Hosts Will Larry and Chad Pytel interview Brock Dubbels, Principal UX and AI Researcher at CareTrainer.ai. Brock discusses how CareTrainer.ai leverages AI to address the current care crisis in elderly populations. He highlights the growing demographic of individuals over 70 and the significant shortage of caregivers, exacerbated by COVID-19. CareTrainer.ai aims to alleviate this by automating routine tasks, allowing caregivers to focus on building meaningful relationships and providing personalized, compassionate care. The platform utilizes AI to manage tasks such as documentation, communication, and monitoring, which helps caregivers spend more time engaging with patients, ultimately enhancing the quality of care and reducing caregiver burnout.
Brock elaborates on the specific tasks that CareTrainer.ai automates, using an example from his own experience. He explains how AI can transform transactional interactions into conversational ones, fostering trust and authenticity between caregivers and patients. By automating repetitive tasks, caregivers are freed to engage more deeply with patients, encouraging them to participate in their own care. This not only improves patient outcomes but also increases job satisfaction and retention among caregivers. Brock mentions the alarming attrition rates in caregiving jobs and how CareTrainer.ai’s approach can help mitigate this by creating more rewarding and relational caregiving roles.
Additionally, Brock discusses the apprenticeship model CareTrainer.ai employs to train caregivers. This model allows new caregivers to learn on the job with AI assistance, accelerating their training and integrating them more quickly into the workforce. He emphasizes the importance of designing AI tools that are user-friendly and enhance the caregiving experience rather than replace human interaction, and by focusing on customer obsession and continuously iterating based on feedback, CareTrainer.ai aims to create AI solutions that are not only effective but also enrich the entire caregiving profession.
- CareTrainer.ai
- Follow CareTrainer.ai on LinkedIn.
- Follow Brock Dubbels on LinkedIn. Visit his website: brockdubbels.com.
- Follow thoughtbot on X or LinkedIn.
Transcript:
WILL: This is the Giant Robots Smashing Into Other Giant Robots podcast, where we explore the design, development, and business of great products. I'm your host, Will Larry.
CHAD: And I'm your other host, Chad Pytel. And with us today is Brock Dubbels, Principal UX and AI Researcher at CareTrainer.ai, which is transforming health care and caregiving with a human-first approach to artificial intelligence. Brock, thank you for joining us.
BROCK: Hey, thanks for having me, guys. I'm excited to talk about this.
CHAD: Brock, let's get started with just diving into what CareTrainer.ai actually does. You know, so many businesses today are getting started with or incorporating artificial intelligence into their product offerings. And I know that it's been something that you've been working on for a long time. So, what is CareTrainer?
BROCK: Well, CareTrainer is an opportunity in the midst of a crisis. So, right now, we have what's called a care crisis for the elderly populations. If you were to look at the age of the North American population and look at it over the next 10 years, about 65% of our population will be over the age of 70. And right now, we are understaffed in caregiving by almost 20%. Caregivers, especially after COVID, are leaving at about a 40% clip. And enrollment in these care programs is down 9%, but yet that older population is growing.
And in the midst of this, we've just recently had an executive order called the Older Americans Act, which states that we actually have to reduce the ratio of caregivers to patients, and we need to give more humane interaction to the patients in these facilities, in homes and help them to retain their dignity. Many of them lose their identity to diagnosis, and they're often referred to as the tasks associated with them.
And what CareTrainer attempts to do is take many of the tasks out of the hands of the caregivers so that they can focus on what they're good at, which is building relationships, learning and understanding, acting with curiosity and compassion, and demonstrating expert knowledge in the service to caring for patients, either in homes, facilities or even post-acute care.
WILL: You mentioned your hope is to take some of the tasks away from the caregivers. Can you go a little bit deeper into that? What tasks are you referring to?
BROCK: Let's think about an example. My mom was a public health nurse, and she worked in child maternal health. And these were oftentimes reluctant counseling sessions between she and a young mother or a potential mother. And if she were sitting there with a clipboard or behind a computer screen and looking at the screen, or the clipboard, and doing the interview with questions, she would probably not get a very good interview because she's not making a relationship. It's not conversational; it's transactional.
