going to explore with you today for the next .

And we want this to be a conversation with all of you as well.

And so you're going to see we'll have three different pauses throughout here to ask some polling questions that'll help us in the future of learning live in AI and education.

So first, I'm going to start by introducing the panel so you all know who we are.

I am Jessica Bernards, I'm a math professor, Pearson author and an AI and education consultant.

And I will have Mustafa go ahead and introduce himself next.

Thank you, Jessica.

I am Mustafa Akben, assistant professor of management and director of AI integration at Elan University, North Carolina.

I work across teaching, research, universal operations, and I see a electricity both in classroom and institution.

So I'm excited to be here today.

All right, Doctor Syed, if you'd like to speak.

Hello, everyone.

I'm Saeed Bahari.

I lead the Center for Future Studies at the University of Dubai.

My work focuses on AI governance, digital transformation, and strategic foresight.

I'm especially interested in making AI literacy a core competency for every learner and helping educational institutions to embed it systemically across curricular teaching and assessment.

I'm delighted to join this important conversation today.

I'm very excited to have you.

All right, and Claudia.

Hi everyone.

I'm Claudia del Pozo, director and founder of EON Institute, a Mexican think tank that focuses on helping societies thrive in the age of AI.

Our work sits at the intersection between public policy, social impact, and emerging tech.

And of course, we're talking a lot about AI governance, future work, education, democracy, and our work has to do with connecting Latin America to the global conversations and bringing Latin America's perspectives to them.

Thank you everyone for being connected, especially people from for Mexico.

I know it's a day off.

Thank you so much.

We are so thrilled to have all three of you.

I know I've already learned so much from speaking with you all.

We're going to start with our first question and it's going to be to everybody.

We'll start with Claudia since Claudia went last on this last one.

So defining AI literacy.

We use the term AI literacy so much, but can it can mean so many different things to different people.

And So what does it actually look like for a student in practice and where have you all seen it working?

Well, this is a big question and we each have about s for answering it.

So I apologize, but go ahead and start with Claudia.

Thanks, Jessica.

So I want to focus specifically on what it means for students.

It doesn't mean just using it and having a general idea.

It means a really understanding how it works and where its limitations are, because where the limitations is, are is where we need to come in and have our, our human judgment in place.

And I think something really important for students is also understanding that while a lot of the LLM tools look very similar, they treat information very differently.

And so based on what you're trying to do, you should use one or another.

So for example, ChatGPT and Claude, which I'm sure everyone knows their general purpose assistance.

So you'd use them more if you want to search and synthesize.

But if you really want something that's more search oriented, you might go more to perplexity because it focuses on retrieving sources 1st and then working with that information.

And then if you want to work on a specific set of documents and material you already have and you go to notebook LM because it's a lot more more restricted.

So I think for a student, it means also knowing which tool to use, when to use it, why they're using it, and when they need to kind of not trust it.

I love that and having some guardrails.

We really need to make sure students understand those guardrails along with it, which is why I love the Pearson AI study tool with how it has those and already embedded within that.

Go ahead.

And Mustafa, let's have you go next in.

In line with Claudia's points, I see a literacy relation between the tool capabilities and human responsibilities.

Students needs to know how to get useful help, but also what information to protect, what to ask, how do you verify, and what do you think about and with and without AI.

We publish a recent students guide to AI.

It's publicly available, downloaded more than 20,000 times.

Students guide to ai.org people can access.

In that guide, we focus on durable human wisdoms and how people make choices across boards and time and we see similar skill set being happening.

And for me, as a practical test, whether students show their AI literacy, they can show their reasoning and include to decide and make their own judgement when to follow AI and not.

That is kind of the state that kind of test, litmus test that I have at least I can add.

It's great.

All right, Doctor Saeed.

All right.

So for me, I guess AI literacy is about the ability to work with AI effectively, question it intelligently and take responsibility for, for how we use it.

That brings 3 or 4 components here.

It's about understanding how AI works, you know, it's about practical skills that students need to have to be able to use it effectively.

And also it's about ethical awareness, knowing when, when the AI you know biases and, and, and you know about transparency and, and other things.

And the human judgement, I think is really very important for students.

I guess, you know, being able to critically evaluate, evaluate its output is also very important.

