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Welcome to ABA on Tap, where our goal is to find the best recipe to brew the smoothest, coldest, and best tasting ABA around.
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I'm Dan Lowry with Mike Rubio, and join us on our journey as we look back into the ingredients to form the best concoction of ABA on tap.
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In this podcast, we will talk about the history of the ABA brew, how much to consume to achieve the optimum buzz while not getting too drunk, and the recommended pairings to bring to the table.
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So without further ado, sit back, relax, and always analyze responsibly.
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All
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right, all right.
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This is your ever-grateful co-host, Mike Rubio.
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Thank you for coming back.
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This is part two with Mr.
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Adam Ventura of Intraverbal AI.
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Enjoy.
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Yeah, that's tough.
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And I feel like you had two questions there.
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So I'll start with the first one.
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So I'm assuming when you say KPM, key performance metrics?
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Correct, yeah.
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And like what to evaluate people on and say the program's successful.
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Because my experience with working with private equity was always just about like efficiency base.
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Yeah.
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And so that just becomes a scorecard, right?
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And I think it should be a balanced scorecard.
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And this was one of the key lessons that I learned from work doing OBM consulting for a few years is the importance of employee and organizational scorecards being balanced.
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You know, so yes, you can't, do you need profit measures on your scorecard?
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Yeah, you do.
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If you're not making a profit, you can't be in business.
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And people need to be able to say that out loud without getting pilloried for identifying the obvious.
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However, when you create these scorecards, that can't be the only metric on there.
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So yes, net revenue is important, but you also need to have...
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measures of social validity on there are the families happy more or less maybe that's the wrong word but are the families satisfied with the service that you are producing then you get into and I think Mike you just brought it up like how do you define quality service and I think there's some folks in our field that don't behave like honest brokers when we have those discussions are there some fair points that yeah it's really hard to measure because for example you can't or you're going to have trouble using a percentage measure because some behaviors are uh much more deleterious to the health and wellness of the client than others so you can say oh i reduced um some i i reduced stereotypy by 80 okay that's great but if you have another um topography like elopement where the client is running out into the middle of the street, I reduce that by 80%.
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That's good.
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But if he's still running out into the middle of a busy intersection, 20% of the time, that's still a life threatening behavior.
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So coming up with a, and I'm working in technology now, so I'll call it an algorithm.
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Coming up with an algorithm for these insurance companies to use is a big challenge.
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However, I don't think it's an insurmountable challenge.
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I think it's something that if you get some of the smartest behavior analysts in our field together, I think they could figure out.
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And are there gonna be some edge cases?
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Yeah, there is.
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But I think if we don't wanna do harm to our science, and that's really kind of my professional mission is disseminating and moving forward the science, I think we need to be very careful with this because if people are doing bad ABA therapy out there, it's going to reflect poorly on our science and then we're gonna start regressing scientifically and as a field more broadly.
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That makes a lot of sense.
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My last question about your business and then maybe we can transition or I can pass it to you, Mike.
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I'm sorry, I've been asking a lot of questions here.
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So you created this business.
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had these conversations, expanded to 300 employees, and then you did sell, you said, to private equity.
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So can you talk about maybe your thought process with that, your thoughts on them being able to maintain your vision and mission, or even if that was a concern, and maybe if they were able to be successful with that or not?
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Yeah.
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I didn't really speak publicly until recently on the Beyond the Science podcast about why I sold my company, but I had a...
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Family tragedy at the time.
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I had no interest in selling my company.
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I wanted to continue to grow it.
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It was my life's purpose.
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And I had a family tragedy.
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Somebody in my family passed away unexpectedly.
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No, no, no.
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It was seven years ago, eight years ago, whatever it was.
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And I realized that I didn't have...
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I didn't have a great relationship with my family at all.
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There were some people in my immediate family that I hadn't spoken to in a decade.
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And I realigned my priorities.
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I really felt like my legacy was my business.
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And when that happened, I made the decision that I needed to have a relationship with my family.
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I mean, I hadn't...
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I hadn't spoken to my dad in 12 years.
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I hadn't spoken to my sisters in like nine years.
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I hadn't spoken to my mom in, I don't know, five, six, seven years, something like that.
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And while the tragedy was tragic, it opened up an opportunity for me to be successful personally.
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And all I could think about, all that mattered to me was professional success.
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I had no relationship success either.
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I was a mess professionally.
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personally dating.
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I was a hot mess dating.
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I had no relationship with my family.
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And I just made a transition at that point when that tragedy struck to grow up personally.
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And I really made that transition and discovered that my immortality project, my legacy wasn't my business.
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It was my family.
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It was having kids.
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And it was getting married.
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It was having a stable relationship.
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And when I made that transition, I realized that I couldn't do that myself.
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I needed help.
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And I tried to transition somebody into the CEO role so that I could address what had just happened.
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Because when you have a family tragedy, a lot of people need help.
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And I needed to be there more for my family.
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Whenever something terrible happens and somebody has to step down from leadership role in any industry, they're like, oh, I have to spend more time with my family.
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I literally had to spend more time with my family.
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And I put somebody else in the role.
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And as soon as I did that, we got a Medicaid audit in Florida.
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And it was a mess.
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And as it turned out, Medicaid decided, Florida Medicaid at that time decided not to pay us for about five months.
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And they owed us seven figures of money.
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And I didn't have that money in the couch cushions in my home.
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So luckily, we managed to send everything over that they asked for, got through it.
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Funny enough, I always like telling this story.
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After we sold the company, Private Equity went to Florida Medicaid and said, listen, we're buying Adam's company.
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And they told them at the time, they're like, oh, yeah, we audited his company and he's one of our best providers.
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And I wanted to strangle them because it would have been nice if they would have realized that earlier.
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But that's OK.
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So I the company that bought us, we were their platform company and the first company that they bought and everything that they promised that they would do, they did.
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And.
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They grew to be a very big company and then ended up selling again after that.
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I understand how the business works, but I hold no ill will towards the notion of private equity.
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For as many bad private equity stories that we hear, I know personally of 20, 25 stories that a small ABA provider that doesn't know how to run a business that was this close to going under, private equity swooped in and saved them from their business going under.
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So I don't have that animosity towards private equity.
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Are there some bad behaving actors in private equity?
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Yeah.
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Are there some private equity platforms that shouldn't own an ABA business?
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Sure.
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But is there something inherently wrong with that business model?
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No, I don't think so.
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Dan, to your point earlier, they need to refine their scorecards, I think some of them, to include clinical quality, to include some of those measures of social validity.
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And that's where if they get behavior analysts to work with them, like I know some of private equity companies do right now, then things get better.
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And I guess that's my overall thoughts on private equity and their involvement in ADA.
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Yeah.
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Well, thank you for sharing that story.
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That was very insightful, and I appreciate that.
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I was going to
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say the same thing.
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Thanks for sharing the personal side and then getting into the private equity piece, and we're very glad for your experience there, and very glad to hear somebody share a positive experience on private equity, because those aren't the stories you hear, right?
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The stories you hear are all the negatives.
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What is it you think really goes wrong in those moments?
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Is it Is it a bad private equity actor usually?
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Is it people just not knowing how to deal with private equity when they're going through these interactions?
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What would you tell somebody out there who is maybe getting an offer from private equity or might need help to stay alive?
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What would you caution them about?
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What would be your best advice?
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There's a lot of...
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So I'll answer the last question first.
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There's a lot of consultants out there that will help walk somebody through a sale of their business.
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Don't feel the other thing I would say to those folks is don't feel bad about wanting to sell your business.
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And, you know, I thought I was going to get a lot of pushback from people because I sold my business in 2018.
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And that was really in the beginning of private equity and how that stuff happened.
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And I actually made the decision to sell my business in late 2017.
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My family tragedy happened in October of 2017.
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And I made the decision really within a month and a half, two months, something like that, that I was going to have to step down.
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And I really expected a lot of pushback.
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I really did.
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I thought people were going to vilify me and I was going to be pilloried from a public standpoint in our field.
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And there was a lot of people, a lot of colleagues that I had that worked in different parts of our field that when I told them, their response was, congratulations, good for you.
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And I couldn't believe I heard it, you know, and I felt like it was kind of reassuring.
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They're like, look, you know, I guess because this was people, these were people that knew me.
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I lived and breathed my company.
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It was the only thing that mattered to me.
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And That turned out to be part of the problem with my personal life is that's all that mattered to me.
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But they knew that for the few people that knew what was going on in my life, they understood why I was doing it.
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So I would say the first thing that I would say to those folks is don't feel bad about doing it.
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Second thing I would say is find a consultant that can explain everything to you, how everything works.
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I think that that's really helpful.
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I would say part of the reason why this goes wrong so many of these times is because a lot of these private equity companies bring a medical model into ABA.
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I don't agree with the idea that we should be making ABA the medical model that insurance companies are used to dealing with.
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I think there's a lot of problems with that.
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And I think private equity companies just swoop in and say, this is just like the...
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the string of dentist locations that we purchased last year and then sold for a profit.
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We can run it the same way as we do You know, a dentist's office or an orthopedist's office or something like that.
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And it just doesn't work that way.
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We have a very unique field with a tiered service delivery model that doesn't exist in other fields.
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So I think the smartest private equity companies are the ones that hire behavior analysts to help them make better decisions.
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I think if they don't, that's where the problems come in.
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I think most behavior analysts, especially seasoned behavior analysts that have been in the field for a while, that care about the clients, that care about the science will sit down with the private equity companies and say, yes, you need to make a profit.
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To make a profit, you need to be more efficient.
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Yes, agreed on both of those, but you also need to provide a good service, and here's what I mean by a good service, and here are the outcomes that you need to look for.
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And if those behavior analysts can communicate that appropriately and the private equity companies are willing to listen, then you get good outcomes.
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If those two things don't happen, you get bad outcomes.
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So let me ask you this, and please correct me if I'm wrong, because like I said, I'm not too well-versed in private equity, but from some things that I've talked about with people, they've said that that does make sense, but since private equity a lot of times isn't there for the long run...
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by the time that they're going to have to pay the piper for the lack of clinical quality, they will have already sold and it won't be their problem anymore.
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It'll be on to somebody else.
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So if they can just make it more efficient, regardless of the clinical quality, get the metrics up and sell, that'll be on somebody else's doorstep.
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I don't know how often that happens now.
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At least I think that they're becoming, these private equity companies have become They've been doing it now for almost a decade.
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So they're starting to figure things out, number one.
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Number two, if you sell a company, there's a whole bunch of provisions.
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And I learned about this when I was selling my company.
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There's a whole bunch of provisions in those agreements that say that if things fall apart three months in, you're in a lot of trouble as a seller.
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So I think...
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Private equity companies are becoming wise to this and realizing that it's not just a three-year turnaround anymore, that it's a three- to five-year turnaround, maybe five- to seven-year turnaround, and that it's bad business to run a bad business.
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So if you're running a business that all you care about is billable hours, and then all of a sudden audits show up, clients get hurt, social media plays a big role in this too.
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If you run a crappy company...
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Behavior analysts are going to make it well known in those Facebook groups and on LinkedIn and things like that.
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And you become, your brand becomes known for that.
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And anybody that's looking to acquire you, a bigger private equity company or whomever it is, they're going to do their due diligence.
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They're going to not just look at your books.
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They're going to look at your brand.
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They're going to look at how people have rated you on Glassdoor.
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So I don't think this is 2018, 2019, 2020 anymore.
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This is 2025.
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And those people that run those billion dollar private equity funds, they didn't become billionaires by making stupid decisions.
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And I think that they look back and say, you know what?
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We saw this company or that company collapse.
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Why did that happen?
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In a lot of cases, it's because they didn't care about clinical quality or treated their employees like crap.
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Thank you for clarifying.
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I appreciate that.
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Like I said, I'm pretty ignorant to the whole thing, so I'm just saying what I hear, and thank you for clarifying that.
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That was very insightful.
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Yeah, very good information.
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So you sold, and I'm going to skip over a few things here just in the interest of time.
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But now you're delving into artificial intelligence and how that's going to fit into the future of ABA, whether that's autism treatment or whatever that may present.
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And I think it behooves us to diversify more and more in how we're actually employing behavior analysis to help people.
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Talk to us a little bit about what you're doing now, what got you interested in that over time, and then anything else you want to share and we'll help you unpack it and discuss it.
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Yes, that was
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great.
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Thank you for the question.
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Actually, one of the businesses that I moved into after I sold my ABA therapy company was opening a practice management software company.
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I made a lot of mistakes with that company.
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I learned what I like doing and what I don't like doing.
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When we were talking maybe about 30 or 40 minutes ago, I talked about how much I hate ABA admin.
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One of the things you have to do when you start an ABA practice management software company is you have to deal with a lot of admin and you have to really become a medical billing expert.
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It's interesting because I have a software team that I've been working with for 10 years.
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Something that our lead developer explained to me a few years ago and he's like, Adam, medical billing software is its own specialty because it's so complicated.
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You have to know so much about that industry and you have to merge two fields together, software and insurance companies.
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It's very difficult.
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Um, so I realized that, um, I didn't want to do practice management.
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It just wasn't something that I wanted to do, but I liked technology a lot, a lot.
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And when AI really started coming on the scene, uh, really even before, uh, chat GPT, everybody knows chat GPT and it kind of burst onto the scene a few years ago or a couple of years ago.
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Um, I started talking a lot to my development team about.
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where we can move forward and the answer that they always gave me was ai and i thought about what my professional mission is and my profession professional mission is to move the science and practice of behavior analysis forward that's what matters to me we were talking about the science earlier it really matters to me i taught at university for 12 years i enjoy teaching the science i enjoy disseminating it and when some of those large language models really burst onto the scene in 2022, we started having those discussions about how I can merge my professional mission with this new emerging technology.
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And where I kind of landed as our initial product offering was I wanted to make the practice of behavior analysis more evidence-based.
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So what do I mean by that?
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When we go into a home, a clinic, a group home, a school to work with a particular kiddo, there's almost exactly zero behavior analysts that show up with a binder full of journal articles.
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It's just not going to happen.
00:21:02.772 --> 00:21:06.138
And even if you did, it's not practical.
00:21:06.700 --> 00:21:11.567
If you've got a kiddo that's engaging in that spaghetti tantrum thing, you can't...