And when we have these transactional relationships, oftentimes, we're not building trust. We're not expressing authenticity. We're not building relationships. It's not conversational. And we don't get to know the person, and they don't trust us. So, when we have these transactional relationships, we don't actually build the loyalty or the motivation. And when we can free people of the tasks associated with the people that they care for by automating those tasks, we can free them up to build relationships, to build trust, and, in many cases, become more playful, expose their own vulnerability, their own past, their own history, and, hopefully, help these patients feel a little bit more of their worth.
Many of these people worked meaningful lives as school teachers, working at the fire department, working at the hardware store. And they had a lot of friends, and they did a lot for their community. And now they're in a place where maybe there's somebody taking care of them that doesn't know anything about them, and they just become a person in a chair that, you know, needs to be fed at noon. And I think that's very sad.
So, what we help to do is generate the conversations people like to have, learn the stories. But more importantly, we do what's called restorative care, which is, when we have a patient who becomes much more invested in their own self-care, the caregiver can actually be more autonomous. So, let's say it's an elderly person, and, in the past, they wouldn't dress themselves. But because they've been able to build trust in a relationship, they're actually putting on their own blouse and slacks now. For example, a certified nursing assistant or a home health aide can actually make the bed while they're up dressing because the home health aide or certified nursing assistant is not dressing them or is not putting the toothpaste on the toothbrush.
So, what we're doing is we're saying, "Let's get you involved in helping with restorative care." And this also increases retention amongst the caregivers. One of the things that I learned in doing an ethnography of a five-state regional healthcare system was that these caregivers there was an attrition rate of about 45% of these workers within the first 30 days of work. So, it's a huge expense for the facility, that attrition rate.
One of the reasons why they said they were leaving is because they felt like they weren't building any relationships with the people that they were caring for, and it was more like a task than it was a care or a relationship. And, in fact, in many cases, they described it as maid service with bedpans for grumpy people [chuckles]. And many of them said, "I know there's somebody nice down there, but I think that they've just become a little bit hesitant to engage because of the huge number of people that come through this job, and the lack of continuity, the lack of relationship, the lack of understanding that comes from building a relationship and getting to know each other."
And when we're talking about taking the tasks away, we're helping with communication. We're actually helping with diagnosis and charting. We're helping with keeping the care plan updated and having more data for the care plan so that nurse practitioners and MDs can have a much more robust set of data to make decisions upon when they meet with this patient. And this actually reduces the cost for the care facilities because there's less catastrophic care in the form of emergency rooms, prescriptions, assisted care, as well as they actually retain their help. The caregivers stay there because it's a good quality of life.
And when those other costs go down, some of the institutions that I work for actually put that money back into more patient care, hiring more people to have more meaningful, humane interactions. And that's what I mean about taking the tasks off of the caregiver so that they can have the conversations and the relational interactions, rather than the transactional interactions.
CHAD: One thing I've heard from past guests and clients that we've had in this space, too, is, to speak more to the problem, the lack of staff and the decline in the quality of care and feeling like it's very impersonal causes families to take on that burden or family members to take on that burden, but they're not necessarily equipped to do it. And it sort of causes this downward spiral of stress and quality of care that impacts much bigger than just the individual person who needs the care. It often impacts entire families.
BROCK: Oh yeah. Currently, they're estimating that family, friends, and communities are providing between $90 and $260,000 worth of care per person per year. And this is leading to, you know, major financial investments that many of these people don't have. It leads to negative health outcomes. So, in a lot of ways, what I just described is providing caregiver respite, and that is providing time for a caregiver to actually engage with a person that they're caring for, teaching them communication skills.
And one of the big things here is many of these institutions and families are having a hard time finding caregivers. Part of that is because we're using old systems of education in new days that require new approaches to the problem. And the key thing that CareTrainer does is it provides a guided apprenticeship, which means that you can earn while you learn. And what I mean by that is, rather than sitting in a chair in front of a screen doing computer-based training off of a modified PowerPoint with multiple-choice tests, you can actually be in the context of care and earning while you learn rather than learning to earn.
CHAD: Well, at thoughtbot, we're a big believer in apprenticeships as a really solid way of learning quickly from an experienced mentor in a structured way. I was excited to hear about the apprenticeship model that you have.