I've seen this is working.

Probably we have an experience here in the UAE.

Our Ministry of Education has mandated AI literacy for all public schools this year in 2026 for AI literacy is integrated in the curriculum.

Educators are also being trained in AI literacy, especially with a focus on, on, on ethical use and assessment through usually those student surveys and, and teacher surveys as well.

I love that.

And I'll just add a few things.

I think also it's helping students understand what happens to your brain when we offload our thinking and learning to AI.

So we're not just saying don't use AI in these ways, but we're helping them understand why using them in those ways we'll end up having consequences for themselves in the long run and how to use AI to as a thinking partner and learning partner instead of, again, that offloading.

One of the analogies I always use is AI is kind of like a Lamborghini.

It's super smooth and modern, but if you don't have a human in control at the wheel that knows the rules of the road, how it should be moving and driving, it's going to crash and burn.

And so same thing with AI.

We shouldn't be using it unless we know what we're asking it to do so that we can make sure we're using it appropriately.

But on top of using AI, we need to help students learn how to be critical consumers of media.

Because now with all of the synthetic AI that's coming out with, you know, videos and, and images and photographs that look so real, they're constantly getting bombarded with those visuals and their social media and ads.

And so really being able to look at something and understand that we need to look at see if there's reliable sources that are also sharing this information to see if it's a reliable like a true video or if it's an AI video before we hit that share button and start having all of this stuff getting perpetuated.

That's really not true.

And that was AI driven to make someone be have a viral video.

So I think it's all of those things.

I love, I love what everyone shared.

Thank you.

We're going to move on to institutional ownership.

So if AI literacy is becoming a core competency, who should own it within an institution and what needs to be true for that responsibility to translate into consistent practice?

So doctor said, you just talked about in the UAE how you guys are already starting to do these things.

So I'm going to have this question be for you.

Great.

So AI literacy, I believe is a shared responsibility with a clearly accountable academic leader.

I think institutional accountability needs to be with the Provost or or someone equivalent in academic as academic leader because AI literacy concerns the quality of learning, assessment and and graduate capability as well and should be implemented across the institutions.

Program leaders should embed embedded into curricula and educators need to integrated and teaching an assessment, while the technology and governance teams should provide appropriate tools and safeguards for the responsibility to translate into consistent practices.

I believe there are five important things must be established.

First, there must be a shared definition of competitiveness of of competence.

Every graduate should be able to use AI appropriately, evaluate its output to recognize ethical implications and explain their own decisions.

But also it must be built into learning and assessment.

We need to identify where the students you know, first encounter these capabilities, where they practice them and where they demonstrate them.

Third, educators need also time and the preparation and support.

We cannot expect teachers to develop, you know, students AI judgement without proper AI literacy training.

Students also need clear expectations and rules when to use AI and when not to use AI, and also equitable.

They should understand when AI is appropriate, how to acknowledge it, and what understanding they must demonstrate independently.

And finally, leaders must examine evidence of learning.

So success means students can recognize and reliable answers justify the choice, their choices and take responsibility for their work.

So finally, there are three conditions I think must be established for consistent practices, a university wide standard.

I think this is something important with a clear, defined capability and an accountable academic authority.

Second, the planned learning journey, including names, named courses, assignments where where students develop and demonstrate those capabilities.

And last but not least, an ongoing review process includes faculty support, scrutiny of assessment and update and updates as AI and professional expectations change.

Yeah, I think that's wonderful.

And when you're talking about the AI literacy for faculty, I think MIT just came out with a study and they did a bunch of research on this in August is one that came out this report where they talked about AI literacy.

So many schools K through 12 and higher Ed or just doing like a one hour training and checking the box.

It's just a check box.

And that's not enough for AI literacy, especially for educators.

They need to have a very robust understanding of how AI works, how to make sure that we're teaching our students appropriately with bias.

We don't want them to perpetuate bias throughout their understanding.

How they can start using it with assessments.

How do we assess in the age of AI?

All of these things need to be involved in that.

And how do we have critical conversations with our students about appropriate use and inappropriate use?

And that doesn't happen in a one hour, you know, overall training.

And so I think it's really changing that narrative to what schools have been doing to really get that robust AI literacy training out there.

