The Hidden Trillion-Dollar Tax on Your Balance Sheet: Fixing Organizational Friction
WethosAI — https://wethos.ai/resources/videos/the-hidden-trillion-dollar-tax
Source video: https://www.youtube.com/watch?v=pA7d_VJafmk

Heat. Heat. Hello and welcome to the Conference Board. Today we're talking about the hidden trillion dollar tax on your company's balance sheet. In fact, the way your teams are making decisions, accountability, and the way you compete in today's incredibly competitive business environment. My guest today is Stuart McClure who is a prominent cyber security and AI entrepreneur veteran who has started five organizations, five companies, two of which had incredibly successful exits, one of which was McAfee and the other BlackBerry.

and he has spent 35 years, not to age you, using AI to predict and prevent catastrophic cyber attacks at companies like Cylance. And now as CEO of WethosAI, you're taking that same predictive intelligence to a new kind of let's say malware which is human organizational friction, a topic that I particularly love and it exists in all organizations and we know that it's there but you think at WethosAI you can do it better.

So, we're gonna spend some time talking about this today.

Thank you so much. Yeah, I'm looking forward to it.

Great. What

I am too.

People are going to think about this.

So, we're asking you the question and please go ahead and cast your vote. Thinking about how your team operates today, what's the primary reason that deci key decisions get delayed? And we have a number of options here for you. So link to some key biases, information, alignment theory, loss aversion, status quo bias, and angry way.

What do you think is going to be most popular? Well, it just depends on the audience, you know, and it depends on the cultures inside of each company, which is largely led by the CEO and the executive leadership team.

You know, if you if you ask a Jamie Dimon of that nature, that kind of a question, it's going to be we just get buried in slow decision making, multiple committees making these decisions that are overly complex, but really they're simple. complex

that that creates this culture. But then you have others that are startup mindseted or smaller companies that just want to move, just want to pivot fast if they're failing. So it just I think it depends. I'm really curious to see what comes.

I love that you gave us both ends of the spectrum. Let's take a look at what our audience had to say.

Okay. H that's exactly what we predicted. Okay, so we're seeing that this is great 61%. So the majority of you are saying needing broad buy in or multiple approvals before acting. We calling that stakeholder management.

as a corporate veteran myself, I would say that is the socialization all very important. and you talk very much about that being alignment theater.

So this kind of tease up my next question.

So let's talk about what you mean by that and the hippo effect which I actually I I know that well but I've not heard that term before. I love it. So let's talk about that a little bit. What does that mean? Yeah.

And what's point of view on that? So the the hippo effect basically says that the highest paid officer or individual that's on the meeting often simply gets deferred to.

Right? meeting

and it it becomes almost like pretend alignment.

Like everybody's on the call. They're supposed to have a stake in the decision-making and own the action. But often their voice gets simply drowned out because we just want to make the boss happy. We just want to make the most senior person happy. It makes total sense.

And it's actually leveraging what, you know, I call human vulnerability.

So I've spent Tell me a little bit about that.

Yeah. vulnerabilities,

right? Systems and networks and applications.

Now I've turned all my attention using AI into the human vulnerability. So, what are our vulnerabilities as humans inside the workplace?

It's things like this. It's meetings where your voice is really, really important, but it's challenging for you to be heard. You might be an extreme introvert.

Yep.

Now, we still pay for your brilliant mind. them

because we're deferring to either the loudest voice or the highest paid officer. But nine out of 10 highest paid officers simply want the best decisions and the best consensus and collaboration that can possibly be had. They don't have to have and I used to say it all the time. If I'm the smartest person in every room I walk into, we have a real problem.

Yes.

Because there's no way.

that's

I can be the smartest person in every single room. Nor should I be by the way.

I'm paying people to be smarter than me. So that's where I think all of us as leaders really have to recognize these unconscious vulnerabilities that happen to us every single day. We call them unconscious cognitive biases.

Now they've served us well to survive in the world and thrive as best we can but they don't always work for every situation. biases

unconsciously so that you can be almost what we call metacognitive. You can be thinking but you also can be thinking about how you think. acting

and testing those decisions out. it,

right?

