- August 01, 2024
- Gambling
Researchers at the International Gaming Institute on the campus of UNLV are diving deep into the effects of gambling on public health. Whether studying banking habits alongside gambling activity or creating chatbots to assist and educate users about responsible gaming, AI and machine learning is being utilized to develop guardrails that support responsible gaming. In this episode, Dr. Kasra Ghaharian, Director of Research at the International Gaming Institute, shares how his researchers are having an impact on responsible gambling.
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Transcript:
Speaker 1 (Dr. Kasra Ghaharian)
You and your sports betting website. Why you like O Chatbot? How much did I lose last month? you lost this much. How about you set a limit?
00;00;11;17 – 00;00;43;22
Speaker 2 (Shane Cook)
Welcome to Wager Danger. I’m your host, Shane Cook, Gambling Disorder Program Director, Gateway Foundation. Our guest today is Dr. Kasra Ghaharian the director of research at the International Gaming Institute, located on the campus of the University of Nevada, Las Vegas. Kas I discussed his work at the intersection of public health, banking, gambling and artificial intelligence and how this information can be used to both identify problem gambling as well as create guardrails to support responsible gaming.
00;00;43;24 – 00;01;07;11
Speaker 2
There are many layers to his studies and many directions to explore from the potential of banks to study for patterns of deposits and withdrawals, to identify problem gambling, to using chat bots to assist and educate users on reducing gambling harm to how some day in the not so distant future A.I. will be able to design a custom game for you.
00;01;07;14 – 00;01;13;15
Speaker 2
There’s so much to think about and we’re going to cover a lot of ground. Welcome to the show, Kaz.
00;01;13;18 – 00;01;17;26
Speaker 1
Thank you. Pleasure to be here. Thank you for the invite. Excited to start chatting.
00;01;17;26 – 00;01;40;21
Speaker 2
Yeah, absolutely. Had a chance to get together over the past couple of weeks. We were together at the National Conference on Problem gambling out in San Diego. I want to start out kind of from the beginning here and just kind of get a background on the International Gaming Institute, which is on the campus at UNLV. Can you tell us?
00;01;40;21 – 00;01;56;11
Speaker 2
I would bet that a lot of people don’t realize that there’s actually an institute that’s dedicated to the world of gaming and that it exists at UNLV in Las Vegas. Can you tell us a little bit about it?
00;01;56;14 – 00;02;25;00
Speaker 1
Yeah, 100%. Yeah. I don’t think you’re wrong, guy. Maybe there are a lot of people who don’t know that exist right here, but we are here. The International Gaming Institute is located at UNLV. What the institute is really about is studying anything and everything to do with gambling. You know, whether that’s policy, regulation, operations analysis, responsible gambling, problem gambling.
00;02;25;02 – 00;02;53;24
Speaker 1
We’re interested in looking at all of those things. Okay. And we kind of do that under three main pillars of our institute. And I’ll just briefly go over these. So we obviously do that with a lot of research. That’s the area that I’m responsible for. And I head up as director of research here at the institute. You know, we conduct various different programs and research projects through industry funded projects as well as wide public wants.
00;02;53;24 – 00;03;17;27
Speaker 1
We go out for university guidance, we go out for we work with PhD students, Martha studios, even undergraduate students. So we do we can go dive into the research we do later on and then off the research. We also have the innovation which is headed up by my colleague Dan. So he actually has a great program where students can come in with a game design idea.
00;03;17;27 – 00;03;39;24
Speaker 1
It might be like a gambling game, it could be a board game, could be an educational game, it could be anything. But he takes students from kind of this idea stage to like full product prototype stage. And his his department actually files more patents than any department on campus, which is quite cool. And finally, we have our kind of education and knowledge section.
00;03;39;27 – 00;04;08;11
Speaker 1
That’s where we do various different programs. We have the Center for Gaming Regulation in this like kind of a world leader in delivering education and knowledge on new technology to the gaming space regulation, that kind of thing. And yeah, we have lots of cool other programs is that like we have our Yes program, which is the Young Executive Scholars Program where we kind of connect with the Las Vegas community, teach them about the hospitality and gaming industry.
00;04;08;14 – 00;04;13;23
Speaker 1
So yeah, lots of cool stuff. You can go to our website. I’m sure you’ll post in the show notes.
00;04;13;26 – 00;04;28;03
Speaker 2
Yeah, definitely. Yeah, I just think it’s fascinating and I appreciate you kind of walking us through. But on a more personal note, how did you find yourself at the International Gaming Institute?
00;04;28;05 – 00;04;58;03
Speaker 1
Yeah, it’s a it’s a story I like to tell, actually, because it is quite fitting. So obviously, you might have can tell by my accent. I wasn’t born and raised in the US or Las Vegas in particular, so I was born in England, London, England. And yes, but my, you know, childhood and adolescence in the UK did my bachelor’s degree and business at the University of Surrey just outside of London.