00:21:12.897 --> 00:21:26.315
response block that with one hand and page three in the idea that, because there's tens of thousands of journal articles out there, you know, that you're going to find the one and the intervention that's there, it's just not going to happen.
00:21:26.815 --> 00:21:36.748
So one of the things that we wanted to do was bring, with this technology, bring the science into the practice.
00:21:37.548 --> 00:21:53.733
And something that we started doing was setting up deals with publishing houses to connect these AI systems to that information and making it available in the moment.
00:21:54.094 --> 00:22:02.307
So you can literally pick up one of these mobile devices and say, my client's engaging in this, what should I do?
00:22:02.528 --> 00:22:14.278
Now, I want to make this very clear that, especially if you're an RBT listening to this, You need to do what your behavior analyst tells you to do, not what an AI system tells you to do.
00:22:14.298 --> 00:22:35.888
However, if you're a BCBA and you're looking for ideas on how to deal with a unique form of SIB or you want to set up toilet training in a unique setting and you need some ideas, you need a sounding board to bounce ideas off of, these types of tools are the way to do it.
00:22:36.834 --> 00:22:49.346
We set up our company called Introverbal AI, and we feel like the name of the company is appropriate because you plug a whole bunch of mans into our system.
00:22:49.386 --> 00:22:54.271
You ask questions, you make requests, and our system gives answers back.
00:22:54.452 --> 00:22:55.733
And that's why we came up with the
00:22:55.753 --> 00:22:56.394
name.
00:22:56.414 --> 00:22:56.755
I love it.
00:22:56.775 --> 00:22:57.496
That's fantastic.
00:22:58.757 --> 00:22:59.057
Thank you.
00:22:59.096 --> 00:22:59.397
Thank you.
00:22:59.637 --> 00:23:03.201
And with our system, our system...
00:23:03.521 --> 00:23:14.239
allows you to search through tens of thousands of journal articles to find the answers to not just clinical questions, but academic questions.
00:23:14.960 --> 00:23:19.105
And we took this base model and we started building on top of it.
00:23:19.807 --> 00:23:27.839
And we created a goals product that we have that helps you create goals for your clients.
00:23:27.900 --> 00:23:35.278
And then we ended up adding like 10,000 client goals or 10,000 clients worth of goals.
00:23:35.358 --> 00:23:40.767
It turned into like a million actual individual goals that it kind of pulls from.
00:23:41.347 --> 00:23:49.680
We developed a functional behavior assessment product that touches on not only those goals, but also the literature as well.
00:23:50.280 --> 00:24:35.942
So not to get too deep into the products, our system was really meant to improve the science and practice of behavior analysis and we tried to do that with um starting off with the foundation of the literature you know what were we all taught what was drilled into our brains in graduate school do evidence-based practice always reference the literature you know if you were in a good graduate program you were reading eight to ten journal articles a week you know and you really had to dive in do deep dives into these articles to make sure you understood why things were done the way that they were done and recognizing good research from bad research.
00:24:36.943 --> 00:24:57.585
And that was a big impetus as to what we wanted to do and I'll never forget the first time our lead developer came to me and he said, okay, we connected the two here and then I just started asking questions and it gave me answers instantaneously and it gave the in-text citation and then it gave a full reference list And it did it in like four seconds.
00:24:57.805 --> 00:25:03.573
And I was like, holy crap, you know, like just imagine the difference that we can make with all of this.
00:25:03.653 --> 00:25:18.512
And I think that was my introduction to AI and why I kind of fell in love with what we can do with this technology and how it can augment, not replace our practice.
00:25:19.329 --> 00:25:19.790
Sold.
00:25:20.070 --> 00:25:24.958
I was going to say, I can vibe with that, but you are speaking this guy's language 100%.
00:25:25.278 --> 00:25:45.164
So just, I'm already having visions of, you know, in all fairness, I can be very, I've been very critical on the show and in the past professionally about, you know, you've got these staff meetings and you end up taking time away from clients to sit down for two hours and talk about billable matters and, you know, efficiency.
00:25:45.224 --> 00:26:19.449
And you're not, training anybody you're not professionally developing anybody truly in the bread and butter of the the service delivery and and that knowledge so the idea that i mean i think a lot of that why that happens is it takes time to develop those training materials so as a bcba as a manager or whatever title you have if you're in a position of inciting that professional development it can be very cumbersome to go and find those articles that can be very cumbersome to read through those articles and what you're presenting here is going to really make that a lot easier much more accessible and that's super exciting
00:26:19.509 --> 00:26:42.295
you mentioned read through the articles when I was doing BCBA study groups because we would do those a lot for people in their coursework studying to get the BCBA you put a journal article in front of them and it might have been might as well have been Mandarin Chinese like people did not want to read it didn't understand what it said and I mean to be fair like the way that they're set up isn't you know it's very lab heavy it's not great to read it's not like a Exciting.
00:26:42.335 --> 00:26:43.537
Well, exciting isn't the best word.
00:26:43.576 --> 00:26:44.818
It's not an easy read a lot
00:26:44.838 --> 00:26:45.078
of times.
00:26:45.098 --> 00:26:45.740
No, no, no, it's not.
00:26:45.779 --> 00:26:47.722
It's not easy to translate or to apply.
00:26:47.823 --> 00:26:59.820
So you end up coming away with knowledge that you may not fully understand, that you have to process, that you have to discuss with other people, that you might need a language model to do some translation for you, to do some summary for you.
00:26:59.840 --> 00:27:01.002
That sounds fantastic.
00:27:01.683 --> 00:27:03.987
Tell us a little bit about some of the other features that you're looking at.
00:27:04.007 --> 00:27:06.991
So I would imagine that's one feature that's part of your system.
00:27:07.031 --> 00:27:08.354
What else are you developing?
00:27:09.569 --> 00:27:10.290
Yeah, absolutely.
00:27:10.330 --> 00:27:12.394
Thanks for asking about it.
00:27:12.776 --> 00:27:14.278
Yeah, that's really a great system.
00:27:14.479 --> 00:27:24.336
So some of the other products, our goal, our clinical goal right now is to go through the entire life cycle of the client.
00:27:24.635 --> 00:27:27.361
So from intake to discharge.
00:27:28.021 --> 00:27:34.232
So we're going to be releasing our assessment product coming up soon.
00:27:34.786 --> 00:27:36.228
And I'll use that as an example.
00:27:36.587 --> 00:27:37.829
We're super excited about that.
00:27:37.849 --> 00:27:42.855
So our assessment product allows people to upload all of that.
00:27:43.497 --> 00:27:48.042
You know, like when you go to do an assessment, you get a ton of information, let's say, from your office.
00:27:48.083 --> 00:27:51.748
Let's say you're a VCBA and you get a ton of information from your office.
00:27:51.768 --> 00:27:53.230
You get a diagnostic report.
00:27:53.671 --> 00:27:58.717
You get somebody else's behavior plan or re-auth or assessment or something like that.
00:27:59.117 --> 00:28:01.520
And you're expected to read through 40 pages of
00:28:01.601 --> 00:28:02.382
documents.
00:28:02.402 --> 00:28:02.461
Yep.
00:28:02.561 --> 00:28:05.145
before you go to see the client and good luck with that.
00:28:05.326 --> 00:28:07.289
Nobody's gonna be able to read through all of that.
00:28:08.030 --> 00:28:17.307
So the very first step in our assessment cycle is somebody at the organization uploads that documentation into our system.
00:28:17.346 --> 00:28:36.127
Our system processes all of that information provides a summary, and then suggested questions for the BCBA to ask during the interview portion of the assessment, and emails it to them and says, here, for this particular kiddo, here's a summary.
00:28:36.469 --> 00:28:42.037
This is everything that you're going to need to know, and here's some questions that we recommend asking.
00:28:42.698 --> 00:28:46.063
So when the BCBAs come in, they're armed with that information.
00:28:46.784 --> 00:28:50.109
Now, once they get in, the next step, and we're...
00:28:50.978 --> 00:28:55.763
Part of our goal, we have a two-pronged goal at Intraverbal AI.
00:28:56.384 --> 00:29:00.088
We want to solve a practical problem and do good science.
00:29:00.670 --> 00:29:07.678
Those are our two main values or pillars or aims at our organization.
00:29:08.439 --> 00:29:09.980
So we want to solve a practical problem.
00:29:10.000 --> 00:29:24.242
And another practical problem that you have when you're doing an assessment is you have a pen and you have your paper and you're furiously taking notes, trying to listen, trying to ask questions, and that's a huge challenge.
00:29:24.843 --> 00:29:36.298
So what we set up is practitioners can do this, whether they're doing telehealth or they're in-person, they can grab their mobile device or they can do it on their desktop.
00:29:36.858 --> 00:30:11.352
Our system transcribes the entire interaction between the practitioners and the families and it takes all that information in, and it allows them to press a button, and our system reviews the interview up to that point, and then checks the journal articles, the literature, and says, based on these two buckets of information, here are some questions that you should ask before you leave.
00:30:12.113 --> 00:30:13.194
So that happens to all of us.
00:30:13.214 --> 00:30:26.761
When you do an assessment maybe, You finish the assessment, you get in the car, you drive down the street and then you're like, crap, I forgot to ask about toilet training or I forgot to ask what medication the kiddos are on or something like that.
00:30:27.403 --> 00:30:37.054
Our system handles that for you and provides questions and says, hey, you forgot to ask about medications or hey, you forgot to ask about this.
00:30:38.096 --> 00:30:43.582
Once that's done, that's the indirect portion of the assessment.
00:30:43.682 --> 00:30:44.803
the assessment.
00:30:44.844 --> 00:30:56.057
So I was always taught that a good FBA involves three distinct sections, an indirect assessment, a direct assessment, and then a functional analysis if needed.
00:30:56.898 --> 00:30:59.001
So that takes care of the indirect assessment.
00:30:59.423 --> 00:31:14.277
Then our system does the direct assessment piece, where it records all of the data and observations that you take during the direct observation portion, allows you to upload data sheets into it.
00:31:15.238 --> 00:31:36.397
And then when you get to the last piece, which is the report, you go in, you sit down and you press a button and our system takes all of that information, the initial intake, the indirect assessment transcription, the direct assessment piece, puts it all together into a insurance ready report.
00:31:37.018 --> 00:31:49.397
And the way that we set this up is we hired BCBA peer reviewers that work at the insurance companies to evaluate the reports that we were creating.
00:31:49.919 --> 00:31:57.425
And we created a scorecard for them and they told us approve, not approve, approve, not approve, and here's why.
00:31:57.465 --> 00:32:14.942
And then we made the changes over the course of a few different iterations so that when our system generates the report, all that really needs to be done at that point is the behavior analyst needs to put their signature on it.
00:32:15.063 --> 00:32:19.728
And I don't mean just their actual signature, but make the report their own.
00:32:20.169 --> 00:32:24.913
And that's where this is really augmented intelligence, not artificial.
00:32:26.556 --> 00:32:29.719
We joke around that it's insurance ready, but it's really not.
00:32:30.099 --> 00:32:38.846
It requires that last step for the behavior analyst to come in and say, well, This isn't really in my tone of voice.
00:32:38.865 --> 00:32:43.512
I don't think maybe we should have this recommended intervention.
00:32:43.532 --> 00:32:52.965
I really think that the function of this behavior, the hypothesized function of this behavior is really this, and they come in and do that piece.
00:32:53.125 --> 00:32:57.231
But our tool solves a huge problem.
00:32:57.291 --> 00:33:03.480
It literally saves eight to 10 hours of report writing, and it does good behavior analysis.
00:33:04.226 --> 00:33:09.330
Sorry if I dragged on there, but I really wanted to capture the essence of what we're trying to do.
00:33:10.751 --> 00:33:16.657
So does your report, does that report also come up with hypothesized goals as well?
00:33:18.179 --> 00:33:19.079
Oh, yeah, absolutely.
00:33:19.160 --> 00:33:24.806
So what we've really created in Intraverbal AI is an ecosystem.
00:33:24.965 --> 00:33:31.652
And something else that I think is very important to share is all of these products, I do not...
00:33:34.018 --> 00:33:37.061
I don't get 100% of the profit of these.
00:33:38.123 --> 00:33:45.692
And the reason that I'm bringing that up is because I've set up partnerships with a whole bunch of behavior analysts.
00:33:46.233 --> 00:33:52.442
And what Introverbal AI is, it's really an AI ecosystem for behavior analysis.
00:33:53.162 --> 00:34:01.752
And what we've done is we've partnered with a whole bunch of subject matter experts to put out different products and tools.
00:34:02.498 --> 00:34:17.344
We've got, and I know it's a long answer to your simple question there about the goals, but we've partnered with a subject matter expert for assessments, somebody for supervision, somebody for BACB test prep, which is going to be coming out at the end of the summer.
00:34:18.045 --> 00:34:23.514
And we've partnered with somebody for goals to generate goals within our system.
00:34:23.956 --> 00:34:27.141
So we've got a whole tool that just helps to generate goals.
00:34:27.585 --> 00:34:42.652
And that connects with our assessment system so that when the assessment report is generated, it generates suggested goals based on the assessment tools that you used during the assessment cycle.
00:34:42.753 --> 00:34:49.786
So whether you used a Vineland or a VB Map or an ABLES or something like that, it takes all of that into consideration.
00:34:50.242 --> 00:34:56.112
and the subject matter experts that we've worked with to create that report.
00:34:56.172 --> 00:35:06.871
And you can see it, we very proudly put that on our About Us section of our website, the different people that we partnered with, and we've got a whole bunch more partners that we're gonna be announcing.
00:35:07.172 --> 00:35:22.452
And I do wanna say this because I feel like it's very important to the mission and the values of our company is, What we wanted to create is a collective consciousness of information and behavior analysis.
00:35:23.233 --> 00:35:39.599
And we wanted to not just get all of the information from so many smart people that wrote those journal articles and did that research, but we also wanted to get the practitioners and the peer reviewers and set up all of these partnerships.
00:35:40.139 --> 00:35:43.567
So I am not the sole owner of Intraverbal AI.
00:35:44.027 --> 00:35:59.085
We are a community of behavior analysts that all have an ownership stake in the products that we're putting out here so that we can create this digital community of experts and expertise.