And then feeding it back hopefully into a loop, a learning loop where you get better and better and faster and faster and that's that's it. I mean, that's all knowledge work is at the end of the day. Well, that's a really great way and a clear way to think about knowledge work because you often hear about this and we hear about decision-making and there's so much data and how do we make the best decisions.

We're not talking about today, but we're talking about what happens in the room. Yes. and the alignment that also happens before the meeting. And I know you've kind of quoted Andy Jassy as well as Jamie Dimon in this whole alignment theater. But let's make this practical. Would love to take a look at this and we're going to move on from the poll and we are going to take a look at a WethosAI platform demo.

Yeah, let's have a little fun with this. Obviously, to really hit the point home. So, in the demo that you're about to see, they'll roll that out. You will start to see what I call meeting parody. You know, I don't mean parity as in equal, but like parody as in we're going to have a little fun with this.

Yeah.

So, as we see every single day as we join a meeting, there are many different effects that could occur. And the first of which is what we talked about the hippo or the highest paid officer being present. And this often happens when I get on a meeting embarrassed to say it even to this day. Now we helps tremendously on the back end because now I can completely simulate the decision making based on the stakeholders that are part of that and need to be collaborated with.

meeting

to prior before the meeting. diversity

presented,

it's now okay, we've already had this meeting. We've already discussed about this topic specifically.

We're using your pers specific perspective to contribute substantively to that decision. And now we just have to come on board as humans and take action. we have to agree to the decision or refine it if we don't and then take action and measure it over time.

Right?

So that is the most important part. So I don't know if we can tee that up.

Yes, we'd love to see Yeah, we're going to run that demo.

You should see that momentarily and then you'll There we go.

are

Why are we here again? We're waiting for Stuart to join our fearless leader.

Sorry I am late gang. So, what has the team decided?

Okay, everyone. Did you take a look at the deck I sent out? No one looked at it. Okay, let me run you through it all live again right now. I really need your feedback.

All right, so hopefully you'll recognize a lot of those moments because we see them every single day in just about every single way. But I'm going to show you how we completely upend this dynamic with WethosAI. So you can take any concept, any idea, include anybody in how they think and and why they think what they think and include their perspective and viewpoint into the discussion all without anyone actually being there.

So inside of the WethosAI platform, we chose the topic and the goal. We chose the people that need to be involved in and own ultimately the decision and the action and be held accountable, which is a big part of the gap in AI today. You can't hold AI accountable for decisions. You have to rely on humans and for the foreseeable future you'll need to.

But as you can see, each of these opinions and viewpoints based on the topic and the goal is all simulated to an over 90th percentile alignment with how you actually think and bringing your unique perspectives into the workplace and for every decision. So we can do this for individuals and we can do this for the institution as well.

So institutional knowledge now becomes quantifiable. We can actually bound decisions inside of cultural controls or mission vision values so that decisions do not go off rails from the company, the organization or the department itself. And the decisions can be auto assigned. So decisions can be documented, objections can be documented, conflicts can be documented.

All of that becomes then a way to simply understand quickly how we made this decision, why we came to be with this ultimate idea of how to fix something or to change things going forward. And then a complete summarization and an accountability system in effect for everybody to own now. And in this case, these are all simulated discussions and simulated decisions that now we can jump onto a meeting and instead of talking about this, we can talk about the solution and if we need it to be refined or if we can take action and and start to move forward with it.

So this is a big part of and obviously the voice over is is playing right now as well to sort of walk through it.

Okay, great. Oh, there we go. All right. So that is WethosAI in a nutshell in terms of really changing the way that we think about coming together, making decisions and then taking action on them very very quickly. This is the key. organization

and that's one of the things that holds us back. You know I've been senior leader at Intel, at McAfee, at Ernst & Young. I know the machinery that gets created and it's in part why I started different companies from scratch is because I knew we had to fix this.

you

and I'm the final brave thought is that I can actually apply this to every company under the sun. alignment

instead of theater but actual alignment in the workplace. So when we think about that, let's talk, we're going to move into this kind of whole differentiation between the cognitive twin and the digital twin. us

faster,

cut through the alignment theater. Tell me a little bit about what that means.

So, what we've spent two years non-stop trying to build is how do we take a human being and all of their unique experiences in life and memories and how they've formed neurologically their brain and their behavior? How do we quantify that so that we can represent them? Yeah.

