Welcome everyone to this evening's installment of Divine Mercy University's webinar series for mental health awareness month.
I see, people are still gathering, joining the call.
I'm going to, share just a little bit about our presenter this evening.
Well, first, our our series has a real focus on the intersection of mental health and technology.
It's entitled humans over algorithms.
And I am to make it personal to start off.
I'm Brian Lohman, alumni coordinator here at Divine Mercy University.
I've been here, about nine months and actually come from a technology background myself as a corporate recruiter within the government and commercial world.
And I also am in the master's in counseling program.
So I have an eye toward becoming a clinician down the road.
For this series, we've already had a thousand participants thus far.
We're only halfway through.
We have, after Jerome this evening, we have May 28, Kathy Erwin.
She is one of our, counseling, professors.
And then, June 3, Garrett Boyer and Laura Cusimano.
Doctor Boyer and Doctor Cusimano, they met here at DMU in the PsyD program.
So, they're going to be doing a tag team as a husband and wife couple.
So they are our last two.
This evening, we're really grateful that Jerome is gonna be joining us.
He's based in the San Francisco Bay Area and received his bachelor's in computer science at University of California, Riverside and his master's in psychology here at Divine Mercy University.
I really think that the intersection of Jerome's expertise and his passion are a are a great fit for this midpoint webinar, just marrying technology and and faith.
He's an engineering leader and engineering builder.
He works really at that intersection of, artificial intelligence, human behavior, and real world systems.
He's about a decade of expertise in, software engineering and leadership.
He's led teams all the way from early stage startups to large scale organizations, building products that serve literally millions of users.
He's also contributed to initiatives at the intersection of technology and the Catholic faith through collaborate excuse me, collaborations with Sacred Spark, Catholic Polytechnic University, TABELLA, and other mission driven organizations.
His work really focuses on that realm of promoting trust, intentionality, and authentic human connection in an increasingly digital world.
And as that technologist and a person of faith, he's really interested and has a passion for the ethical and psychological implications of AI, namely, you know, how systems influence attention, motivation, identity, and how we can really design technology that respects the the dignity of each and every human person.
He's a great example of somebody who is in the world, but not of it.
He's working in a technical corporate secular realm, but also with a foot in the the church with his work.
And it's just a great witness to see him, a face of DMU out in the world, and we're really overjoyed to welcome Jerome as he shares his his expertise, his passion, and his faith, as he speaks on the theme of, augmenting care, not replacing it.
In one technical note, there'll be plenty of questions, I'm sure, which, come to mind, that Jerome is happy to address.
He and I chatted that we would like to do that throughout.
So, if there's a point he makes that you want to clarify or you want to follow-up or you just would like to comment, please, pop a note in the chat box and I will be sharing that with Jerome so he can respond to it throughout.
So with that, let's hand things over to Jerome Placido.
And, welcome, Jerome.
Great to have you.
Thank you.
Thank you, Brian.
And, thank you, everyone, for joining.
Super excited and so happy to be here.
As as Brian mentioned, I'm I'm a proud alumnus of Divine Mercy University.
In 2020, I completed my master's of science in psychology.
And, you know, I've been in in technology for ten, fifteen years, working in software and engineering leadership.
Those who know me know I'm always trying to marry and see the interesting intersections between the two things I'm very passionate about, which is technology and my Catholic faith.
In more recent years, my work has focused a lot on AI systems, on operational scalability, on data quality, how we evaluate AI to ensure that it's safe, it's accurate, that we're doing the right things with it.
And more practically, just using a generative AI.
I have my own AI bot that I stood up as a weekend project.
His name is Leo.
He sits here on my desk, and he helps me to schedule meetings, answer emails, do research for webinars, things like that.
In my current role, my my day job when I'm not AI Batman at night, my current role is at Turing.
I work on initiatives related to improving quality and reliability on AI driven workflows and operational systems.
Outside of that professional work, I experiment a lot.
And I, as Brian mentioned, I I, work a lot with a lot of mission driven Catholic organizations, consulting and and helping them leverage these technologies in a in a in a meaningful way.
I do want to note that today I am speaking independently, not as a in an official capacity for my employer or any affiliated organizations.
These perspectives that I share and opinions are my own.
And I also just want to take the time now because I've experienced so much growth, and I'm so grateful to have been a part of a cohort in Divine Mercy University that I just want to express my gratitude for being invited to be a part of this conversation today.
So I look forward to the discussion that we're gonna have.
And there's a lot I think that I'm going to bring up that is maybe a little spicy.
But I definitely think it's worth talking about.
So, yeah, absolutely.
If there's any questions at all, like Brian had said, we'll just raise them in the chat and we'll answer them ad hoc.
So before we begin the actual conversation of what the intersection is between psychology and and health care in general, I thought it might be good to ground us in some some concepts.
So what is artificial intelligence?
Well, AI or artificial intelligence is a broad field of computer science focused on creating systems capable of performing tasks that typically require human intelligence.
Pattern recognition, decision making, these sort of tasks, when done by a computer, we consider it to be called artificial intelligence.