BROCK: Well, it's really exciting, isn't it? I mean, when you begin looking at what AI can do as...let's call it a copilot. I thought some of the numbers that Ethan Mollick at Wharton Business School shared on his blog and his study with Boston Consulting Group, which is that an AI copilot can actually raise the quality of work, raise the floor to 82%, what he calls mediocrity. 82% was a pretty good grade for a lot of kids in my classes back when I was a Montessori teacher.
But, in this case, what it does is it raises the floor to care by guiding through apprenticeship, and it allows people to learn through observation and trial and error. And people who are already at that 82nd percentile, according to Mollick's numbers, increase their productivity by 40%. The thing that we're not clear on is if certain people have a greater natural proficiency or proclivity for using these care pilots or if it's a learned behavior.
CHAD: So, the impact that CareTrainer can have is huge. The surface area of the problem and the size of the industry is huge. But often, from a product perspective, what we're trying to do is get to market, figure out the smallest addressable, minimum viable product. Was that a challenge for you to figure out, okay, what's the first thing that we do, and how do we bring that to market and without getting overwhelmed with all the potential possibilities that you have?
BROCK: Yeah, of course. I start out with what I call a GRITS model. I start out with, what are my goals? Then R, let's review the market. How is this problem being addressed now? I, what are my ideas for addressing these goals, and what's currently being done? And T, what tasks need to be completed in order to test these ideas? And what steps will I take to test them and iterate as far as a roadmap?
And what that allowed me to do is to begin saying, okay, let's take the ideas that I can bring together first that are going to have the first initial impact because we're bootstrapping. And what we need to be able to do is get into a room with somebody who realizes that training caregivers and nursing is something that needs a review, maybe some fresh ideas. And getting that in front of them, understanding that that's our MVP 1 was really important. And what was really interesting is our MVP 2 through 5, we've begun to see that the technology is just exponential, the growth and progress.
Our MVP 2 we thought we're going to be doing a heck of a lot of stuff with multimedia reinforcement learning. But now we're finding that some of the AI giants have actually done the work for us. So, I have just been very happy that we started out simple. And we looked at what is our core problem, which is, you know, what's the best way to train people? And how do we do that with the least amount of effort and the most amount of impact? And the key to it is customer obsession. And this is something I learned at Amazon as their first principle.
And many of the experiences that I brought from places like Amazon and other big tech is, how do I understand the needs of the customer? What problems do they have, and what would make this a more playful experience? And, in this case, I wanted to design for curiosity. And the thing that I like to say about that is AI chose its symbol of the spark really smartly. And I think the spark is what people want in life. And the spark is exploring, and it's finding something. And you see this kind of spark of life, this learning, and you discover it. You create more from it. You share it. It's enlightening. It's inspirational. It makes people excited. It's something that they want to share. It's inventing. It's creation.
I think that's what we wanted to have people experience in our learning, rather than my own experience in computer-based training, which was sitting in front of a flashified PowerPoint with multiple choice questions and having the text read to me. And, you know, spending 40 hours doing that was kind of soul-killing. And what I really wanted to do was be engaged and start learning through experience. And that's what came down to our MVP 1 is, how do we begin to change the way that training occurs? How can we change the student experience and still provide for the institutional needs to get people on the floor and caring for people? And that was our first priority.
And that's how we began to make hard decisions about how we were going to develop from MVP 1, 2, 3, 4, and 5 because we had all the big ideas immediately. And part of that is because I had created a package like this back in 2004 for a five-state regional care provider in the Midwest. Back then, I was designing what could only be called a finite game. I'm designing in Flash for web. I'm doing decision trees with dialogue, and it's much like a video game, but a serious game. It's getting the assessment correct in the interactions and embedding the learning in the interaction and then being able to judge that and provide useful feedback for the player.
And what this did was it made it possible for them to have interactive learning through doing in the form of a video game, which was a little bit more fun than studying a textbook or taking a computer-based test. It also allowed the health system a little bit more focus on the patients because what was happening is that they would be taking their best people off the floor and taking a partial schedule to train these new people. But 45% of those that they were training were leaving within the first 30 days. So, the game was actually an approach to providing that interaction as a guided apprenticeship without taking their best people off the floor into part-time schedules and the idea that they might not even be there in 30 days.
