E157 | How can AI Technology help Therapists? (w/ Sean Ruane)

Sean Ruane is the founder and CEO of Mind Data. A lifelong entrepreneur, Sean's goal is to combine his business accumen with his own experiences of mental health difficulties to form a company than can help practitioners deliver high quality mental healthcare. 

Disclaimer: The Thinking Mind does not have any financial affiliation with Mind Data.

Interviewed by Dr. Alex Curmi. Dr. Alex is a consultant psychiatrist and a UKCP registered psychotherapist in-training.

Check out The Thinking Mind Blog on Substack: https://substack.com/home/post/p-174371597

If you would like to invite Alex to speak at your organisation please email alexcurmitherapy@gmail.com with "Speaking Enquiry" in the subject line.

Alex is not currently taking on new psychotherapy clients, if you are interested in working with Alex for focused behaviour change coaching , you can email - alexcurmitherapy@gmail.com with "Coaching" in the subject line.

Give feedback here - thinkingmindpodcast@gmail.com Follow us here: Twitter @thinkingmindpod Instagram @thinkingmindpodcast

Give feedback here - thinkingmindpodcast@gmail.com Follow us here: Twitter @thinkingmindpod Instagram @thinkingmindpodcast

Transcript

Speaker: [00:00:00] Welcome back to The Thinking Mind and to our second podcast of 2026. Today we're gonna be revisiting the topic of mental health and ai. Obviously, we have had a few podcasts recently where we've talked really about the downsides of AI with regards to mental health. Today we're gonna be talking a little bit more about The Upside, and I'm very excited to bring you a conversation with Sean Rowan.

Sean is the founder and CEO of Mind Data, a company which uses AI driven technology to help improve the impact of mental health initiatives like therapy and other services. I really like talking to Sean. He's a lifelong entrepreneur. He himself has experienced difficulties with his own mental health, including depression and suicidal thoughts.

He's a big advocate of therapy, and he felt psychotherapy really helped him, and after having his own successful startup, which was called customer success. He was really passionate about [00:01:00] using his business acumen to help things in the mental health space, and that's why he founded Mind Data. So today we talk all about that and also some misconceptions that he'd love to clear up about AI and the AI industry more broadly.

Some of the key lessons that he learned from entrepreneurship and how he sees entrepreneurship as a catalyst for self development. And I'm very passionate about this as well. I think there's nothing like starting your own business to help test your character and using that friction you need to improve your skills and your resilience and your ability to handle different situations dynamically.

We talk about the importance of measurement when it comes to improving something, and of course, that's what Mind Data is all about. And we also discuss some of the ethical concerns that he has when it comes to using AI in the mental health world. His predictions about where he sees the industry going more broadly in the next [00:02:00] decade, including from a financial investing perspective.

This is something I've become more interested in more recently, and obviously something that's talked about quite a lot online is, is there a so-called AI bubble? How should investors think about the AI industry and so on? I would like to point out that the thinking mind has no financial affiliation with mind data, but I do think the mental health world can learn a lot from the business world and vice versa.

So this is really the kind of conversation I love to have on the podcast. One quick announcement before we get into today's conversation. I will be participating in a live event with Rose Cartright. So Rose people may know is a friend of the podcast and previous guest. She's the author of the book Pure about her experiences with OCD and subsequently has written the maps we carry about trauma and psychedelics.

And she's launching a new series of mental health events called How Not to [00:03:00] Heal. The first event in that series will be called Mental Health Reimagined Beyond the Medical Model, and she has kindly invited me to participate in that event. We're gonna be talking about. All sorts of fascinating topics, including things like diagnoses, medication, how should we be approaching mental health more holistically?

And aside from myself, another guest will be Ashley Murphy Byner. She's a clinical psychologist and researcher, and she's gonna be talking about all of her expertise when it comes to things like OCD, psychedelics, complex trauma. I'd love for you guys to come to the event. I'll be putting a link where you can buy tickets to this event in the description of this podcast.

They're about 16 pounds. We'd love to see you there, and thank you again to Rose for the invitation. In the meantime, I hope you guys are having a good start to your 2026. Maybe you've got some resolutions, you have planned some goals you're trying to work [00:04:00] towards. If there's any content you guys would like to help you achieve your resolutions in some way, don't hesitate to reach out to us, and you can do that via any of our social media channels.

Or our Email Thinking Mind podcast@gmail.com. We will be continuing to do film analysis episodes, so if you have any movies that you'd love to see discussed on the podcast, again, feel free to contact us about that. As always, thank you all so much for listening, and now here's today's conversation with Sean Ruane.

Thank you so much for joining me. 

Speaker 2: It's a real pleasure. Thank you so much for the invitation. I'm looking forward to this. 

Speaker: I'm excited to learn more about Mind Data, your personal story with mental health. But first, you know, listeners of the podcast will know I'm increasingly fascinated by ai. Until recently, we haven't discussed much.

We have started to discuss it. Now we have a couple of episodes about AI coming up. It's being talked about so much, isn't it? Both in terms of what AI could offer [00:05:00] the dangers. People who are investing in AI are freaked out about the possibility of a bubble. It's all over the place. I'd love to know, you know, as someone who has a company that has used ai.

What are some misconceptions about it that you'd love to clear up? 

Speaker 2: I think the first misconception is, and I think it comes from the, the, the naming of it, artificial intelligence. I think there's an implication that, uh, large language models are conscious. They have their own beliefs, they're sentient. Um, and I think that that can cau inadvertently cause a lot of kind of fear mongering now.

This is obviously being recorded in 2025, so this might date the episode. We don't know where AI will end up at some point, but as of today, it's not a sentient, conscious, uh, program, if you will. So it is incredibly good at using large amounts of data and effectively, um, being exceptional at pattern recognition.

Um, and, and I think that that can manifest itself in [00:06:00] seemingly coming across as intelligent and having its own beliefs, but it's somewhat masking, uh, the processes that happen behind. So I think that the more people can understand how large large language models actually work, how they recognize patterns based on large amounts of data, uh, and then, and then have, uh, more accurate outputs.

I think that might quell a little bit of the fear around this Terminator style sentient being, you know, so I think that recognizing that it's not conscious at this stage is a big misconception I would say. 

Speaker: And it's very reassuring. It is, it's a strange feature of humanity that we, we tend to assume things are conscious when we're not.

There's even that like philosophical notion of like panpsychism, that perhaps rocks are conscious or rivers are conscious. We tend to project a lot on people, don't we? 

Speaker 2: Yeah, that's so true. And I think that this is happening now, and I think that because we do have the ability to interact intelligently, um, large language models [00:07:00] can give us insightful answers that we expect it to.

Um, so there is this idea that it, it is understanding me, it's learning from me, and to a certain degree it is. But like you said, we can personify inanimate, uh, objects and, and certainly AI at the moment is inanimate program. Uh, but just very good, uh, uh, kind of, uh, replicating this that you and I as two sentient beings are having.