00:35:59.646 --> 00:35:59.925
Does that make
00:36:00.487 --> 00:36:00.586
sense?
00:36:00.606 --> 00:36:01.007
A lot of sense.
00:36:01.027 --> 00:36:01.527
That's exciting.
00:36:01.668 --> 00:36:02.668
That's very exciting.
00:36:02.949 --> 00:36:06.211
And thank you for taking the time to explain all the elements there.
00:36:06.231 --> 00:36:07.253
I think it's very important.
00:36:07.873 --> 00:36:18.141
Starting with the idea, so I think that for me, a phrase that gets kicked around, especially in the old days when we did paper and pencil, it was very easy to create templates.
00:36:18.802 --> 00:36:34.878
And then before, we even talk about it at our company now, it's one of those words, I hear template and I'm like, oh, you're trying to save yourself And you're running the risk of being lazy and just replicating treatment plans across clients because it's similar enough.
00:36:35.478 --> 00:36:38.222
And obviously, there's a lot of problems to be had there.
00:36:38.282 --> 00:36:48.353
So when you first hear about sort of artificial intelligence, if you will, generating these things immediately, especially somebody of my age might be like, well, wait a minute, we're going to run into that problem.
00:36:48.693 --> 00:36:53.458
But the way you describe it clearly avoids that in terms of generating a wealth of ideas.
00:36:53.498 --> 00:36:54.960
And then I love the way you put the onus.
00:36:54.960 --> 00:36:55.840
on the professional.
00:36:55.880 --> 00:36:56.822
Make that your own.
00:36:57.342 --> 00:36:59.003
You're going to get a big lump of clay.
00:36:59.043 --> 00:37:11.193
You better sculpt that down to make sure it reflects your client or your purpose because otherwise then you do run that risk of going back to just a template, a very generalized cookie cutter template.
00:37:11.835 --> 00:37:17.780
The way you've described it though really presents a lot of safeguards and you're promoting people make this information their own.
00:37:17.860 --> 00:37:24.925
So yeah, let the computer pump out a bunch of possibilities and then you apply it to your particular client.
00:37:25.378 --> 00:37:26.139
Yeah, absolutely.
00:37:26.219 --> 00:37:31.664
It's interesting because when I got into the field, I think in 2004, 2005, you know what we used to call treatment plans?
00:37:31.684 --> 00:37:36.909
They were called IVPs, individualized behavior
00:37:36.929 --> 00:37:37.329
plans.
00:37:37.389 --> 00:37:38.070
And
00:37:38.269 --> 00:37:43.956
somehow along the way, the I got removed to rather just behavior plans or treatment plans.
00:37:44.016 --> 00:37:48.500
And I don't know what happened to the I, but they should be individualized treatment plans.
00:37:48.559 --> 00:37:59.811
And the great part about this new technology is so much of it is based on and there's so many factors in the technology that so much of it is based on your data set.
00:37:59.891 --> 00:38:01.157
What do you have in your data set?
00:38:01.257 --> 00:38:03.644
And where is your data coming from?
00:38:04.387 --> 00:38:12.322
And how many different, exemplars and non-exemplars do you have that it can reference to get ideas from?
00:38:13.003 --> 00:38:16.927
And that's part of what makes it quote unquote smart.
00:38:18.028 --> 00:38:19.849
So I think that that's really important.
00:38:20.070 --> 00:38:21.090
And yes, absolutely.
00:38:21.172 --> 00:38:28.778
We've all seen, we've all worked at companies where we've seen that, where people just have the cookie cutter behavior plans.
00:38:29.099 --> 00:38:29.980
Yeah, the gold banks.
00:38:31.420 --> 00:38:32.121
Yeah, the gold banks.
00:38:32.242 --> 00:38:34.304
And look, I don't want to hate on the gold banks.
00:38:34.985 --> 00:38:43.251
I think the gold banks, can be helpful and something I say all the time because I use AI 25, 30 times a day.
00:38:43.291 --> 00:38:50.001
And I almost never take what AI gives me and use it.
00:38:50.440 --> 00:39:01.577
But, and I said this in another talk that I did, that I use, let's say, ChatGPT or Clod or Grok to come up with names for projects that I'm working on.
00:39:02.177 --> 00:39:09.349
I have never once actually used the name It's just given me a sounding board and said, hey, you know what?
00:39:09.809 --> 00:39:10.913
Here's a whole bunch of ideas.
00:39:11.032 --> 00:39:11.673
And then I read it.
00:39:11.773 --> 00:39:15.681
I'm like, that's a great way that I can think of a name.
00:39:15.902 --> 00:39:20.150
And I didn't think that I could come up with a name for this project in this format.
00:39:20.871 --> 00:39:25.219
And then I take that and I build on it and I come up with something of my own.
00:39:25.860 --> 00:39:26.422
And I think...
00:39:26.818 --> 00:39:29.079
That's really what our systems are meant to do.
00:39:29.380 --> 00:39:30.382
Does it solve problems?
00:39:30.661 --> 00:39:51.083
Does it save the BCBA eight hours of writing a treatment plan and fighting with, I don't know how long you all have been in the field, but when I first got into the field and Microsoft Office, if you try to grab a graph from Excel, copy and paste it into Word, it would literally explode on the Word template.
00:39:51.123 --> 00:39:53.706
Like it would go from a graph this big to a graph this
00:39:54.047 --> 00:39:54.108
big.
00:39:54.168 --> 00:39:54.568
Yep, been there.
00:39:54.708 --> 00:39:56.190
Yeah.
00:39:56.481 --> 00:39:58.724
And do we solve those problems?
00:39:59.164 --> 00:39:59.724
Absolutely.
00:39:59.826 --> 00:40:01.286
Do we save you frustration?
00:40:01.327 --> 00:40:02.467
Absolutely.
00:40:02.909 --> 00:40:13.981
But you as a BCBA are an intricate part of the service and you have to be because at Introvert AI, we do not do artificial intelligence.
00:40:14.340 --> 00:40:16.282
We do augmented intelligence.
00:40:16.724 --> 00:40:25.393
We partner with the scientists and the practitioners in our field to improve AI the science and practice of behavior analysis.
00:40:25.773 --> 00:40:27.536
Sorry, I don't mean to sound like a commercial here.
00:40:27.577 --> 00:40:30.822
I'm passionate about what we're doing, so it's exciting.
00:40:30.922 --> 00:40:33.846
It's coming across, and we appreciate your passion.
00:40:34.507 --> 00:40:36.250
We are very excited about what you're talking about.
00:40:36.570 --> 00:40:37.632
That is super exciting.
00:40:38.213 --> 00:40:40.195
Are you getting an echo on your end, Adam?
00:40:42.038 --> 00:40:43.661
No, I don't hear an echo on my end.
00:40:43.701 --> 00:40:44.561
Do you get an echo?
00:40:44.601 --> 00:40:45.923
Yeah, I'm hearing it
00:40:45.943 --> 00:40:46.264
a little bit.
00:40:46.284 --> 00:40:46.704
It's okay.
00:40:50.590 --> 00:40:52.494
Okay, the echo's gone.
00:40:52.706 --> 00:41:00.400
So what I'll do when I ask you a question, Adam, I'll just mute you for one second and then I'll because we just get an echo on our end and then I'll open it right up to you.
00:41:00.440 --> 00:41:14.670
But man, that is so, so exciting about like bringing the whole ecosystem together and also bringing like the legitimacy of the research back in, because that's something that I feel like is as long as people are getting reimbursed and the actual the.
00:41:15.074 --> 00:41:18.177
behavior service delivery, we've gone so far away from the researcher.
00:41:18.197 --> 00:41:19.440
We've lost our research base.
00:41:19.460 --> 00:41:20.360
That is so
00:41:20.661 --> 00:41:20.822
exciting.
00:41:20.842 --> 00:41:22.023
I love the way it all comes together.
00:41:22.063 --> 00:41:30.735
One of my favorite things to do in terms of analysis and creating a treatment plan, for example, is brainstorming.
00:41:31.315 --> 00:41:38.125
And it's also one of the more taxing things that I do because it takes a lot of time and it takes a lot of energy.
00:41:38.690 --> 00:41:39.190
Energy.
00:41:39.210 --> 00:41:39.530
It's back.
00:41:41.373 --> 00:41:43.155
But what you're talking about is going to save us that.
00:41:43.255 --> 00:41:45.659
It's going to create, it's going to generate the brainstorm in a sense.
00:41:45.699 --> 00:41:52.027
And then again, I can't stress enough how important it is that you are saying, take it, take it and make it your
00:41:52.648 --> 00:41:52.708
own.
00:41:52.748 --> 00:41:55.532
Yeah, absolutely.
00:41:55.552 --> 00:41:59.358
And I think that's a critical piece here is, is it better
00:41:59.739 --> 00:41:59.798
now?
00:41:59.818 --> 00:42:00.179
You're good.
00:42:00.420 --> 00:42:00.780
You're good.
00:42:00.840 --> 00:42:01.141
Awesome.
00:42:01.601 --> 00:42:03.684
Yeah.
00:42:03.724 --> 00:42:13.023
That's a critical piece of what we're doing here because I know that there's a lot of fear that people are going to lose their jobs to AI.
00:42:13.063 --> 00:42:18.829
And I've been saying this from the beginning and I'll say it again now, you're not going to lose your job to AI.
00:42:19.250 --> 00:42:22.213
You're going to lose your job to somebody that's using AI.
00:42:22.952 --> 00:42:32.422
And that's kind of the tough love that I like to give is you have to start using these tools and it's expected.
00:42:32.463 --> 00:42:37.088
Like at our organization, it is expected for you to use AI.
00:42:38.489 --> 00:42:46.340
When we send documents to each other, you know, you can always tell if something's generated by AI, there's certain markers that you can tell.
00:42:46.380 --> 00:42:48.722
When I see them, I don't get upset.
00:42:49.003 --> 00:43:36.909
I get happy in a sense because I know that they're making the most of their time and they're coming up with better quality policies and procedures or a new way for us to add a cool feature to our system or something like that but we work in in aba in a one of the most human fields imaginable and the way that i see this is you need humans to teach other humans how to be better humans and that's at the foundation of what we do in behavior analysis Some of those robots that companies are working on, I don't know if you all have seen like the Boston Dynamics videos or the Tesla robot videos.
00:43:37.168 --> 00:43:38.150
They're super cool.
00:43:38.210 --> 00:43:43.514
But if I've got a kid that's diagnosed with autism, I don't want him working with a robot.
00:43:43.896 --> 00:43:53.465
I want him working with another human being because there's so many nuances that are involved in being a human and being a good human.
00:43:53.922 --> 00:43:57.407
that can only come from other human beings.
00:43:58.668 --> 00:44:07.663
But I also want the humans that work with my family or work with any family to be able to make the most of their time.
00:44:07.722 --> 00:44:09.204
So be efficient, number one.
00:44:09.264 --> 00:44:11.969
And number two, and more importantly, be effective.
00:44:12.309 --> 00:44:21.454
And that's where connecting with the literature comes in is you can, yes, Our system, for example, makes reports easier to write.
00:44:21.514 --> 00:44:22.096
That's great.
00:44:22.396 --> 00:44:24.177
But I also want you to do better practice.
00:44:24.318 --> 00:44:25.880
And that's where the literature comes in.
00:44:26.221 --> 00:44:26.641
I love that.
00:44:27.021 --> 00:44:30.126
We actually spoke with Michael Dowd from Alpaca Health.
00:44:30.365 --> 00:44:32.228
Have you heard of him before?
00:44:32.648 --> 00:44:33.050
Oh, yeah.
00:44:33.070 --> 00:44:33.210
Yeah.
00:44:33.309 --> 00:44:40.539
Michael and I did a panel together on AI, I would say maybe about five months ago at a conference in New York.
00:44:41.621 --> 00:44:41.800
Yeah.
00:44:41.820 --> 00:44:49.101
And they were working on he's got a great understanding of AI and I think they were working on a Progress Notes AI.
00:44:49.242 --> 00:44:49.322
Yeah.
00:44:49.623 --> 00:44:49.842
Yeah.
00:44:51.105 --> 00:44:53.429
So that was going to be my question.
00:44:53.889 --> 00:44:54.309
Yeah, I guess.
00:44:55.851 --> 00:44:57.614
Feel free to unmute yourself at any time.
00:44:57.675 --> 00:44:59.177
Just get rid of the echo.
00:45:00.197 --> 00:45:17.876
But like Mike said, my big concern from AI was that it's what I've seen from a lot of practice management software now is that it makes things more efficient, but It goes from helping people in ABA to now ABA develops all of their programs based around that.
00:45:18.338 --> 00:45:21.240
to fit into whatever the practice management software is.
00:45:21.280 --> 00:45:23.523
So it's not necessarily even helping anymore.
00:45:23.543 --> 00:45:26.646
It's now guiding and it's all just based on efficiency.
00:45:26.666 --> 00:45:37.597
And when I spoke with Michael and then now yourself, Adam, it's really enlightening to think about the new actual individualization that AI can actually provide to the service delivery model.
00:45:37.637 --> 00:45:49.041
And it's actually kind of almost the inverse of a gold bank because it's taking all of this information that is given to it in this FBA and the indirect and direct assessment And individualizing it for the client.
00:45:49.081 --> 00:45:52.025
So it's almost kind of the opposite of a gold bank, which is really exciting.
00:45:52.606 --> 00:45:53.809
I do have one question for you.
00:45:54.309 --> 00:45:56.293
So feel free to anything you want to add on to that.
00:45:57.233 --> 00:46:00.659
One thing that Mike has always talked about is with data.
00:46:00.739 --> 00:46:07.469
And you mentioned it, too, with the paper and pencil and something that for I've been in the field almost 20 years, Mike's been in longer.
00:46:07.873 --> 00:46:13.601
that we've always tried to grapple with, being able to take data while engaging the individual that you're working with.
00:46:13.661 --> 00:46:15.023
It's kind of like texting and driving.
00:46:15.083 --> 00:46:17.925
You can't really do both at the same time.
00:46:18.045 --> 00:46:25.275
So while we take data at our company, we really try to focus on the interaction versus running 100,000 trials to get data points.
00:46:26.056 --> 00:46:45.563
Is there a way in your program or something you're trying to develop, something you've brought up, a way of kind of recording a session or something like that and basically being able to take and quantify and track programs without actually taking data based on keywords that are heard or answers or things like that?