00;04;58;05 – 00;05;26;15
Speaker 1
And while I was there, I got really into poker, actually, I think in high school I got into playing poker with my friends. I remember playing poker at my parents garage. I brought like fell table and, you know, used to get my friends out on the weekend and we used to do like a poker tour and we always used to watch like World Poker to win the World Series on ESPN and stuff.
00;05;26;15 – 00;05;46;21
Speaker 1
So like, you know, we’d be in their shades and hoodies and stuff and yeah, and they had so, so the so fun times. But yeah, then at university, actually I helped set up the University Poker Society. So like every Sunday we would get together, we play a poker tournament. It was like, you know, like a very small stakes poker tournament.
00;05;46;29 – 00;06;08;26
Speaker 1
But that’s around the time online poker started getting really big as well. So I used to play wine poker a lot after I graduated, was still playing online poker, came to Vegas a couple of times on a like a poker holiday, if you will, and just really loved the city, didn’t want to become a professional poker player, but thought it would be cool to work in the gambling industry.
00;06;08;26 – 00;06;30;07
Speaker 1
And the casinos found out about you. And I’ll be. And I was like, Yeah, I’m going to go and just try it out. I thought, Yeah, you know, I’ll come for a year, then I’ll go back and work for a casino in the UK. But you know, one thing led to another. I met my wife, you know, got a job and yet at the time had eight years later.
00;06;30;08 – 00;06;34;11
Speaker 2
So yeah. So everything kind of fell into place then.
00;06;34;14 – 00;07;03;29
Speaker 1
Yeah. I think, you know, at a massive turning point. Dr. Beau Ballard, he teaches this class called the Sociology of Gambling. So it’s all about how gambling affects society of people and literally has cost like, changed the trajectory of my life. I was like, Wow, this is so cool. I want to work in this industry. And he taught that class in such a way as to warn, like, you know, point out the benefits that the gambling industry could could bring.
00;07;03;29 – 00;07;22;14
Speaker 1
But also, you know, he’s very like transparent in terms of like, you know, Bay can create these harms and things like that. Okay. And I thought that was amazing, that kind of, you know, yeah, I can provide a lot of economic benefit and things like that. But there’s also this, you know, potential harm it can can cause as well.
00;07;22;14 – 00;07;29;09
Speaker 1
So I thought that I was always interesting to me and that is obviously done a lot because that’s kind of why research now is so.
00;07;29;09 – 00;07;51;22
Speaker 2
Yeah, sure. Is there a fair amount of that understanding there within the Institute that, yes, this is an industry that typically it’s portrayed as an industry that’s about fun and excitement and things like that, but also on the other hand, recognizing that there is a potential harm that exists.
00;07;51;25 – 00;08;17;07
Speaker 1
Yeah. I mean, from our standpoint, I mean, everyone who works there or what we do, we’re very, very cognizant of that. I think it’s a very strong narrative across the industry in general. You know, I think, yeah, maybe there’s pockets of maybe not talking about it enough, but I think generally speaking there is acknowledgment of that. And certainly here we definitely appreciate that.
00;08;17;13 – 00;08;40;18
Speaker 1
And I mean, a lot of our stuff is focused on that. Like we we run the Nevada public gambling projects Institute and that attracts people in treatment. So that’s a very specific kind of that, you know, research project problem gambling. But as I said, we do lots of other things as well that when we’re doing those other things, we’re very cognizant of putting the safeguards in place, firewalls in place.
00;08;40;18 – 00;08;45;02
Speaker 1
So you know, where we’re called this at, all those potential methods.
00;08;45;03 – 00;09;13;01
Speaker 2
Okay. All right. That’s great. So let’s let’s shift gears a little bit and talk about where your focus began as you approach to your PhD program and your research where that started. If I understand correctly, it took a turn at some point. And maybe turning back to kind of the original area of research that you were interested in studying.
00;09;13;03 – 00;09;16;18
Speaker 2
So can you just tell us a little bit about that?
00;09;16;20 – 00;09;41;23
Speaker 1
Yeah, let’s go back so go back a little bit further, actually. So I did my master’s here also at UT and that was actually, as I said, I k when I was interested in the business and working for casinos and things. So my master’s thesis was actually on casino slot floor optimization. So. So how can mathematics help in terms of optimizing the slot floor now?
00;09;41;23 – 00;10;05;14
Speaker 1
Like what? Which machines did you have on the floor? What kind of combination of machines? So that was like kind of more business orientated obviously. And then I worked in industry after that. After about five or six years at industry, I got interested in like health and public health, but not specifically about gaming. I was interested in nutrition and lifestyle and that kind of thing.
00;10;05;17 – 00;10;25;26
Speaker 1
And I had the like some little forays into a startup company around that. We don’t have to talk about that because it’s not gambling related by mentioning it, because what I went back to do my Ph.D., I very much wanted to. Yes, study gambling, but then start like kind of weave in this interest in public health and health and wellbeing that I had.