Speaker: Right. And I guess the other distinction is between a specific intelligence and an artificial general intelligence. What, what is that? Could you unpack that distinction a bit? 

Speaker 2: Yeah. So, um, the, at some point we will, uh, arrive at artificial general intelligence. Now, at the moment, uh, artificial intelligence models, large language models are very good, but they're very narrow and deep.

They're incredibly good at doing certain specific types of tasks or subsets of broad knowledge. So you may get something like SOA that is incredibly good at kind of reproducing imagery, for example, um, et cetera, et [00:08:00] cetera. I won't go to all the different examples, but at the moment is, is deep and narrow.

Task focused, if you will, context specific. Artificial journal intelligence is what you and I and other human beings have, and it's this idea of being very good at multiple different wide sets of tasks and different contexts. Now, at the moment, uh, we don't have, uh, an oracle all knowing kind of, um, AI that can do multiple different, uh, aspects.

So that's, that's where we're at at the moment. I think we're on the precipice of, of maybe approaching that. But that's certainly the, the, the difference. It's having very specific context, task-based models at the moment, and one day we'll string all those together and create something that's kind of like the unified field, if you will.

Theory of, of ai, 

Speaker: are you broadly an AI optimist? Is that fair to say? 

Speaker 2: I am actually, uh, I'm cautiously optimistic with, with ai. It reminds me of, um, I grew up in the, in the countryside of, of Lincoln Shear in here in England. And, uh, in a previous life, I, as an electrician, and I promise this [00:09:00] has, has a, has a relevance here.

Uh, and we, uh, we used to, uh, do lots of electrical work around different village halls that we have here in the uk. And, uh, on one of the village hall, there was a, a history board of the village. There's this black and white picture of this Victorian lady. As you would see on any movie. And this woman had burned herself to death in the high street of the village.

It was not the, the caption I was expecting to read. And she, and she, she committed suicide, um, through burning herself, through fear of electricity, uh, electrification of villages was happening. And, and there was a lot of fearmongering around the impact of, um, how electricity can maybe affect our minds, our bodies, things like that, that might get it fields.

Um, and, um, and she, and she, she died by suicide by doing that. And I thought, actually. You can, you can do a lot of damage with electricity, but our world has been positively transformed with the, the benefits of electricity. And that story has kind of stuck with me to say that AI isn't [00:10:00] inherently good or inherently bad.

It's an incredibly, incredibly powerful tool that we have the ability to decide how we wield this. So I'm a cautious optimist, uh, with, with AI personally. 

Speaker: Now we're gonna talk about mind data, which uses technology like AI to help people with their mental health. Yep. What mo motivated you to get involved in the mental health space?

Speaker 2: It's a deeply personal story. So when, uh, is about 10 years ago when I was at university, I was an old undergraduate student studying business, um, due to personal circumstances, a, a loss in, in my family. Um, I became suicidal and depressed. Um, I'm a big believer now that you somewhat sleepwalk. Into depression.

You, you don't wake up consciously and think, I'm now depressed. I need help. It's, uh, turning the, the light down on a dimmer switch day by day and just, you know, things happen and before, you know, it's death by a thousand cuts. And, and I was planning my own suicide, deep, deep depression, and I had my life saved and changed by an amazing student [00:11:00] counselor called Betty.

And it's during that time that I made it my life's mission to improve the mental health of 1 million people around the world. Um, to have a, a purpose that was greater than my circumstances. Something that I could hang my hat on, shall I ever fall into depression again. And so that's my why. That's why after building and, and selling a company in London, uh, that I thought now's my time after the pandemic to really start to see how can I use my experience with technology to try to put a dent in universe and, and help improve the mental health of a of a million people, hopefully.

Speaker: And it's great to hear more about your story because. You seem like a cheerful, energetic, optimistic person. Clearly, you have a lot of purpose. You never know, speaking to you that you had mental health difficulties in the past, so hearing your story can be kind of reassuring in a sense that this is something that can affect anyone.

Speaker 2: I think it's very true. I think the one thing that I learned going through suicidal ideation, depression. Was that depression is the great equalizer. Mental health, uh, does not discriminate. Um, I've known [00:12:00] people that are successful multimillionaires that have, uh, depression, uh, people that, um, are down on their, their luck have depression.

There doesn't seem to be generally any rh or reason, uh, as to the type of demographic or person personality that that can struggle with mental health issues. Uh, mine was situational. Um, and I know that people will, will struggle with kind of, uh, genetically driven, uh, pre predisposition to, to mental health.

Um, I do think I have a little bit of that. Uh, I have a history of mental health and, and multiple suicides, um, within, within the family actually. Uh, but I'd never experienced, uh, depression before. So it's a long answer to say that I'm now far more empathetic to the person that is driving a Ferrari, quote unquote, that seemingly happy and think you are, you are just as likely, you're just as likely to be struggling.

Uh, you can't buy your way out, uh, or marry your way out of mental health issues. 

Speaker: There's something about having a, a lot of wealth that I, I actually think might predispose someone to having a mental [00:13:00] health problem, especially if they grow up around it because there's something about extreme wealth which really insulates you from reality.

And I think one of the things we need to be mentally healthy is to kind of touch ground, if you like, and to actually have some friction in our lives when our lives become frictionless. It can quickly feel kind of boring and meaningless. 

Speaker 2: I totally agree with you. I totally agree with you. It's, um, here in England it rains a lot and I think that we have a greater appreciation for the sun for, for that exact reason.

Oh, yeah. You know, um, and I think that being grounded, um, having the, the trials and tribulations of life can put the positives and the winds and the successes into wonderful context. I think if you remove the challenges, the trials and tribulations, the growth opportunities, the rainy days, um, then I think that the, it has a, a numbing effect where it's like Christmas day every day.

So I totally agree with you. Yeah. 

Speaker: I, you know, I, I'm a psychiatrist and a psychotherapist, so I give [00:14:00] therapy to people. It sounds like therapy was helpful for you. It'd be really helpful for me to know. What in the therapeutic process helped you, do you think? 

Speaker 2: There were multiple things that helped me and, and I've had years off therapy on and off.

For what it's worth. It wasn't just that reaction of period for two years. The first thing I would say that was a real. Before and after for me is when Betty first asked me, how are you feeling, Sean? I explained how I was feeling and she said, and why? Why, why do you think you're feeling that way? That was a real kind of, you know, watershed moment for me.

No one had ever challenged me to try to articulate why, uh, I, I kind of thought that, uh, emotions were some, something that was passive. It was something that was uncontrollable. It was just a, a passing experience and it, and it was what it was. So the first thing was having a professional to really interrogate me and help me ask the right questions.

So why was I feeling certain emotions blew my mind. That's the first thing. The second thing is having, um, an objective sounding board. So when I came with [00:15:00] these challenges, these thoughts, having Betty or Peter or whoever else was my therapist, be able to say, why were you experiencing that? How do you think that affected you?

