Emotional Intelligence is the New AI with Nic Gibson, Founder of inTruth

Speaker A: Mhm.

Speaker B: Hi and welcome to Show Me the Data, a podcast where we discuss the many ways in which our lives and the decisions we make are impacted and depend on data. I'm Tom, your host for the day, and I'm a director at the Relational Insights Data Lab and the Griffith Data Trust at Griffith University. Today in studio, I'm joined by my co host, Jessica Chen, who's doing her first job as a co host. And today we are joined by Nicole Gibson. Nicole is a visionary entrepreneur, acclaimed social entrepreneur, international speaker, author, and global thought leader. She's the founder and CEO of Intru Technologies, the world's first emotion biotech company. Pioneering wearable technology and AI that measures and helps master emotional states in real time. With a bold mission to revolutionize personal well being, leadership and human connection, Nicole is driving a global shift towards making emotional intelligence as valued and measurable as iq. I'm really excited for this conversation. Let's dive in. Show Me the Data acknowledges the traditional custodians of the land on which we are reporting today, and we pay our respects to the others, past, present, and emerging. Welcome, Nick. So before we get to intro, can we start about your public leadership? You know, you were the youngest mental health commissioner in the country. I think you still hold that record.

Speaker A: Uh, I believe so, yeah.

Speaker B: So I'd like to know how you got into that. And since we're a data podcast, it would be really nice if you could sort of tell our listeners where do you think we have missing data in that really complicated problem on mental health?

Speaker A: Yeah, well, I think actually my background serving as a commissioner really informed that understanding and maybe an even deeper context that's really important before we go into what my role as commissioner consisted of. And the gaps that I saw was actually the journey that I embarked on several years before I became commissioner at 21, which was a nonprofit that I founded at 18. And at that time I was beating the drum saying that there's a really huge influence on mental health that is cultural and environmental. And that was this really taboo opinion at that time, because the leaders in the space were very much of the opinion that mental health is a biological predisposition, that if you get a diagnosis of depression, it's kind of like a cancer diagnosis. The best you can do is manage it. And I had this really different view. I thought the way that we were living actually fundamentally as a Western civilization was at the sort of epicenter of the crisis, which was a very, um, unpopular M opinion. And so my first challenge as an entrepreneur at that time was to go out and try to understand if that was a shared perspective and if the reason people weren't saying that out loud was more due to the stigma and the fear or if I was sort uh, of way off. And at 19 I embarked on what became a two year uh, tour, uh, around the country, around Australia, where I would go and set up uh, spaces for these kinds of conversations within community. And originally I thought that that would be, you know, kind of a three month exploration. And it grew into this really significant tour that at the time was sponsored by sun super, which is now um, the Australian Retirement Trust. And so that gave us kind of the funding to grow that tour. Uh, and in that time there was 300 communities that um, my then team and I went to and tens of thousands of stories that we had heard in all different kinds of environments and social class and experiences. But really at the core of what people were sharing, which was ultimately their story, was this consistent message that every single person just wants the same thing, which is to love and be loved and to feel a sense of belonging and acceptance. And it sounds really obvious but these were actually the things that were really missing from the fabrics of our society. And looking back 15 years I think that that's only accelerated for a multitude of different reasons and I think tech is a big culprit for that and we can get to that later. But after that two years I started to put my advocacy together because I wanted to influence this conversation. I could see that government was spending pretty much 100% of their budget on crisis intervention and there was so much good that came from opening up these spaces within community. Now we would kind of consider this prevention, early intervention, peer support. These terms weren't really terms back then. And so this advocacy that I was bringing to the table was quite pioneering. I co founded or was a big part of, I don't know if you can really co found a parliamentary friendship group, but I was a big part of the inception of that parliamentary friendship group of youth mental health with a couple of really leading edge senators that I met on that tour, uh, and in that launch, which was a really kind of critical moment, I think looking back for my journey. Basically we created an event in Parliament and invited the relevant parliamentary stakeholders to talk about the power of community intervention and preventative mental health care, especially in youth mental health. And off the back of that, Tony Abbott's cabinet started to do due diligence and several months later asked me to serve as commissioner, um, which was pretty much going from um, gear one to Gear six in terms of polarity, like going from living in these communities to serving at the highest level and informing our federal budget, which at the time was 27 billion. And when I stepped into that role, I said yes. And I served in that role for three terms. I had a lot of visibility that made me realize the importance of just closing the disparate nature of how decisions are made. Not just in Australia, but I think in all countries where you have the people on the ground that decision making affects, who have a very different version of what they need and what they want. And people sitting in an ivory tower at the highest level who, um, I say it with respect, can't really divorce themselves from their own interests. And it made me recognize the importance of putting power closest to the people paraphax. And how the way that our society is currently designed in its bureaucratic structures and its corporate structures will never get us there. And I think that was where the sort of renegade in me was really fired up to take on a, uh, different kind of pursuit which eventually led me to.