Inside of this virtual simulated world of decision-making so that every company can get to speed and get to high quality expert knowledge decision-making in the frame of the human resources that they have in place. And that really turned into this complete behavioral framework and system of quantification for both traits and cognitive biases. So we track on over a hundred individual behavioral traits.

Let's stop for traits or just let's define traits.

decision

uniquely you. Right.

Uniquely you. Yeah. Strength and opportunity areas. Ex. Oh absolutely right. And we call them they're not strengths or weaknesses. They're actually just unique ways of existing that you bring to the table that make your decision-making unique.

hundred

over a hundred of these traits. So I'll show you in a second.

Yep.

Then we also track and manage or measure over 120 cognitive biases. Now these are the invisible forces that drive us every single day. You're not even aware of most of these. When you see the list that we have we are tracking on, you'll start to realize, wow, this invisible world of the drivers of our decision-making is actually mappable.

It's actually understandable. solve

that creates your unique contribution into any discussion.

So we map and create what we call a cognitive twin.

So not just a digital twin. people

twin

and often it's for all kinds of reasons. to

this

2013

great

function

so we can virtualize its function now why would you do that in cyber security well because I can hack it Right.

If I can virtually hack it without, you know, actually taking down, you know, some sort of like oil rig. Yes. know,

or security system at a airport or any of those kinds of things. If I could do that all virtually, now I can harden it. I can make it stronger. I can make it more defensible.

And so that's the same concept here, but we're now mapping it to pure thought.

Right. Right. And that's the cognitive component.

That's the cognitive part. Exactly. So quite a unique way of looking at the twinning aspect.

So I'm thinking a little bit more about this and I know we're going to get into Kahneman's thinking systems one two and you're adding in three but also he talks very much about the cognitive biases as part of you know his work and his argument does my cognitive twin grow as I grow? Does it learn? Does the context kind of shape my cognitive twin?

you

yep

that that's how you are forever. forever

right

yes

success

learn

yes

you

you

AI

think

system

okay

knowledge

that

right

ultimately changes and morphs so that's what's so important about this cognitive twin as well it's not just the full-blown own sort of quadrillion space of uniqueness that we create with traits of biases.

But it's but it's also simply that we learn about you all along the way. it,

y

as you create your own memories and your own new decisions and your experiences and contribute into it now, it learns who you are at every moment.

So if I make a mistake, which is which is great, right? Because we're operating so quickly today. And I really don't think that you can compete and survive in business without making mistakes and get moving quickly and iterating.

What you're saying is my cognitive twin will be able to learn with learn.

you,

right?

So that if you learned something yesterday and you want to apply it to a decision today, you can do that.

It's amazing.

Yeah, it really is groundbreaking and innovative technology.

Should we take a look at it?

Yeah, let's do it.

All right, great. So, we're going to run our, second demo and you're going to do some voice over and we'll talk a we have some time, so let's talk a little bit about it after.

Okay. Okay. Great. All right. So, the big question always with a cognitive twin is the how and the why. How do we measure what we're measuring and why you think the way you think? So at the very very top level we have a four core elements of behavior which is ideas, relation, action, order. Now this means that you might be a storyteller or you might be somebody practical.

You might need to relate to people as as a personal level or you want to relate to data. And this diverse set at the top level can also be seen through the prism of either being concrete or more abstract. As you can see here, I'm much more abstract by most measures at the top level, which is what you would expect.

But here's where we get into the detail. So these are the traits that have been documented and quantified and my relationship to each of these traits. So I might be mo low, medium, high. I might have high confidence in each trait. And the same thing with the cognitive biases. So as it's observed, these are my it' be a shock, right? Innovation bias, overconfidence effect, like all of these things.

This is the natural part of it. So how does that play into it?

Well, because we know you so well at that level, now I can start to learn about myself more. I can improve and achieve set any goal I want to for me personally or at work. But also I can actually engage my virtual twin, right? So my cognitive twin. So in here I'm actually asking, well, how do you know what you know about me and how I make decisions?

So it will actually enumerate all of the elements that really make me unique versus Arenita out in the world or anyone else.