Within this realm of artificial intelligence, there's some other terms that we should be aware of.
And these are sort of building blocks to to help us understand what we know today in in the commercial realm realm is like chat g p t or Claude or any of those other commercial apps.
First, machine learning.
What is machine learning?
Machine learning is a lot of classification and ranking, a lot of statistics and math to help create risk and prediction models across the dataset.
So we are going to take a dataset and do pattern detection on those datasets to help predict other parts or other things about that data.
That's machine learning in its traditional sense.
It's systems that learn patterns to make data or to learn patterns from data to make decisions.
Next, is generative AI, and this builds on machine learning.
So instead of just predicting outcomes, a, b, c, and what's next is d, it also generates new content like text, images, code, or audio.
It works by learning patterns from massive datasets.
And these datasets are used to train the models.
And then it will predict the most likely next piece of information.
This is a very rudimentary way of thinking about it.
But if you if anyone has an iPhone or it's also on Android as well, but, autocomplete, when you say, hello, how are you?
And then at the bottom of that tab on on autocomplete, it says doing.
It's predicting what your what your next thing that you're gonna say is.
That is more likely in the machine learning realm, but it delves a little bit and helps us to to maybe see more concretely what we mean by the likely next piece of information.
So we train these models on a ton of data.
Initially, it was data across the entirety of of the Internet and then use that data to find these patterns to help predict what's the likely next word, sentence, phrase, or thing that should be generated within this model.
Hence, generative AI.
Now, conversational agents is probably what most of us have been have used or are starting to use.
It's very funny.
At my parish, we were preparing for a gala, a fundraising gala to help build our church.
And I had everyone from folks who have been retired using chatGPT to college students using chatGPT.
And so it's across the board.
A lot of people are using these things.
But what they're using really are conversational agents.
Now conversational agents take the generative AI that has been developed, and it they create a system, and maybe let's consider it a harness to help these generative AI models do more.
So it combines them with memory, with tools, with workflows and actions so that it's not just generating a response, but they can assist with tasks.
So for example, when we go and chat gpt, and we say, you know, tell me everything you know about Pope Leo the fourteenth.
It's not only gonna take the the information it was trained on, which if you remember maybe two, three years ago, was trained only up until 2022.
And so there was a limit on its world of knowledge.
Since then, they've added tools to enable it to search the web so I had more relevant information for you.
They've created a harness around these models so that they are able to do more.
Simple way to think about it is this.
We have we have machine learning that learns.
We have generative AI that creates and the conversational agents that assist and act the feet of the model.
Great.
So that's a I know it was a little little long, but I think these nuances help to dispel some of the ideas.
As soon as you know that generative AI are are the fuel of conversational agents and that it's more a statistical model of predicting what's the likely next word that the user is going to expect.
It's a lot harder to believe that these models are thinking.
And so there's a lot of nuance around the actual complexity of those prediction machines, but that is exactly what they do.
They predict.
Now, let's frame artificial intelligence against the backdrop of psychology today.
Most of you who have a background in psychology or part of the industry know this already.
And I know there's other things to be addressed, but I just want to maybe address one of the pressures here that may lead to us using and potentially misusing artificial intelligence.
Let's take a look at the math of the global mental health crisis as it exists today.
Currently, in the world today, according to the World Health Organization in 2025, there are nine hundred and seventy million people worldwide that experienced a mental illness.
That is if you stood people shoulder to shoulder around the world, we could wrap the world about 12 times.
Now with that particular burden, the need, there's also a gap.
There just aren't enough providers to serve for those nine hundred and seventy million.
Some of those because of disparity in their location.
Some of those because of lack of access.
But just in general, even where there is some access, it's still hard.
The economic cost to that, according to The Lancet, is $5,000,000,000,000 in global economic losses annually.
This the statistic, while it it shows the the large impact from a from a maybe economic standpoint, doesn't also account for the emotional toll of the suffering of nine hundred and seventy million and the lack of ability that we can provide to help them.
And there's a real bottleneck here.
In The US specifically, twenty three percent of individuals will wait over twelve weeks for a face to face care.
And the longer waits, as we know, actively exacerbate patient conditions.
This is part of the landscape that we live in today.
And so and by the way, this particular crisis, you can frame it with other parts in other industries.
And so you have this overwhelming need of something.
And so AI seems really seductive and tempting at this point because AI doesn't sleep.
It's available twenty four seven.
You can access it twenty four seven, three in the afternoon, three in the morning.
It eliminates geographic and temporal barriers.
It doesn't matter whether I'm California or I'm in London or I'm in Bangalore, India.
And it's scalable to help support isolated or marginalized populations.
In addition to that, there have been certain studies that have shown that people who have used some of these commercial chatbots have had a high sense of zero judgment zones.
This is mainly because in speaking with a computer, there's less apprehension of sharing things.
And so there's a reduced reduced social anxiety of impression management.
And then in addition to that, you theoretically could scale this to millions of users given the right infrastructure, given the availability of of the, you know, compute.