So, that's kind of a lot to describe, but I would say that the focus on the MVP 1 was, this is the problem that we're going to help you with. We're going to get people out of the seats and onto the floor, off the screen, caring for people. And we're going to guide them through this guided apprenticeship, which allows for contextual computing and interaction, as we've worked with comparing across, like, OpenAI, Anthropic, Google, Mistral, Grok, trying these different approaches to AI, figuring out which models work best within this context. And, hopefully, when we walk in and we're sitting with an exec, we get a "Wow," [laughs]. And that's the big thing with our initial technology. We really want a wow.
I shared this with a former instructor at the University of Minnesota, Joe Gaugler, and I said...I showed him, and he's like, "Wow, why isn't anybody doing this with nursing and such?" And I said, "Well, we are," you know, that's what I was hoping he would say. And that's the thing that we want to see when we walk into somebody's office, and we show them, and they say, "Wow, this is cool." "Wow, we think it's cool. And we hope you're going to want to go on this journey with us." And that's what MVP 1 should do for us is solve what seems like a little problem, which is a finite game-type technology, but turn it into an infinite game technology, which is what's possible with AI and machine learning.
WILL: I love, you know, you're talking about your background, being a teacher, and in gaming, and I can see that in your product, which is awesome. Because training can be boring, especially if it's just reading or any of those things. But when you make it real life, when you put someone, I guess that's where the quote comes from, you put them in the game, it's so much better. So, for you, with your teacher background and your gaming background, was there a personal experience that you had that brought out your passion for caregiving?
BROCK: You know, my mom is a nurse. She has always been into personal development. By the time I was in sixth grade, I was going to CPR classes with her while she was [inaudible 19:22] her nursing thing [laughs]. So, I was invited to propose a solution for the first version of CareTrainer, which had a different name back in 2004, which we sold. That led to an invitation to work and support the virtual clinic for the University of Minnesota Medical School, which is no longer a thing. The virtual clinic that is the medical school is still one of the best in the country, a virtual stethoscope writing grants as an academic for elder care.
And I would have to say my personal story is that at the end of their lives, I took care of both my maternal grandmother in her home while I was going to college. And then, I took care of my paternal grandfather while I was going to college. And, you know, those experiences were profound for me because I was able to sit down and have coffee with them, tell jokes, learn about their lives. I saw the stories that went with the pictures.
And I think one of the greatest fears that I saw in many of the potential customers that I've spoken to is at the end of a loved one's life that they didn't learn some of the things that they had hoped from them. And they didn't have the stories that went with all the pictures in the box, and that's just an opportunity missed.
So, I think those are some of the things that drive me. It's just that connection to people. And I think that's what makes us humane is that compassion, that wanting to understand, and, also, I think a desire to have compassion and to be understood. And I think that's where gaming and play are really important because making mistakes is part of play. And you can make lots of mistakes and have lots of ways to solve a problem in a game. Whereas in computer-based training and standardized tests, which I used to address as a teacher, there's typically one right answer, and, in life, there is rarely a right answer [laughs].
CHAD: Well, and not really an opportunity to learn from mistakes either. Like, you don't necessarily get an opportunity on a standardized test to review the answers you got wrong in any meaningful way and try to learn from that experience.
BROCK: Have you ever taken one of those tests and you're like, well, that's kind of right, but I think my answer is better, but it's not here [laughter]? I think what we really want from schools is creativity and innovation. And when we're showing kids that there's just a right answer, we kind of take the steam out of their engine, which is, you know, well, what if I just explore this and make mistakes?
And I remember, in high school, I had an art teacher who said, "Explore your mistakes." Maybe you'll find out that their best is intentional. Maybe it's a feature, not a bug [laughs]. I think when I say inculcate play or inspire play, there's a feeling of psychological safety that we can be vulnerable, that we can explore, we can discover; we can create, and we can share.
And when people say, "Oh, well, that's stupid," and you can say, "Well, I was just playing. I'm just exploring. I discovered this. I kind of messed around with a little bit, and I wanted to show you." And, hopefully, the person backs off a little bit from their strong statement and says, "Oh, I can see this and that." And, hopefully, that's the start of a conversation and maybe a startup, right [laughs]?