Uh, and, and ask the intelligent questions back to me was something, and the reason why I say objective. Uh, a therapist wasn't someone that was involved with my life. I felt unapologetic. It wasn't my partner. It wasn't my, my brother, my best friends. I didn't feel, I didn't feel a burden to them. And one thing I did struggle with, with depression was the fear of being a burden to those people I cared about.

Now, when I walked into a therapy room, I didn't have that. This was what this person was being paid to do. I was, I was happy to unpack everything without feeling guilty for, uh, to, to them. Um, so they were the, the two main aspects that that really helped me process my emotions, uh, without them being emotionally involved.

Speaker: Yeah. That's fascinating. I, I talk a lot, and I'm doing a bit of writing about this idea that emotions are really important to understand that, like you said, they're not just these [00:16:00] passive experiences. They often contain really, really helpful information. Like, it's really good to know, oh, I'm feeling envious.

Why do I feel envious? Why do I feel resentful? What does the sadness mean? Mm-hmm. What does this anger mean? And also how can I use these emotions actually to improve my quality of life? But we don't really talk about emotions on that level at all. We kind of talk about emotions like the, the positive ones as the things that make life good and the negative ones as kind of a nuisance.

Speaker 2: Yeah. I, I don't think that we have deep enough conversations, uh, you know, culturally or societally. Uh, and it seems so far that most of my deeper conversations. Well with a therapist. And I think that was really beneficial and it's given me a lifelong tool. Um, it's quite easy in my own mind to, uh, imagine what would Betty say?

What, what would she ask right now? Mm-hmm. You know, 

Speaker: and, and it's the, you've internalized your therapist to be. 

Speaker 2: Exactly. And I think that we all have that ability. We all have that shadow [00:17:00] work to be done. You know, when we're sitting struggling with something, you know, even if we've never had therapy, you can probably sit on the edge of your bed and think, what are the questions that I'm not asking myself?

What, what's the bit that I'm, I'm conveniently kind of ignoring and putting to the back of my mind? And I think a therapist for me was that person. Say, let's open that box in the bottom of your mental wardrobe that, you know, you're not opening. And so I, I, I kind of personify Betty in my mind and just think, why do you feel that, Sean?

Come on, let's dig deeper. Let's think sensibly now. So she really helps. Uh, even though she's passed away now, unfortunately, um, she's still in the back of my mind, you know? 

Speaker: There's even an interesting analogy to be drawn with something like chat, GPT say, because when you are using a large language model, you quickly come to the realization that the limitation is the the questions you ask it.

So like that's the only thing holding you back from getting like really great answers. The same is often true with people and their minds. Like people's minds are these amazing supercomputers that [00:18:00] can generate lots of answers and solve problems. What I find as a therapist is most people just don't know what questions to ask themselves, or they're not in the habit of asking themselves useful questions.

So like a question like, why does my life suck? It's a question many people ask themselves, but it's not a very constructive question. Whereas a question like, how could I make my life 1% better today? That's a super useful question. And so a lot of my work as a therapist that's actually. Like you experience just helping people?

What helping people realize? What are the right questions to, to ask? In this moment of my own mind, 

Speaker 2: there's a saying in, uh, computer programming, which is quickly becoming outdated now with ai, but, um, Geico, gi G it means garbage in, garbage out. Uh, and so bad code in, you're probably gonna have some poor outputs, uh, um, of your, of your programs or, or your tools that you're developing.

And I think that's very true. This, this Geico analogy of, you know, you know, bad [00:19:00] questions in, you're probably gonna get poor low quality answers out. So you're absolutely right that, that, um, the answers are directly proportional to the quality of questions that we ask. And, and, uh, and, and I think that a, a therapist, uh, can certainly be be the, the person to help ask high quality questions for sure.

Speaker: I mean, hopefully, I think that's one of the main, like, I think non judgmentalism to create that atmosphere, which you implied as well where you can say anything and asking right questions. I think just those two things alone can do a lot of the heavy lifting. And therapy. It'd be great to hear about some of your work.

So you mentioned you had one business before Mind Data. What was that business about? 

Speaker 2: Um, yeah, well that was the first kind of serious or successful business. So I've, I've, I've built, um, uh, startups or, or businesses since I was a teenager. Lots of failed experiments, so it's kind of in my blood being an entrepreneur.

But this one was, uh, an HR technology company, so I didn't found this business. Actually, there was two co-founders and I joined those two guys. [00:20:00] Um, and this was a, uh, a piece of technology that helped organizations replace annual appraisal reviews of their employees with an ongoing iterative approach to, uh, employee development.

Um, and so that was built on regular check-ins between a team member and their manager, agile objective setting, and in the moment feedback to, to colleagues. Um, and so we, we scaled that company, uh, and then exited that, uh, about four years. Nearly five years ago now. Uh, so it was a really good kind of, uh, you know, start and, and end to a, a startup chapter.

You know, it was kind of had all, all the experiences within that five year period. It was a, it was a wonderful, wonderful chapter. 

Speaker: Do you recommend, um, entrepreneurship as a kind of vehicle for personal development? 

Speaker 2: I hope I don't sound hyperbolic here. I I can't think of another pursuit that would help you grow more than being an entrepreneur.

Um, I, I honestly can't. I mean, I think there are some brilliant, um, hobbies and [00:21:00] career paths out there that will inevitably help us grow and entrepreneur is, or being an entrepreneur in the pursuit of growing a business. Is outside from my experience, outside of being a parent, the hardest thing you can go through.

Um, it's, it's statistically unlikely to work. So you have to find a purpose that is, is going to outweigh the inevitability of why you should not be doing this. It's so difficult, it's so unlikely to work. There's a lot on the line financially, uh, professionally, you know, it's, uh, it's the single greatest, uh, stretching of the envelope of personal growth I've ever done.

My life, um, right next to being a parent. Um, you wear many hats as an entrepreneur, you will fail consistently. You have to put yourself into, uh, a very uncomfortable situations. You know, we all, we all gravitate towards a certain set of skills that we're very good at. Whether that's public speaking, presentations, [00:22:00] maybe, uh, organization, attention to detail.

Being an entrepreneur forces you to do all of those things. Those things that you're not very good at. You have to get good at doing very quickly. Um, so I would highly recommend, um, at some point in everyone's lives trying something entrepreneurial. Uh, because even if the business or or pursuit fails, you will absolutely come out a better person for it.

You will have so many greater experiences. My view, my view that is Yeah. 

Speaker: I was gonna ask you because I can, when people consider doing something. My experience, their mind jumps to, well, am I gonna be successful or not? So they think, okay, should I start a company? Well, am I gonna be rich? Uh, is it gonna work?

But what you're saying I think is very important and kind of radical, which is that as long as you do your best, even if it's not successful, you get a ton out of it. 

Speaker 2: Yeah. You, you win-win. You literally [00:23:00] are win-win. Um, you, you either fail the business and you come out, um, a, a, a better person. Um, I would say not, not as a, as a human being.