You could theoretically scale this to address the gap.
And there's a near zero marginal cost for the information delivery.
Now all of this makes it really attractive to say, hey.
Let's use AI, which says these really nice and pretty things to answer and address this gap.
Now, unfortunately, this gap exists today, and this is the world that we live in.
And there are already individuals today who are using commercial chatbots as a quote emotional sanctuary.
And that is the term they have used in a study done in 2024 to describe their interactions with AI chatbots.
So this isn't this isn't a theoretical.
People are going to these chatbots at today, to seek support, empathy, care, and even to triage difficult situations, like breakups with a boyfriend or girlfriend, estranged relationships with fathers, and finding a certain sense of comfort in these interactions.
So that is sort of where we're at today.
Now, one of the things I love about our faith in the Catholic churches is that the timeless teachings of the church have have been able to been projected against the idea of artificial intelligence.
But we're definitely deepening in that understanding.
And Pope Leo has definitely been leading the way, especially since he entered into his pontificate.
I actually used AI just a couple nights ago, and I asked it, I asked Leo, my my chatbot, to do a deep research and pull all of the resources of all the different times Pope Leo has mentioned AI in any any particular address, whether it's a address for World Communications Day or address to the participants of any jubilee of governments.
A lot of these things and it pulled back a ton and he has spoke a ton about AI.
One of the things that he said, and he has acknowledged that AI is not going anywhere.
And it's not that it's a technological problem, but more so that it's an anthropological problem.
And what he means by that is that our understanding of the human person needs to needs to be firmed firmed up and and and bolstered so that we can approach the use of this technology in a certain way, especially when you have a technology that makes it sound like it's being empathetic towards you.
The simulation it encroaches on human relationship death And then human memory is, he says, is generative and machines are static.
And he's just continues to try to remind us sort of the difference between these two.
He also said to a group of young people to avoid digital bubbles that weaken discernment.
And more importantly for this for this group here, he's spoken specifically to folks in health care and reminds us that care is a noble proportion is noble in proportion to fragility, and that we should maintain the patient provider relationship.
And then he urged us that AI should enhance but never replace the nobility of that care.
Now, he's it.
Unfortunately, the market and the conditions that that AI is being developed in really make it hard to create an ethical sort of scaffolding around AI.
But nonetheless, as most of you know, he's definitely trying to tackle that, especially with his upcoming encyclical, I believe, magnifica humanitas, or magnus magnificent humanity.
I'm really looking forward to the the encyclical.
I was disappointed that it was delayed because I was hoping to just comb through it and read it 10 times over in preparation for this webinar.
But maybe Brian, if you'll have me again, maybe we can discuss it further in a future webinar.
But he's definitely trying to address that.
And I think it's important because the market and the the ecosystem that AI is being created in today, its incentives for the creation and furthering of AI are more for capital gains to increase the the profits of shareholders and to increase the value of those particular private organizations.
And so when those become the sole, motivators within these organizations, or maybe not the sole, but the strongest motivators, we we we tend to, as Pope Leo has said, as Pope Francis has said, we tend to push to the side the marginalized, those who are forgotten and the weakest in our society.
And so Poplio calls for a global governance and something to help ensure the common good equity and reliability of these technologies.
Great.
Now I'd like to spend a couple minutes as we talk about just AI as a whole to talk a little bit about, some of the some of the potholes that that we may encounter in using it.
I should I should mention that this the thesis and may may not be apparent in my introduction, but the thesis is that we can and should use AI, but there are definite things that we should be aware of.
And part of my goal in this presentation is to help you to be aware of these potholes, these caveats, so that when you do use it, you're aware of when you have to dive deeper or maybe look for a different solution.
Jerome, if I could just pop in with a question on my own Sure.
To address to the the audience is, have you found, as it is with many things, not just, new technologies or, new challenges or opportunities, but, I think just within human nature that the extremes are always easier to embrace than sort of the the the via media, the middle way of salvation, if you will.
So in this realm, it's it's an easy thing to say, well, listen.
You know?
No.
AI isn't from God, but, you know, it comes from, the the hearts and minds and hands of of those who were given gifts by God.
And so, it it just needs to be There's no concerns in it.
It's just how it's ethically used.
There's nothing baked negatively into it.
But I think of the Sure.
Some of the engineers from the social media platforms who said, No, no, no.
It's not just that these things are used nefariously.
It was baked in to be addictive.
Like, that's how we made it.
So there's one extreme, which is just, well, you know, it's always gonna be good.
There's nothing negative inherently about it.
Or the other extreme to say, well, we we rejected wholeheartedly, which means that the people like you and others are not gonna be guiding us on it.
And so, do you see people sort of tending to one extreme or another versus sort of that middle way of, listen, there's guards around it, Leo's writing on it, and I'm grateful he is.
Do you find that we're just sort of trying to get our get our bearings and find that middle way?
You know, I think I think getting your bearings is the right way to really look at this.
I think people don't know what they don't know yet.