Mustafa or Claudio, do you have anything you want to add to this?

You guys are good.

OK, so we're going to start with an audience poll.

So on the screen, you're going to see two questions, which best describes AI literacy at your institution today?

And then how role specific should AI literacy become?

I'm going to give you about a minute to go ahead and fill those out.

This feels very suspenseful and I'm very excited to see the results.

I know I am too.

All right, so it looks like we had about 53%.

That said, we are at an early stage, no formal approach yet.

We're still defining what AI literacy means.

Oh, and this is kind of split.

And the second one, how role specific should AI literacy become?

Most people chose a common foundation, but most expectations should be discipline or role specific.

So one thing I saw in the chat was you can just use AI to create an AI literacy guide for students.

And I just want to pause about that because again, part of this AI literacy is we need to, we're the experts.

And so I've tried to do that and I will tell you, it's not good what comes out from that.

And so just again, you always want to have that human in control and making sure that we're using our own pedagogy and research as we're creating these guides and having expertise to kind of look over them.

We can't just take an AI output because there's an AI output.

It's going to be pretty up high, and it's really important that we have all that detail that students really need.

So this next question is for Claudia.

A lot of faculty innovation starts individually.

What helps institutions move from isolated experimentation towards something more coordinated and scale scalable?

And what tends to make the biggest difference?

I'm so glad you asked this question because I think there's huge misunderstanding when it comes to AI.

We have this idea that I will save us time and give us more efficiency, and it will, but not immediately at first.

We need to invest so much time to make sure we eventually get that return.

And I've seen a lot of institutions and organizations kind of throwing like really powerful models at their teams and then saying why aren't we more efficient already?

And then that's not how it works.

You know, to understand it, first you need to create a strategy.

Before that, you need to do some research and you're going to go through a lot of iteration between thinking, experimenting and strategy.

So I want to give you kind of three steps that always need to be reiterated, which is start with the why and the what.

A lot of people are adopting AI without understanding why they they want it, what they want it for, where can it add value?

What problems are you trying to solve?

Where don't you want AI?

What should be the role of humans?

And I think that what's interesting at this stage is you can already ask people in your teams how they're using AI.

You need to have this conversation with the entire faculty.

From there, you can build an initial strategy, you know, guidelines, policies, governance is really important and which tools are authorized and supported.

And then the last element that I would add, which I don't see happening, is creating conditions for experimentation and shared learning.

Why do you have regular sessions to exchange use cases, create challenges to encourage faculty to try new tools, share workflows, successes, but also failures.

Where does it not work?

Because if we don't do that, everyone's starting from zero and we really need, don't need to start from from the bottom.

We can work together.

So that would be my advice, Agreed.

I think we need a global like where we can all share ideas and things that we've done.

It would be so great to have just like a Slack page for everybody, but that would probably get very overwhelming.

So we're going to move on to Mustafa's and talk about thinking alongside AI.

So how can educators help students use AI in ways that support their thinking rather than replacing it, which is, I think I've heard everyone say something about that in here already.

And what approaches have you seen that's worked particularly well in the classroom?

So that is one of the challenging questions.

I mean we are addressing all those challenging question, but that is one of the for me as well.

There's a couple of ways that I try to approach and I'm happy to share a few of them.

So our brain and students brain didn't change at least yet.

We know it maybe in the future what changes they have right now easy access to such a tool and gets them to pass difficulty without any kind of struggle.

And we know that from the learning science.

Learning needs difficulty, learning needs struggle.

Struggle is the word that learning and neural networking our brain.

So the question isn't AI or not how we are going to use AI to advance or maybe prevent a certain way.

The more like how we bring this struggle, the productive struggle back in the classroom despite against AI.

There are a couple of really nice research has shown that AI can be utilized to advance and use as a struggle makers in the classroom.

Such as you had developed a new AI tutor, rather than giving direct answer, it pushed students towards much more supervised tutoring system.

That's increased students learning outcome.

And also based on my practices and based on my reading discussion with other experts, I just noticed there's a couple of approach we can adopt in our classroom to make it much more clear and much more better.

The first one is be explicit.

That is a part that I believe we need to increase that explicit with students and open communication with them.