00:46:49.088 --> 00:46:50.670
Yes, absolutely.
00:46:50.730 --> 00:46:52.793
So that's a big part of what we're working on now.
00:46:52.853 --> 00:46:57.298
And that's a component of our direct assessment piece right now.
00:46:58.599 --> 00:47:02.485
We're going to be expanding on that as part of our roadmap later on this year.
00:47:02.605 --> 00:47:11.797
But I love what you talked about there with regards to multitasking, whether you're in session or you're doing an assessment or whatever it is.
00:47:12.257 --> 00:47:21.771
If you're trying to take data and trying to maybe interact with a client, it's kind of an impossible task, to be honest with you.
00:47:21.811 --> 00:47:30.884
And there's so much cool technology that's coming out soon that involves capturing.
00:47:31.184 --> 00:47:50.496
So there's technology that we're doing research with right now called computer vision that can take a video of something that's happening in a particular setting and identify everything that's happening there, the number of times that it's happening, how long it happens for.
00:47:52.077 --> 00:47:54.199
Yeah, that's something you're interested in, Mike?
00:47:54.500 --> 00:47:54.940
Very much.
00:47:55.702 --> 00:47:56.802
Very much.
00:47:56.822 --> 00:48:03.197
Yeah, yeah, and that's just really going to change the nature of ABA data collection.
00:48:03.257 --> 00:48:13.530
So the way that the direction I think this is going is we're going to change from, we're going to go from data collectors to IOA experts.
00:48:14.092 --> 00:48:22.402
So we're going to go in and say, AI system, collect data, and then it's going to collect the data and it's going to report the data back to us.
00:48:22.804 --> 00:48:32.860
And then we're going to sit down and say, is this what we, is this the spirit and actuality of what we want to capture and reference to the data.
00:48:33.240 --> 00:48:33.860
You know what I mean?
00:48:33.900 --> 00:48:38.186
And so it's, look, capturing data is important.
00:48:38.407 --> 00:48:40.510
Knowing how to capture data is important.
00:48:40.530 --> 00:48:42.431
And this is a whole nother discussion for another day.
00:48:42.452 --> 00:48:54.467
I think graduate students still need to learn how to take data because there's little nuances that you learn as part of that process that you'll need to be a good IOA specialist.
00:48:54.967 --> 00:49:14.467
But once you get through all of that, there's a lot of circumstances where it doesn't make sense to sit there with paper and pencil or even a mobile device and button smash and take frequency data on self-stimulatory behavior that happens 100 times in 20 minutes or something like that.
00:49:14.827 --> 00:49:23.177
When you can be intervening or you can be looking at the surrounding environment, what else is going on during that time?
00:49:23.217 --> 00:49:25.961
And that's what this technology promises.
00:49:26.402 --> 00:49:29.706
And that's part of what we're so excited about.
00:49:29.726 --> 00:49:38.179
One of the things I like to say is we've set up our implementation as though we're the only source of SDs in the environment.
00:49:38.280 --> 00:49:44.148
And what you just said, it opens that whole game up to really allow...
00:49:45.121 --> 00:49:48.487
other SDs in the environment to now be noticed.
00:49:48.989 --> 00:49:53.536
You can provide reinforcement to the behavior that results.
00:49:54.077 --> 00:49:55.601
Yeah, very exciting what you're talking about.
00:49:55.681 --> 00:50:05.416
So gentlemen, as I suspected, when Adam kindly popped up on the screen here to start our time together, we have breezed through these two hours.
00:50:06.617 --> 00:50:11.664
And we could probably spend a lot more time talking, but we've taken enough of your time and from you and your family.
00:50:11.704 --> 00:50:13.907
Let's think about some wrap-up points.
00:50:13.987 --> 00:50:15.148
It sounds like Dan's got something.
00:50:15.248 --> 00:50:16.769
Yeah, well, just a question for you, Adam.
00:50:16.791 --> 00:50:21.016
And by the way, the echo just happened late, so it wasn't something that happened early.
00:50:21.056 --> 00:50:22.097
And I apologize for that.
00:50:22.157 --> 00:50:23.659
Thank you for following through.
00:50:23.699 --> 00:50:25.000
I hate to mute and unmute.
00:50:25.561 --> 00:50:28.403
I will open it up to you before we wrap up.
00:50:28.585 --> 00:50:32.568
Is there anything else that wasn't covered that you want to make sure that is...
00:50:33.186 --> 00:50:34.086
discussed today?
00:50:35.128 --> 00:50:37.349
Yeah, absolutely.
00:50:38.210 --> 00:50:57.271
I think I want to stress a couple of things that we've already discussed, which is the AI is going to allow us as we progress with this technology to be better at our jobs and to do less of the tasks in our jobs that we dislike.
00:50:57.791 --> 00:51:03.034
I think everybody in our field likes interacting with other human beings.
00:51:03.494 --> 00:51:06.838
I think we like the interview portion of assessments.
00:51:07.300 --> 00:51:11.646
I think we like the supervision meeting portions of supervision.
00:51:11.666 --> 00:51:18.215
I think we like the parent interaction portion of parent training.
00:51:19.038 --> 00:51:22.001
We like one-to-one human interaction.
00:51:22.041 --> 00:51:26.268
And what this technology promises is a lot more of that.
00:51:26.929 --> 00:51:45.936
I talked about our assessment product that gives the practitioner more time to interact with the parents or the teacher, whomever it is that they're interviewing and connect with them, build a relationship with them on a human level.
00:51:46.739 --> 00:52:23.420
But the same goes for, we also have a supervision product that allows the BCBAs to have more time to interact with their supervisee and really understand what's going on in the supervisee's life as opposed to sitting there furiously taking notes and identifying is this direct or indirect hours and how many hours did you spend with the client versus doing indirect hours and doing all of those complicated formulas to figure out whatever the BACB requirements are at the moment.
00:52:24.505 --> 00:52:34.202
Our technology, and I'll just speak for ours at Intraverbal, Our technology is designed to make that process easier and more reinforcing.
00:52:34.262 --> 00:52:39.648
So it's not just low response effort, it's more engaging, it's more meaningful.
00:52:39.728 --> 00:52:47.159
You get to spend more meaningful time with your supervisee, talking about different case scenarios and experience.
00:52:47.619 --> 00:52:50.764
It allows you to dive deeper into the research.
00:52:51.425 --> 00:52:58.385
And overall, I think helps our mission, which is, Improving the Science and Practice of Behavior Analysis.
00:53:01.057 --> 00:53:01.878
Right on, right on.
00:53:02.199 --> 00:53:02.980
Thank you so much.
00:53:03.179 --> 00:53:03.599
Love that.
00:53:31.023 --> 00:53:38.695
a plug, where people can find you, and that way our listeners, and we'll also include this in the show description, our listeners know where to find your products and where to find your information.
00:53:42.820 --> 00:53:44.262
Yeah, thank you so much for asking.
00:53:44.322 --> 00:53:48.989
So if you all are interested, please check out introverbal.ai.
00:53:49.268 --> 00:53:55.838
So you can Google us, you can just go directly to our website, like I said, which is www.introverbal.ai.
00:53:56.001 --> 00:53:59.588
or you can reach out directly to me.
00:54:00.349 --> 00:54:04.375
The only social media platform that I personally focus on is LinkedIn.
00:54:04.394 --> 00:54:06.197
I'm on LinkedIn pretty much all day.
00:54:06.237 --> 00:54:12.487
Feel free to message me anytime on LinkedIn, or you can use our contact form on our website.
00:54:13.710 --> 00:54:20.922
We do have an Instagram page for Introverbal and LinkedIn as well, so feel free to reach us.
00:54:21.442 --> 00:54:41.635
through any of those channels or if you see me at a conference I regularly present at conferences especially this year I'm all over the place presenting feel free to come up and talk to me if you'd like a demo of how our system works or if you'd just like to sign up or if you'd like to just have a discussion with us about
00:54:41.675 --> 00:54:42.195
how
00:54:42.536 --> 00:54:53.344
our system works on the back end feel free to reach out to us we can have a whole discussion about how we protect PHI and how HIPPO works in our system.
00:54:54.086 --> 00:54:57.338
Feel free to contact us at any of those channels and we'd be happy to get back to you.
00:54:58.273 --> 00:54:58.715
Awesome.
00:54:58.735 --> 00:54:59.275
Well, thank you.
00:54:59.315 --> 00:55:00.096
Thank you so much.
00:55:00.496 --> 00:55:05.023
We'd like to do a few wrap-up points here, and you gave me a lot, so I had to write them down.
00:55:05.123 --> 00:55:09.809
So as we wrap up here, before our tagline, what would we learn from Adam?
00:55:10.250 --> 00:55:17.478
Solve the practical problem, do good science, make the report your own, augment your intelligence, don't make it artificial, and...
00:55:17.900 --> 00:55:19.442
Always analyze responsibly.
00:55:19.641 --> 00:55:20.001
Cheers.
00:55:20.302 --> 00:55:20.943
Thanks a lot, Mr.
00:55:20.983 --> 00:55:21.384
Ventura.
00:55:21.423 --> 00:55:22.005
Thank you so much.
00:55:23.137 --> 00:55:24.019
ABA on
00:55:24.101 --> 00:55:26.728
Tap is recorded live and unfiltered.
00:55:27.349 --> 00:55:28.291
We're done for today.
00:55:28.672 --> 00:55:31.000
You don't have to go home, but you can't stay here.
00:55:31.039 --> 00:55:32.885
See you next time.
00:00:00.000 --> 00:00:19.022
Welcome to ABA on Tap, where our goal is to find the best recipe to brew the smoothest, coldest, and best tasting ABA around.
00:00:19.603 --> 00:00:27.652
I'm Dan Lowry with Mike Rubio, and join us on our journey as we look back into the ingredients to form the best concoction of ABA on tap.
00:00:32.417 --> 00:00:43.334
In this podcast, we will talk about the history of the ABA brew, how much to consume to achieve the optimum buzz while not getting too drunk, and the recommended pairings to bring to the table.
00:00:43.875 --> 00:00:49.143
So without further ado, sit back, relax, and always analyze responsibly.
00:00:49.162 --> 00:00:49.222
All
00:00:52.868 --> 00:00:54.109
right, all right.
00:00:54.402 --> 00:00:56.905
This is your ever-grateful co-host, Mike Rubio.
00:00:57.526 --> 00:00:58.746
Thank you for coming back.
00:00:59.048 --> 00:01:00.909
This is part two with Mr.
00:01:01.149 --> 00:01:03.432
Adam Ventura of Intraverbal AI.
00:01:03.493 --> 00:01:04.313
Enjoy.
00:01:04.353 --> 00:01:09.280
Yeah, that's tough.
00:01:09.480 --> 00:01:11.121
And I feel like you had two questions there.
00:01:11.182 --> 00:01:12.323
So I'll start with the first one.
00:01:13.364 --> 00:01:16.688
So I'm assuming when you say KPM, key performance metrics?
00:01:16.748 --> 00:01:17.469
Correct, yeah.
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And like what to evaluate people on and say the program's successful.
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Because my experience with working with private equity was always just about like efficiency base.
00:01:26.477 --> 00:01:26.677
Yeah.
00:01:26.796 --> 00:01:29.359
And so that just becomes a scorecard, right?
00:01:29.439 --> 00:01:31.862
And I think it should be a balanced scorecard.
00:01:32.063 --> 00:01:44.539
And this was one of the key lessons that I learned from work doing OBM consulting for a few years is the importance of employee and organizational scorecards being balanced.
00:01:44.998 --> 00:01:52.903
You know, so yes, you can't, do you need profit measures on your scorecard?
00:01:52.944 --> 00:01:53.385
Yeah, you do.
00:01:53.745 --> 00:01:55.828
If you're not making a profit, you can't be in business.
00:01:56.388 --> 00:02:04.117
And people need to be able to say that out loud without getting pilloried for identifying the obvious.
00:02:04.757 --> 00:02:09.082
However, when you create these scorecards, that can't be the only metric on there.
00:02:09.643 --> 00:02:14.128
So yes, net revenue is important, but you also need to have...
00:02:15.490 --> 00:03:20.542
measures of social validity on there are the families happy more or less maybe that's the wrong word but are the families satisfied with the service that you are producing then you get into and I think Mike you just brought it up like how do you define quality service and I think there's some folks in our field that don't behave like honest brokers when we have those discussions are there some fair points that yeah it's really hard to measure because for example you can't or you're going to have trouble using a percentage measure because some behaviors are uh much more deleterious to the health and wellness of the client than others so you can say oh i reduced um some i i reduced stereotypy by 80 okay that's great but if you have another um topography like elopement where the client is running out into the middle of the street, I reduce that by 80%.
00:03:20.981 --> 00:03:21.963
That's good.
00:03:22.024 --> 00:03:28.573
But if he's still running out into the middle of a busy intersection, 20% of the time, that's still a life threatening behavior.
00:03:29.074 --> 00:03:35.864
So coming up with a, and I'm working in technology now, so I'll call it an algorithm.
00:03:36.685 --> 00:03:41.951
Coming up with an algorithm for these insurance companies to use is a big challenge.
00:03:42.051 --> 00:03:44.816
However, I don't think it's an insurmountable challenge.
00:03:45.195 --> 00:03:52.987
I think it's something that if you get some of the smartest behavior analysts in our field together, I think they could figure out.
00:03:53.649 --> 00:03:55.973
And are there gonna be some edge cases?
00:03:56.312 --> 00:03:57.014
Yeah, there is.
00:03:57.054 --> 00:04:27.024
But I think if we don't wanna do harm to our science, and that's really kind of my professional mission is disseminating and moving forward the science, I think we need to be very careful with this because if people are doing bad ABA therapy out there, it's going to reflect poorly on our science and then we're gonna start regressing scientifically and as a field more broadly.
00:04:28.286 --> 00:04:29.187
That makes a lot of sense.
00:04:29.547 --> 00:04:34.992
My last question about your business and then maybe we can transition or I can pass it to you, Mike.
00:04:35.072 --> 00:04:36.634
I'm sorry, I've been asking a lot of questions here.
00:04:37.175 --> 00:04:39.038
So you created this business.