00;10;25;26 – 00;10;50;23
Speaker 1
I wanted to be that into like a study on something in gambling. So I originally set out to study shift workers, which would nothing to me at the time because I was interested in circadian rhythms, Vitamin D, how these things can affect your health, and maybe the possibility of how it could lead to some or maybe being more susceptible to risks such as gambling addiction or something like that.
00;10;50;29 – 00;11;15;10
Speaker 1
So that was something I was really interested in on the onset of my Ph.D. Unfortunately, code, it happened. And studying something like that was already possible because I wanted to actually study workers who were working right. And during COVID, people weren’t working. So instead what happened was we initiated a group initiative and called the Payments Research Collaborative. Now, this was quite timely, right?
00;11;15;10 – 00;11;35;24
Speaker 1
Because if we all remember during COVID, we were doing anything and everything to try and mitigate disease transmission. And one of the things in the gaming sector was, okay, we need to move to cashless and also around that same time, online gaming was also exploding as well, things like that. So there was all this focus on digital payments.
00;11;35;27 – 00;12;15;06
Speaker 1
So for my Ph.D. research, what I looked at was kind of this intersection between payments modernization, which is basically the move from cash to digital payments methods and what does that mean for gambling and responsible gambling. So that was like the focus of my Ph.D. research. Obviously, with this payments technology comes a lot of data. So also during APAC, I looked at how machine learning, which is basically getting insights from huge amounts of data, how could that be leveraged with payments data to kind of give us some insight about responsible gambling and potential markers of gambling harm?
00;12;15;08 – 00;12;31;05
Speaker 2
Okay. So what did that lead to in terms of discoveries and things like that? What if we glean from that from that base of knowledge that exists? They’re tracking the payments.
00;12;31;08 – 00;12;52;25
Speaker 1
So that the data we had access to was like kind of cutting edge gambling specific Venmo or payment, whatever it is. So you basically transferred money from your bank account to this wallet and then you could use that wallet on an online merchant or in a casino to deposit money onto the machine or onto the website. So all we could see really was deposits and withdrawals.
00;12;52;25 – 00;13;14;19
Speaker 1
We didn’t see bets, right, Which is typically what a lot of the work that has been done in the past or might data analysis and machine learning, a lot of it is looked at the better information. So like how much did someone bet how often did they bat, what games did they bet on? That was a kind of a not so much analysis done on this kind of higher level.
00;13;14;19 – 00;13;42;03
Speaker 1
Just the deposits and the withdrawals that are happening. And so we focused on that. And it was quite interesting what we found, because it looks as though simply from just those deposits and withdrawals is you can actually extract some behavioral patterns or markers that could indicate someone is perhaps someone you could monitor a bit more closely. It wouldn’t like you wouldn’t be able to diagnose someone for maybe sort of the base of their data.
00;13;42;05 – 00;14;08;12
Speaker 1
That would be very difficult. But you could perhaps identify clusters of people who would warrant further monitoring. So so that’s kind of what we found, I think is quite important because it shows that payment providers in the industry maybe have an onus of responsibility here. Right. Right. And maybe then that maybe financial institutions, because your bank can see your deposits and withdrawals to gambling merchants wherever.
00;14;08;12 – 00;14;18;10
Speaker 1
Right. So I think it’s important because it shows that we can use that kind of data to identify people who potentially could worried by the monitoring.
00;14;18;11 – 00;14;41;01
Speaker 2
Okay. So you’re saying then that that you can extrapolate from that data then there are certain patterns that certain individuals exhibit. Those who are potentially problem gamblers have a very definitive set of behaviors when it comes to. Yeah. Okay.
00;14;41;04 – 00;15;11;27
Speaker 1
So it’s also like I’ll go to like the specifics. What we found. So we use something called cluster analysis, which is basically trying to identify clusters of different groups of people. Now, now in our dataset, we identified five different courses. Two of them were very big clusters that basically composed of the majority of people in our dataset. I think like I think it was about 90% were in these like what we called low risk or minimal risk clusters.
00;15;11;27 – 00;15;23;24
Speaker 1
They were, you know, casual making a few deposits, maybe lost a couple of hundred bucks over the course of a year. So we did really we identify those are a kind of the minimal risk. But then we.
00;15;23;24 – 00;15;28;10
Speaker 2
List probably less frequent. Yeah, that’s okay. All right.
00;15;28;11 – 00;15;55;11
Speaker 1
Yeah. Occasional occasional spenders, whatever it was. And then but that was the three clusters that were the other 10% of people that their behavior was very different from those that that majority of the population they had. Like higher frequency of deposits, higher declines, like a lot of their transactions were declined maybe due to insufficient funds or maybe they reach their deposit limits.
00;15;55;14 – 00;16;19;23
Speaker 1
We saw a low withdrawal amount, so they didn’t withdraw as much as the majority of the population. They also had a deposit amount variability like the amount they deposited was know maybe 1110 to 1000 to 100 to 500. It was very, very okay. So it was like those kind of markers that we found amongst this very small population.
00;16;19;23 – 00;16;21;20
Speaker 1
It was about 10% of the population.