And it's that uniqueness that we need to present forward because if you look at how AI is built, it's generic. Okay, it's generalized. It's been trained on general data, not on you specifically. And that's where we change the game.

And so because of this, now we can actually understand why you make the decisions that you make.

And now you can iterate very quickly into the best decision, test it out in the real world, and feed it back into the decision-making system so you can get better.

And so this is what we and what we do every single day for every single employee. You could take it from a leader down to their senior leaders or you could take it all the way to the frontline individual contributor and up into the leaders and managers of those people as well.

Great. So let's let's spend a little bit of time like unpacking this a bit. So if I if you and I are part of the team, we're in a team meeting, how would I prepare prior and then I would feed back in what happened into the meeting?

So you can do it a number of ways. One is if you have materials that you've already prepared or thought through any documents or powerpoints or whatever it is, you can include that as part of the decision-making.

So that confines it or that controls the context. You can also map into drives that you would normally be sharing like let's say if you're a Microsoft shop, you could go into you know your OneDrive or your SharePoint drive or whatever. If you're Google, you can go into Google Drive. So you can you can map your decisions to the institutional knowledge as well as the individual project knowledge.

That's amazing.

Yes. Okay.

So now I can literally set you know my vision and my values inside of every single decision.

Oh that's where the culture piece comes in. Okay. We have that we have the institutional knowledge.

Exactly. company

then that decision is going to be underweighted.

Okay.

Right. Right. be

because if it doesn't align to the mission and vision, well then you either need to ditch it or you need to change the mission vision. Like if somebody says, "Look, we're only going to make decisions that are," and this is an easy one and a dumb one, but they're all they're all legal and ethical decisions, right? want,

you know, non-defrauding legal and ethical decisions, right?

And someone makes a decision that is not that. and

that

SPF and Yeah. Like I mean, you go on and on and on with this, right? And a lot of the group think and a lot of the hippo effect all occurred in that. Yep.

Yeah. you're just deferring to the smart people, the ones that get paid more than you, right?

And that's where the biblical fail really comes. But

team

decision,

alignment,

right?

Like automatically. So now you can walk into any discussion with anybody else and be in near complete sync before you even start. Now, does that even do you like the output of the meeting? Do you get so we have all of these elements and it's helping shape some of the decision-making. Do you get some sort of document that says this is what was covered here are the action items and it includes all of this.

Exactly. So, you go into any of these virtualized or simulated discussions and you can actually contribute in there. great

so you can see okay we first started with this idea these people had these great ideas but ultimately were proven to not be viable so we're going up with the second or third choice and these are the commitments people have made the actions that will be taken and then the dates that we've set.

Okay. plan,

the whole thing.

Now, does my cognitive twin have a name?

You can certainly name your own cognitive twin. Absolutely. And you can create your own profile inside of it. as

And does that person does that twin join me in the meeting?

It can join you in the meeting. Okay. Yes. Today we use it.

I just want to make it really practical for our audience.

Yeah. I mean, look, the practicality is you have it when I get back to my desk. So I want to make sure I understand.

Stack

and you want to be able to see the meeting, you can prepare for the meeting virtually. So you can run through different scenarios, what we call Monte Carlo simulations of the meeting. Like let's say you want a certain outcome.

Yep.

You can model the best pathing to get to that outcome. Or you can simply let it run. And we'll show you that in a second. when

coach,

it's like having a real time live facilitator slash coach slash mentor slash everything to guide you hyper intelligence but based on you and your pattern of thinking.

Could you also and I don't know if the answer to this could you red team it also if you wanted to use that technique? And maybe we should tell the audience because I think that's a really important we're using so many of these military terms, but I think that's a really good one too, especially when we think of group think in the Bay of Pigs.

That's right. security,

you know, I wrote many books on red teaming. So I know we didn't talk about author.

Yes. So hacking on this was my brand back in the day and the whole mindset was the defenders are the ones that need the most help, not the adversary. So if we document the adversarial techniques to educate the defenders Yeah.

barrier

of you know cyber assets that you can now protect against. So that red teaming concept still comes into play here inside of just everyday meetings. We can take a goal or objective and we can actually stress test it.

Great. Well, how how could we make this work? Or how would this fail most most frequently? AI,

which again is a big deal.

Oh yeah.

realize

great,

right? That's catastrophic.