Speaker B: In truth, yeah, it's kind of interesting. Like a lot of other people would have chosen a different path and would have maybe become a minister. Like, you get sort of sucked up by the Canberra system. Yeah, you're quite unique. Like, there's not a lot of people who would, uh, give. It's not to say give that up, but. Well, there's a level of comfort and belonging there, not per se, to solve the initial thing that you want to solve. But yeah, it's a system, sure, totally.

Speaker A: And I think we have a lot of career politicians, um, and even career

Speaker B: public administrators, for sure. If they would have given the big chance to be a commissioner at 20 something, they would turn around.

Speaker A: I received all the hate for that, for sure. All the death threats and all the hate mail you can imagine, uh, because I just fell into it. And people had worked, you know, for 40 years to hold the title. But I think that's. That's the difference, um, between pursuing something for the status and for the title or pursuing something because you're truly trying to solve a problem. And I think this is where entrepreneurs tend to be very unique. That it's. It. It tends to be the obsession with solving the problem that, um, overrides, you know, the lack of glory you experience on the journey. It's kind of an obsession. And I've heard Elon Musk say it, like many people think that they would want to be me, but the reality is very different. When you have a problem, you're obsessed with solving. It's a double edged sword.

Speaker C: So you've touched on what led you to create In Truth. But was there a personal why behind focusing specifically on measuring emotions? I'd be curious to hear your answer to that.

Speaker A: Sure, yeah. I mean definitely. Uh, it was the application of first principles thinking that led me to the innovation that is now in Truth. And at the beginning of that kind of thought experiment was I felt like everyone's favorite thing in the policy space and the mental health sector to say was we need to validate outcomes. So, um, the curiosity in me was like, okay, well what are the ways that we are validating outcomes? And that led me down a sort of a deep rabbit hole of the lack of quantification around outcomes. And even where there was quantification, it was all subjective report. And when you go back, uh, I know you have some, uh, academics that listen to this podcast, I say it respectfully, have a lot of respect for the field of psychology. But at the same time, if you go back to the history and the origin of that, it was kind of a soft science that was forced to be considered as a hard science in that it's the only science that we can reference that's using subjective data, um, and sort of forcing the world to receive it as objective data. And that has created the DSM 5. And I think the DSM 5 causes a lot more pain than it does in good because you're basically being judged through a subjective lens that doesn't consider the intricacies of the individual. And then also understanding emotion is at, uh, the core of our unconscious. It's at the core of our decision making. 80% of our behavior is unconsciously driven by emotion. And emotion isn't what we think it is. Societally, you know, we use kind of emotion and feeling interchangeably. But if I ask you how you're feeling and you say, I feel happy. M on an autonomic level, you've experienced about 50 emotions before you've even answered that question. That's following models like the temporal model of emotion. And so we're trying to, you know, reach into this unconscious problem by subjectively analyzing it. And I could just see how much room that creates for the lack of best practice putting huge amounts of funding into things like cognitive behavioral therapy, even though the mental health outcomes aren't really improving. And through my unique lens, I think because I had that very deep experience in community and then sort of experience at the highest level of where funding moves and then Big Pharma's Interest in all of that, which is a whole other part of this, and how those interests are kind of all in bed with each other in America, I'd say more than here, but it still exists in Australia. We needed sort of a source of truth. And I see that source of truth as data that actually captures that deeper level of what's going on for the human being. And so my first question was, what if we could measure emotion? And how is that being measured right now? And it's being measured with K10 tests and panoscales, but what if we could actually measure emotion the same way that we can put someone through an MRI scan, um, and have that be an objective source of truth to understand the way people, uh, are being emotionally driven, influenced what interventions are actually working for them, knowing that emotion's the biggest driver for behavioral change and that our definition internally of health is health is agency, Agency over ones mind, emotional state, spirit, body, to give someone back sovereignty and agency over their mind, over their emotions, over their body, over their spirit. And I just, I think as a team, we believe that the, the way people are currently engaging, not just with the healthcare system, but with life in general and society in general, is actually disabling their sense of free will and agency. And that is causing a sickness that I think if we don't address, we're hitting a place, not evolution, that's going to create sort of irreversible damage, where even the question what does it mean to be human? Isn't being respected or revered in the way that it deserves.