I don't mean, uh, emotionally or empathetically, but you, you are certainly better, well-rounded. It'll make you a better employee if that's what you choose to do. Are you a better negotiator? You're a better salesperson. You, you think differently? Forces you to think innovatively, uh, and, and be a better problem solver.

And that's if, if the business fails, if it wins, you hopefully have financial upside and you get all of those life lessons. The one thing that I would say to would be entrepreneurs is. Tackle it with the journey in mind because statistically speaking, you are not going to come out a millionaire from this.

Uh, if you keep at it, maybe your second, your third, your fourth business probably will. But it's extremely unlikely that your first pursuit is gonna make you rich, you know, and so there is a bit of a misconception around entrepreneurs are these, are these just millionaires, overnight [00:24:00] people? Um, that's not how I see of being an entrepreneur.

Speaker: Something I've toyed with in the past is this, this distinction between employed mindset and self-employed mindset. Um, in the past couple of years, I've been self-employed and what I, I still work for people and I have contracts with people, et cetera, but, but essentially I'm self-employed. And what I love about that is when you're employed, you're kind of like, how do I do the least amount of work in the time that I'm forced to be at the office?

Because regardless of, uh, what you do or don't do when you're employed, you're kind of paid the same amount. So there isn't that incentive. When you're self-employed, you're forced to take charge of your time. Uh, you're forced to make things more efficient. You're forced to think about, what's the quality of my work?

How am I actually getting fulfillment? Am I doing a good job? Am I delivering something of value? So it's like a, for me, it's been a totally. Different paradigm. And I have a sense of that [00:25:00] sense of agency ownership. I've become much better at initiating tasks like I feel at school. People are largely conditioned to do the work that's set out for them, which is really, you know, conditioning people to be employed eventually.

But school very rarely says, gives you something open-ended and tells you, you know, figure out how to do that yourself. And so a lot of intelligent professional people I know have a real trouble starting any kind of project because that gap from having nothing to, to making something concrete is very difficult for them to traverse.

Speaker 2: Yeah. Yeah. The zero to one, I'm not sure if you've ever read that book Zero to one, but if, if, uh, you haven't or your listeners haven't, I'd highly recommend it. And I think that, um. Yeah, one of the, the, the biggest differences is paid for your time versus paid for your output. Uh, you know, and I think that's the biggest differentiator.

And as you quite rightly said, if you're paid for your time, obviously [00:26:00] you are, you are, you are only gonna be doing, you know, if you're only paid for a certain amount of time, you are not gonna spend a minute longer for free. For example, if you're paid for your output, it doesn't matter how long or how short you spend on this.

The, the focus is, can I solve this problem, deliver value to a certain person for hopefully some commercial game if we're talking entrepreneurial? Um, and so I think that we should teach that more in schools. I really do this entrepreneurial mindset. We can separate it from entrepreneur equals business person.

I think an entrepreneurial mindset we can absolutely adopt as doctors, psychiatrists, um, electricians, whoever it is, is this idea of just thinking. How do I take, how do I create something that wasn't there before and deliver value? And how do I do that, uh, in, in a creative way where I don't have a linear path set out to me?

How do I kind of traverse that zero to one? Uh, I think e everyone benefit from thinking with an entrepreneurial mindset, 

Speaker: especially with ai, uh, technologies as they continue to improve. 'cause even if you have, [00:27:00] uh, $20 per month chat, GPT subscription, you essentially have an employee. They can't do anything, but you do have an employee of sorts.

So you're kind of a boss of sorts. And so what that cause upon you to do is be a little bit creative and to be able to delegate and start to think a little bit more. Big picture, you know, chat, GPT immediately promotes you from being a writer to an editor, which is a problem if you've never been trained to be a writer, but certainly gives you a lot more optionality, you know, in terms of what you can do.

A lot more power. I, 

Speaker 2: I totally agree with you. I think that the biggest thing that, um, humans are, are brilliant at is this creativity. This zeroes one, this innovation mindset that at the moment, large language models aren't particularly brilliant at doing of, of being a creative outta the box thinker. So if we delegate as the, the administrative tasks and, and create more space for creativity and like you said, strategic thinking, we can work really [00:28:00] effectively hand in hand with our chatt PT employee.

Speaker: Um, it would be great to hear more about mind data. So what are you guys doing over there? 

Speaker 2: When I first created mind data, um, I, I spotted a problem that I had in therapy. Now I'm always a big, big advocate of, of therapy as, as you know, but there was something that was broken for me that didn't sit right.

Um, and it was this idea that. It felt as though the conversation between patient and therapist hadn't changed in 150 years. The idea was that I come into a room after one or two weeks. My therapist has had no contact with me. She has no idea what I've been going through, and the first question was always, Sean, good to see you.

How have you been over to you? What's been going on now with a sober mindset and organized mind? It seems like a fairly logical question to answer. When I was depressed and I was suicidal, it was incredibly difficult to observe. Try. I had 60 bias, um, trying to collect my thoughts all the while I was on the clock.

We have a therapy hour, which is 50 minutes to allow for the 10 minute [00:29:00] changeover, as you know. And so one minute, two minutes, four minutes, five minutes, it's precious time. Um, that was wasted by me just kind of trying to update my therapist as bedside. I could. It didn't feel right. It did, it felt broken.

Um, so I created a digital journal that enabled me to track my emotions and thoughts and feelings in the moment, uh, as they were so I didn't have to overwhelm my memory. And I had these insights shared with my therapist on a portal. So the idea here was I could walk into a room, my therapist would say, uh, Sean, Alex, good to see you.

I know you've had a challenging week. Thursday. Looked particularly hard for this reason. Did you wanna speak about it? Now? We're still person, uh, person led, person centered. I can take the conversation in whichever direction I want, but going in warm and having, uh, and, and as a, a foundation for my, the, was really important to make the most of our effective conversation.

So they became the two pillars on which I built mind data on. And since then, um, when we've deployed, uh, this technology universities, um, we spotted a, a gap [00:30:00] where e employee assistance programs or EAPs within the UK who deliver, um, third party therapy to employees, uh, for, for organizations over relied on engagement metrics as their number one proof of success.

You would pay me a million, million dollars a year, and I would say great news, 33% of your employees have had at least one therapy session with, uh, our therapists this quarter. It's a leaving indicator. It does not mean that these employees are getting better. So, um, we use artificial intelligence to analyze journal entries, self-reported symptoms, and we derive thematic analysis, sentiment analysis and visualization of mood trends over time to help bolster, uh, a quantifiably way of proving mental health improvement alongside the usage.

And I think that's really important to have sensible conversations that we can say, look, not only do we know how people are using our services. We can start to understand the impact. Are we seeing certain themes drop away on a certain [00:31:00] demographic of, of people, for example? So that's kind of our three main pillars of our technology that, that we use to improve the quality of service and the output measurement of mental health interventions.