Tell the students use it for this and use not use it for that and here's why.

Do not give the students a policy.

This is the syllabus based on that, you shouldn't use it more reason.

When people see the significance of these in their personal life, they're going to connotate and connect them, connect this issue better.

So the second flip the order, I will say I do flip classroom and some people may get angry at that because I didn't change my design of class.

Since Chipt just came, I've been doing flip classroom and I got less impacted that I understand it's not possible for every classroom, But when you bring these exercises application in the classroom, you're going to have a first hand experience how students apply the knowledge that you, you know, imbued them.

And the third is there is a place again, I always stress to use it and not I personally believe you need to establish the baseline, whatever concept and you need to set these foundational knowledge.

Maybe you can just go over the semester to introduce some of the AI tools when you go to, you know, second-half of the semester.

So my message here, keep difficulty in classroom, they bring these positive struggle and move it where you can see it.

As an educator, we know our class better than others and overall that is the place.

Kind of comments that I can add, love it.

I'm a huge proponent of flipped classrooms big time.

So there's going to be a new audience pool that will come up.

Which is which one of these would most help educators build AI literacy into teaching and learning?

And which one of these areas is currently the biggest gap at your institution?

Give you guys another minute for this one.

All right.

So we got pretty 51% of practical training, experimentation and peer learning.

That's huge.

And that's what I think is really helpful for educators is having those tangible things that they can leave a training with.

And then we're very split again on #2 here.

Which one of these areas is currently the biggest gap at your institution?

It looks like majority of people said practical training, experimenting and peer learning, which I completely agree with those.

Both of those answers go hand in hand.

All right, so let's move on to what we'll be doing.

Let's see Claudia again, and we're going to talk about some new models of teaching.

So what's an example of AI in teaching that you felt genuinely new to you?

So not simply a faster version of something we were already doing, but a meaningfully different learning experience.

Right?

Thanks for the question and I want to give two.

I want to give 2 examples.

So the first one has to do with creating a really different learning experience.

When I was back at university, I remember we had so much reading to do, so much that we had something called reading week, a week where all classes were canceled and we could dedicate it to catching up on our reading.

But I wonder how necessary that would be nowadays.

I mean, nowadays you can upload material to different tools, some of them like notebook LM turning into a realistic podcast.

It's really entertaining and you can actually interrupt and ask questions.

So that's just, yeah, that's really exciting.

And if you're not doing the same thing faster, you're actually experiencing and engaging with the material differently.

And imagine we're only a few years into this technology.

Imagine where it could go.

The second one, and this one I'm really excited to share, is changing what we assess, redesigning learning for a world, for an AI world.

So I was speaking with this professor and what he was telling me is he doesn't just ask students to write a paper.

He knows they're going to use AI.

So what he asks for is for them to use AI, give him the final output, but also give him the conversation that the student had with the LLM.

And he grades both.

And that way we can evaluate the thinking process, not just the output.

You know, what did they ask?

Where did they challenge it?

How did they improve the results?

And I think these are the examples that we need to be collecting and sharing.

And the poll really showed it.

So yeah, I don't think banning AI is the answer because if we know one thing for certain about the future is that AI will be there.

So if we're not teaching our students to use it properly, responsibly, that would be a mistake.

Love that answer, completely agree.

Let's move on over to Mustafa student preparedness.

So students often arise on campus already using AI.

This goes straight with what Claudia just said.

What do you notice about how prepared they are to think critically alongside it?

And what do you see the biggest gaps?

So here's what I noticed.

They are fluent with AI and when you look at the survey data, you're going to see 9590 personal students are using AI.

Even in high school they arrive but they don't arrive calibrated.

And previously I imagined AI fluency is not AI literacy.

There was a research if I'm not wrong from the computer in human behaviour or something.

They gave people 20 logical reasoning problem from LSAT and they let them use AI and not use AI.

And when people use AI, the performance up almost three points.

They are fluent.

They are using very nice sales assessment.

After one hours all on general went up.

People feel better and people feel much more accomplished.

However, when people look at how people calibrate it, calibration means how much they actually know what they know and what they don't know.

There is a huge gap.

It's like a Dunning Cragger effect.

Most interesting part of it, students with much more calibration underestimate their learning student without less calibration overestimate.