But once once AI makes a bad decision, it's catastrophic. Y

them

here

so

and

that's right right because you what are you going to do? You going to fire the AI that made the bad choice? Are you going to dock its pay? formal

No, it's silly. It's ridiculous. So,

you absolutely have to have humans in the loop.

Yes,

bad,

right? AI

to perfect the outcome.

But the but what we does and what I'm hearing is that by having this cognitive twin, it's really helping you make much better probably informed decisions to compete in a very fast-paced yes uncertain business world.

Yeah, we we basically we create your cognitive twin but we back it with the power of AI full the expertise and knowledge of AI, right? So your unique perspectives and how things should be problems should be solved and decisions made but all with the infinite knowledge and expertise of a general AI as well. So both of that comes into partnership with every decision that you make.

We did such a beautiful job of actually segueing into our our next topic which is the a the fear of AI.

Yes. mean

before we we do have another poll. So please stay with us. But I do want to make sure that we hear that from you.

Well, so the fear of AI is pretty universal and you know some of it is legitimized and some of it is certainly valid. Others are a bit hyperbolized and the problem is trying to cut the wheat from the chaff and figure out the separation of the two.

So if you look at the what AI is really really good at and you look at what humans are really really good at if you could just think of it like that and separate the two in that way.

How do you do that though?

So what do you have any guiding principles? I think our audience would really enjoy that.

Honestly there's a couple of real simple principles I think that you can you can guide from. So first is AI is really good at deep and broad knowledge. So if you have a question expertise question if you want an expert if you want general knowledge or information absolutely no problem. That you want to leverage it all day long in every decision that you make because you don't want to go into blind into these decisions.

whole

PhD expert that would take you weeks and weeks and weeks to collect all that data of many analysts back in the day.

Oh my gosh. I mean days, weeks, months to prepare this kind of doc data, right?

And that's what AI is fantastic at. So leverage it all day long like that as a tool.

accountability,

right?

It's horrible at real world wisdom and experience.

See, what AI has built in is literally a word predictor. So if you fed it enough words, it can predict the most likely, the most probabilistic answer to any question. But it certainly does not have any wisdom. It doesn't have experience in the real world. No. Right.

Like this desk is physical. I know that if I hit my hand on it, it's gonna hurt my hand.

Right.

AI will never know that.

At least not the models that we've built so far. Right.

Okay.

do

world models.

World models. Okay.

So, what that means is real simple. memory

and then try to train the AI inside of it.

Okay.

Abiding to the physical laws of that virtual world, right?

world,

the consequences of what happens from bad choice.

That's right. And and then over time, you know, days, years, months, whatever to build this knowledge of what works and what doesn't. So, wisdom and experience. But again, it's only in that virtual.

Okay. So from these role models and for that actually like being able to you know we're seeing that in everyday corporate America. Where are we? How how long do you think that is?

Oh it's it's many years away.

I would say three to five at minimum. Yeah. Three to five minimum. Yeah. I mean well it depends on the scale you're talking about. But yes in in the AI world that's lifetimes away.

But in business terms no it's pretty quick. Yeah it's pretty quick. Now,

so we need to be aware of it, but today's immediate threat is not that.

But this is a really important distinction. So, world models build this 3D world inside of a computer. outside

the mind, right? world,

what we do at WethosAI is the opposite. We go inside the mind.

Okay?

We build a 3D model of your mind. think,

think

and that's what gets infused into these cognitive twins in effect. Yeah, exactly.

All right, great. discussion

making

so you can think about that from your team to your organization to the enterprise level what is your biggest concern And that's kind of this outsourced thinking, lack of trust, lack of accountability, privacy and culture, or you have no concerns at all.

see

All right. So, I can see thank you to all of our attendees that are submitting.

What are you thinking is going to be the most important?

Well, I'm really curious. way

mean

analyst

expert

board

decision-making

yes

thinking

y

that only humans and you can uniquely bring to the table with every decision. So to me, I think a big a big set of folks that I talk to are very fearful that they're just going to start to outsource more and more of their decision-making to AI, which of course will be the end of their company if they do that truthfully because AI is generalized.

It's not specific. And you need to take all that expertise and knowledge and make it specifically powerful for you in a critical thinking way.