Speaker: So the first two pillars is that, is the first pillar, the journaling, and then the second pillar is the analysis of that journal that the therapist can use. 

Speaker 2: Yeah, so it's actually the, the, the third is the analysis. The first is the, the journal entries. The, the middle pillar is the therapist portal. So this is where they can store their notes.

This is where they can see the insights, uh, on their, on their patients and on their clients. So they're the three main, you know, patient, uh, pillar, therapist pillar, and then the, the analytics pillar. 

Speaker: Okay. Okay. And is this service particularly being marketed towards the mental health professional who is seeing clients or towards the client who might go and see a therapist?

Speaker 2: This was, uh, when you start a business, we made lots of failures. So we have, in the business world, lots of pivots. So, uh, when I first started Mind Data, it was just Pillars one and two, and it was marketed towards [00:32:00] therapists. Um, and I had some wonderful early adopters to take on this technology, um, to deploy with their, their patients.

And we had some amazing case studies, um, of how it improved, uh, the, the quality of, of therapeutic relationship. Um, the, the speed in which they were covering topics, um, over, uh, same, uh, number of sessions was, was increasing because they, they weren't kind of hitting a soft reset each week, so they were saving kind of five or 10 minutes each session and after five sessions, it's a whole other session that they've actually had in therapy instead of therapeutic conversation.

The first lesson I, I learned, and I'd, I'd, I'd share with, with the audience is when we look at the market of adopting new technologies, uh, we have a bell curve. And on one end of the bell curve, we have innovators and early adopters. Then you have the early and late majority, which it makes up the, the middle 80%.

If you are, then you have the laars at the end. Um, I created a false positive by, uh, deploying my technology to the early [00:33:00] adopters and some brilliant, positive feedback. But of course, they're therapists that are open to technology. They're open to different ways of doing things. They're open to improving, uh, the quality of service.

I quickly learned that to scale a business, you need to be selling to the early and late majority, that middle bell curve, when my technology started to bump against this middle majority, if you will, I had a lot of pushback. I realized that generally as a general rule, I found that self-employed therapists were not open to innovative ways of doing things.

They were quite, uh, pessimistic and skeptical of any type of technology. And so when I was trying to sell to the vast majority of these therapists, they say, well, I'm happy with my pen and paper, and I don't need to know what my client has been going through outside of a session with person centered, whatever comes top of mind is the most important.

Sean, I don't see you solving a problem here, so no, thank you. Um, and obviously as a, as a innovator, as someone that has been on the other side of the therapy [00:34:00] couch, I passionately disagreed with them. I know firsthand that whatever I brought up top of mind. Was simply there because it was top of mind. I was struggling with recency bias.

It wasn't the most important thing that I wanted to discuss, because quite regularly, 20 hour, 24 hours, 48 hours later, after my therapy session, inevitably something would pop up. And I think I really want to speak to Betty about that. So, kind of through, through analogy, uh, sorry, through, um, anecdote and lived experience, I knew that, well, that can't be true, Mr.

Therapist, you know, I, I know that that's not true. That top of mind isn't the most important. Um, but nonetheless, I'm not a therapist. I'm, I'm a punk that was depressed and suicidal. I've been through lots of, you know, patient experience, but I'm not, I'm not a doctor. I'm not a therapist. And who am I to try to change the minds of these, the vast majority of these therapists?

So I, I abandoned that. Um, I realized that I, I can't, I can't, maybe I'm early to market. Maybe I need more millennial therapists in the market, um, to, to be more comfortable. [00:35:00] Who knows? Who knows, but. I had a lot of pushback, uh, understandably, and I respect the market. It's not my job to try to change the mind.

So I made my, my pivot to how do I deploy this technology to a more commercial setting and a more commercial setup where maybe we are not asking self-employed therapists to take time out of their, uh, their day to, um, you know, spend one or two minutes looking at a snapshot of a, of a summary of a week.

And that's where we then said, okay, great. Let's analyze these insights. Let's create a dashboard. Let's help these, um, commercial. Therapists, um, create more of a compelling business case and prove their ROI to their corporate partners that they're charging and, and that's the direction that we took. 

Speaker: So a commercial therapist, you mean a therapist kind of that's embedded within a company, say, 

Speaker 2: yeah.

Yeah. It could either be someone embedded in a company or some that's affiliated with an EAP, where, you know, they're, they're part of an offering that the EAP will [00:36:00] charge Apple or Google or Amazon, whoever it is, you know, X number of dollars per, per employee per year. And that way it's a different dynamic.

And, and we do see that actually a lot of these EAPs, since the pandemic are being asked more and more to prove the mental health outcomes, not just the adoption raise with, with the purse strings being tightened. It's really important that we don't just deliver. Therapy sessions for the sake of it. We, we deliver and we deliver on improving mental health outcomes so that the CFO can draw a straight line with quantifiable output of mental health, with something that they care deeply about, such as employee engagement, employee turnover, for example.

And we kind of, we bridge, we help bridge that gap with our analytics. So yeah, that's the journey. 

Speaker: And so, so the technology is helping to demonstrate the improvement in mental health outcomes, uh, as a result of the therapy. 

Speaker 2: Exactly. Yeah. I mean, one of the conversations, one of the terms that I had a lot [00:37:00] from hardcore CFOs, CTOs ceo, I CEOs, was mental health was this fluffy thing that sat in the corner.

Uh, it was the right thing to do for employees during the pandemic. We think it's the right thing to do humanely, but it seems to sit over here. And then we have sensible business conversations around ROI. We quantify everything we do in a business. This kind of mental health support is something we struggle to quantify.

Uh, and so that's where mind data comes in to say, let us do the analytics and let us bridge the gap between, you know, qualitative conversations and journal entries. And let us put some hard numbers on this to help you draw a line between ROI business cases. 

Speaker: So is that what you would call a thema thematic analysis, where you can look at someone's sessions and say, okay, patient X, their first few sessions, you can see thematically, quite pessimistic, quite rigid, quite inflexible thoughts, patterns, and by [00:38:00] session 10, a lot more optimism.

They seem to be coming up with solutions on their own. They seem to be a lot more mentally flexible. Hence we can say something is improving. Is it something like that? 

Speaker 2: It's very, very similar. So we'd use a sentiment analysis, um, to, to try to measure how emotional they're, they're recording their own thoughts and they're conversing in that way.

The thematic analysis helps us, um, chunk and categorize the themes that are coming out of these conversations. So, for example, on our dashboard, we may see that white, broadly speaking, white middle-aged employees that work in sales, the number one theme that's driving low mental health is financial anxiety.

For example, after x number of sessions with this, uh, third party therapy practice, we can see that actually that financial anxiety has dropped away from the top five negative drivers. And actually they've reframed it because now appearing in the top five positive drivers for wellbeing, for example. So, [00:39:00] so that, so we can start to understand the themes that are coming out and it's important to be able to.