00:04:39.490 --> 00:04:44.995
had these conversations, expanded to 300 employees, and then you did sell, you said, to private equity.
00:04:45.016 --> 00:04:56.028
So can you talk about maybe your thought process with that, your thoughts on them being able to maintain your vision and mission, or even if that was a concern, and maybe if they were able to be successful with that or not?
00:04:57.949 --> 00:04:58.930
Yeah.
00:04:59.831 --> 00:05:08.541
I didn't really speak publicly until recently on the Beyond the Science podcast about why I sold my company, but I had a...
00:05:09.026 --> 00:05:10.569
Family tragedy at the time.
00:05:10.588 --> 00:05:13.192
I had no interest in selling my company.
00:05:13.213 --> 00:05:14.975
I wanted to continue to grow it.
00:05:15.156 --> 00:05:16.858
It was my life's purpose.
00:05:17.699 --> 00:05:18.982
And I had a family tragedy.
00:05:19.021 --> 00:05:23.550
Somebody in my family passed away unexpectedly.
00:05:23.569 --> 00:05:25.814
No, no, no.
00:05:26.213 --> 00:05:29.879
It was seven years ago, eight years ago, whatever it was.
00:05:29.899 --> 00:05:33.084
And I realized that I didn't have...
00:05:33.569 --> 00:05:36.213
I didn't have a great relationship with my family at all.
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There were some people in my immediate family that I hadn't spoken to in a decade.
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And I realigned my priorities.
00:05:43.622 --> 00:05:47.327
I really felt like my legacy was my business.
00:05:47.809 --> 00:05:56.060
And when that happened, I made the decision that I needed to have a relationship with my family.
00:05:56.100 --> 00:05:57.021
I mean, I hadn't...
00:05:58.370 --> 00:06:00.153
I hadn't spoken to my dad in 12 years.
00:06:00.173 --> 00:06:02.516
I hadn't spoken to my sisters in like nine years.
00:06:02.536 --> 00:06:07.685
I hadn't spoken to my mom in, I don't know, five, six, seven years, something like that.
00:06:07.725 --> 00:06:18.300
And while the tragedy was tragic, it opened up an opportunity for me to be successful personally.
00:06:18.622 --> 00:06:22.949
And all I could think about, all that mattered to me was professional success.
00:06:23.329 --> 00:06:25.312
I had no relationship success either.
00:06:25.331 --> 00:06:26.334
I was a mess professionally.
00:06:26.497 --> 00:06:28.360
personally dating.
00:06:28.379 --> 00:06:30.442
I was a hot mess dating.
00:06:30.463 --> 00:06:33.266
I had no relationship with my family.
00:06:33.305 --> 00:06:43.298
And I just made a transition at that point when that tragedy struck to grow up personally.
00:06:43.819 --> 00:06:52.910
And I really made that transition and discovered that my immortality project, my legacy wasn't my business.
00:06:53.290 --> 00:06:54.050
It was my family.
00:06:54.531 --> 00:06:55.994
It was having kids.
00:06:56.482 --> 00:06:57.863
And it was getting married.
00:06:57.884 --> 00:07:00.065
It was having a stable relationship.
00:07:00.726 --> 00:07:07.053
And when I made that transition, I realized that I couldn't do that myself.
00:07:07.435 --> 00:07:08.095
I needed help.
00:07:08.495 --> 00:07:16.805
And I tried to transition somebody into the CEO role so that I could address what had just happened.
00:07:16.865 --> 00:07:21.170
Because when you have a family tragedy, a lot of people need help.
00:07:21.269 --> 00:07:23.692
And I needed to be there more for my family.
00:07:24.545 --> 00:07:31.692
Whenever something terrible happens and somebody has to step down from leadership role in any industry, they're like, oh, I have to spend more time with my family.
00:07:32.053 --> 00:07:34.735
I literally had to spend more time with my family.
00:07:35.456 --> 00:07:36.819
And I put somebody else in the role.
00:07:36.858 --> 00:07:42.444
And as soon as I did that, we got a Medicaid audit in Florida.
00:07:42.805 --> 00:07:44.005
And it was a mess.
00:07:44.526 --> 00:07:52.834
And as it turned out, Medicaid decided, Florida Medicaid at that time decided not to pay us for about five months.
00:07:53.817 --> 00:07:59.124
And they owed us seven figures of money.
00:07:59.985 --> 00:08:04.591
And I didn't have that money in the couch cushions in my home.
00:08:05.492 --> 00:08:12.641
So luckily, we managed to send everything over that they asked for, got through it.
00:08:13.023 --> 00:08:14.925
Funny enough, I always like telling this story.
00:08:14.944 --> 00:08:20.773
After we sold the company, Private Equity went to Florida Medicaid and said, listen, we're buying Adam's company.
00:08:21.346 --> 00:08:27.853
And they told them at the time, they're like, oh, yeah, we audited his company and he's one of our best providers.
00:08:28.413 --> 00:08:33.739
And I wanted to strangle them because it would have been nice if they would have realized that earlier.
00:08:37.562 --> 00:08:38.384
But that's OK.
00:08:39.806 --> 00:08:49.176
So I the company that bought us, we were their platform company and the first company that they bought and everything that they promised that they would do, they did.
00:08:49.956 --> 00:08:50.878
And.
00:08:51.361 --> 00:08:57.009
They grew to be a very big company and then ended up selling again after that.
00:08:57.029 --> 00:09:06.162
I understand how the business works, but I hold no ill will towards the notion of private equity.
00:09:06.682 --> 00:09:29.038
For as many bad private equity stories that we hear, I know personally of 20, 25 stories that a small ABA provider that doesn't know how to run a business that was this close to going under, private equity swooped in and saved them from their business going under.
00:09:29.639 --> 00:09:33.823
So I don't have that animosity towards private equity.
00:09:33.864 --> 00:09:37.947
Are there some bad behaving actors in private equity?
00:09:38.149 --> 00:09:38.349
Yeah.
00:09:39.230 --> 00:09:45.461
Are there some private equity platforms that shouldn't own an ABA business?
00:09:45.662 --> 00:09:45.903
Sure.
00:09:46.384 --> 00:09:50.374
But is there something inherently wrong with that business model?
00:09:50.835 --> 00:09:51.817
No, I don't think so.
00:09:53.100 --> 00:10:05.842
Dan, to your point earlier, they need to refine their scorecards, I think some of them, to include clinical quality, to include some of those measures of social validity.
00:10:06.283 --> 00:10:15.138
And that's where if they get behavior analysts to work with them, like I know some of private equity companies do right now, then things get better.
00:10:15.639 --> 00:10:21.850
And I guess that's my overall thoughts on private equity and their involvement in ADA.
00:10:21.870 --> 00:10:21.950
Yeah.
00:10:22.177 --> 00:10:23.460
Well, thank you for sharing that story.
00:10:23.500 --> 00:10:26.083
That was very insightful, and I appreciate that.
00:10:26.605 --> 00:10:26.985
I was going to
00:10:27.005 --> 00:10:27.527
say the same thing.
00:10:27.586 --> 00:10:39.907
Thanks for sharing the personal side and then getting into the private equity piece, and we're very glad for your experience there, and very glad to hear somebody share a positive experience on private equity, because those aren't the stories you hear, right?
00:10:39.947 --> 00:10:41.450
The stories you hear are all the negatives.
00:10:42.230 --> 00:10:45.517
What is it you think really goes wrong in those moments?
00:10:45.636 --> 00:10:48.774
Is it Is it a bad private equity actor usually?
00:10:48.815 --> 00:10:54.525
Is it people just not knowing how to deal with private equity when they're going through these interactions?
00:10:54.725 --> 00:11:03.043
What would you tell somebody out there who is maybe getting an offer from private equity or might need help to stay alive?
00:11:03.884 --> 00:11:05.006
What would you caution them about?
00:11:05.106 --> 00:11:06.249
What would be your best advice?
00:11:07.831 --> 00:11:08.373
There's a lot of...
00:11:08.833 --> 00:11:11.278
So I'll answer the last question first.
00:11:11.298 --> 00:11:17.667
There's a lot of consultants out there that will help walk somebody through a sale of their business.
00:11:18.749 --> 00:11:24.035
Don't feel the other thing I would say to those folks is don't feel bad about wanting to sell your business.
00:11:24.236 --> 00:11:30.184
And, you know, I thought I was going to get a lot of pushback from people because I sold my business in 2018.
00:11:30.905 --> 00:11:35.874
And that was really in the beginning of private equity and how that stuff happened.
00:11:36.289 --> 00:11:41.073
And I actually made the decision to sell my business in late 2017.
00:11:41.835 --> 00:11:45.438
My family tragedy happened in October of 2017.
00:11:45.458 --> 00:11:52.465
And I made the decision really within a month and a half, two months, something like that, that I was going to have to step down.
00:11:52.504 --> 00:11:56.969
And I really expected a lot of pushback.
00:11:57.409 --> 00:11:57.929
I really did.
00:11:57.950 --> 00:12:05.778
I thought people were going to vilify me and I was going to be pilloried from a public standpoint in our field.
00:12:05.857 --> 00:12:16.240
And there was a lot of people, a lot of colleagues that I had that worked in different parts of our field that when I told them, their response was, congratulations, good for you.
00:12:17.061 --> 00:12:22.288
And I couldn't believe I heard it, you know, and I felt like it was kind of reassuring.
00:12:22.307 --> 00:12:27.816
They're like, look, you know, I guess because this was people, these were people that knew me.
00:12:27.836 --> 00:12:31.841
I lived and breathed my company.
00:12:32.182 --> 00:12:34.105
It was the only thing that mattered to me.
00:12:34.465 --> 00:12:40.326
And That turned out to be part of the problem with my personal life is that's all that mattered to me.
00:12:41.368 --> 00:12:49.254
But they knew that for the few people that knew what was going on in my life, they understood why I was doing it.
00:12:49.395 --> 00:12:54.220
So I would say the first thing that I would say to those folks is don't feel bad about doing it.
00:12:54.801 --> 00:13:00.886
Second thing I would say is find a consultant that can explain everything to you, how everything works.
00:13:01.768 --> 00:13:03.288
I think that that's really helpful.
00:13:04.129 --> 00:13:15.244
I would say part of the reason why this goes wrong so many of these times is because a lot of these private equity companies bring a medical model into ABA.
00:13:16.765 --> 00:13:25.917
I don't agree with the idea that we should be making ABA the medical model that insurance companies are used to dealing with.
00:13:26.017 --> 00:13:27.599
I think there's a lot of problems with that.
00:13:28.179 --> 00:13:32.544
And I think private equity companies just swoop in and say, this is just like the...
00:13:33.378 --> 00:13:38.764
the string of dentist locations that we purchased last year and then sold for a profit.
00:13:39.147 --> 00:13:46.668
We can run it the same way as we do You know, a dentist's office or an orthopedist's office or something like that.
00:13:47.269 --> 00:13:48.809
And it just doesn't work that way.
00:13:48.830 --> 00:13:55.817
We have a very unique field with a tiered service delivery model that doesn't exist in other fields.
00:13:56.479 --> 00:14:05.428
So I think the smartest private equity companies are the ones that hire behavior analysts to help them make better decisions.
00:14:06.114 --> 00:14:09.662
I think if they don't, that's where the problems come in.
00:14:09.682 --> 00:14:23.513
I think most behavior analysts, especially seasoned behavior analysts that have been in the field for a while, that care about the clients, that care about the science will sit down with the private equity companies and say, yes, you need to make a profit.
00:14:23.905 --> 00:14:26.370
To make a profit, you need to be more efficient.
00:14:26.591 --> 00:14:36.490
Yes, agreed on both of those, but you also need to provide a good service, and here's what I mean by a good service, and here are the outcomes that you need to look for.
00:14:36.530 --> 00:14:45.509
And if those behavior analysts can communicate that appropriately and the private equity companies are willing to listen, then you get good outcomes.
00:14:45.769 --> 00:14:47.994
If those two things don't happen, you get bad outcomes.
00:14:48.975 --> 00:15:04.869
So let me ask you this, and please correct me if I'm wrong, because like I said, I'm not too well-versed in private equity, but from some things that I've talked about with people, they've said that that does make sense, but since private equity a lot of times isn't there for the long run...
00:15:05.282 --> 00:15:11.690
by the time that they're going to have to pay the piper for the lack of clinical quality, they will have already sold and it won't be their problem anymore.
00:15:11.710 --> 00:15:12.750
It'll be on to somebody else.
00:15:12.791 --> 00:15:20.500
So if they can just make it more efficient, regardless of the clinical quality, get the metrics up and sell, that'll be on somebody else's doorstep.
00:15:22.624 --> 00:15:25.647
I don't know how often that happens now.
00:15:25.947 --> 00:15:33.100
At least I think that they're becoming, these private equity companies have become They've been doing it now for almost a decade.
00:15:33.520 --> 00:15:36.405
So they're starting to figure things out, number one.
00:15:36.466 --> 00:15:41.173
Number two, if you sell a company, there's a whole bunch of provisions.
00:15:41.354 --> 00:15:44.177
And I learned about this when I was selling my company.
00:15:44.719 --> 00:15:53.613
There's a whole bunch of provisions in those agreements that say that if things fall apart three months in, you're in a lot of trouble as a seller.
00:15:54.094 --> 00:15:56.418
So I think...
00:15:57.409 --> 00:16:13.211
Private equity companies are becoming wise to this and realizing that it's not just a three-year turnaround anymore, that it's a three- to five-year turnaround, maybe five- to seven-year turnaround, and that it's bad business to run a bad business.
00:16:13.772 --> 00:16:25.226
So if you're running a business that all you care about is billable hours, and then all of a sudden audits show up, clients get hurt, social media plays a big role in this too.
00:16:25.548 --> 00:16:27.009
If you run a crappy company...
00:16:27.457 --> 00:16:33.783
Behavior analysts are going to make it well known in those Facebook groups and on LinkedIn and things like that.
00:16:34.004 --> 00:16:38.109
And you become, your brand becomes known for that.
00:16:38.328 --> 00:16:46.777
And anybody that's looking to acquire you, a bigger private equity company or whomever it is, they're going to do their due diligence.
00:16:46.996 --> 00:16:48.938
They're going to not just look at your books.