00;16;21;20 – 00;16;52;27
Speaker 2
Okay. So I guess you do start to make some assumptions based on what you’re seeing there then, because when you’re telling me that the amounts of deposits or the amounts of withdrawals are fluctuating wildly immediately, I think, okay, this is somebody who’s taking money that that they come in contact with. And however much they come in contact with that’s going to they’re going to maximize their deposit.
00;16;52;29 – 00;17;00;20
Speaker 2
So whether they’re getting $1,000, they put it in or they come across $20, they still put that in.
00;17;00;23 – 00;17;24;08
Speaker 1
That could definitely be a hypothesis that could be bad. So, yeah, this is this cost of analysis approach is certainly exploratory and it kind of gives us this information and then we can form further hypotheses on and then you can do more research to test those hypotheses. So I like that example you gave me. yeah, maybe this means that someone’s getting any money they have in depositing it.
00;17;24;10 – 00;17;47;21
Speaker 1
Let’s go ahead and test that now at another study. Validate that. So yeah, we can make lots of assumptions based on these final that none of them could. Basically we could in on this analysis, say that that is definitive. Obviously, more research would have to be done. But I would say that’s invalid hypothesis to make. Okay. To say 100% true would be incorrect, but I’d say it’s a valid assumption.
00;17;47;25 – 00;17;48;20
Speaker 1
Yeah.
00;17;48;23 – 00;18;10;22
Speaker 2
Okay. Yeah. So, so so then you’ve got this set of data. Is is that where it ends or have you, have you done some additional, you know, tag on or tangential studies based on this. Based on the original research.
00;18;10;24 – 00;18;32;22
Speaker 1
Yeah. Yeah. So that obviously we, we got a lot of data. So I looked at a small subset of this data for my PHC. I recently had, we really had a PhD student and his name is now Dr.. I will call him Dr. Piyush Pratik. So he recently graduated for his dissertation. He also looked at this dataset. He also did some cluster analysis.
00;18;32;22 – 00;19;04;03
Speaker 1
But what was interesting with his cluster analysis, whereas I didn’t my on the whole one year dataset, he did his throughout time, so he created clusters throughout time. So cluster for one month to month, three month for throughout the year. And that we kind of track people through through time. So maybe someone starts in that low risk cluster, but then after two, three months, they moved into that higher interest stuff with the very interesting.
00;19;04;03 – 00;19;35;17
Speaker 1
So that that dissertation is going to be probably out soon for people to see. I’m really excited for him to share that work with the world. I think we have plans to maybe apply that kind of thinking to some other datasets. We have. We benefited from a nice part partnership, collaboration. Academics are very sensitive to the ways they use when they talk about work study, but we’ve been working with the Department of Trust in the UK.
00;19;35;19 – 00;19;50;07
Speaker 1
They clearly supported us by giving us some access to open banking data in the UK, which is really amazing. Open banking is something that kind of the UK and the EU have pioneered can based.
00;19;50;09 – 00;19;56;00
Speaker 2
Can you give us a definition of open banking because it’s a unique term.
00;19;56;03 – 00;20;21;12
Speaker 1
Is so I just know it doesn’t exist here in the U.S. yet, but it might in a few years. So open banking, the whole idea is that it puts the control of your bank data in the hands of the consumer. So the consumer has control over who gets access to their banking data. Now, when I say banking data, that means, you know, you have a Bank of America, Wells Fargo Chase account.
00;20;21;14 – 00;20;48;23
Speaker 1
Those transactions in your statement, you have control who can access that data, because at the moment in the U.S., it’s pretty much the bank, the kind of decides who gets access to that data. And the UK, on the other hand, you could say apply for a new car loan, maybe that no provider is like, okay, I want to assess your, you know, your ability to to take on this loan by open banking.
00;20;48;23 – 00;21;12;28
Speaker 1
So then the user can say, okay, I’m opting in to this open banking network and I’m allowing this loan provider to access all of my bank account data from all of my bank accounts. So then that line provider can have a stronger assessment of my financial health well-being, okay, vulnerability. And it can give that lender a better idea in terms of that person’s financial health.
00;21;13;00 – 00;21;33;28
Speaker 1
Now, this could have really important implications for gambling, right? Because if someone signs up for online gambling website and then they opt in for open banking, perhaps you could then assess their risk level based on their prior behavior or whether that’s gambling or financial behavior. Okay. Is that your destination? Yeah, yeah.
00;21;34;00 – 00;21;46;28
Speaker 2
Yeah. No, I kind of understand what what you’re getting at there. I guess I struggle a little bit with the, Well, I guess we. We do that via.
00;21;47;00 – 00;21;48;03
Speaker 1
Right. Privacy.
00;21;48;05 – 00;22;05;05
Speaker 2
yeah. The privacy of it. For one, it does make the individual feel. I, I would think that you have some means of control over who’s accessing that information, whereas here it’s pretty much shared pretty freely.