And while, for a technologist like me, I mean, the second that ChatGPT came out in 2020, '20 or yeah, around 2020, I popped it up and I had it compose a prayer.
I'm like, hey, compose a Catholic prayer for me.
And it did it beautifully.
I could even argue that maybe that was the first Catholic thing it did in the entirety of GPT.
But it's even though it's that old, five years old, it's still fairly new to a lot of the population.
So it's more of a wait and see moment for for maybe people who aren't used to using these technologies or don't know enough about it.
That being said, though, Pope Leo, in an address has mentioned that this technology is not neutral.
We can't we can't just sit here and think that it is neutral.
Not because there are nefarious things behind it, but because there is a worldview that has gone into either the development of this technology or even the the, the data that's that, the models are trained on.
And that's part of what I I plan on presenting here is that, it's not so much that it's not so much that there are sort of like, there is a middle way.
I think we're trying to navigate to find what that middle way is.
But I think that there are a lot of caveats that people may not be aware of to help them navigate to that middle way.
Does that make sense, Brian?
That's perfect sense.
Exactly.
Thanks for responding to that.
Yes.
Anybody else who wants to jump in, please.
Awesome.
Thank you.
Thanks, Jerome.
Yeah.
Absolutely.
So getting into those caveats, one of the hard things about the use of artificial intelligence in general and large language models is it essentially is a black box problem.
Even for myself who uses it as a developer, you sort of poke at it.
It says something.
You poke at it again.
It could say something completely different the next time around.
It's not deterministic at all.
And the decision logic that it makes or that it uses to say different things are really hidden because of the way that it's been developed.
It's very convoluted.
The deep learning models make it impossible to trace the exact rationale behind some of the things that it says.
That in turn used in a psychiatric or mental health setting makes it really hard to understand why something is said.
There's also a deficit in validation sometimes.
Now, there are extensive quality assurance processes that both the these organizations have in place to check that a model is saying the things within its boundaries.
And even some quality, there's a lot of quality checks even for the the training data that's going into these models now.
So but while those are there, it's impossible in the real world to really draw the right boundaries to make sure that it is not making, you know, irrelevant correlations or saying the wrong thing at the wrong time.
There's also a lack of of, or ambiguity and liability.
If something happens and we're using a chatbot in in in the mental health setting, who's liable?
Is it the developer who wrote the code?
Is it the CEO?
There's aren't any there aren't any things in place to understand when something does go wrong, who's to blame?
Now, I do wanna I do wanna share a recording.
One of the things I did to prepare for for this webinar today was and something that I do quite frequently is that I will take my thesis, my premise of whatever I'm working on this.
I do this at work.
I do this in preparation for talks.
And I and I tell AI to sort of present it back to me and try to poke holes at it and sort of play devil's advocate.
However, this time, instead of doing that, I just gave it all the resources that I was reading that I was combing through.
And I'm like, you know, I just wanna go for a run, and I'm gonna have it synthesize the data and just read it back to me in whatever way that it comes back.
And I'm gonna share that that recording now.
And this is, unprompted.
This is just it telling me sort of the the, synthesized, version of the sources that I gave it.
Imagine pouring your deepest, darkest trauma out to a therapist who never ever judges you.
Right.
A companion who, you know, perfectly tailors their personality to your exact emotional needs.
And who never gets tired of hearing you loop through your anxiety.
Yeah.
Exactly.
And who is available to talk at literally three in the morning.
Which is, I mean, unheard of in traditional therapy.
Totally.
Now imagine finding out that this profound, life changing, emotional sanctuary is actually just a string of code.
That's it.
Now for maybe the, untrained, ear, that sounds fine.
I hear a little bit of bias there.
And me knowing the me knowing the data that I put into it, which was about 60%, Pope Leo cautioning against the use of data, 40% neutral and actually some sort of like naysayers of not using data in the field of psychology.
The fact that AI took that and gave me this output, I can't tell you why it did that.
But I can tell you that it it's it seems really apparent in this particular recording that it was for the use of this and it actually said at the end it wrapped up in this this podcast that I had to create.
If an AI can perfectly mimic a loving and insightful therapist, and as a direct result of that interaction, your brain genuinely releases serotonin, your physical anxiety drops, and your depression actually fades, does it truly matter that the AI doesn't actually feel empathy?
And so now granted, none of this this is sort of just posing the question and and it's it could be considered neutral.
But I in this was surprised to sense a little bit of swaying in the direction of one way versus the other way with just the neutral resources that I gave it.
This is just an example.
I'm not saying that this has happened all the time.
I ran it again against the same set.
I had it create another another podcast and it was completely different.
It was more neutral and more balanced.
So just an example of of sort of the opaque decision logic it uses to synthesize data for us.
Before you go, we have a question from Violetta.
Give me a second.
Let me Violetta, you had had a, a point you want to make?
Hey, Violetta.
I I would like to, ask if, this, we will have access.
Like, I am a middle school and high school teacher, and I would love to be able to, share this with, my students.
We will be yes.