CHAD: Well, there are so many opportunities in so many different industries to have an impact by introducing play. Because, in some ways, I feel like that may have been lost a little bit in so many sort of like addressing problems at scale or when scaling up to particular challenges. I think we trend towards standardization and lose a little bit of that.
BROCK: I agree. I think humans do like continuity and predictability. But what we find in product is that when we can pleasantly surprise, we're going to build a customer base, you know, that doesn't come from, you know, doing the same thing all the time that everybody else does. That's kind of the table stakes, right? It works. But somebody is going to come along that does it in a more interesting way. And people are going to say, "Oh."
It's like the arts and crafts effect in industrialization, right? Everybody needs a spoon to eat soup, a lot of soup [laughs]. And somebody can make a lot of spoons. And somebody else says, "Well, I can make spoons, too." "And how do I differentiate?" "Well, I've put a nice scrollwork design on my spoon. And it's beautiful, versus this other very plain spoon. I'll sell it to you for a penny more." And most people will take the designed thing, the well-designed thing that provides some beauty and some pleasure in their life. And I think that's part of what I described as the spark is that realization that we live in beauty, that we live in this kind of amazing place that inspires wonder when we're open to it.
MID-ROLL AD:
When starting a new project, we understand that you want to make the right choices in technology, features, and investment but that you don’t have all year to do extended research.
In just a few weeks, thoughtbot’s Discovery Sprints deliver a user-centered product journey, a clickable prototype or Proof of Concept, and key market insights from focused user research. We’ll help you to identify the primary user flow, decide which framework should be used to bring it to life, and set a firm estimate on future development efforts.
Maximize impact and minimize risk with a validated roadmap for your new product. Get started at: tbot.io/sprint.
WILL: You mentioned gamifying the training and how users are more involved. It's interesting because I'm actually going through this with my five-year-old. We're trying to put him in kindergarten, and he loves to play. And so, if you put him around a game, he'll learn it. He loves it. But most of the schools are like, workbooks, sit down; focus, all of those things.
And it probably speaks to your background as being a Montessori teacher, but how did you come up with gamifying it for the trainee, I guess you could say? Like, how did you come up with that plan? Because I feel like in the school systems, a lot of that is missing because it's like, like you said, worksheets equal that boring PowerPoint that we have to sit down and read and stuff like that. So, how did you come up with the gamifying it when society is saying, "Worksheets, PowerPoints. Do it this way."
BROCK: I think that is something I call the adult convenience model. Who's it better for: the person who has to do the grading and the curriculum design, or the kid doing the learning? And I think that, in those cases, the kid doing the learning misses out. And the way that we validate that behavior is by saying, "Well, you've got to learn how to conform. You've got to learn how to put your own interests and drives aside and just learn how to focus on this because I'm telling you to do it." And I think that's important, to be able to do what you're asked to do in a way that you're asked to do it. But I think that the instructional model that I'm talking about takes much more up-front thought.
And where I came from with it is studying the way that I like to learn. I struggled in school. I really did. I was a high school dropout. I went to junior college in Cupertino, and I was very surprised to find out that I could actually go to college, even though I hadn't finished high school. And I began to understand that it's very different when you get to college, so much more of it is about giving you an unstructured problem that you have to address. And this is the criteria under which you're going to solve the problem and how I'm going to grade you. And these are the qualities of the criteria, and what this is, is basically a rubric.
We actually see these rubrics and such in products. So, for example, when I was at American Family, we had this matrix of different insurance policies and all the different things in the column based upon rows that you would get underneath either economy, standard, or performance. And I think it was said by somebody at Netflix years ago; there's only two ways to sell bundled and unbundled. The idea is that there were these qualities that changed as a gradient or a ratio as you moved across this matrix. And the price went up a little bit for each one of those qualities that you added into the next row or column, and that's basically a rubric.
And when we begin to create a rubric for learning, what we're really doing is moving into a moment where we say, "This is the criteria under which I'm going to assess you. These are the qualities that inform the numbers that you're going to be graded with or the letter A, B, or C, or 4, 3, 2, 1. What does it mean to have a 4? Well, let me give you some qualities." And one of the things that I do in training companies and training teams is Clapping Academy. You want to do that together?
WILL: Yeah, I would love to.
BROCK: Would you like to try it here? Okay. Which one of you would like to be the judge?
WILL: I'll do it.