00;22;05;07 – 00;22;24;16
Speaker 1
Yeah, well, what, It’s not in your control, right? You don’t really have a say who you can have access to it or nor is this the bank’s decision. Hey, here. Really, when you opt in in for this in the UK there’s obviously like this bunch of small print and T and C’s, right? So I mean, who’s going to read all of this when they’re opted in for the banking big.
00;22;24;16 – 00;22;45;11
Speaker 1
I do that but you know I think there’s a lot of benefit that can be had with open banking. I think there’s a lot of cool tools and apps and and there’s lots of work going on in the responsible gambling space, gambling protection space in the UK around this technology. The UK Gambling Commission is really looking at the data to see how it can help support their affordability checks.
00;22;45;13 – 00;23;01;29
Speaker 1
So in the UK, I’ve proposed these affordability checks where if you hit certain spend levels, operators have to check that you can afford to gamble that much money. Okay, so Open back is being looked at to support that kind of infrastructure. Okay. Which is interesting.
00;23;01;29 – 00;23;15;08
Speaker 2
Right. So, so that’s how your partnership is shaping up then with the UK banking system is those are the types of things that you’re exploring based on this data set.
00;23;15;10 – 00;23;42;02
Speaker 1
Okay. So yeah, as I said though, and so the data that we got is kind provided by a company called Department of Trust to have a solution that that kind of doing this affordability check stuff with. But they provided us with an open banking dataset and what we’re interested in looking at well, what I’m interested in looking at really specifically is what is the relationship between financial harm and gambling involvement?
00;23;42;04 – 00;24;12;02
Speaker 1
And I know there’s lots of harms that can be experienced by someone who gambles too much, right? There’s the financial harms, there’s the psychological harm, there’s maybe relationship disruption, disruptions to their work that I think there’s a real argument, and this has been written about in the literature a lot by other very well-established researchers, that financial harms are perhaps the most important, where you’re looking at all of those hard because they could act as a trigger.
00;24;12;02 – 00;24;40;09
Speaker 1
Right. And they’re very that blatant that they’re like, if you lose loads of money like that, that’s evident in data. You can see that. And then that could act as a trigger for other things, i.e. lose your money to buy a house that’s going to have effect with your personal relationships. So either one of so I think there’s a real argument to say we need to hone in on identifying what this financial experience of harm is.
00;24;40;11 – 00;25;06;07
Speaker 1
And I don’t believe for my knowledge, there’s really been a good study on can we look at this data to see if there’s any relationship between the experience of financial hall vulnerability and gambling? Because because of what we what can we look at in a bank statement? you’ve been overdrawn this much. You’ve missed your mortgage payment. you’ve got load make ten different layers on all different people.
00;25;06;09 – 00;25;13;04
Speaker 1
What is that, Any relation between that and gambling and which way is the relationship. So that’s something I’m really interested in looking at.
00;25;13;04 – 00;25;50;07
Speaker 2
Okay. I think that all of this is very fascinating and it’s interesting to me that that there are these types of studies going on. How is artificial intelligence playing into the role of capturing and analyzing these large data sets that you’re you’re currently building? Is it something that that you see is being leveraged appropriately, nefariously? I would think it could go one of two directions.
00;25;50;09 – 00;25;59;16
Speaker 2
When you start applying a AI and there’s there’s got to be an ethics component of that involved here. Can you talk about that at all?
00;25;59;18 – 00;26;24;27
Speaker 1
Yeah, 100% go out. That’s all I talk on at the National Council on Problem Gambling code. Also I would say yeah, I can talk about that. So yeah, to your point, I mean I think AI holds a lot of power here. I as I said, I use cost analysis on that data. Whether you consider cluster analysis, a machine learning approach is, you know, your personal preference.
00;26;25;01 – 00;26;51;09
Speaker 1
It kind of fits into what we call unsupervised machine learning. But yeah, a lot of the work, at least in gambling with like these large datasets, we’ve again begun to get access to, has leverage machine learning methods or more traditional statistical methods to gain insights on this data. So that’s what’s been the bulk of applications at least the past decade or two.
00;26;51;11 – 00;27;22;07
Speaker 1
Now with the other set of generative AI since, you know, the release of chat CBT Right. I think that is kind of changing the landscape a little bit because now now we’re talking about when we talk about I think people might is always directly go to chat CBT and large language models that’s really where all the focus is right now, which is a big paradigm shift I think from pre 2020 to what I was all about.
00;27;22;07 – 00;27;50;00
Speaker 1
Ready machine learning, deep lie they go in that way, stuff going on, which then eventually led to this explosion of generative AI and language models which have just huge applications. So yeah, you I mean this is something we looked at with a study that we just recently got published or looking at what the AI and ethics mean, what is AI and ethics mean and the gambling sector, because you’re absolutely right for what it can be used for a benefit.
00;27;50;00 – 00;28;25;14
Speaker 1
Maybe it can help with protecting players and doing all this predictive analysis in terms of identifying someone’s susceptibility to harms. But on the other hand, of course it could make marketing and game design and all of those things way more powerful, way more efficient. What happens when we literally have aged away today? Games, Microsoft a couple of months ago released a language model where you could literally enter a quote about a video game you would like to be created and then this thing would create that video game.