It's kind of increasing students confidence without a real kind of underlying foundation in their learning.

And that is an important students need to know that a real conceptual knowledge how they model work.

They can overestimate, they can overestimate their learning with AI and still we need to rely on that old method.

Sometimes you need to go with the not taking handwriting parts.

So gap isn't access.

Many students already can access companies already giving a lot of great availabilities, good, good or bad.

It is more like using it effectively to focusing on their learning.

And when we look at that, they focus on efficiency rather than learning.

The mindset I believe needed to change the gap is mindset here, if that makes sense.

Yeah, it makes complete sense.

Well, so said.

All right, Saeed, for let's talk about pace of change.

So higher education moves deliberately for good reason, but AI is evolving so quickly.

I think I saw some a couple people in the chat talk about that.

So our institutions moving fast enough and I think we all pretty much know that answer.

And how do we preserve quality without allowing the pace of change to leave us behind?

We've got about two minutes for this answer.

So I'm, I'm really not surprised when we looked at the, at the poll, the first poll that came out with 53%, you know, saying that, you know, still net AI literacy is not systemically applied at that at university.

I think my, my opinion, the progress here is uneven really.

Some institutions are moving in a good pace, but generally across the education sector and institutions ability to redesign learning and assessment is struggling to keep pace with the students user AI and many have have indicated this.

I think the speed that matters is how quickly can how quickly they can establish educational sound practices.

I believe that institutions need the stable educational principles that is important but more agile and adaptable and institutional practices.

For example, a critical thinking, disciplinary knowledge, ethical responsibility and human agency.

These are should be remain foundational, but the tools, the teaching methods, the guidance need more more frequent review and practice.

I would emphasize 3 things I think first, establish a minimum AI literacy baseline and we spoke about this early.

So for students should already be learning how to use AI effectively, verify and judge the output, recognize the bias and and limitations, protect the data and take responsibility for AI assisted work.

And the second, and I would stress again this this fact is that invest urgently and faculty AI literacy again, you know, faculty are very well trained on AI literacy.

Of course, they can't transfer this knowledge to students.

We spoke about, you know, redesigning assessment.

But I would say 11 important thing is that to really replace the static AI policies with adaptive governance, I mean institutions need continuous cycle of I come from a foresight perspective.

So when they need a continuous cycle of sensing, experimenting, evaluating and updating, they should regularly scan, you know, what is changing around the environment, run controlled experiments, examine evidence you know of, of, of learning and risk and update guidance, you know, and curriculum and curriculum accordingly.

I think the ambition, the ambition here should be to move quickly enough to shape the students use of AI, but at the same time carefully enough to demonstrate that it strengthens their their learning.

Makes very much that's makes sense.

We're going to throw up the last audience poll for you all.

We've got a minute to do this so that we have a chance to just really get our closing.

So who should have primary responsibility for leading AI literacy across an institution?

And oh, I'm really interested to see what you all have to say about that.

And then what would best demonstrate that a student is genuinely AI literate.

Yeah.

Michelle is saying in the chat, I need all of the above on #2 completely agree.

I think all of those have to be stakeholders within that conversation.

But who should be the top leading it?

All right, about s to finish this.

OK.

So we got responsibilities should be shared across all these.

Not surprised that people said that.

I do think we need institutional leadership, though, to kind of be that primary person because we do need to make sure that we have funding for this and that they're putting funding models towards this and showing that it's something that's a value because if we don't have funding, it's not going to go mainstream.

And then for the next, Oh my gosh, our poll 2 questions are always all over the place, but they can demonstrate capability both with and without AIA.

100% agree with that one.

All right, our closing action.

So we only have here.

So if we can try to keep it to like s for our answers.

For an educator or academic leader who wants to move from discussion to action, what is 1 concrete thing you would encourage them to start doing next week to strengthen AI literacy?

So what can you all start doing right away?

Let's go ahead and start with Sayid on this one.

OK, so I would I would ask an educator to run a exercise, a short AI literacy diagnostic.

Give the students a realistic AI generated response related to their subject and deliberately include maybe a mixture of useful insights, some factual errors, unsupported claims and missing perspective.

And then ask the students identify what they trust and question.