Speaker B: I get what you're saying. I used to work in pharma and there's a lot of subjectiveness, psychology and psychiatry, but even in normal drugs, there's tests, people say how you feel and stuff. And the challenge is, well, how the, like with temperature, we all experience the same temperature, right. So we know what freezing is and we know what boiling looks like and what it feels like if you put a finger in it. Um, but with emotion there's no external reference point, it's all internal. So if you ask someone on a scale from 0 to 10, that's quite challenging because it's like pain.

Speaker A: Totally.

Speaker B: It's like, well, how do we know that my seven is your seven? Yeah, how do we know that my happy is your happy? So I think that's very interesting that you try to measure that. And particularly, I think what you said before about the preventative space, that's usually where things fall. Right. Because you can't quantify.

Speaker A: Exactly. And then philanthropists don't want to fund it, government's nervous for funding it, and that's it. What in truth is doing is externalizing that internal data, which actually is real and is objective. But because there's never been a window into it, it's remained unseen. And I think culturally we've all assumed this bias, that emotion is kind of this intangible thing, but what it actually is is an autonomic signal that's happening every 200 milliseconds that is consistent across all mammals. And it actually, it shocks me more and more every month that I work on. In truth, that no one has ever attempted to standardize it, considering how core it is to the human experience. I kind of, when I give keynote talks, I kind of put it in the same vein as standardizing time, which has allowed us to do complex global trade, standardizing language, which has given us complex thought, philosophy, science, et cetera. But emotion, which is central to the human experience, we're all just kind of comfortable with. I don't really know what that is. It blows my mind, actually. Um, and when we show people this kind of objective standard of emotion, the way that it liberates them to understand themselves and others in their life is quite profound.

Speaker C: So I've watched a lot of videos on Apple watches and they explain that they don't actually measure heart rate every single second because then the battery would drain really quickly. And I understand that you don't create the hardware component yourself, so I'm wondering if you had any challenges with getting metrics like heart rate and sleep tracking and getting that accurate data into a format that you can actually analyze.

Speaker A: Yeah, um, absolutely. M. Well, a couple of things. So the way that our model works is by being fed raw beat to beat interval data. So beat to beat interval data is the data that comes from the PPG sensor on the Apple watch or I'm wearing a Garmin. Garmin's one of our official partners. Apple's very hard to get the granularity that we need because they're, uh, protective, ah, of that. Um, and there's kind of a bigger question there around where we think the market will move in general because software is the next wave, right? It's like there's only so much real estate. I'm wearing two wearables right now. Um, and trying to fight for real estate on the wrist or real estate on the hand is becoming kind of a losing battle, I think, because the quality of PPG sensors is there. Uh, and we'll continue to iterate if we wanted to white label PPG sensors from China for about $4 a unit. So the hardware game, I uh, think the competition is what it is now. So the next wave in that market is how you restructure that data and make it mean new things. So I referenced the MRI before. What the MRI really was was looking at how they could take a very static symbol and translate that signal into clear images. I think it's a really nice reference for what we're doing at intruth. We're taking a signal that's very noisy, the raw beat to beat interval signal, which is a millisecond to millisecond signal that goes up into our servers and the server then applies our machine learning model and that's been trained off lab data where basically without saying too much we've exposed people to um, stimulus, captured a series of their biometric inputs and then used that to basically train our model on how to decipher emotion. And basically just with quantity of data and now the power of machine um, learning you could take a signal that just once upon a time we could never dream of finding information in that signal because it was so noisy to being able to zero in on that signal and actually delineate something very profound. And in our case that's, that's emotion. So that's basically the higher level of how we've done what we've done and what that means is PPG sensors and the subsequent beat to beat interval data, sometimes it's referred to as IBI intervene interval data is so narrow. Like the difference between the raw BBI data from an OURA ring to a Garmin to a bias trap is really not that significant. So these are kind of alterations that we can correct through multimodal machine learning in the back end to sort of um, allow this cross device functionality. And I think that this will be the next wave in the wearable space is companies like in truth, um, applying unique software to that particular signal.