BROCK: Okay. As the judge, you're going to tell me thumbs up or thumbs down. I'm going to clap for you. Ready? [Claps] Thumbs up or thumbs down?
CHAD: [laughs]
WILL: I say thumbs up. It was a clap [laughs].
BROCK: Okay. Is it what you were expecting?
WILL: No, it wasn't.
BROCK: Ah. What are some of the qualities of clapping that we could probably tease out of what you were expecting? Like, could volume or dynamics be one?
WILL: Yeah, definitely. And then, like, I guess, rhythm of it like music, like a music rhythm of it.
BROCK: Okay. In some cases, you know, like at jazz and some churches, people actually snap. They don't clap. So, hands or fingers or style. So, if we were to take these three categories and we were to break them 4, 3, 2, 1 for each one, would a 4 be high volume, or would it be middle volume for you?
WILL: Oh, wow. For that, high volume.
BROCK: Okay. How about rhythm? Would it be 4 would be really fast; 1 would be really slow? I think slow would be...we have this cultural term called slow clapping, right [laughter]? So, maybe that would be bad, right [laughter]? A 1 [laughter]? And then, style maybe this could be a non-numerical category, where it could just be a 1 or a 2, and maybe hands or slapping a thigh or snapping knuckles. What do you think?
WILL: I'm going off of what I know. I guess a clap is technically described as with hands. So, I'll go with that.
BROCK: Okay, so a 4 would be a clap. A 3 might be a thigh slap [laughter]. A 2 might be a snap, and a 1 would be air clap [laughter].
WILL: Yep.
BROCK: Okay. So, you can't see this right now. But let's see, if I were to ask you what constitutes a 12 out of 12 possible, we would have loud, fast, hand-to-hand clap. I think we could all do it together, right [Clapping]? And that is how it works. What I've just done is I've created criteria. I've created gradients or qualities. And then, we've talked about what those qualities mean, and then you have an idea of what it might look like into the future. You have previewed it.
And there's a difference here in video games. A simulation is where I copy you step by step, and I demonstrate, in performance, what's been shown to me to be accurate to what's been shown to me. Most humans don't learn like that. Most of us learn through emulation, which is we see that there's an outcome that we want to achieve, and we see how it starts. But we have to improvise between the start and the end. In a book by Michael Tomasello on being human...he's an anthropologist, and he studies humans, and he studied other primates like great apes. And he talks about emulation as like the mother using a blade of grass, licking it, and putting it down a hole to collect ants so that she can eat the ants.
And oftentimes, the mother may have their back to her babies. And the babies will see the grass, and they'll see that she's putting it in her mouth, but they won't see the whole act. So, they've just [inaudible 33:29] through trial and error, see if they can do it. And this is the way an earlier paper that I wrote in studying kids playing video games was. We start with trial and error. We find a tactic that works for us. And then, in a real situation, there might be multiple tactics that we can use, and that becomes a strategy. And then, we might choose different strategies for different economic benefits.
So, for example, do I want to pay for something with pennies or a dollar, or do I want a hundred pennies to carry around? Or would I rather have a dollar in a game, right? We have to make this decision of, what is the value of it, and what is the encumbrance of it? Or if it's a shooting game, am I going to take out a road sign with a bazooka when I might need that bazooka later on? And that becomes economic decision-making.
And then, eventually, we might have what's called top site, which is, I understand that the game has these different rules, opportunities, roles, and experiences. How do I want to play? For example, Fallout 4 was a game that I really enjoyed. And I was blown away when I found out that a player had actually gone through the Final Boss and never injured another non-player character in the game. They had just done the whole thing in stealth. And I thought that is an artistic way to play. It's an expression. It's creative. It's an intentional way of moving through the game.
And I think that when we provide that type of independent, individual expression of learning, we're allowing people to have a unique identity, to express it creatively, and to connect in ways that are interesting to other people so that we can learn from each other. And I think that's what games can do.
And one of the hurdles that I faced back in 2004 was I was creating a finite game, where what I had coded in decision trees, in dialogue, in video interactions, once that was there, that was done. Where we're at now is, I can create an infinite game because I've learned how to leverage machine learning in order to generate lots of different contexts using the type of criteria and qualities that I described to you in Clapping Academy, that allow me to evaluate many different variations of a situation, but with the same level of expectation for professionalism, knowledge and expertise, communication, compassion, curiosity. You know, these are part of the eight elements of what is valued in the nursing profession.