Verify 2 claims, maybe using independent, credible, credible sources and recognize any bias, ethical concerns, or important emissions and improve the answer and explain the reasoning behind behind their change I behind their changes I.

I think this exercise will show how they can evaluate evidence, recognize limitations and remain intellectually responsible at the same time for the academic leader.

Maybe repeat the same experiment, but with that different department and group and then see, you know, the common findings that that that that can come out of this.

I think the result will can guide us to, to to to look into more into curriculum changes, faculty development and and future assessment design.

Love it.

OK, go ahead, Claudia or actually Mustafa, you just unmuted, so let's go away for you next and then we'll do Claudia.

Yeah, I did.

I did a research on that similar issues.

Look at how the complexity of, you know, level of jobs increase, how people's usage of AI change.

And I see the similar patterns in education institution as well.

What I'm trying, what I'm what I'm coming, we need to learn AI to teach AI, we need to understand and the AI literacy across the top of the leader sometimes is lack.

If you want to do something tomorrow for your students, learn how to use AI because students want to learn ethically and if you learn, you're going to teach better.

Great, go ahead, Claudia.

Great.

And I think this ties in really well with Mustafa about how to learn.

So for my answer, I want to take you back to the 90s.

Remember when we started getting computer in our home, they came with some games like Minesweeper, which is a horrible game, but it helped us get comfortable with right clicking, left clicking, navigating, exploring.

We learned how to use computers through games.

And why are we not doing that nowadays?

I think that if you could take one concrete action next week, it would get to get together small AI exploration group within your institution to create dedicated time to play with AI.

It's not about attending a training.

There's no stress.

There's no expected results other than just, you know, getting familiar with it and seeing OK, how good to do the different tools work to understand how they behave.

Where do they help, where do they not?

Or do they fail?

Definitely.

And where do you think human participation needs to remain?

So kind of like a low stress, no pressure, no, no particular result expected, just playing.

And then what works and what doesn't?

And again, stop making everyone figure it out from zero.

And I'll just add this one last thing.

I know we're about to be over, but one of the things that it's this activity is posted on every learnereverywhere.org.

But one of the things that I started doing in my classroom with my calculus classes, I actually have them for one of their labs.

Every week we do labs, I have them create an AI chat bot, which sounds brilliant, like technical.

It's not.

You just give them the right prompt to use, but it shows them how they can use AI to enhance their learning.

It models that for them perfectly.

And so the prompt is I'll pick a topic that's hard for them to learn about.

So you substitution.

So explain you substitution to me like I'm in fifth grade #1 #2 have me explain what you just said back in my own words and critique me once I have explained it back correctly.

Then give me 3 practice questions of various difficulties, one at a time.

If I get the answer wrong, help probe me to figure out where I made that mistake.

And then come up with a similar question for me to try again.

And then if I get it right, move on to the next question.

And then our my students would turn in their AI chatbot log as well as the work that they did for each of the three practice questions.

And that was so huge for them.

That just got the reflections that they had on that were like, wow, I now know I can use AI in this way and it helps him really understand it and personalize it to me and how I learn and what I was making mistakes on instead of just giving me the answer.

So I'm going to remember that so much more and wow, I can actually use this for more than just calculus.

I can start using this prompt in all my other classes.

That's the cool thing where if you're not using a Pearson product, definitely go there.

But that's the really neat thing with what we have already built into Pearson products with that AI study tool is those guard rules are already in there.

Will they will really help the students learn and grow and be engaged in that learning process to understand where they're making mistakes and explain it to them in a way that they'll understand.

So I definitely recommend if you are using a Pearson product that you kind of get into that AI study tool and give it a give it a try.

I've been extremely impressed with it.

So I think that is all of our time today.

But thank you so much everyone for being here.

I know there were so many other things we could have talked about.

Someone talked about wanting to hear about assessment strategies, which that could be a full presentation in itself.

We will be coming out, we are all on the AI strategic panel for our council for, for Pearson.

And so there will be a document coming out where we're going to be talking about assessment in the world of AI.

So definitely keep your eyes and ears open for that.

We'll we'll delve into that.

Really appreciate everyone being here.

So fun to see where everyone's coming from and just appreciate your time and have a wonderful rest of your day.