00;28;25;14 – 00;28;25;28
Speaker 1
00;28;26;01 – 00;28;26;10
Speaker 2
Wow.
00;28;26;10 – 00;28;49;00
Speaker 1
So what what does it mean for gambling when we could do that with slot machines? I want to create a slot machine with X, Y and Z, and, you know, it just creates it. And maybe even in real time based on player preferences. What is that? What does that mean in terms of engagement risk? You know, very interesting questions.
00;28;49;02 – 00;29;04;13
Speaker 2
Wow. Yeah. I’m sorry. Yeah, I didn’t realize that that capability is out there. I shouldn’t be surprised just because it seems like the pace of AI, it just is uncontrolled.
00;29;04;13 – 00;29;33;29
Speaker 1
So. So this idea, what you’re talking about here with the pace, there’s this theory called the singularity, and you heard of it now. So so is the book you need to read if you want to find out more about AI is by Ray Kurzweil. It’s called The Singularity Is Near, and it’s a very big book. But in general terms, what he’s talking about and I think he wrote the book like 20 years or three years ago or something, I can’t remember.
00;29;34;02 – 00;30;01;14
Speaker 1
But what he’s talking about is that, you know, there’s this line of human intelligence. There’s just been gradual over time. There’s a steady increase in human intelligence over time. Right. So that line is fairly steady and straight. Now, let’s take a look at the line of AI intelligence, like let’s look at that line. And I read that line on the same way that human intelligence.
00;30;01;14 – 00;30;34;17
Speaker 1
Right. And it’s very low. It’s even underneath human intelligence for a lot of the time. But then the kind of slices slowly climb up, up and up and up until it’s almost vertical. Right. Because once we hit AGI, which is artificial general intelligence, that means when we reached AI, that is that the same level of intelligence as a human that is going to trigger exponential growth of AI because it’s going to be able to create even smart A.I. and that pace of change is going to shoot up.
00;30;34;20 – 00;30;46;02
Speaker 1
And that’s the singularity, okay? Because we’re not going to be able to control this exponential growth. So, yeah, yeah, scary stuff. It could be scary. So then you be, you know, with everything that sounds like doom, doomsday is the.
00;30;46;04 – 00;30;46;18
Speaker 2
Right.
00;30;46;21 – 00;31;08;23
Speaker 1
Thing. So whether this is going to be great for humanity, that’s going to lead to all like disease free, no one’s going to have to watch because I can just do all the work for us and we can live in this like beautiful harmony. But in terms of gambling, I think, you know, what we really have to be cognizant of is, yes, it holds these benefits, but there’s also these risks as well.
00;31;08;25 – 00;31;32;02
Speaker 1
And I think, you know, one of the strong things that came out of our research was about these safeguarding strategies, about around using AI. And I think there’s like three key things to consider. One is like collaboration. So I think that does have to be when organizations are using AI for marketing, for engagement, for game design, for whatever it is.
00;31;32;02 – 00;31;55;26
Speaker 1
I think it’s important for those organizations to include a diverse set of stakeholders in that decision making teams. So if there’s like someone trying to decide to use AI for a new game design, bring in the responsible gambling person to enter the conversation so that they can highlight what their concerns might be. Right? Don’t develop it. And just in one department, you know, I think that’s going to be really important.
00;31;56;01 – 00;32;23;21
Speaker 1
What can regulators do? Do we need new regulations around this or can we or are gambling regulations already stronger or not? And education, I think, is going to be really important for for this collaboration to work. Someone who’s an expert in responsible gambling is also going to need to know how to talk about AI. They’re going to at least need to know the basics to talk to someone like a developer why those two people need to talk to each other.
00;32;23;24 – 00;32;25;05
Speaker 1
So I think that’s what needs to happen.
00;32;25;05 – 00;32;55;19
Speaker 2
Yeah. Do you do you see having the perspective as a UK perspective? And then here in the US where we’re a federated, we have multiple states, every state has its own regulation, its own rules. What’s your sense of how much of a challenge it is here versus the UK, Australia, other nations that are big into gambling as well?
00;32;55;21 – 00;33;14;24
Speaker 1
Yeah, it’s such a good point. And I was actually I was actually at another talk at the Commons throughout last week and someone had asked about this. A very excellent point, the one you just brought up that like you know in the UK we have the UK Gambling Commission which is they, they, they, they regulate it on a national basis.
00;33;14;24 – 00;33;35;21
Speaker 1
Right. If that agency in the US it’s all done state by state. And you know what she was saying was that we really do perhaps need a federal level agency if there’s going to be some real change happening. And I think that was quite a poignant thing to say because it is clearly very complicated. I still don’t understand it.
00;33;35;21 – 00;34;00;23
Speaker 1
It was like very fine to me when I was here and I was like, I don’t think I’m going to bother trying to understand this side of, you know, I obviously, after my understanding a little bit. So but it is I mean, it’s hard, isn’t it, because every state is very different. And yeah, I do think for for what it means for my regulations and the appropriate safeguards in place, I do think it’s a barrier.