00:16:48.999 --> 00:16:51.162
They're going to look at your brand.
00:16:51.621 --> 00:16:55.265
They're going to look at how people have rated you on Glassdoor.
00:16:55.809 --> 00:17:01.061
So I don't think this is 2018, 2019, 2020 anymore.
00:17:01.442 --> 00:17:02.924
This is 2025.
00:17:02.965 --> 00:17:13.067
And those people that run those billion dollar private equity funds, they didn't become billionaires by making stupid decisions.
00:17:13.468 --> 00:17:15.833
And I think that they look back and say, you know what?
00:17:16.673 --> 00:17:19.738
We saw this company or that company collapse.
00:17:19.938 --> 00:17:20.859
Why did that happen?
00:17:21.039 --> 00:17:27.208
In a lot of cases, it's because they didn't care about clinical quality or treated their employees like crap.
00:17:28.028 --> 00:17:28.951
Thank you for clarifying.
00:17:29.010 --> 00:17:29.852
I appreciate that.
00:17:29.892 --> 00:17:34.258
Like I said, I'm pretty ignorant to the whole thing, so I'm just saying what I hear, and thank you for clarifying that.
00:17:34.278 --> 00:17:35.098
That was very insightful.
00:17:35.219 --> 00:17:36.461
Yeah, very good information.
00:17:36.500 --> 00:17:42.608
So you sold, and I'm going to skip over a few things here just in the interest of time.
00:17:43.170 --> 00:17:53.898
But now you're delving into artificial intelligence and how that's going to fit into the future of ABA, whether that's autism treatment or whatever that may present.
00:17:53.919 --> 00:18:03.468
And I think it behooves us to diversify more and more in how we're actually employing behavior analysis to help people.
00:18:03.508 --> 00:18:13.135
Talk to us a little bit about what you're doing now, what got you interested in that over time, and then anything else you want to share and we'll help you unpack it and discuss it.
00:18:13.135 --> 00:18:13.676
Yes, that was
00:18:15.720 --> 00:18:15.960
great.
00:18:16.300 --> 00:18:17.823
Thank you for the question.
00:18:18.022 --> 00:18:28.178
Actually, one of the businesses that I moved into after I sold my ABA therapy company was opening a practice management software company.
00:18:28.498 --> 00:18:32.243
I made a lot of mistakes with that company.
00:18:34.178 --> 00:18:36.761
I learned what I like doing and what I don't like doing.
00:18:36.781 --> 00:18:42.269
When we were talking maybe about 30 or 40 minutes ago, I talked about how much I hate ABA admin.
00:18:43.009 --> 00:18:53.285
One of the things you have to do when you start an ABA practice management software company is you have to deal with a lot of admin and you have to really become a medical billing expert.
00:18:54.645 --> 00:18:58.352
It's interesting because I have a software team that I've been working with for 10 years.
00:19:00.417 --> 00:19:09.792
Something that our lead developer explained to me a few years ago and he's like, Adam, medical billing software is its own specialty because it's so complicated.
00:19:10.093 --> 00:19:18.767
You have to know so much about that industry and you have to merge two fields together, software and insurance companies.
00:19:18.866 --> 00:19:20.028
It's very difficult.
00:19:20.834 --> 00:19:26.182
Um, so I realized that, um, I didn't want to do practice management.
00:19:26.242 --> 00:19:31.111
It just wasn't something that I wanted to do, but I liked technology a lot, a lot.
00:19:31.971 --> 00:19:43.451
And when AI really started coming on the scene, uh, really even before, uh, chat GPT, everybody knows chat GPT and it kind of burst onto the scene a few years ago or a couple of years ago.
00:19:43.471 --> 00:19:47.157
Um, I started talking a lot to my development team about.
00:19:47.938 --> 00:20:31.138
where we can move forward and the answer that they always gave me was ai and i thought about what my professional mission is and my profession professional mission is to move the science and practice of behavior analysis forward that's what matters to me we were talking about the science earlier it really matters to me i taught at university for 12 years i enjoy teaching the science i enjoy disseminating it and when some of those large language models really burst onto the scene in 2022, we started having those discussions about how I can merge my professional mission with this new emerging technology.
00:20:32.140 --> 00:20:44.112
And where I kind of landed as our initial product offering was I wanted to make the practice of behavior analysis more evidence-based.
00:20:44.692 --> 00:20:46.394
So what do I mean by that?
00:20:46.786 --> 00:21:01.009
When we go into a home, a clinic, a group home, a school to work with a particular kiddo, there's almost exactly zero behavior analysts that show up with a binder full of journal articles.
00:21:01.590 --> 00:21:02.653
It's just not going to happen.
00:21:02.772 --> 00:21:06.138
And even if you did, it's not practical.
00:21:06.700 --> 00:21:11.567
If you've got a kiddo that's engaging in that spaghetti tantrum thing, you can't...
00:21:12.897 --> 00:21:26.315
response block that with one hand and page three in the idea that, because there's tens of thousands of journal articles out there, you know, that you're going to find the one and the intervention that's there, it's just not going to happen.
00:21:26.815 --> 00:21:36.748
So one of the things that we wanted to do was bring, with this technology, bring the science into the practice.
00:21:37.548 --> 00:21:53.733
And something that we started doing was setting up deals with publishing houses to connect these AI systems to that information and making it available in the moment.
00:21:54.094 --> 00:22:02.307
So you can literally pick up one of these mobile devices and say, my client's engaging in this, what should I do?
00:22:02.528 --> 00:22:14.278
Now, I want to make this very clear that, especially if you're an RBT listening to this, You need to do what your behavior analyst tells you to do, not what an AI system tells you to do.
00:22:14.298 --> 00:22:35.888
However, if you're a BCBA and you're looking for ideas on how to deal with a unique form of SIB or you want to set up toilet training in a unique setting and you need some ideas, you need a sounding board to bounce ideas off of, these types of tools are the way to do it.
00:22:36.834 --> 00:22:49.346
We set up our company called Introverbal AI, and we feel like the name of the company is appropriate because you plug a whole bunch of mans into our system.
00:22:49.386 --> 00:22:54.271
You ask questions, you make requests, and our system gives answers back.
00:22:54.452 --> 00:22:55.733
And that's why we came up with the
00:22:55.753 --> 00:22:56.394
name.
00:22:56.414 --> 00:22:56.755
I love it.
00:22:56.775 --> 00:22:57.496
That's fantastic.
00:22:58.757 --> 00:22:59.057
Thank you.
00:22:59.096 --> 00:22:59.397
Thank you.
00:22:59.637 --> 00:23:03.201
And with our system, our system...
00:23:03.521 --> 00:23:14.239
allows you to search through tens of thousands of journal articles to find the answers to not just clinical questions, but academic questions.
00:23:14.960 --> 00:23:19.105
And we took this base model and we started building on top of it.
00:23:19.807 --> 00:23:27.839
And we created a goals product that we have that helps you create goals for your clients.
00:23:27.900 --> 00:23:35.278
And then we ended up adding like 10,000 client goals or 10,000 clients worth of goals.
00:23:35.358 --> 00:23:40.767
It turned into like a million actual individual goals that it kind of pulls from.
00:23:41.347 --> 00:23:49.680
We developed a functional behavior assessment product that touches on not only those goals, but also the literature as well.
00:23:50.280 --> 00:24:35.942
So not to get too deep into the products, our system was really meant to improve the science and practice of behavior analysis and we tried to do that with um starting off with the foundation of the literature you know what were we all taught what was drilled into our brains in graduate school do evidence-based practice always reference the literature you know if you were in a good graduate program you were reading eight to ten journal articles a week you know and you really had to dive in do deep dives into these articles to make sure you understood why things were done the way that they were done and recognizing good research from bad research.
00:24:36.943 --> 00:24:57.585
And that was a big impetus as to what we wanted to do and I'll never forget the first time our lead developer came to me and he said, okay, we connected the two here and then I just started asking questions and it gave me answers instantaneously and it gave the in-text citation and then it gave a full reference list And it did it in like four seconds.
00:24:57.805 --> 00:25:03.573
And I was like, holy crap, you know, like just imagine the difference that we can make with all of this.
00:25:03.653 --> 00:25:18.512
And I think that was my introduction to AI and why I kind of fell in love with what we can do with this technology and how it can augment, not replace our practice.
00:25:19.329 --> 00:25:19.790
Sold.
00:25:20.070 --> 00:25:24.958
I was going to say, I can vibe with that, but you are speaking this guy's language 100%.
00:25:25.278 --> 00:25:45.164
So just, I'm already having visions of, you know, in all fairness, I can be very, I've been very critical on the show and in the past professionally about, you know, you've got these staff meetings and you end up taking time away from clients to sit down for two hours and talk about billable matters and, you know, efficiency.
00:25:45.224 --> 00:26:19.449
And you're not, training anybody you're not professionally developing anybody truly in the bread and butter of the the service delivery and and that knowledge so the idea that i mean i think a lot of that why that happens is it takes time to develop those training materials so as a bcba as a manager or whatever title you have if you're in a position of inciting that professional development it can be very cumbersome to go and find those articles that can be very cumbersome to read through those articles and what you're presenting here is going to really make that a lot easier much more accessible and that's super exciting
00:26:19.509 --> 00:26:42.295
you mentioned read through the articles when I was doing BCBA study groups because we would do those a lot for people in their coursework studying to get the BCBA you put a journal article in front of them and it might have been might as well have been Mandarin Chinese like people did not want to read it didn't understand what it said and I mean to be fair like the way that they're set up isn't you know it's very lab heavy it's not great to read it's not like a Exciting.
00:26:42.335 --> 00:26:43.537
Well, exciting isn't the best word.
00:26:43.576 --> 00:26:44.818
It's not an easy read a lot
00:26:44.838 --> 00:26:45.078
of times.
00:26:45.098 --> 00:26:45.740
No, no, no, it's not.
00:26:45.779 --> 00:26:47.722
It's not easy to translate or to apply.
00:26:47.823 --> 00:26:59.820
So you end up coming away with knowledge that you may not fully understand, that you have to process, that you have to discuss with other people, that you might need a language model to do some translation for you, to do some summary for you.
00:26:59.840 --> 00:27:01.002
That sounds fantastic.
00:27:01.683 --> 00:27:03.987
Tell us a little bit about some of the other features that you're looking at.
00:27:04.007 --> 00:27:06.991
So I would imagine that's one feature that's part of your system.
00:27:07.031 --> 00:27:08.354
What else are you developing?
00:27:09.569 --> 00:27:10.290
Yeah, absolutely.
00:27:10.330 --> 00:27:12.394
Thanks for asking about it.
00:27:12.776 --> 00:27:14.278
Yeah, that's really a great system.
00:27:14.479 --> 00:27:24.336
So some of the other products, our goal, our clinical goal right now is to go through the entire life cycle of the client.
00:27:24.635 --> 00:27:27.361
So from intake to discharge.
00:27:28.021 --> 00:27:34.232
So we're going to be releasing our assessment product coming up soon.
00:27:34.786 --> 00:27:36.228
And I'll use that as an example.
00:27:36.587 --> 00:27:37.829
We're super excited about that.
00:27:37.849 --> 00:27:42.855
So our assessment product allows people to upload all of that.
00:27:43.497 --> 00:27:48.042
You know, like when you go to do an assessment, you get a ton of information, let's say, from your office.
00:27:48.083 --> 00:27:51.748
Let's say you're a VCBA and you get a ton of information from your office.
00:27:51.768 --> 00:27:53.230
You get a diagnostic report.
00:27:53.671 --> 00:27:58.717
You get somebody else's behavior plan or re-auth or assessment or something like that.
00:27:59.117 --> 00:28:01.520
And you're expected to read through 40 pages of
00:28:01.601 --> 00:28:02.382
documents.
00:28:02.402 --> 00:28:02.461
Yep.
00:28:02.561 --> 00:28:05.145
before you go to see the client and good luck with that.
00:28:05.326 --> 00:28:07.289
Nobody's gonna be able to read through all of that.
00:28:08.030 --> 00:28:17.307
So the very first step in our assessment cycle is somebody at the organization uploads that documentation into our system.
00:28:17.346 --> 00:28:36.127
Our system processes all of that information provides a summary, and then suggested questions for the BCBA to ask during the interview portion of the assessment, and emails it to them and says, here, for this particular kiddo, here's a summary.
00:28:36.469 --> 00:28:42.037
This is everything that you're going to need to know, and here's some questions that we recommend asking.
00:28:42.698 --> 00:28:46.063
So when the BCBAs come in, they're armed with that information.
00:28:46.784 --> 00:28:50.109
Now, once they get in, the next step, and we're...
00:28:50.978 --> 00:28:55.763
Part of our goal, we have a two-pronged goal at Intraverbal AI.
00:28:56.384 --> 00:29:00.088
We want to solve a practical problem and do good science.
00:29:00.670 --> 00:29:07.678
Those are our two main values or pillars or aims at our organization.
00:29:08.439 --> 00:29:09.980
So we want to solve a practical problem.
00:29:10.000 --> 00:29:24.242
And another practical problem that you have when you're doing an assessment is you have a pen and you have your paper and you're furiously taking notes, trying to listen, trying to ask questions, and that's a huge challenge.
00:29:24.843 --> 00:29:36.298
So what we set up is practitioners can do this, whether they're doing telehealth or they're in-person, they can grab their mobile device or they can do it on their desktop.
00:29:36.858 --> 00:30:11.352
Our system transcribes the entire interaction between the practitioners and the families and it takes all that information in, and it allows them to press a button, and our system reviews the interview up to that point, and then checks the journal articles, the literature, and says, based on these two buckets of information, here are some questions that you should ask before you leave.
00:30:12.113 --> 00:30:13.194
So that happens to all of us.
00:30:13.214 --> 00:30:26.761
When you do an assessment maybe, You finish the assessment, you get in the car, you drive down the street and then you're like, crap, I forgot to ask about toilet training or I forgot to ask what medication the kiddos are on or something like that.
00:30:27.403 --> 00:30:37.054
Our system handles that for you and provides questions and says, hey, you forgot to ask about medications or hey, you forgot to ask about this.
00:30:38.096 --> 00:30:43.582
Once that's done, that's the indirect portion of the assessment.
00:30:43.682 --> 00:30:44.803
the assessment.