Use these themes, not only on the backend to prove outcomes, but HR teams can use this to help improve interventions. So if we know that, you know, middle-aged white, uh, men, uh, working in sales, or we know that minority females under 25 working in marketing are being, you know, their mentality is being driven by certain overarching themes, well, actually we can get ahead of that by saying, well, what do we do to improve employee onboarding?

You know, how, how do we, we we head that off and be proactive and predictive instead of solely reactive with what we're doing? So that's, that's how we use those themes. 

Speaker: It's interesting because in the kind of self-help, self-development world, which I'm quite familiar with, one of the first things they say is, if you want to improve an area of your life, you need to start measuring stuff.

You know, if you want to lose weight, you need to weigh yourself. It's a good idea to weigh yourself to be good. It's good to know how many calories you're [00:40:00] eating, roughly. Those measurements give you a baseline and then. The really cool thing about measurement is as you actually make those improvements, you can track progress, which aside from being informative is very motivating.

You can say, okay, I actually am down two kilos this week. Something is moving. We don't have really measurement. I mean, we have rating skills, but they're not used commonly in private therapy practice. So it sounds like something that can give a real insight into how sessions are going could be really useful for 

Speaker 2: Yeah, I think for, for two reasons.

So, so number one, if, if we look at, um, certain, um, traditional surveys or questionnaires on, on getting baselines of, of mental health, the problem is, one of the challenges that I think as a patient that they had was it was a little bit like when we have an MOT on a car, it's periodic, it's fixed. It's kind of a snapshot in time and it's, it, it, it gets us some way there.

But the most important thing is having a drip feed of insights on the [00:41:00] journey and you can't be expected to answer quite an in depth. Mental health questionnaire or survey every week, for example. And one of the things that I struggled with was motivation around progression. So we have this spotlight effect, I think, where we seem to magnify the emotion that we're experiencing in the moment.

So when I was on my journey, if I had a bad week, it was very difficult to understand that that may have just been a blip within an otherwise upwards trend. It felt all encompassing and I was a big proponent of paper journal. Uh, I still do that from time to time actually, so it found it very therapeutic.

But the challenge with these, you know, pages and pages is it didn't give me a sense of progress. I could flick randomly to a page six weeks ago, but was that better or worse than I'm feeling now? So the visualization of seeing a trend and saying, Hey, do you know what, I'm on a downward trend, but. Do you know what the tangent is up?

Uh, and, and I'm kind of 63% [00:42:00] higher subjectively than I was when I started this journey. And that can really help that context setting to keep the motivation rather than saying, this isn't working. I feel terrible. Again, what was the point of three months of therapy? You, you, you're sometimes unaware of the progress you've made, so you can't improve what you don't measure as the, as the old adage goes.

Uh, and I think it's really important 

Speaker: and it's nice to give that sense of, uh, overarching structure to therapy because otherwise it can feel a little bit like these snapshots without sort of a larger structure that the client can appreciate, okay, this is this whole block of, of therapeutic work that I'm doing with all the intricacies.

Instead, it can feel a bit disjointed at times. Um, I'm, I'm also interested in the idea of using writing as an actual intervention. Uh, sometimes even in the therapy room. Does mind data do anything around. Writing techniques that, uh, clients can use either on their own time or in a session to process stuff.

Speaker 2: [00:43:00] Not, not at this stage. It doesn't. It's a very, um, client led journal, uh, entry. So when you, when you record a journal entry, it takes in two data points. Number one is a subjective zero to 10 scale, uh, which most people can usually report. How are you feeling right now? I 10. Well, subjectively I'm feeling a three or a seven, for example.

So it's quite low, cognitive low, just to just record that of how I'm feeling. And then you've got a free text box to record as much or as little as you like. Um, it's optional, so you don't need to even record it. You might just wanna snapshot how you're feeling in the moment to help us plot on a graph, you know, your, your subjective mood score, progress, if you will.

Um, now it may be that one day we look to improve that. And again, with ai, we kind of have a, a slight coach in your pocket that helps you, um, guide through how you record that. Maybe it has intelligent questions, uh, but at this stage with delivery, wanting to keep it quite universal. Our technology can be used by coaching as much as it can by a therapist, for example.

Um, and we, we also appreciate that, um, therapists that have yeast mind [00:44:00] data are quite protective. Um, they're quite rightly the gatekeepers. And so we've, we've always been very conscious of saying, we are a tool. We're not a guide. So we are a tool that can be used by your clients or by your patients, but you can instruct your clients how you wish them to use it.

And so we, we do pick up a lot of trepidation, fear of therapists saying, well, hang on. Now, what is that gonna be doing when my client isn't with me? How do I know it's not gonna be asking the right questions or the right prompts? I'm very nervous around that, Sean. So we've always come back to the common denominator of keep it simple, keep it client led.

But the framing and the instructions are always by the therapist, just as they do now with going home and writing in a paper journal. I used to have prompts and thoughts and instructions by my therapist, say, look, Sean, this week, why don't you try X? Why don't you think about Y? And so we, we just say, look, the the lowest friction approach here is we are just a digital version of that [00:45:00] paper journal.

In the future, we can do some clever things, but let's not reinvent the wheel right now. 

Speaker: Yeah, that makes sense. And it's the, it's the logical first step and it's the least risky approach. 'cause what you hear when people are using like chat GPT for therapeutic reasons is obviously it's the active part with where people get into trouble and chat.

GPT can promote risky behaviors or promote like unhelpful thought patterns. So that makes total sense. Are there any downsides to using this technology that you've observed? Like from your case studies, from therapists, from clients, anything? 

Speaker 2: Inevitably there are downsides with, with, with this, the, the first thing, um, I would say is I.

And it's such a trade off. Um, I do both With paper-based journaling and digital journaling, I think that there's something more intimate with paper-based journaling. When I see my own handwriting, I sit down with a physical, uh, notepad and I write my thoughts. There's something a little bit colder and a bit more clinical when I'm typing my [00:46:00] thoughts.

I must admit, however, the trade off is that my journal will not give me any analytics, any insights, any data. It, it just won't give me anything back. Uh, it's kind of a, a download of my thoughts. It's therapeutic and then it's gone, if you will. So the downside is that it's less intimate. There's less tactical feedback with, you know, uh, with writing in, in a journal.

Um, the other thing is, and it depends the state of state of mind that you're in, um, if you download your thoughts into minds data and you have these insights that come up, you're not forced to frame your thoughts as much. Um, you're not forced to kind of think, how am I gonna frame this with my therapist?

So again, it's a trade off. Um, if you are really struggling with recency bias and you really have cloudy mind, foggy mind, it's a, it can be a godsend for you. Um, but obviously it's a tool to be used. You wouldn't want any parts of your mind to atrophy, you know, around your framing. Um, and again, that could be a future improvement with mind data, where [00:47:00] before going into a session.