Speaker B: Once you then have the emotional state, like what you said before about we're all technology is sort of all pointing us inwards, become less and less connected. You said it very politically so you said it way better than I did. Um, but it's really then what do you expect to happen when we are able to measure emotion? M Because then it's the software to get the data right, but then the software.

Speaker A: Yeah, yeah. So I mean we can explore this conversation through um, what we hypothesize the individual experience being um, which is very important to us because that's a life at the end of the day, um, to how that might affect immediate social connection, relationship with a partner or best friends. And perhaps as the founder, uh, what excites me the most, which is the global implication of all of a sudden having this type of data that we can consider. And when I sort of cast my mind 5 to 10 years from now, in truth, I think we have the potential to become kind of a global authority on emotion data because no one's attempted to collect emotion data at scale like this. And the question in my mind becomes how can we influence geopolitical affairs? How can we influence the way healthcare um, makes decisions? How can we influence public health with that volume of data? Because right now the emotional well being of people is essentially removed from any sort of decision making. Um, which I think mental health advocates have been saying, just not in a way that can be heard for a long time. When I was appointed onto the commission, the media release that was put out to Australia was mental um, health commissioner with lived experience appointed to the National Mental Health Commission. And that was this big deal that someone with a lived experience of mental illness could ever hold a position of authority in the mental health space.

Speaker B: You know, while a surgeon can definitely also have a knee surgery.

Speaker A: Yeah, exactly. So this kind of bias that, that is just a lack of empathy and a lack of understanding and this kind of pride filled reality that we've created around um, sort of I guess intellectual superiority that disregards people emotional well being. And I think culturally we're seeing the pendulum swing too far the other way as a result of those um, sort of hierarchical structures in our society where Gen Z's and Alphas are trying to free themselves from any label or any point of conservative kind of um, values. And that's also equally dangerous. So I think this type of data hopefully gives us a source of truth into the true well being of humanity. And you can't unsee what's seen. You know, I think we have a tendency as a world to watch a war in Syria and not feel anything. And that is um, that's not right, you know, because if it was a sister or a mother or a daughter or a son or a brother we would. And so the, the, the real key to our evolution I believe is the capacity to experience empathy and compassion for all of humanity. And our brains have not evolved to be able to do this. You know, we can empathize meaningfully with maybe 120 people, but we have decision makers and we have power players in our world that with single decisions or single announcements On X can change the lives of billions of people. This is unprecedented levels of power in the hands of few. And the people don't have a point of power in that equation. And this is where I think data like in truth can really be disruptive because it's power in solidarity. It's a collective of data to show in some ways kind of a collective consciousness because so many people doubt themselves when you have a handful of people that basically get to dictate where humanity goes next. Which by the way, living in Silicon Valley I don't think is a good direction. It's very transhuman. We're not doing enough to actually preserve organic life. And this is central to our mission to actually build biological and natural data sets that reflect human intelligence rather than giving our power away to artificial intelligence, non human intelligence. These aren't conversations that we have enough. And I think data at scale will hopefully enable that.

Speaker B: I like it, I like what you said. It's kind of like so human to human. It could help you have a argument with your spouse.

Speaker A: Mhm.

Speaker B: And you can understand each other. And then at a high level it's sort of a, it's a next level of democracy.

Speaker A: Mhm.

Speaker B: Where everyone has a vote but they don't have to think about. I want to have that. It's just what do you feel? And then the way that then you transmit or sum it up across the billions of individuals is sort of trivial. But as long as you can do it at the individual, you can sort of scale it out.