That is that's just really the heart of this conversation. for

exactly

anyone in organizations today regardless of where you sit at the individual level at the team level at the senior executive level that or at the board level this really important. So let's take a look at what our audience said.

yeah

right

pretty much. Okay. Yeah. And then privacy culture. Yeah you're know that's that's right. Yeah, let's talk a little bit before we go into your demo and we're going to talk a little bit about systems your idea on systems three thinking. I would love because I really think as a thought leader it's important for us to hear what you have to say on because nearly you know a significant portion of our attendees privacy and culture.

What do you think about that?

Yeah, so privacy and culture is a real concern. Obviously I think of it too as even bigger than that. liability,

right? There's a lot of elements and dimensions of this problem. And then you know making sure that aligns to your culture and we certain we solve both of those problems and challenges inside of WethosAI. safety

is along our certifications that we've built in and we've built from scratch day one inside the architecture. experts

like yeah it was a thought before we even had the idea of the company right like how do we secure all this? How do we make it scale? How do we make it private, right? How do we make it controllable by you, the individual?

So all of that had to be a part of the architecture of the of the product and the company completely.

And so that's that was a big big effort because imagine I hate to say it but like imagine you know we get impacted by that. I mean it would be a huge challenge and hurdle to get over as cyber security experts for I mean my whole team is basically from cyber side. covered

and I think it's really important that our that that point like sinks in with the audience because I don't think everyone's thinking like from the AI emanation of this work like are you coming in with a risk perspective?

Yes. Exactly. And are you thinking about the corporate governance side of this? And it's sorry it's really important.

Yeah. No, the risk part is I mean for bigger companies it's more natural.

Yep.

Because they're so used to it like well we can't make any decision until compliance gets through till governance takes a look.

And that's fine. I you know obviously we respect that that step and that motion and we'll engage with any team on that front. make

back to the alignment theater.

Exactly. Yeah. Okay.

And so that was always a bit of frustration for me and holding senior level positions is I couldn't actually cut through that. I couldn't short circuit it.

And so we try to make it as fluid and as u seamless as humanly possible to get through that step and to get onto the meat and potatoes of the meal. Great. So, if we kind of go back to the other you know big point that our audience chose as what was one of their most important areas here which is this kind of outsourced thinking.

Yes.

Let's talk about this concept of system one and two and then you've identified systems three thinking. Can you talk with us a little bit about that?

Yeah. And I I really encourage everybody to to take a beat at some point and look into this space.

Yes. do

we want to talk about the author.

Yeah, sure. Daniel Kahneman I mean you know and his partner who now it just escapes my memory but they both Yes. That's right. very

they're

economist and psychologist. That's right.

Yep. unique

Exactly. I was really fascinated when I first heard about this and you know I hate to admit it but I only heard about this system thinking maybe 10 years ago. like

2013

systems

it

one

and then you have this critical thinking now what is what is really critical thinking I think that's important to talk about I and you know a lot of people can see different ways, but this is sort of how I see it.

So, you take all of the lessons that you've learned in terms of success and survival, and now you put it into multi-dimensions. You put it into a time variable. So, you can say, well, let's see if I had if I had done this differently, what would the outcome be? Or you could, so you're doing it in parallel. You could do it, going forward many, many steps.

You can go backwards many, many steps. But the second most important variable is context.

Yeah. So now taking the context of not just your context because we all think that the world works exactly as we see it and it is how we see it but of course it's not.

Well we always say the idea of like you need to walk in somebody else's shoes.

That's exactly right. And you see the world very differently than mine. okay

especially when you want uniqueness of thought which AI world does not give you today. Mhm. Mhm.

There's no uniqueness in its thought.

Right.

There's no originality.

It's all what it's already learned of what all humans have produced.

Right. Right.

That's it.

So, it's this concept of system three which takes it to the next level. second,

think,

quantify it, put it into a cognitive twin, and now get the speed of your system two at system one speeds. Now, that is what we call system 3 thinking.

Okay, great.

And that that's the premise and the idea behind everything that we do.

It's ambitious, but I think it's it's great.

I know. I I don't know how to do easy and small.