We can intelligently send certain questions to say, before you go in, here's a snapshot of things that you've been through. Why not think about how you're gonna frame this with Alex, for example, maybe we send intelligent summaries to Alex or Betty, you know, based on their, what they would like to see from their, their patients.

Um, so they're the two traits, obviously from a a commercial perspective. Um, and the, the, the trade off is around, I think, education and adoption and change management with the professional big, big trade offs. That's why we've had to make a pivot. Um, I see a lot of trepidation around technology, uh, and fear, uh, around, i, I don't want to know how my, my client has been feeling outside of a session.

I dunno what to do with that. Will they become over reliant? So we've put in good safeguarding to say that this journal entry, you know, this isn't a 24 hour Samaritans line where your therapist is available. There's no two-way communication on mine data. Um, they will use this as part as they do. They'll review their notes [00:48:00] from last week.

While they're reviewing their, their notes from last week, they spend 60 seconds having a snapshot. Um, but I think that the, the biggest downside right now of this technology is change management of, of therapists. And, and I think that whether it's mind, state or otherwise, the one thing that, again, I'm trying to be self-aware here, I'm not a qualified therapist.

Okay? So anybody, whether it's you, Alex, or anybody else listening, please do not think that I'm here to tell you how to do your job. Of course I'm not, I'm not qualified to say that. But the one thing I would implore nervous therapists that are worried about adopting new types of technology to enhance their services is that, um, chat, EPT and the like are, are replacing therapists.

Um, whether we like it or not, they are, um, now for the general public. There's a lot of positives that come from that generally because we've suddenly got access to an intelligent conversational portal that enables us to frame and offload our thoughts where there was no outlet to those if you weren't going to [00:49:00] therapists, for example.

However, what that's doing is that maybe some of those people that would've engaged with a therapist says, well, maybe I don't need to. I've got a 24 by seven 20 pound a month therapist that I can use to help frame and ask intelligent questions back to me. And you know, there's this old adage of, AI isn't going to replace your job.

Someone using AI is going to replace you. And I think that we're already seeing that in the therapy world. And for those therapists that are saying, I'll never use technology, I'm worried about it. Try to educate, try to understand how you can use therapy to enhance human led therapy so that you do future-proof yourself and you're not replaced by something that I don't personally believe in, but a chat bot that's a therapist in your pocket.

I've always been an advocate of using technology to improve human led therapy. I'm always gonna advocate for that, even with all the pushback that I had from therapists. I still think that there's a place for the Betty's and Alexs in this [00:50:00] world that use technology. So that just might my kind of like peace offering to, to, to, to, to nervous therapists.

It can be used as a great tool if you embrace it. 

Speaker: No, I think it makes sense and I guess everyone has to have a certain amount of humility here that we are limited, you know, we are flawed and it stands to reason that responsibly used technology can increase our capabilities to help people. Is that such a radical notion?

Is that a bad thing? 

Speaker 2: Mm-hmm. Agreed. 

Speaker: Um. Does mi does mind data ask for specific information from clients? Like how has your sleep been, you know, appetite, energy levels, does it get metrics on that kind of stuff? 

Speaker 2: Very good question. And right now, no. One of the themes that we've, we've had with mind data, um, which I think does fly in the face of a number of different technology companies is, um, we, we've never wanted to use a sledgehammer to crack a nut.

So we've been deliberately simplistic in our approach and methodical with the types of features that we [00:51:00] roll out. Um, and so at this point, no, we, we don't integrate that. Now, one of the, the future things that we are looking at is with our smart watches or or other health apps, can we start to bring in this kind of 360 wide holistic data sets to bring into mind data, use AI to then start to unpack unconscious patterns that may have, uh, uh, uh, a leading impact on our mental health.

So it could be to your point that when we bring in asynchronous data points, that we could say that, Hey, did you know that based on geolocation every time you're at this specific office, for example, um, when your heart rate doesn't go above a certain amount of time in a certain period of time, indicating no exercise, when we see that you are eating more of this type of food for, you know, we know that statistically speaking, it's likely that your mental health subjectively is going to drop by 17%, for example.

So I'm a big believer that with the right amount of data and uh, um, uh, and insights, [00:52:00] we can move toward predictability. We're never gonna get to a hundred percent predictability. But I do believe with the right insights we can get so far ahead of, you know, tackling the upstream causes rather than focusing on improving the reactive, uh, symptom improvements, if you will.

Speaker: Yeah, and I like that. I'm quite passionate, uh, about the idea that what we do physically has a huge impact on our mental health and in some sense. A lot of people still, I think, hold a lot of skepticism that, for example, your nutrition will affect, you know, your mental health, whether or not you exercise.

And they may not hold that skepticism consciously. If you ask them, they might say, you know, no, of course it will affect it, but it won't actually lead to their behavior being different. They'll know it abstractly. So a technology that can help make that connection really concrete. Like, yes, when I went running three times a week, my mood was like five points better.

I love that because again, measurement is [00:53:00] so, uh, helpful for motivation. 

Speaker 2: Yeah, I totally agree. And I think that, um, measurement and insights and did, you know, moments, I mean, we, we carry so many unconscious habits and behaviors and we really only wake up, as I said, you sleep, walk into low mental health most of the time, and it was that first day that you had an extra coffee.

You, you forego that bottle of, uh, water, for example. You skip the workout because it's raining. Those individually do not have directly a big negative impact on our mental health, at least consciously, but they compound over time. And you're right. If something like my data can say, Hey, here's a flag. When this last happened, Alex, in three weeks time, we saw this.

So why not try tomorrow just to go for a walk. You know, you can bring in, um, weather patterns as well into this kind of big data analytics and say, look, we know it's raining tomorrow, so why not try 50 press up at home? Mm-hmm. Uh, [00:54:00] it looks like it's gonna be nice tomorrow, so why not go for a, a one mile walk for its so we can start to be, um, to a degree of predictability, but also hyper-personalized as well of what works for you as well.

That's the bit that I'm excited about, about the future of mind data. 

Speaker: Yeah. Another area that could be very useful, uh, this could apply to is alcohol. And especially, you know, everyone's aware of the dangers of being addicted or dependent on alcohol, but a lot of people, uh, a lot of really high achieving people have that, like chronic low level drinking where the, you ask them, how much do you drink?

And they say, oh, you know, two or three pints, three or four times a week. Which doesn't seem like a lot, but actually if you add that up, it's a huge amount of units. They don't necessarily realize the impact that's having on mood, anxiety, sleep. Again, super useful if a, if an app could help to like connect those dots.

Speaker 2: Yeah, I think you're absolutely right and I think that coming back to one of your early questions of, you know, the [00:55:00] benefits of a a therapist is generally a psychologist, psychiatrist, therapist, counselor, they're great dot connectors. Um, and they can have an outside view of, well, you may not be seeing something here.