We are recording, and we'll be sharing this on, DMU's YouTube channel.
So, yes, please share this Y Beyond and with your students.
And and, what what, something is speaking to you about wanting to share this with them?
I'm sorry.
I I couldn't, There's some relevant points that Jerome is, discussing you'd like to share with your students?
Yes.
I think that, the information is very valuable.
And, like, the instructor is is curious about, you know, that I, being in the that I am in the classroom, they, well, the students right now, like, they are My point is that the, the district is very, concerned about how they are training us to, to be able to, teach the students, but at the same time as, I forgot the person that is presenting, it's state stating, it is very hard to compete with AI because this is open twenty four seven no matter what geographical part of the world you are.
And then it's it's like, how can you, as a teacher, you can teach and not, impart it to your students that, you know, to use their in intelligence to because right now, like, if you give them, for example, an essay or even asking a question on the classroom, they go they go to JWT to do anything.
They are not actually thinking.
And when he was sharing about, you know, that how this, intelligence is, like, it's not going anywhere, but how can they are able to protect themselves against themselves?
Because it's like they are cheating themselves.
Sure.
Yeah.
Violet, I think that you bring up a valid point.
I I do think, part of my background, by the way, I did about ten years in in education technology, and my most recent experience was, helping to sort of implement AI systems within an EdTech system.
And so for someone from the outside looking in to teachers, I my heart goes out to you.
And to navigate all this, I think is really, really hard.
I have been passionate about EdTech for such a long time and education as a whole.
I do think that some of similar to what we need to do here in psychology, some of the ways that we teach, some of the methodologies we use fundamentally have to change and evolve because AI is not going anywhere.
And I think that the challenge is on now administrators, teachers to make sure that one, these systems are safe, and two, that they continue to be aware of these caveats while also promoting the things that we want to capture within tech education itself, which is human flourishing and the growth of that that individual, both emotionally but also intellectually.
And so, yeah, I completely agree with you.
Part of me actually is eager.
I was telling Brian this earlier.
I'd love to be a student again, just to see what it's like to be a student in this AI world.
Because it is a lot easier now, for example, to study a particular subject if you have the right tools and methodologies to employ know what right tools and methodologies to employ.
Right?
Similarly, for those in psychology, when the next 20 research papers come out, it's a lot easier to intake that information now using artificial intelligence.
Great.
We had one more.
I'm not sure if you wanna make a comment.
It's because we have a few teachers here tonight.
Adriana, you were making a point that, yes, you you are in the classroom as well.
You you understand the concerns.
Did you have something you wanted to offer?
Sorry, Adriana.
I needed to unmute you.
You can go ahead if you'd like to chat.
Hello?
Yes.
Oh, well, yeah.
Really concerned because I work with neurodivergent students.
Mhmm.
And we keep telling them that they are, you know, as important as anyone else.
But how can they even compete when this is going just, you know, so so fast?
And with them, it's like baby steps.
So just basically, oh, it it's I could hear the the, the tension in the in the teacher's voice.
And, yeah, in a in in a moment, I panic, but I also remember that god is bigger, and he loves us all, and he has a purpose, and he has a plan.
Yeah.
But it's it's just kind of difficult not get getting overwhelmed.
Thank you.
Yeah.
Thank you, Adriana.
Yeah.
I agree.
It's a lot to keep up with.
It's it is overwhelming.
I do think, though, that, it also is a it's a matter of framing as well.
For neurodivergent students or students maybe who need more attention and care, and this also translates to any helping profession, those under our care.
If done correctly, it frees the the caretaker, the administrator, whoever it frees us up to pay more attention to them if we do it correctly.
And so what I'd love to do is switch because I recognize that the maybe the first half of this was sort of like, oh AI.
It's this really big thing and it's constantly changing.
It changed, you know, this month versus six months ago, but there are things that we can do proactively today to really allow it to be the tool that helps us and accelerates us so that we can not only be more productive, but also just to be more free to do things that help us to flourish as human beings.
Because I guarantee you that while it there might be professionals at it, there's probably more flourishing found outside of spending eight hours working in spreadsheets and making sure all the numbers add up and little things like these are things that AI can do really well that are low in in personal relational cost and high and just like this very mundane sort of task management stuff.
Before I move there, though, I just do also wanna wanna highlight a couple other systemic risks that we do want to be aware of when we do start using AI or if we do.
One is the emotional dependency making sure our this these emotional attachments sometimes when when people are using AI lead to social isolation becoming overly dependent on on these bots.
Another one is an automation bias.
This is something that I have to watch out for myself or anyone using AI just in the same way that twenty years ago, I knew everyone's phone numbers back of my head.
You could you could ask me for a phone number and I would I would give it to you.
I only know two phone numbers now.
That's it.
I don't know any other phone numbers because my mind is not exercising that particular muscle anymore.
Now it's a lot easier to fall into that trap with automation bias and having LLMs do a lot of these things for you.
So it's very important to select the right things to offload to a, to an AI agent or an AI or a LLM model and to take on the other part for yourself.