00:30:44.844 --> 00:30:56.057
So I was always taught that a good FBA involves three distinct sections, an indirect assessment, a direct assessment, and then a functional analysis if needed.
00:30:56.898 --> 00:30:59.001
So that takes care of the indirect assessment.
00:30:59.423 --> 00:31:14.277
Then our system does the direct assessment piece, where it records all of the data and observations that you take during the direct observation portion, allows you to upload data sheets into it.
00:31:15.238 --> 00:31:36.397
And then when you get to the last piece, which is the report, you go in, you sit down and you press a button and our system takes all of that information, the initial intake, the indirect assessment transcription, the direct assessment piece, puts it all together into a insurance ready report.
00:31:37.018 --> 00:31:49.397
And the way that we set this up is we hired BCBA peer reviewers that work at the insurance companies to evaluate the reports that we were creating.
00:31:49.919 --> 00:31:57.425
And we created a scorecard for them and they told us approve, not approve, approve, not approve, and here's why.
00:31:57.465 --> 00:32:14.942
And then we made the changes over the course of a few different iterations so that when our system generates the report, all that really needs to be done at that point is the behavior analyst needs to put their signature on it.
00:32:15.063 --> 00:32:19.728
And I don't mean just their actual signature, but make the report their own.
00:32:20.169 --> 00:32:24.913
And that's where this is really augmented intelligence, not artificial.
00:32:26.556 --> 00:32:29.719
We joke around that it's insurance ready, but it's really not.
00:32:30.099 --> 00:32:38.846
It requires that last step for the behavior analyst to come in and say, well, This isn't really in my tone of voice.
00:32:38.865 --> 00:32:43.512
I don't think maybe we should have this recommended intervention.
00:32:43.532 --> 00:32:52.965
I really think that the function of this behavior, the hypothesized function of this behavior is really this, and they come in and do that piece.
00:32:53.125 --> 00:32:57.231
But our tool solves a huge problem.
00:32:57.291 --> 00:33:03.480
It literally saves eight to 10 hours of report writing, and it does good behavior analysis.
00:33:04.226 --> 00:33:09.330
Sorry if I dragged on there, but I really wanted to capture the essence of what we're trying to do.
00:33:10.751 --> 00:33:16.657
So does your report, does that report also come up with hypothesized goals as well?
00:33:18.179 --> 00:33:19.079
Oh, yeah, absolutely.
00:33:19.160 --> 00:33:24.806
So what we've really created in Intraverbal AI is an ecosystem.
00:33:24.965 --> 00:33:31.652
And something else that I think is very important to share is all of these products, I do not...
00:33:34.018 --> 00:33:37.061
I don't get 100% of the profit of these.
00:33:38.123 --> 00:33:45.692
And the reason that I'm bringing that up is because I've set up partnerships with a whole bunch of behavior analysts.
00:33:46.233 --> 00:33:52.442
And what Introverbal AI is, it's really an AI ecosystem for behavior analysis.
00:33:53.162 --> 00:34:01.752
And what we've done is we've partnered with a whole bunch of subject matter experts to put out different products and tools.
00:34:02.498 --> 00:34:17.344
We've got, and I know it's a long answer to your simple question there about the goals, but we've partnered with a subject matter expert for assessments, somebody for supervision, somebody for BACB test prep, which is going to be coming out at the end of the summer.
00:34:18.045 --> 00:34:23.514
And we've partnered with somebody for goals to generate goals within our system.
00:34:23.956 --> 00:34:27.141
So we've got a whole tool that just helps to generate goals.
00:34:27.585 --> 00:34:42.652
And that connects with our assessment system so that when the assessment report is generated, it generates suggested goals based on the assessment tools that you used during the assessment cycle.
00:34:42.753 --> 00:34:49.786
So whether you used a Vineland or a VB Map or an ABLES or something like that, it takes all of that into consideration.
00:34:50.242 --> 00:34:56.112
and the subject matter experts that we've worked with to create that report.
00:34:56.172 --> 00:35:06.871
And you can see it, we very proudly put that on our About Us section of our website, the different people that we partnered with, and we've got a whole bunch more partners that we're gonna be announcing.
00:35:07.172 --> 00:35:22.452
And I do wanna say this because I feel like it's very important to the mission and the values of our company is, What we wanted to create is a collective consciousness of information and behavior analysis.
00:35:23.233 --> 00:35:39.599
And we wanted to not just get all of the information from so many smart people that wrote those journal articles and did that research, but we also wanted to get the practitioners and the peer reviewers and set up all of these partnerships.
00:35:40.139 --> 00:35:43.567
So I am not the sole owner of Intraverbal AI.
00:35:44.027 --> 00:35:59.085
We are a community of behavior analysts that all have an ownership stake in the products that we're putting out here so that we can create this digital community of experts and expertise.
00:35:59.646 --> 00:35:59.925
Does that make
00:36:00.487 --> 00:36:00.586
sense?
00:36:00.606 --> 00:36:01.007
A lot of sense.
00:36:01.027 --> 00:36:01.527
That's exciting.
00:36:01.668 --> 00:36:02.668
That's very exciting.
00:36:02.949 --> 00:36:06.211
And thank you for taking the time to explain all the elements there.
00:36:06.231 --> 00:36:07.253
I think it's very important.
00:36:07.873 --> 00:36:18.141
Starting with the idea, so I think that for me, a phrase that gets kicked around, especially in the old days when we did paper and pencil, it was very easy to create templates.
00:36:18.802 --> 00:36:34.878
And then before, we even talk about it at our company now, it's one of those words, I hear template and I'm like, oh, you're trying to save yourself And you're running the risk of being lazy and just replicating treatment plans across clients because it's similar enough.
00:36:35.478 --> 00:36:38.222
And obviously, there's a lot of problems to be had there.
00:36:38.282 --> 00:36:48.353
So when you first hear about sort of artificial intelligence, if you will, generating these things immediately, especially somebody of my age might be like, well, wait a minute, we're going to run into that problem.
00:36:48.693 --> 00:36:53.458
But the way you describe it clearly avoids that in terms of generating a wealth of ideas.
00:36:53.498 --> 00:36:54.960
And then I love the way you put the onus.
00:36:54.960 --> 00:36:55.840
on the professional.
00:36:55.880 --> 00:36:56.822
Make that your own.
00:36:57.342 --> 00:36:59.003
You're going to get a big lump of clay.
00:36:59.043 --> 00:37:11.193
You better sculpt that down to make sure it reflects your client or your purpose because otherwise then you do run that risk of going back to just a template, a very generalized cookie cutter template.
00:37:11.835 --> 00:37:17.780
The way you've described it though really presents a lot of safeguards and you're promoting people make this information their own.
00:37:17.860 --> 00:37:24.925
So yeah, let the computer pump out a bunch of possibilities and then you apply it to your particular client.
00:37:25.378 --> 00:37:26.139
Yeah, absolutely.
00:37:26.219 --> 00:37:31.664
It's interesting because when I got into the field, I think in 2004, 2005, you know what we used to call treatment plans?
00:37:31.684 --> 00:37:36.909
They were called IVPs, individualized behavior
00:37:36.929 --> 00:37:37.329
plans.
00:37:37.389 --> 00:37:38.070
And
00:37:38.269 --> 00:37:43.956
somehow along the way, the I got removed to rather just behavior plans or treatment plans.
00:37:44.016 --> 00:37:48.500
And I don't know what happened to the I, but they should be individualized treatment plans.
00:37:48.559 --> 00:37:59.811
And the great part about this new technology is so much of it is based on and there's so many factors in the technology that so much of it is based on your data set.
00:37:59.891 --> 00:38:01.157
What do you have in your data set?
00:38:01.257 --> 00:38:03.644
And where is your data coming from?
00:38:04.387 --> 00:38:12.322
And how many different, exemplars and non-exemplars do you have that it can reference to get ideas from?
00:38:13.003 --> 00:38:16.927
And that's part of what makes it quote unquote smart.
00:38:18.028 --> 00:38:19.849
So I think that that's really important.
00:38:20.070 --> 00:38:21.090
And yes, absolutely.
00:38:21.172 --> 00:38:28.778
We've all seen, we've all worked at companies where we've seen that, where people just have the cookie cutter behavior plans.
00:38:29.099 --> 00:38:29.980
Yeah, the gold banks.
00:38:31.420 --> 00:38:32.121
Yeah, the gold banks.
00:38:32.242 --> 00:38:34.304
And look, I don't want to hate on the gold banks.
00:38:34.985 --> 00:38:43.251
I think the gold banks, can be helpful and something I say all the time because I use AI 25, 30 times a day.
00:38:43.291 --> 00:38:50.001
And I almost never take what AI gives me and use it.
00:38:50.440 --> 00:39:01.577
But, and I said this in another talk that I did, that I use, let's say, ChatGPT or Clod or Grok to come up with names for projects that I'm working on.
00:39:02.177 --> 00:39:09.349
I have never once actually used the name It's just given me a sounding board and said, hey, you know what?
00:39:09.809 --> 00:39:10.913
Here's a whole bunch of ideas.
00:39:11.032 --> 00:39:11.673
And then I read it.
00:39:11.773 --> 00:39:15.681
I'm like, that's a great way that I can think of a name.
00:39:15.902 --> 00:39:20.150
And I didn't think that I could come up with a name for this project in this format.
00:39:20.871 --> 00:39:25.219
And then I take that and I build on it and I come up with something of my own.
00:39:25.860 --> 00:39:26.422
And I think...
00:39:26.818 --> 00:39:29.079
That's really what our systems are meant to do.
00:39:29.380 --> 00:39:30.382
Does it solve problems?
00:39:30.661 --> 00:39:51.083
Does it save the BCBA eight hours of writing a treatment plan and fighting with, I don't know how long you all have been in the field, but when I first got into the field and Microsoft Office, if you try to grab a graph from Excel, copy and paste it into Word, it would literally explode on the Word template.
00:39:51.123 --> 00:39:53.706
Like it would go from a graph this big to a graph this
00:39:54.047 --> 00:39:54.108
big.
00:39:54.168 --> 00:39:54.568
Yep, been there.
00:39:54.708 --> 00:39:56.190
Yeah.
00:39:56.481 --> 00:39:58.724
And do we solve those problems?
00:39:59.164 --> 00:39:59.724
Absolutely.
00:39:59.826 --> 00:40:01.286
Do we save you frustration?
00:40:01.327 --> 00:40:02.467
Absolutely.
00:40:02.909 --> 00:40:13.981
But you as a BCBA are an intricate part of the service and you have to be because at Introvert AI, we do not do artificial intelligence.
00:40:14.340 --> 00:40:16.282
We do augmented intelligence.
00:40:16.724 --> 00:40:25.393
We partner with the scientists and the practitioners in our field to improve AI the science and practice of behavior analysis.
00:40:25.773 --> 00:40:27.536
Sorry, I don't mean to sound like a commercial here.
00:40:27.577 --> 00:40:30.822
I'm passionate about what we're doing, so it's exciting.
00:40:30.922 --> 00:40:33.846
It's coming across, and we appreciate your passion.
00:40:34.507 --> 00:40:36.250
We are very excited about what you're talking about.
00:40:36.570 --> 00:40:37.632
That is super exciting.
00:40:38.213 --> 00:40:40.195
Are you getting an echo on your end, Adam?
00:40:42.038 --> 00:40:43.661
No, I don't hear an echo on my end.
00:40:43.701 --> 00:40:44.561
Do you get an echo?
00:40:44.601 --> 00:40:45.923
Yeah, I'm hearing it
00:40:45.943 --> 00:40:46.264
a little bit.
00:40:46.284 --> 00:40:46.704
It's okay.
00:40:50.590 --> 00:40:52.494
Okay, the echo's gone.
00:40:52.706 --> 00:41:00.400
So what I'll do when I ask you a question, Adam, I'll just mute you for one second and then I'll because we just get an echo on our end and then I'll open it right up to you.
00:41:00.440 --> 00:41:14.670
But man, that is so, so exciting about like bringing the whole ecosystem together and also bringing like the legitimacy of the research back in, because that's something that I feel like is as long as people are getting reimbursed and the actual the.
00:41:15.074 --> 00:41:18.177
behavior service delivery, we've gone so far away from the researcher.
00:41:18.197 --> 00:41:19.440
We've lost our research base.
00:41:19.460 --> 00:41:20.360
That is so
00:41:20.661 --> 00:41:20.822
exciting.
00:41:20.842 --> 00:41:22.023
I love the way it all comes together.
00:41:22.063 --> 00:41:30.735
One of my favorite things to do in terms of analysis and creating a treatment plan, for example, is brainstorming.
00:41:31.315 --> 00:41:38.125
And it's also one of the more taxing things that I do because it takes a lot of time and it takes a lot of energy.
00:41:38.690 --> 00:41:39.190
Energy.
00:41:39.210 --> 00:41:39.530
It's back.
00:41:41.373 --> 00:41:43.155
But what you're talking about is going to save us that.
00:41:43.255 --> 00:41:45.659
It's going to create, it's going to generate the brainstorm in a sense.
00:41:45.699 --> 00:41:52.027
And then again, I can't stress enough how important it is that you are saying, take it, take it and make it your
00:41:52.648 --> 00:41:52.708
own.
00:41:52.748 --> 00:41:55.532
Yeah, absolutely.
00:41:55.552 --> 00:41:59.358
And I think that's a critical piece here is, is it better
00:41:59.739 --> 00:41:59.798
now?
00:41:59.818 --> 00:42:00.179
You're good.
00:42:00.420 --> 00:42:00.780
You're good.
00:42:00.840 --> 00:42:01.141
Awesome.
00:42:01.601 --> 00:42:03.684
Yeah.
00:42:03.724 --> 00:42:13.023
That's a critical piece of what we're doing here because I know that there's a lot of fear that people are going to lose their jobs to AI.
00:42:13.063 --> 00:42:18.829
And I've been saying this from the beginning and I'll say it again now, you're not going to lose your job to AI.
00:42:19.250 --> 00:42:22.213
You're going to lose your job to somebody that's using AI.
00:42:22.952 --> 00:42:32.422
And that's kind of the tough love that I like to give is you have to start using these tools and it's expected.
00:42:32.463 --> 00:42:37.088
Like at our organization, it is expected for you to use AI.