00;34;00;27 – 00;34;04;12
Speaker 1
Right. And one that does need to be overcome.
00;34;04;14 – 00;34;37;13
Speaker 2
Yeah. All right. So where where do you go from here? And in terms of your your next round of of research, where is your interest kind of taking you as you move forward? Because now you’ve got now you’ve got the entire department. So you so you really have this opportunity to start pulling levers and, and maybe kind of guiding someone and providing mentorship to young PhD candidates and where they’re Yeah.
00;34;37;15 – 00;34;41;19
Speaker 2
Where there might be some interesting things for them to research.
00;34;41;21 – 00;35;03;07
Speaker 1
Yeah, No, you’re totally right. And it’s really great. You know, one thing that’s really great about the International Gaming Institute is that we’re not actually tied to a specific department or college. So typically with a research institute, it might be tied to the School of Psychology or the School of Business. We’re actually just part of the division of research here.
00;35;03;09 – 00;35;31;19
Speaker 1
So that’s a really great thing because that means I can work with anyone. So I’ve worked with computer science students, hospitality students, lecturers in psychology department and in the business school. So and that’s really good for something like gambling, right? Because it is so multi-disciplinary, like, like I say, I was interested in shift work and health, right? I’m interested in data science.
00;35;31;21 – 00;35;55;25
Speaker 1
So as all of these things are at the intersection of very different fields. So yeah, I’m really excited about some of the stuff we have going on of has that, you know, we’re always looking for funding opportunities, so I’m trying to put in some application with some different funding agencies. NSF, ICG have really been good at issuing a lot of funding opportunities recently, so I hope to go for some of those.
00;35;55;27 – 00;36;24;27
Speaker 1
But one project that we recently got funded through a go ahead and you said, so go Ed, is the Google MIT Governmental Organization of Economic Development. They work with the U. And OB Economic Development Department, and we got a grant from them and it’s industry matched with an industry partner. But we basically got funding to develop a chat bot for sports betting, which we’re really excited about.
00;36;24;29 – 00;36;52;22
Speaker 1
And the whole idea, yeah, the whole idea around it is to see if a chat bot could help someone learn about the basics of sports betting so that they understand what they’re going into. They understand the product better, they know the bat types, but also kind of help people learn about responsible gambling behaviors, like the importance of setting a budget, understanding odds correctly, not having any misconceptions about winning that kind of thing.
00;36;52;22 – 00;36;58;15
Speaker 1
So we’re going to develop this chat bot and assesses ability to learn about those things.
00;36;58;15 – 00;37;17;21
Speaker 2
So yeah, I’d be really interested to hear the progress on that one because I think that’s that’s something that’s definitely needed, can be extremely beneficial in early detection and, you know, potential harms that individual may be experiencing.
00;37;17;21 – 00;37;35;21
Speaker 1
Because look at the education content right now. Like if you go to like a sports betting website, I mean I’ve looked at them and there’s like an FCS page or something, you know, and I don’t know the ins and outs of the customer experience and how they get get their information, but you know, who’s going to visit those RFQ pages, Are they?
00;37;35;22 – 00;38;03;07
Speaker 1
You know, so I think, you know, potentially a chatbot could have a bit more of an impact in making sure people are gambling literate. Do they understand or like an entity, Right. Yeah, like similar to like financial literacy, like, you know, I’ve got kids, you know, as they go through that adolescence, I want to make sure they understand how to manage their finances, Like when they go out into the world on that, they can have this level of financial literacy to navigate the world.
00;38;03;09 – 00;38;15;04
Speaker 1
I think the same is true for gambling literacy. When you know if someone is interested in gambling, let’s make sure they have a gambling literacy at an appropriate level. So they can understand what they’re going into.
00;38;15;05 – 00;38;39;29
Speaker 2
Yeah, for sure. And to if there’s a there’s the possibility of many of emerging to the information that you’re taking on or learning through the payments that are, you know, the payment data of an individual and marry that with the chat bot as well, then you’ve got something that’s pretty powerful.
00;38;40;06 – 00;38;53;02
Speaker 1
Yeah, I can imagine like or like even the gambling dates are like are you on your sports betting website? Why. chatbot, how much did I lose last month? you lost this month. How about you set? A limit.
00;38;53;04 – 00;38;54;04
Speaker 2
Right.
00;38;54;07 – 00;39;34;21
Speaker 1
Under that and you know you that might be some customers who are more likely to engage in something like that. But I think you know this the the profile of a sports bettor you know I don’t think it’s any surprise that you know the majority of sports betting young males right at the top. You know that demographic might be more likely to engage in something like a chat bot and and potentially it may be if it also provides benefits to making them a smarter, better, better right but it and then you we when the responsible got mixed up into that experience maybe it could have like you know that kind of dual benefit.