You know, and there's this old adage of, well, I wasn't loved as a child, so that means I drink alcohol as an adult, for example. And, and yeah. And sometimes you need that. That's why I drink 

Speaker: alcohol. Yeah, 

Speaker 2: yeah, yeah. Well I, I've got, I've got dad issues and things like that. I've, yeah. Um, and so I am, I, I'm a, uh, you know, I'm a big believer that if you can have something to connect unconscious dots and bring it consciously to you to help improve.

Hell yeah. I think that's, that's, that's gotta be the future. 

Speaker: Again, just looking at the AI space more broadly, just the industry. You, I know you're a cautious optimist. Is there anything that really worries you about AI and where this could go over the next decade? Say? 

Speaker 2: Yeah, I mean, I guess first it depends on, I think we need to move towards democratizing oversight of ai.

I think that's really important. I [00:56:00] think generally speaking, the collective good outweighs bad actors. Generally, I think the biggest fear I have is bad actors having a monopoly on large language models. Um, you know, there, there are multiple different ways of training, uh, ai, um, and one of the ways is called assisted learning.

So we give that human, uh, feedback, oh, I give it loads of pictures of animals and say, tell me which ones are caps. And it, it shows me three dogs, four bears. And I give it feedback to say, no, it's not. It's go back and try it again, for example. Great. However, if you have an agenda that you are looking to push, very easy to try to manipulate those, uh, you know, those algorithms.

So I'm, I'm worried about the monopolization of large language models and the, uh, the political views and agendas of those countries or those organizations. So I think if we can go towards democratizing these, then I think it'll be brilliant. A bit like mm-hmm. How, how the internet [00:57:00] has, has kind of become democratized.

Um, lots of shadowy places on the internet, a lot of evil and dark things that happen. Um, but thank goodness, either it's not being entirely controlled and every interaction we, that we have with the internet is controlled by a very small subset of, you know, uh, bad actors, if you will. So I think that's the first thing of, of around, you know, how, how do we have oversight, uh, of these.

I think that's really important. The other thing that I'm potentially worried about is, um. The reduction in human connection. Um, you know, I think we are already seeing people that are having intimate relationships with large language models. Um, I think we're, we're already seeing, you know, the cutback of, um, people not seeking help from a human, you know, with a therapist.

I've just got Chachi bt that, that I'll, I'll over rely on. Um, and I think that we need greater education around what AI is and what it isn't. Uh, because it has a great illusion of being effectively a super intelligent human [00:58:00] being. The sitting in, in a box somewhere, but it's not, it is an illusion of that.

Um, and I think that if we really understood how these large language models work, it'll shatter that illusion. And you can use it as a tool, not as a digital person. I think it's really important. Um, so as is true with most things, there's always a double-edged sword because if, if someone is suffering from loneliness.

They have an illusion and they believe that they have some form of relationship with, uh, chat PT for example. Is that inherently a bad thing? Are, are we prepared to say it's better that you are alone rather than having a relationship with, with a large language model and beat the combat, uh, combat the symptoms of loneliness?

Maybe not. So they're the, they're the things that I'm, I'm kind of worried about of how do we ensure that it's used for the greater good and that it's not here to replace human interaction. They're the two things that I'm [00:59:00] quite conscious of, I would say. 

Speaker: Yeah. And I'm pretty much in full agreement with those.

Um, just before we finish, you may not have a strong opinion on this, but for our financial investors out there, there's a lot of talk about there being an AI bubble. Do you think there's a bubble in terms of these. Very, uh, highly valued tech stocks. Should people be investing in AI right now in your opinion?

Speaker 2: It, I think that there could be a little bit of a bubble. So when we look at the stock market, it's effectively a visualization of a group of human psychology. Uh, that's effectively what's visualizing, isn't it? It's built on hype and, you know, and people imagining certain things and, 

Speaker: and actually the function of the stock market is to assign value for things.

I don't think people talk about that or not. That's literally the job of the stock market is to help 

Speaker 2: Yeah. 

Speaker: Everyone arrive at how valuable is this thing and it's really good in the long term, but quite poor in the short term. 

Speaker 2: Yes. Yeah, I totally agree with you and I, and I think that, I [01:00:00] think that there, there may be a pullback of, of, of ai, uh, in terms of valuation because of, I think the height can be built on.

Lack of understanding of what it is. I think that at the moment, this, firstly, this overarching term of AI is thrown around a lot, you know? And so we need to understand, when we say ai, what, what are we talking about here specifically? Are we talking about natural language processing? Are we talking about statistical analysis?

Are we talking about large language bottles, for example? What, what, what are we talking about? AI 

Speaker: is like saying agriculture. Exactly. It's a whole sector thing. You're absolutely 

Speaker 2: right. It's like saying, my company uses technology. What, what, what does that mean? You know, what, what does that mean? So I think that that can come from a lack of understanding and education.

And so we're seeing it as this oracle, this, this all seen, all knowing thing that's gonna change the world and, and that in artificial inflation is, is happening slightly. I think that we will start to see a little bit of a pullback, I think. But I do think that AI is worth investing in. But maybe not necessarily just backing open [01:01:00] AI or Nvidia, for example.

I do think that we are. On a great opportunity like we were in the late nineties with the internet. I think that, um, investing into ways of leveraging ai, creating more AI tools, creating very clever ways of how do we bridge the gap between AI models and humans. Um, you know, there's gonna be an amazing space, for example, for startups in the ad space.

For example, like Google Ads and SEO we're gonna see that again, you know, how do we intelligently push certain products and things like that and ads through, um, large language models, for example. And, you know, roles that we can't even envisage 10 years ago. We can't imagine that the term influencer would've been a multimillion pound job, for example.

And that was only 10 years ago. So there will be jobs that you and I can't even name right now that are created through, you know, large language models, things like that. Um, so I think there's a brilliant time to invest into. [01:02:00] Leveraging ai. Hell yes. And we are in 1998 right now. Um, and we have such a great opportunity to, to leverage that.

There will be billionaires made, mul, trillion dollar companies that will be made off the back of leveraging ai, like companies that leverage the internet, for example. So I would invest in that way, not necessarily just blindly backing Nvidia and Amazon and, and OpenAI, for example, in the long run. Um, I'm long on them for sure, of course.

Um, but in the short term, I think we might be in for a bit of a pullback, I think. But I'm not a financial, it's gonna be a bumpy ride. I think it will be a bumpy ride held. Do not take this, whoever's listening as financial advice. It's just my opinion. Uh, but we're in for a bumpy ride until we normalize, for sure.

Speaker: Yeah. And I, I love that advice of invest in ai, not just financially. There are greater and lesser risky ways to do that, but invest it in your life as in familiarize yourself with the technology. Start asking yourself tho [01:03:00] those questions, how can I be a better employee or self-employed person if I familiarize myself with this technology?

Yeah, I think that's really good advice. Sean, it's been wonderful to speak to you today. Thank you so much. I really enjoyed learning more about the business world. 

Speaker 2: Yeah, thank you so much for the invitation and the great conversation. So thank you again.