I got that. I got that. Well, we are super lucky to have the opportunity to watch our final demo and then I see some questions from our audience. We will be taking questions after we watch this demo. So, we're going to roll that one and then we'll get to our questions. So, if you have questions while you're watching this, please put them into the chat.

All right. So, the final way to look at the problems that we're solving for is to say, look at our calendar. So, every single day you've got meetings in here. You want to prepare for one. You want to be able to simulate one. You want to be able to solve for any problem that you might be having in that particular meeting. We measure maybe a half to two-thirds of all meetings require some sort of decision-making and synchronization.

So you can apply into all of those meetings and you simply state the goal. You state the objective. You then of course can make it as robust as you'd like. You can make it where look we need to collaborate quickly and build consensus quick or you can say look I want everybody to be skeptical. I want everybody to be critical.

I want the best possible idea to come through. This goes back to this Monte Carlo simulation of meetings and ideas so that you can get to the best path forward. Now, as you build the specifics of this meeting that you're about to simulate and you include all the people that are already in the meeting, now you can start to see it work in real time.

And again you can also add in artifacts. So if you have confines or context or a link into an integration of some system that you want the data and information to come into the decision-making then you can do all that and now you'll start to just see it. right

because otherwise we'll have to wait and see with everybody contributing. But once you hit the fast forward, now you can jump down to the very very end and see the decision that was made by all of the simulations that occurred from all the participants. And now I can jump in and clarify things. I can make a change. I can adjust and and that and then I can also call out other individuals and say what do you think?

Are you willing to take this action? Does this make sense? So you get near instant agreement. M

collaboratively

and and now you can really start to take action.

And so you know what that really means is when you start to look at your meetings, you can literally start to see them shrink down to nothing. 5 minutes, 10 minutes, something like that. Because all you're doing is getting on there and saying, "Hey, we agreed to this. Do you agree in real life? And now let's take action." So that's the whole idea.

I love that. As I said, really ambitious. Are we you know what I want to know? Are we down to three days a work? Three days a week work because that's what I want. I always I keep revisiting that concept. Three days a week, four days a week. I think it might be possible with WethosAI for sure.

Sign me up. I'm waiting for it. And I know many especially, you know, our genzers and millennials, which are the majority of the workforce these right now. Yes. think

three or four days would be great. All right, so what I'd like to do is let's take a look at some of the questions.

Yeah. Yeah, I'd love to.

And then I have one question in particular that I'm dying to know. so

all right, the first question is so for the simulation. So Andrew asks us you need a cognitive twin of all participants. So can you explain how that works if you have I don't know five people in the meeting. Can explain how like actually that works?

platform

you can go through a diff you know three different ways of sort of understanding your cognition. Okay. okay,

84

or we can actually do it with zero questions.

Oh,

so you might ask, well, how do you do it with zero questions?

Yes.

Well, right, wrong or indifferent, the world has created a digital exhaust on you. So you've used the internet for years now or decades.

Yes. I mean it makes sense, right?

that,

we can actually take a sort of a sliver skim of what you've put out there yourself. This is just Google searching, right? If we Google search your name, what's coming up?

Keep coming. Yeah.

Taking all of that data and now mapping it. And this is where the real science comes in mapping it into our behavioral framework so that we can understand you cognitively how you tend to make decisions. Again, this you know a zero question. 75%

Accuracy into your cognition. But it gets you started. with

when you start to get on board a system that has to understand you. So that gets people going. Now you can start to get some of the benefit and as you engage on the platform, it enriches your profile. example,

it'll take you and what you've said, your commentary, things like this, and start to derive more decision-making traits.

It'll take a look at your materials and work product. It'll pull that in as well.

Presuming it's not AI generated itself.

And so all of that comes that's an important point.

It is important. And it all over time builds and builds to more and more depth and complexity of your cognitive twin.

Okay, great. And I think look, that's the reality of the world that we're operating in today. I think it's important that our audience is hearing that. Joti

who says, "Is having another tool?" And this is a this is a very fair question. Is having another tool a distraction? Currently, people are already multitasking to the like nth degree. about

Yes,

let's talk about that. Thank you for that question.

Yeah, that is something that's very real obviously especially for enterprises. Yet another tool is not what they're looking for.

So we have two ways to look at this.