And when we have those rubrics, when we have that matrix, we begin to move into a new paradigm in teaching and learning because there's a much greater latitude and variety of how we get up the mountain. And that's one of the things that I learned as a teacher is that every kid comes in differently, but they're just as good. And every kid has a set of gifts that we can have them, you know, celebrate in service to warming up cold spots.
And I think that sometimes kids are put into situations, and so are adults, where they're told to overcome this cold spot without actually leveraging the things that they're good at. And the problem with that is, in learning sciences, it's a transfer problem, which is if I learn it to pass the test, am I ever going to apply it in life, or is it just going to be something that I forget right away? And my follow-ups on doing classroom and learning research is that it is usually that. They learned it for the test. They forgot it, and they don't even remember ever having learned it.
And the greatest gift that I got, having been a teacher, was when my wife and I would, I don't know, we'd be somewhere like the grocery store or walking out of a Target, and a couple of young people would come up and say, "Yo, Mr. Dubbs," And I'd be like, "Hey [laughs]!" And they're like, "Hey, man, you remember when we did that video game class and all that?" And I was like, "Yeah, you were so good at that." Or "Remember when we made those boats, and we raced them across the pool?" "Yeah, yeah, that was a lot of fun, wasn't it?" And I think part of it was that I was having as much fun doing the classes and the lessons as they were doing it.
And it's kind of like a stealth learning, where they are getting the experience to populate these abstract concepts, which are usually tested on these standardized choice tests. And it's the same problem that we have with scaling a technology. Oftentimes, the way that we scale is based on conformity and limited variation when we're really scaling the wrong things. And I think it's good to be able to scale a lot of the tasks but provide great variety in the way that we can be human-supported around them.
So, sure, let's scale sales and operations, but let's also make sure that we can scope out variation in how we do sales, and how we do customer service, and how we do present our product experience. So, how do we begin to personalize in scope and still be able to scale? And I think that's what I'm getting at as far as how I'm approaching CareTrainer, and how I'm approaching a lot of the knowledge translation that we're doing for startups, and consulting with larger and medium-sized businesses on how they can use AI.
CHAD: That's awesome. Bringing it back to CareTrainer, what are some of the hurdles or cold spots that are in front of you and the business? What are the next steps and challenges in front of you?
BROCK: I think the big thing is that I spend a good two to three [laughs] hours a day reading about the advances in the tech, you know, staying ahead of the knowledge translation and the possible applications. I mean, it's hard to actually find time to do the work because the technology is moving so fast. And, like I said, we were starting to build MVP 2, and we realized, you know what, this is going to be done for us in a little while. You know, it'd be cool if we can do this bespoke. But why not buy the thing that's already there rather than creating it from scratch, unless we're going to do something really different?
I think that the biggest hurdle is helping people to think differently. And with the elder care crisis and the care crisis, I think that we really have to help people think differently about the things that we've done. I think regulation is really important, especially when it comes to health care, treatment, prescription safety. I think, though, that there are a lot of ways that we can help people to understand those regulations rather than put them in a seat in front of a monitor.
CHAD: I think people respond to, you know, when there's a crisis, different people respond in different ways. And it's a natural tendency to not want to rock the boat, not introduce new things because that's scary. And adding more, you know, something that is scary to a difficult situation already is hard for some people. Whereas other people react to a crisis realizing that we got into the crisis for a reason. And the old ways of doing things might not necessarily be the thing to get us out of it.
BROCK: Yeah, I totally agree. When I run into that, the first thought that comes to my head is, when did you stop learning [laughs]? When did you stop seeking learning? Because, for me, if I were to ever stop learning, I'd realize that I'd started dying. And that's what I mean by the spark, is, no matter what your age, as long as you're engaged in seeking out learning opportunities, life is exciting. It's an adventure. You're discovering new frontiers, and, you know, that's the spark. I think when people become complacent, and they say, "Well, this is the way we've always done it," okay, has that always served us well?