So how does this look in practice then if we do wanna use AI?
Because, again, my position here is that we should and it would be it would be hard not to in the years moving forward.
A lot of the things that we're doing now, they're already whether or not you like it.
They're already augmented even internally with artificial intelligence.
So we can divide the labor of care with things that we can do algorithmically, which means things that have a pattern and a series of steps to it that need some sort of monitoring, continuous availability, and some standard processor extraction.
First side is the system.
The second side is the part that's more human, the thing that's more accountable morally and ethically.
The person or the part of the system, the person, that is able to make the complex clinical judgment, and interpretation of nonverbal and subtle cues.
I heard it really put really well earlier as I was listening to a couple of talks around this is, as I mentioned before about AI and large language models, AI is really good at noticing patterns behind words.
As I mentioned earlier, it's a statistical model.
So when it when you have a sentence, it can it can take that sentence, do some really cool math and determine what's the next word.
What's the what's the closest thing that this group of words is like.
It's good at analyzing the patterns of words.
But humans were good at understanding the meaning behind words.
So I'm not saying that we should not have AI.
I'm saying let's let AI do what it's really good at.
There's been some great studies that have helped us to understand that when a person is using firsts in describing, I forget the particular study here, but first person sort of descriptions of a situation, when done in a particular percentage or an excessive way, is a leading indicator of depression or anxiety.
Now you for someone who might be a practitioner, a therapist sitting and trying to listen and and be empathetic and to maintain that therapeutic relationship, you may not notice that particular pattern while trying to mirror and empathize.
AI is absolutely the right tool to help to pick up on some of those cues.
The practitioner themselves should be the decision maker of how to react to that particular data.
They still have the moral and ethical responsibility and accountability in that particular in that particular scenario.
And in addition to all that, from my studies at Divine Mercy University and most people who know it and who've had good therapy sessions, know that part of the actual healing process is that therapeutic alliance.
It's that relationship between yourself and the therapist.
I often sometimes joke that finding a good therapist is like dating.
It's really like making sure you have the right fit and finding the right connection with that particular individual.
And so that emotional and personal connection is still there.
It's still very important.
And that connection enables the practitioner that even the teachers to understand the meaning behind the words, But we're still able to use systems like this to maybe look further and look at other maybe leading indicators for other issues.
So what does that look like practically?
Gosh.
I am going a lot slower than I anticipated.
So let me just go through this one here.
For for helping professionals and practitioners, this looks really easy, but it's actually pretty hard to accomplish by yourself.
Using AI for screening and intake support, for triage and risk flagging, for symptom monitoring and documentation, for administrative stuff especially.
If you have to imagine having to reschedule and shuffle yours your your calendar and then sending emails to those respective individuals to explain the change.
All of that, I'm sure takes time and administrative and most people who is don't have that skill or that desire to do these administrative things don't like to do that.
AI does that really well.
And also low intensity support tools, but in limited context.
So chatbots and things but in very limited context.
All these things, I would propose, are useful to a certain extent.
Now, obviously, the screening and intake support, if you just say, hey.
You wanna see me?
Go talk to my chatbot, and then I'll see you after you're done with that.
That's not an ideal experience, first of all.
But second, it takes away the human relationship building that's probably there.
But it could help, for example, if you're in taking in taking someone, if there is a common template that you normally fill out for a particular patient and using AI to take the transcript of a meeting and move it over into that particular intake form.
Simple and easy.
Obviously, there's implications with that and and, what's allowed and what's not allowed.
I'm not taking that into account here, but there are systems that have been approved for for things like that.
So the care workflow is that AI really is in the background and that anyone who's using AI should be in the foreground.
AI now becomes the supporting structure that helps us to do a lot of our administrative tasks.
It should help us for asynchronous monitoring.
An example of this that I thought of now this is maybe not been done yet.
It's an idea that I just had as I was thinking about this was what if you could take all the notes that you had of a client maybe that you've been seeing for ten years?
And maybe with AI to leverage its capabilities to understand patterns, cycles, and triggers for those cycles so that you're more aware in a particular session and more present for those particular triggers.
And maybe some of those triggers you're already aware of, but maybe some might be a surprise to you.
That's just one thing one way to sort of asynchronously modern monitor someone in your care.
But the top most important layer is that a human clinician, a human person interprets the data, provides the empathetic relational care, and exercises the judgment.
It's always going to be a human in the loop call.
We never take the human out of these things because one, why?
Two, the part of the healing process or part of the the support process is that relational aspect.
Now, as I mentioned before, I did attend the Divine Mercy University.
The Catholic Christian meta model of the person has greatly impacted how I even build software.
But it's also impacted how I interpret my human my understanding of the human person and the anthropology.
And so I was as I was thinking about these things, I sort of use that, that framework to sort of create a chart here around what where we should have maybe AI and where AI is possible, where relational complexity is low, the patient vulnerability is low.
We can probably have AI help with some of those things.
Where relational complexity is high and patient vulnerability is high in those one on one sessions, triaging hard moments, a human is necessary there.