00:42:38.489 --> 00:42:46.340
When we send documents to each other, you know, you can always tell if something's generated by AI, there's certain markers that you can tell.
00:42:46.380 --> 00:42:48.722
When I see them, I don't get upset.
00:42:49.003 --> 00:43:36.909
I get happy in a sense because I know that they're making the most of their time and they're coming up with better quality policies and procedures or a new way for us to add a cool feature to our system or something like that but we work in in aba in a one of the most human fields imaginable and the way that i see this is you need humans to teach other humans how to be better humans and that's at the foundation of what we do in behavior analysis Some of those robots that companies are working on, I don't know if you all have seen like the Boston Dynamics videos or the Tesla robot videos.
00:43:37.168 --> 00:43:38.150
They're super cool.
00:43:38.210 --> 00:43:43.514
But if I've got a kid that's diagnosed with autism, I don't want him working with a robot.
00:43:43.896 --> 00:43:53.465
I want him working with another human being because there's so many nuances that are involved in being a human and being a good human.
00:43:53.922 --> 00:43:57.407
that can only come from other human beings.
00:43:58.668 --> 00:44:07.663
But I also want the humans that work with my family or work with any family to be able to make the most of their time.
00:44:07.722 --> 00:44:09.204
So be efficient, number one.
00:44:09.264 --> 00:44:11.969
And number two, and more importantly, be effective.
00:44:12.309 --> 00:44:21.454
And that's where connecting with the literature comes in is you can, yes, Our system, for example, makes reports easier to write.
00:44:21.514 --> 00:44:22.096
That's great.
00:44:22.396 --> 00:44:24.177
But I also want you to do better practice.
00:44:24.318 --> 00:44:25.880
And that's where the literature comes in.
00:44:26.221 --> 00:44:26.641
I love that.
00:44:27.021 --> 00:44:30.126
We actually spoke with Michael Dowd from Alpaca Health.
00:44:30.365 --> 00:44:32.228
Have you heard of him before?
00:44:32.648 --> 00:44:33.050
Oh, yeah.
00:44:33.070 --> 00:44:33.210
Yeah.
00:44:33.309 --> 00:44:40.539
Michael and I did a panel together on AI, I would say maybe about five months ago at a conference in New York.
00:44:41.621 --> 00:44:41.800
Yeah.
00:44:41.820 --> 00:44:49.101
And they were working on he's got a great understanding of AI and I think they were working on a Progress Notes AI.
00:44:49.242 --> 00:44:49.322
Yeah.
00:44:49.623 --> 00:44:49.842
Yeah.
00:44:51.105 --> 00:44:53.429
So that was going to be my question.
00:44:53.889 --> 00:44:54.309
Yeah, I guess.
00:44:55.851 --> 00:44:57.614
Feel free to unmute yourself at any time.
00:44:57.675 --> 00:44:59.177
Just get rid of the echo.
00:45:00.197 --> 00:45:17.876
But like Mike said, my big concern from AI was that it's what I've seen from a lot of practice management software now is that it makes things more efficient, but It goes from helping people in ABA to now ABA develops all of their programs based around that.
00:45:18.338 --> 00:45:21.240
to fit into whatever the practice management software is.
00:45:21.280 --> 00:45:23.523
So it's not necessarily even helping anymore.
00:45:23.543 --> 00:45:26.646
It's now guiding and it's all just based on efficiency.
00:45:26.666 --> 00:45:37.597
And when I spoke with Michael and then now yourself, Adam, it's really enlightening to think about the new actual individualization that AI can actually provide to the service delivery model.
00:45:37.637 --> 00:45:49.041
And it's actually kind of almost the inverse of a gold bank because it's taking all of this information that is given to it in this FBA and the indirect and direct assessment And individualizing it for the client.
00:45:49.081 --> 00:45:52.025
So it's almost kind of the opposite of a gold bank, which is really exciting.
00:45:52.606 --> 00:45:53.809
I do have one question for you.
00:45:54.309 --> 00:45:56.293
So feel free to anything you want to add on to that.
00:45:57.233 --> 00:46:00.659
One thing that Mike has always talked about is with data.
00:46:00.739 --> 00:46:07.469
And you mentioned it, too, with the paper and pencil and something that for I've been in the field almost 20 years, Mike's been in longer.
00:46:07.873 --> 00:46:13.601
that we've always tried to grapple with, being able to take data while engaging the individual that you're working with.
00:46:13.661 --> 00:46:15.023
It's kind of like texting and driving.
00:46:15.083 --> 00:46:17.925
You can't really do both at the same time.
00:46:18.045 --> 00:46:25.275
So while we take data at our company, we really try to focus on the interaction versus running 100,000 trials to get data points.
00:46:26.056 --> 00:46:45.563
Is there a way in your program or something you're trying to develop, something you've brought up, a way of kind of recording a session or something like that and basically being able to take and quantify and track programs without actually taking data based on keywords that are heard or answers or things like that?
00:46:49.088 --> 00:46:50.670
Yes, absolutely.
00:46:50.730 --> 00:46:52.793
So that's a big part of what we're working on now.
00:46:52.853 --> 00:46:57.298
And that's a component of our direct assessment piece right now.
00:46:58.599 --> 00:47:02.485
We're going to be expanding on that as part of our roadmap later on this year.
00:47:02.605 --> 00:47:11.797
But I love what you talked about there with regards to multitasking, whether you're in session or you're doing an assessment or whatever it is.
00:47:12.257 --> 00:47:21.771
If you're trying to take data and trying to maybe interact with a client, it's kind of an impossible task, to be honest with you.
00:47:21.811 --> 00:47:30.884
And there's so much cool technology that's coming out soon that involves capturing.
00:47:31.184 --> 00:47:50.496
So there's technology that we're doing research with right now called computer vision that can take a video of something that's happening in a particular setting and identify everything that's happening there, the number of times that it's happening, how long it happens for.
00:47:52.077 --> 00:47:54.199
Yeah, that's something you're interested in, Mike?
00:47:54.500 --> 00:47:54.940
Very much.
00:47:55.702 --> 00:47:56.802
Very much.
00:47:56.822 --> 00:48:03.197
Yeah, yeah, and that's just really going to change the nature of ABA data collection.
00:48:03.257 --> 00:48:13.530
So the way that the direction I think this is going is we're going to change from, we're going to go from data collectors to IOA experts.
00:48:14.092 --> 00:48:22.402
So we're going to go in and say, AI system, collect data, and then it's going to collect the data and it's going to report the data back to us.
00:48:22.804 --> 00:48:32.860
And then we're going to sit down and say, is this what we, is this the spirit and actuality of what we want to capture and reference to the data.
00:48:33.240 --> 00:48:33.860
You know what I mean?
00:48:33.900 --> 00:48:38.186
And so it's, look, capturing data is important.
00:48:38.407 --> 00:48:40.510
Knowing how to capture data is important.
00:48:40.530 --> 00:48:42.431
And this is a whole nother discussion for another day.
00:48:42.452 --> 00:48:54.467
I think graduate students still need to learn how to take data because there's little nuances that you learn as part of that process that you'll need to be a good IOA specialist.
00:48:54.967 --> 00:49:14.467
But once you get through all of that, there's a lot of circumstances where it doesn't make sense to sit there with paper and pencil or even a mobile device and button smash and take frequency data on self-stimulatory behavior that happens 100 times in 20 minutes or something like that.
00:49:14.827 --> 00:49:23.177
When you can be intervening or you can be looking at the surrounding environment, what else is going on during that time?
00:49:23.217 --> 00:49:25.961
And that's what this technology promises.
00:49:26.402 --> 00:49:29.706
And that's part of what we're so excited about.
00:49:29.726 --> 00:49:38.179
One of the things I like to say is we've set up our implementation as though we're the only source of SDs in the environment.
00:49:38.280 --> 00:49:44.148
And what you just said, it opens that whole game up to really allow...
00:49:45.121 --> 00:49:48.487
other SDs in the environment to now be noticed.
00:49:48.989 --> 00:49:53.536
You can provide reinforcement to the behavior that results.
00:49:54.077 --> 00:49:55.601
Yeah, very exciting what you're talking about.
00:49:55.681 --> 00:50:05.416
So gentlemen, as I suspected, when Adam kindly popped up on the screen here to start our time together, we have breezed through these two hours.
00:50:06.617 --> 00:50:11.664
And we could probably spend a lot more time talking, but we've taken enough of your time and from you and your family.
00:50:11.704 --> 00:50:13.907
Let's think about some wrap-up points.
00:50:13.987 --> 00:50:15.148
It sounds like Dan's got something.
00:50:15.248 --> 00:50:16.769
Yeah, well, just a question for you, Adam.
00:50:16.791 --> 00:50:21.016
And by the way, the echo just happened late, so it wasn't something that happened early.
00:50:21.056 --> 00:50:22.097
And I apologize for that.
00:50:22.157 --> 00:50:23.659
Thank you for following through.
00:50:23.699 --> 00:50:25.000
I hate to mute and unmute.
00:50:25.561 --> 00:50:28.403
I will open it up to you before we wrap up.
00:50:28.585 --> 00:50:32.568
Is there anything else that wasn't covered that you want to make sure that is...
00:50:33.186 --> 00:50:34.086
discussed today?
00:50:35.128 --> 00:50:37.349
Yeah, absolutely.
00:50:38.210 --> 00:50:57.271
I think I want to stress a couple of things that we've already discussed, which is the AI is going to allow us as we progress with this technology to be better at our jobs and to do less of the tasks in our jobs that we dislike.
00:50:57.791 --> 00:51:03.034
I think everybody in our field likes interacting with other human beings.
00:51:03.494 --> 00:51:06.838
I think we like the interview portion of assessments.
00:51:07.300 --> 00:51:11.646
I think we like the supervision meeting portions of supervision.
00:51:11.666 --> 00:51:18.215
I think we like the parent interaction portion of parent training.
00:51:19.038 --> 00:51:22.001
We like one-to-one human interaction.
00:51:22.041 --> 00:51:26.268
And what this technology promises is a lot more of that.
00:51:26.929 --> 00:51:45.936
I talked about our assessment product that gives the practitioner more time to interact with the parents or the teacher, whomever it is that they're interviewing and connect with them, build a relationship with them on a human level.
00:51:46.739 --> 00:52:23.420
But the same goes for, we also have a supervision product that allows the BCBAs to have more time to interact with their supervisee and really understand what's going on in the supervisee's life as opposed to sitting there furiously taking notes and identifying is this direct or indirect hours and how many hours did you spend with the client versus doing indirect hours and doing all of those complicated formulas to figure out whatever the BACB requirements are at the moment.
00:52:24.505 --> 00:52:34.202
Our technology, and I'll just speak for ours at Intraverbal, Our technology is designed to make that process easier and more reinforcing.
00:52:34.262 --> 00:52:39.648
So it's not just low response effort, it's more engaging, it's more meaningful.
00:52:39.728 --> 00:52:47.159
You get to spend more meaningful time with your supervisee, talking about different case scenarios and experience.
00:52:47.619 --> 00:52:50.764
It allows you to dive deeper into the research.
00:52:51.425 --> 00:52:58.385
And overall, I think helps our mission, which is, Improving the Science and Practice of Behavior Analysis.
00:53:01.057 --> 00:53:01.878
Right on, right on.
00:53:02.199 --> 00:53:02.980
Thank you so much.
00:53:03.179 --> 00:53:03.599
Love that.
00:53:31.023 --> 00:53:38.695
a plug, where people can find you, and that way our listeners, and we'll also include this in the show description, our listeners know where to find your products and where to find your information.
00:53:42.820 --> 00:53:44.262
Yeah, thank you so much for asking.
00:53:44.322 --> 00:53:48.989
So if you all are interested, please check out introverbal.ai.
00:53:49.268 --> 00:53:55.838
So you can Google us, you can just go directly to our website, like I said, which is www.introverbal.ai.
00:53:56.001 --> 00:53:59.588
or you can reach out directly to me.
00:54:00.349 --> 00:54:04.375
The only social media platform that I personally focus on is LinkedIn.
00:54:04.394 --> 00:54:06.197
I'm on LinkedIn pretty much all day.
00:54:06.237 --> 00:54:12.487
Feel free to message me anytime on LinkedIn, or you can use our contact form on our website.
00:54:13.710 --> 00:54:20.922
We do have an Instagram page for Introverbal and LinkedIn as well, so feel free to reach us.
00:54:21.442 --> 00:54:41.635
through any of those channels or if you see me at a conference I regularly present at conferences especially this year I'm all over the place presenting feel free to come up and talk to me if you'd like a demo of how our system works or if you'd just like to sign up or if you'd like to just have a discussion with us about
00:54:41.675 --> 00:54:42.195
how
00:54:42.536 --> 00:54:53.344
our system works on the back end feel free to reach out to us we can have a whole discussion about how we protect PHI and how HIPPO works in our system.
00:54:54.086 --> 00:54:57.338
Feel free to contact us at any of those channels and we'd be happy to get back to you.
00:54:58.273 --> 00:54:58.715
Awesome.
00:54:58.735 --> 00:54:59.275
Well, thank you.
00:54:59.315 --> 00:55:00.096
Thank you so much.
00:55:00.496 --> 00:55:05.023
We'd like to do a few wrap-up points here, and you gave me a lot, so I had to write them down.
00:55:05.123 --> 00:55:09.809
So as we wrap up here, before our tagline, what would we learn from Adam?
00:55:10.250 --> 00:55:17.478
Solve the practical problem, do good science, make the report your own, augment your intelligence, don't make it artificial, and...
00:55:17.900 --> 00:55:19.442
Always analyze responsibly.
00:55:19.641 --> 00:55:20.001
Cheers.
00:55:20.302 --> 00:55:20.943
Thanks a lot, Mr.
00:55:20.983 --> 00:55:21.384
Ventura.
00:55:21.423 --> 00:55:22.005
Thank you so much.
00:55:23.137 --> 00:55:24.019
ABA on
00:55:24.101 --> 00:55:26.728
Tap is recorded live and unfiltered.
00:55:27.349 --> 00:55:28.291
We're done for today.
00:55:28.672 --> 00:55:31.000
You don't have to go home, but you can't stay here.
00:55:31.039 --> 00:55:32.885
See you next time.