Speaker C: So I read on your page about different use cases across government, healthcare and businesses like improving team performance. And I know a few people worry about personality tests because they don't want their boss knowing personal details like that, whether they're uh, good fit for the team. So using in Truth or team performance. You must get a lot of questions about this since you're collecting quite sensitive data on um, people's emotions. And so probably people will ask how you ensure that you're only collecting what's necessary, how that data is analyzed and stored securely, and how do you usually respond to these privacy concerns?

Speaker A: Yeah, I mean it's the most common question we get, and rightly so, like we actively as a brand and I hope that was reflective in what you had read. Encourage people to question corporations, um, when it comes to sensitive data. So there's a few um, parts to that. You know, how do we handle the ethics of say, the technology being used, um, as a weapon against someone in the workplace to say, you know, you're an angry person and therefore we're going to fire you. There's really simple ways to do that. The first is aggregating the data so that the data that's handed to the employer or the decision maker, ah, is an aggregate view so they can't single anyone out. Um, and really at the end of the day that's the data they're most interested in. An executive, a CEO, um, ahead of wellbeing, wants to understand overall how's the coherence in our workplace. Or take the use case of construction for example, where there's a lot of workplace injury due to emotional escalation or fights, which is something that we've heard from different consulting with that industry. The CEOs of those construction companies just want to see a site map. They don't want to pick on Jessica for what she was doing at 10am on Tuesday, doing this, this and that. Um, so there's a level of safety in that. But we also want to empower uh, those end users to have the discretion around their own personal information. So when your boss gets sent an aggregate report, you also will get sent your personal report which will be sent to you and not to them. So there's an opportunity in that, if you want to kind of go on that journey as an organization, to have broader conversation around how things are affecting individuals, that can happen, but that's always at the discretion of the individual and not the employer. The second part of that conversation is data storage. So pretty much all biotech companies you see in the market right now, like consumables, um, store their data on central servers and encrypt the data. And that encryption is how they kind of say this data is safe. Um, we want to do this very differently by using a model called federated learning, which is actually quite popular in research, which looks at the central server being a mothership, but there being a local model that sits on device. And that local model that sits on device has all of your identification data. And that local model is watching out for any interesting insights that could improve the parent model without needing to send any of your personal information to that server. So there's a couple of really great things about that and I give talks on this to encourage more people in the biotech space to consider alternative ways of storing their data. Because there's no real reason other than driving shareholder value with central data, you know, as to why we wouldn't use systems like this because they're not, they're not, um, like they're pretty well established data Infrastructures, they're just not being used in commercial spaces. Another thing that I really love about using a system like federated learning is we don't have to go down the route of heavy patenting. We don't have to put patent after patent in an era where trying to protect data infrastructure is kind of futile because AI is going to be democratizing it all anyway. But rather we open source it and say if you're interested in our ah, data, build on our infrastructure. Plug in Truth as a data layer into your university, um, into your industry, um, and they can do so understanding that the identification data is safe. Um, what's great for us as a company is that we have that early mover advantage and the more people that build on us, the more intelligent that central model becomes. So there are actually quite simple solutions to some of these problems. The issue often comes down to shareholder interest, driving value through means of extraction and addiction, which is a big, big problem with technology today and reselling that centralized data. So the more a company has your personal information, the more power they have to monetize that information by selling it to data brokers, so on. So our biggest challenge in promoting sovereignty of data has been can we create comparable value to our shareholders by building an infrastructure that doesn't vest on the interest of storing identity data and selling that to data brokers.

Speaker B: So what you said before about the federated learning, quite fascinating. Trying to do submitting financial crime.

Speaker A: Mhm.

Speaker B: Because no one wants to share that data. Uh, and the challenge is usually homogeneous data because yours is already homogeneous. It works. So when you're trying to reset individual, it means that it has to be calibrated to the individual.

Speaker A: Mhm. Yes. So you go through a period of baselining. It takes um, three to seven days and then the tech will continue to baseline you.

Speaker B: Okay.