The first is once I think you see the value and the value of your team and the how plugged in you can be notification wise. We have a mobile app.

It'll actually tell you, yeah, you made this decision or do you approve or not to approve? Things like this. So it makes it very seamless. But if you are allergic to yet another tool, no problem. We actually support the Microsoft stack and the Google stack. So we'll sit in Slack. So we'll sit in the stack where you work. So if you're in Teams, we're in chats and we're in channels.

Mhm.

Right.

We're in your meetings.

Yep.

We're in Slack channels, things of this nature. So you want to engage us, engage our simulated brainstorming, things like this. You can do that directly from those stacks.

Okay? So it's not an additional. What I'm hearing is it's not an additional. like

it's already plugged in. It's integrated now. Yeah. Okay.

And we spent a lot of time making sure that we can integrate properly.

Thank you for that question. I love We have a lot of questions here. Thank you audience for your questions. Keep them coming. We still have another five minutes. So we would love to hear from you. All right. Kathy,

great question. How do you see enabling systems three autonomy? think

you

wrong

wrong

but there is no AI today no AI today that can truly replace humans without them being in the loop. Now, you could argue, okay, there's data analyst positions where people just sit there and take a look at data and analyze it. Okay, sure. data,

right?

So, you know, how that ratio is going to work out, I don't know. It might not be a one for one. It might be a 2:1, 3:1, 5 to1. I something like this. But that's but that's what you're going to I think see this is my theory is as more and more AI is implemented they're going to realize humans need to be a part of that decision-making loop because of the experience and wisdom in the real world and the accountability alone.

loop

of

people

statistics

are very concerned about where they're going to fit into the organization. You know, let me just say one thing on this topic. Yes. Is

we'll come back for another.

Yeah. Everybody

world

are going to say what they need in a self-serving way. things

And I'm not naming names so I don't want to be I'm not picking on anybody.

That will be self-serving.

Okay. two

thinking when you hear something like this model's too scary to even release. Okay, that's marketing. That's pure hype. Okay,

think about it beyond the hype and think about well what is it really going to mean if they get the hallucination rate down from 15% to 10%. Right.

Well, not much. rate,

you absolutely have to have humans in the mix. You said below 1%.

Below 1% at a minimum.

And right now it's much higher. Okay.

Oh, it's at 15 to 25%. Yeah. Just hallucinations alone.

So you need humans in. It's don't drink the Kool-Aid.

I You know what? I think that's so important to and I know we're not because we've talked about CNBC so much as we were preparing for this, but I think that that is a really important message when we're thinking about workforce dynamics. We're thinking about the labor markets. we're thinking about from an econ you know a macroeconomic standpoint and it's really important for our viewer our members at the Conference Board to hear that.

So thank you for you know your perspective and thought leadership on that. So that's great to hear.

Thank you. Yeah.

so one more question from our audience and I think we might have answered this but I'm going to thank Andrew who also asked this question. When you are embedded into OneDrive so if we're in Microsoft right?

Yes. Yes. and documents are continually being updated.

Yes.

Does have a way of seeing those iterations to make real-time decisions?

Yes. So we call them sync points. Okay, that's the technical term.

drive,

but we honor the permissions of them. So let's say there's a document that's part of a sync point that you don't have access to, but I do. So you'll not be able to see the derived results from that document.

Okay, that makes sense.

So all the permissions are honored in effect through the decision-making process.

Okay. So that also hits at like the privacy and the culture question we talked about.

solve,

a very complex problem to solve and that's, you know, took quite a while.

Right. Okay. important

and impacts the decision-making right when you might not have all the information which is something to yeah people should know about that so as we're closing out and I want to thank everyone for participating this was super special to have you here in person we are really thrilled I would love for you to be able to leave us with the last word.

What would you like viewers to walk away with?

You know, the the power of AI is in your hands. It it really is. harness

to make decisions quick to act, learn, and then feed it back into better decision-making, the better you and the better your company and your team, your organization is going to be. So, embrace it, don't fear it, and leverage it to your advantage. I love that. I'm feeling much calmer than I did when I walked in. You should. You should. It's It's great.

Thank you so much for joining us and we hope to have you back soon.

I hope so.

I'm Rita Meerson and thank you so much for joining us today. We hope to see you again next time.