And there are a lot of cultural issues that go with this. So, for example, there are cultural expectations about the way kids learn in class. Like, kids who come from blue-collar families might say, "Hey, you know what? My kid is going to be doing drywall, or he's going to be working fixing cars, or he's going to be in construction, or why does he need to do this? Or why does she need to do that? And, as a parent, I don't even understand the homework." And then, there are the middle-class folks who say, "You know what? I'm given these things. They need to be correct, accurate, and easy to read. And that's my job. And I don't see this in my kids' curriculum."
And then, there are the creatives who say, "Hey, you know, this has nothing to do with where my kid is going. My kids are creative. They're going to have ambiguous problems that they have to come up with creative solutions for." Then you get to the executive class where, like, these elite private schools, where they say, "My kid is going to be a leader in the industry, and what they should be doing is leading groups of people through an activity in order to accomplish a goal."
And those are four different pedagogical approaches to learning.
So, I'm wondering, what is it that we expect from our caregivers? And I've got kind of a crazy story from that, where this young woman, [SP] Gemma, who was a middle school student, I gave her the option, along with my other kids, to either take a standardized test on Greek myths, or they could write their own myth. And she wrote this myth about a mortal who fell in love with a young goddess. Whenever they would wrap and embrace and kiss, a flame would occur.
One day the mother found out and says, "Oh, you've fallen in love with a mortal. Well, here you shall stay. This shall be your penance." And she wrapped her in this thread, this rope, and dipped them in wax so they would be there forever. But then the flame jumped to the top, and that is how candles were created.
And I read that, and I was...and this is, like, you know, 30 years ago, and I still have this at the top of my head. And I was like, "Gemma, that was amazing. Are you going to go to college?" And she says, "No." "No? Really? What are you going to do?" "I want to be a hairstylist." And, in my mind, my teacher mind is like, oh no, no, no, no. You [laughs] need to go to college. But then I thought about it. I thought, why wouldn't I want a smart, skilled, creative person cutting my hair? And, you know, people who cut hair make really good money [laughter].
And the whole idea is, are we actually, you know, empowering people to become their best selves and be able to explore those things? Or are we, you know, scaring them out of their futures with, you know, fear? Those are the big hurdles, which is, I'm afraid of the future. And the promise is, well, it's going to be different. But I can't assure you that it's not going to come without problems that we're going to have to figure out how to solve. And there are some who don't want the problems. They just want how it's always been.
And I think that's the biggest hurdle we face is innovation and convincing people that trying something new it may not be perfect, but it's a step in the right direction. And I think Hans Rosling in Factfulness said it very well. He said, "Things are better than they were before, but they're not great." Can we go from good to great? Sure. And what do we need to do? But we always are getting better, as long as we're continuing to adapt and create and be playful and look at different ways of doing things because now people are different, but just as good.
CHAD: Brock, I really appreciate you stopping by and bringing your creativity, and energy, and playfulness to this difficult problem of caregiving. I'm excited for what the future holds for not only CareTrainer but the impact that you're going to have on the world. I really appreciate it.
BROCK: Well, thank you for having me and letting me tell these stories, and, also, thanks for participating in Clapping Academy [laughter].
WILL: It was great.
CHAD: If folks want to get in touch with you or follow along with you, or if they work in a healthcare organization where they think CareTrainer might be right for them, where are all the places that they can do that?
BROCK: You can reach me at brock@caretrainer.ai. They can express interest on our website at caretrainer.ai. They can reach me at my personal website, brockdubbels.com, or connect with me on LinkedIn, because, you know, life is too short not to have friends. So, let's be friends [laughs].
CHAD: You can subscribe to the show and find notes for this entire episode along with a complete transcript at giantrobots.fm.
WILL: If you have questions or comments, email us at hosts@giantrobots.fm.
CHAD: You can find me on Mastodon at cpytel@thoughtbot.social.
WILL: And you can find me on Twitter @will23larry.
This podcast is brought to you by thoughtbot and produced and edited by Mandy Moore.
CHAD: Thank you again, Brock. And thank you all for listening. See you next time.
AD:
Did you know thoughtbot has a referral program? If you introduce us to someone looking for a design or development partner, we will compensate you if they decide to work with us.
More info on our website at: tbot.io/referral. Or you can email us at: referrals@thoughtbot.com with any questions.
Support Giant Robots Smashing Into Other Giant Robots