Speaker A: Um, so every seven days it'll kind of look at your baseline and then your baseline is sort of being compared to the global averages. Um, our user interface mimics the circumplex model, the valence arousal model. And we show the user, okay, your baseline is kind of sitting here, um, and then that is dynamic. So what we actually want to see in some use cases, like ah, really high stakes use cases, one example would be we're starting to work with a few partners in the family violence space and they want to see changes to the overall emotional baseline as perpetrators of violence go through anger management. So their baseline might sit in a really, um, negative valence, high stress place in the circumflex model. And after 10 weeks, we would hope that we can see meaningful change where they're actually able to, um, shift the emotional baseline, which would be powerful insight. And then looking at other metrics like spikes recovery is one of the metrics we can produce, which looks at, uh, you went through emotional escalation, how long did it actually take you to recover. So if you use violence as a use case, we might see that, um, a perpetrator of violence goes into anger and it actually takes them about five hours to come back to a balanced state. And so what we can look out for is what's actually supporting that person to bring their spike recovery down to like 10, 15 minutes so that they actually start to develop that sense of strength and control over their own emotional state.

Speaker B: So you see this, you see your app, inter. Like the immediate interface for me would be with meditation.

Speaker A: Yeah. As an API. That's definitely one of the. Yeah.

Speaker B: Because like meditation, that's kind of like one thing is like you want to learn to control your emotion when you get angry as quickly as possible.

Speaker A: Yeah.

Speaker B: Without sort of damaging your psyche. Getting back to, you know, is normal.

Speaker A: Yeah.

Speaker B: And being able to measure that would be quite powerful. Like, you can intuitively feel it if you, um, meditate enough. But if you would be able to measure it.

Speaker A: Yeah.

Speaker B: Be quite interesting.

Speaker A: Can accelerate the time, we think. And yeah, it's a great use case. I think consumer wellness, um, will come together with biometrics in a pretty big way in general, like beyond just in truth, over the next couple of years, I think that's where that market will go. As wearables become more popular. Um, we're, to be honest, very focused on looking at, um, vertical integration where we believe we can have the most impact. So I think family violence is a pretty powerful example because it affects one in four families in Australia. I mean, it's a big problem.

Speaker B: Yeah. And you could do it. The problem is a lot of people feel frustration or anger and they ignore it until it pops.

Speaker A: Yeah.

Speaker B: And you could, by measuring it, could sort of give people warning ahead of. It's like measuring your heartbeat.

Speaker A: That's right.

Speaker B: You don't have a heart attack because you can see before you feel the pain.

Speaker A: Uh, yeah.

Speaker C: Shall we move on to the last question, just to wrap up?

Speaker B: We can. But I know what you're going to say because you want your own data.

Speaker A: What's that?

Speaker B: So we asked this question to all our guests. Uh, it's. The final question is if you could have any data set in the world without ethical financial limitations. What Would it be?

Speaker A: Yeah, I think you nailed it. I think everyone's answer to that question should be, I would choose to reclaim all of my data from every single corporation, every single data broker on the planet. And I'll tell you what, if you were to do that, you would know more about yourself than what I think a lifetime of personal development could teach you.

Speaker C: Yeah, I think there's like an app out there that's like helping you delete data. It's um, like called Incogni, I think.

Speaker B: But have they deleted it?

Speaker C: That's what.

Speaker A: Yeah, you don't know.

Speaker C: They give you a report and saying that they do delete it. But then what if we had one that collected?

Speaker A: Yeah, that'd be cool. M. We need to build those solutions. Um, I'd like to remind any investors listening to any of these conversations, we vote with those dollars and the venture money that's going into um, tech right now is defining what the next thousand years looks like. But they're thinking with five year return horizons and that's very problematic right now, in my opinion.

Speaker B: I agree. It's a very interesting times of your life.

Speaker A: Yes.

Speaker D: Today's episode of Show Me the Data was proudly co produced by myself, Retta Chappell and my talented colleague Jessica Chen, who also does our expert editing. To listen to more episodes, head to your favorite podcast provider or search for Show Me the Data and Riddle on platforms like LinkedIn, YouTube, Google and more. We hope that by sharing these conversations about data informed decision making, we can help to inform a more inclusive, ethical and forward thinking future. Making data matter is what we're all about and we'd love to hear why data matters to you. To get in touch, you can tweet us on xridl, uh uh, send us an email or better yet, follow subscribe and leave us a five star review. Thank you for listening to Show Me the Data. And that's it till next time.