00;39;34;21 – 00;40;14;19
Speaker 2
Yeah interesting. Yeah it’s interesting I mentioned to you when we were together out in San Diego, Dr. Joshua Grubbs at University of New Mexico, and one of the areas of study for him is looking at the demographics of sports betting and things like that. I think I think there’s probably an opportunity there, as you suggest, to help people understand what they’re getting into a little bit more, because sports betting, you know, you can be the greatest sports knowledge base, but that doesn’t necessarily make you a better, better.
00;40;14;19 – 00;40;20;07
Speaker 2
Yeah, right. Yeah. You’re still you’re still dependent on the odds that exist.
00;40;20;09 – 00;40;43;05
Speaker 1
So. Right. And I think as well there’s got to be this risk with sports people who are into sports like they’re like, I’m so knowledgeable. Like I know everything there is to know about this school. And then they think maybe that translates to being a successful school is better, right? Because by that maybe they have no idea how like odds work and things like that.
00;40;43;05 – 00;41;20;02
Speaker 1
Exactly. So I think that’s a real waste. So, yeah, hopefully maybe this chatbot could be the the big thing that that helps us out. But yeah, that’s just one project that I’m really excited about and we’ll see where that one goes. And we’ve got some other projects going on, but that one specifically is great because again, going back to the multi-disciplinary nature of this, so this project, it’s always got myself, he’s in that AGI, I’ve got a PhD student who is coming to RPA and lighting and technology in the lighting and technology department and first year had Samantha Wells.
00;41;20;05 – 00;41;41;19
Speaker 1
She’s going to be working with us on that project. Then I have a guy called Richard Young who is a he’s an instructor in the business school. He teaches a class on large language models and big data. And so he’s going to be helping develop the chatbot. He’s also doing this Ph.D. in computational neuroscience, and he has a full time job.
00;41;41;19 – 00;42;02;07
Speaker 1
So I don’t really know how he has over everything, but there’s him. And then we also have a a consultant for the University of Waterloo in Canada who is a data science expert, Dr. Lucas CoLab. So you see, this is great. So we have a gambling castle myself, lighting and technology, business and computer science all working together in Kodiak.
00;42;02;07 – 00;42;03;06
Speaker 1
So it’s just really cool.
00;42;03;06 – 00;42;12;15
Speaker 2
Yeah, that is cool. Well, I hope. Yeah. Yeah. Again, I hope you’ll keep me posted or allow me to check in every now and then and see how maybe we.
00;42;12;15 – 00;42;14;22
Speaker 1
Can be with maybe we can do a show on it in a year.
00;42;14;22 – 00;42;18;17
Speaker 2
I would love that. I would love. That’d be a good follow up.
00;42;18;19 – 00;42;22;13
Speaker 1
Yeah, we can. We can I do it on, like, test of it?
00;42;22;21 – 00;42;26;09
Speaker 2
Perfect. I like it. All right. Okay.
00;42;26;14 – 00;42;30;16
Speaker 1
So if I ever committed myself to the awesome show.
00;42;30;19 – 00;42;45;22
Speaker 2
I’m going to hold you to it because I appreciate the conversation. Is there is there anything additional any parting words, final thoughts that you’d like to include here?
00;42;45;25 – 00;43;00;22
Speaker 1
No, really, I just want to say really thank you to you to you, Shane, for having me on. I think this podcast is a great idea. I think we need more of them and I’m just happy to contribute to this great content you’re putting out there. So they’re great stuff. That’s all I’m going to say.
00;43;00;23 – 00;43;02;05
Speaker 2
My pleasure. Yeah.
00;43;02;08 – 00;43;14;14
Speaker 1
All right. And of course, if anyone worth the contact me there, they’re happy to wait. Looking for people to work with more students, Other faculty, industry partners. Yeah.
00;43;14;18 – 00;43;18;19
Speaker 2
And. And how would they find your class best?
00;43;18;19 – 00;43;29;25
Speaker 1
Is email ready? Kazuo Dr. Hari in that you and I’ll be edu. I’m also on Meet ten. Okay. I’m I’m usually pretty responsible link to it as well so what that.
00;43;29;29 – 00;43;36;25
Speaker 2
We’ll drop both the your email address and through your LinkedIn profile in the show notes.
00;43;36;28 – 00;43;39;20
Speaker 1
Thank you very much. Thank you.
00;43;39;22 – 00;44;14;02
Speaker 2
We love hearing from you. So please take a moment to like, share and comment on our podcast. You can reach out to us directly via email at Wage or Danger at Gateway Foundation. Talk. Look for us on Facebook and Twitter at Recovery Gateway, on LinkedIn, at Gateway Dash Foundation, or through our website at Gateway Foundation. Dot org Wager Danger is supported through funding in whole or in part through a grant from the Illinois Department of Human Services and the Division of Substance Abuse Prevention and Recovery.
00;44;14;05 – 00;44;30;02
Speaker 2 And remember, Recovery is a lifelong process. If you are a family member struggling with a gambling problem, call Gateway at 8449753663 and speak with one of our counselors for a confidential assessment.