And there's no space for AI to take any any part of the decision making process.
Now you can obviously still use it to augment some of your some of your triaging and things like that.
But in general, I I would follow something like this to help augment care while leveraging artificial intelligence.
And so you have the intersection of these two circles where you have a system that supports the things that you do, And you have human tasks that are solely part of your realm and responsible for and accountable for.
So, for example, the AI can understand the structure and content or context of of health records of socio demographics, and it can process massive amounts of data.
And then the human clinician is more focused on connecting, judging, when to act, and responding in those empathetic ways to alleviate suffering.
Ultimately, the real question is the kind of care and what kind of person our systems are forming.
And we have to keep that in mind when we use artificial intelligence.
If we just threw an AI chatbot at our patients, at those who are helping and saying, hey, use this, We have to understand sort of the biases that we, the biases maybe that the model has, the limitations and AI has and the sort of outcome and the system that you are creating in that particular environment.
However, if you are bolstering your ability as a clinician to care for those in your care by increasing insights, making it easier to to take time with you.
In my view, these particular technologies should multiply our ability to help more people, but not without a human in the loop.
A human's always in the middle.
But rather than seeing maybe five people at a time, maybe now I can see six or seven people because I don't have to document as much as I needed to before because AI does that for me.
And that is pretty much it.
I just wanna thank everyone again.
And, if anyone has any questions, I'll I'll definitely stick around for any questions that you might have.
Jerome, thank you.
I I I think I was really struck by, that very helpful and insightful chart of balancing vulnerability and relational needs, you know, where we can use AI versus where we must have, as you say, that human interaction and sort of AI as a supporting structure and how it can look for, as you say, patterns or undercurrents, you know, but, it it's it's a, a supporting tool.
You know?
So I I love that you you have woven that, woven that throughout, and that's that's an excellent, flow, really.
And it's it's, all for serving the human person.
Like, really just toward that end, if it can help us be attentive to, listen to, understand, and serve, and heal, then all the better.
Absolutely.
Thank you.
If folks wanna pop any notes in the chat, they can do so, or people have been raising their hands, and we can certainly open you up to to a question.
So we can certainly stick around for a few minutes if people want to pick Jerome's brain.
And as I mentioned, this will be available.
I shared in the chat youtube.com backslash divine mercy university, pretty easy to remember.
That's our YouTube channel.
Subscribe there.
Follow us on LinkedIn, Facebook.
The other two presentations on May 28 and June 3 will be featured there, and you can find a registration link.
And yes.
So they they will all be made available.
So we're gonna we're gonna share the ones we've already done and the ones we have yet to do.
Any resources that are good, Jerome, for people to, of course, as you mentioned, Leo, you know, keep an eye on the on the Vatican there.
I know that there have been some, some books and some different speakers who are touching on this issue.
Do any come to mind if people wanna sort of do a little bit of a deep dive and follow-up, to to read elsewhere?
Yeah.
Absolutely.
I'm a big fan of, the work that's being done, at it's a company called Long Beard.
Yes.
Are you familiar with Long Beard?
I am.
I I met and his name escapes me.
I met him at a, a conference in New York hosted by the Nap Institute about six months back.
Yeah.
I don't know why his name escapes me as well.
Yeah.
He leads Magisterium AI specifically.
Matthew Harvey Sanders?
There you go.
Matt.
Matthew Harvey Sanders.
So, I follow him very closely.
He does a lot of talks on panels around artificial intelligence and sort of intersection with Catholic theology and anthropology.
I think what he's doing with some of the projects with Magisterium AI, where he is digitizing whole libraries that are in the Vatican is a great way to sort of like digitally evangelize to these LLM models since they are trained on internet data.
It's ingenious, I think.
There's also just people associated in the same sort of circle, where, for example, father Philip Larry, I follow him a lot.
I believe he has a book on artificial intelligence that I've read as well.
Those are I think those are some great resources.
I'm a big fan of Magisterium AI, for those who have not heard of it.
It's a AI chatbot that is trained on Catholic magisterial teachings.
So that's encyclicals, writings of the holy fathers, and some select writings of saints and things like that.
Mhmm.
It's a great resource if you're looking for clarity on on Catholic teaching and things like that.
I I will also say Excellent.
In in that same vein, you know, chat gpt can also be a good resource for some of these things.
Again, we have to be aware of, like, the nuances.
So, for example, if you ask chat gpt, I asked once about the Eucharist, and it uses language that isn't strictly wrong, but it doesn't really speak to sort of like the source and summit of our faith.
Right?
It doesn't call it a symbol necessarily.
But it doesn't use the language that we would use as Catholics to describe the Eucharist, which is expected.
That said in my own evaluation of a lot of these LLM systems, I have found that they tend to veer more towards Western Christianity than any other religion.
So for example, in over a weekend, I just decided to do a fun experiment.
And I said, hey, like describe to me the perfect marriage and wedding.
And it describes a Christian wedding, white veil, white dress, chapel, and all those things.
It's not using any other, it's not using any like Eastern or or other culture, cultural weddings.
What that speaks to is it's still a bias, by the way.
So it's biased towards Christianity and Western culture.
But that bias there exists.
And these are the things that I was speaking of earlier.
Being aware of these biases help us to understand and use the tool a little bit better.
Right.
Sort of the guideposts, you know, and and, you know, that that it is not entirely, you know, morally neutral, as you say, and and, to not shy away or to be fearful, but but to use it with with a certain sobriety and a caution.
And, you know, as you would, you know, a mechanical tool that can do good or can cause harm if you don't know how to wield a chainsaw.
So Yep.
Absolutely.
Yes.
Elizabeth had a question.
What safeguards are in place to ensure ethical use, confidentiality, and responsible note taking practices and or documenting in general, within certainly the the counseling space?
I'm sure she's referring to.
Yeah.
Elizabeth, I, I can't speak to any particular solutions.
I do know some some exist out there.
But I do know they have to they have to adhere to, whatever guidelines, that for any technology, including the type that you use for, for meeting virtually with with clients.
I don't have any names off the top of my head, nor I don't think I'd actually on a webinar, endorse them if I don't know, only heard of them in passing.
But I do know some exist out there.
But I do think that is low hanging fruit for a lot of clinicians to look into.
Because it is, I think, while that is important work, it's work that AI does really well.
Mhmm.
Andrew made an interesting point just about the the, you know, praying for wisdom and guidance in in our our searching.
And and in the same way that, I think if this is what you're saying, Andrew, you know, that there is, there can be sort of an unhealthy curiosity or an anti intellectual, like, well, listen, I'm just gonna find this answer out there.
I mean, even pre AI, I mean, in the early days of the Internet where, it was just, you know, search engines, and we obviously know that you can get everything from, you know, catechesis and connecting with old friends to, you know, some nefarious stuff to say.
You know, so going and like understanding sort of our heart and our mind and our intentions as we go into, into sort of that search mode, if you will.
So, yeah.
Yeah.
I think he makes a great point.
And Andrew, I Pope Leo has said that, you know, access to data doesn't translate to wisdom.
It doesn't.
And I think that we have to take that to mind.
Similar to the way that being able to connect virtually like this doesn't mean that we've created like, like genuine human connection.
It can contribute to that.
But there's more to it than just the ability for us to email each other.
Right?
In the same way, having access to more data in a more consumable way definitely doesn't necessarily mean that we are, accessing wisdom itself.
Yeah.
Right.
Daniella has a good question.
Did you see that or I can share it?
Sure.
I'll I'll go and read it.
Why does it feel like ChatGPT gets me?
Sometimes it says similar things to what my therapist would tell me.
Is that because it's drawing from common knowledge or statistics?
It does give me good advice.
How can I use it cautiously?
This is great.
You know, ChatGPT gets you.
I don't know if I want to be careful how I say this.
I think we should have the give these companies the benefit of that that they're not trying to make these things specifically addictive to us.
Right?
But this this idea of these models getting us, it's because they're very agreeable to us.
And that helps us to create an open space.
There was a, by the way, I'll share it when I share this Brian with with you.
I'll include all the sources and everything if anyone wants that.
The sources are there.
There was this great study about this about this agreeability of these chatbots create an open space that make it very easy for us to share.
And so in a certain sense, when you think about these these kids or even adults who start to create the strong attachment to their chatbots, you almost feel for them because these chatbots are responding in a way that is agreeable, that is open, and they're they're, they're being made to sound personal, or I'm thinking about that, or I I see what you mean.
And it's very like a person talking to you.
And so it draws you in to that.
Now, whether or not it's drawing from common knowledge or statistics, it could be drawing from a lot of different things.
There there are long running memories that the a lot of these commercial agents will use so that they store information that they know about you so that it's more convenient for you to use later.
But then it also draws from a general knowledge as well.
Looks like there's another question from Patrick.
Kind.
Yep.
Yeah.
So the question is, can a basically, does AI weaken the human brain or develop the human?
If yes, how?
And if no, why?
Thanks.
Great question.
I actually was looking into this a little bit.
And honestly, I think the technology is just too new.
A lot of the research that I was looking at is very limited in scope.
So for example, there was research talking about how talking with AI chatbots had improved greatly symptoms of depression in college students.
That was a sample size of one week, which by the way, I wouldn't have blinked that if I didn't go to DMU.
Like I going to DMU, Brian, I gotta tell you, I was able to take in this research and question very, very well some of the data.
And it said, you know, these college students reported after one week, they started to feel so much better from their symptoms of depression.
Well, one week is not a long time.
And actually, the peak of using chatbots happens around five days.
After five days, people tend to fall off.
And so, like, it's hard to know whether this use of AI is actually helping the individual or not because the data is limited.
So Patrick to your question, I think I think a hypothesis can be made both ways, leaning on previous research from other experiences and technologies.
But I think we have to wait and see.
All of that to say there is some common sense in there for us to leverage, right?
There's this idea of cognitive load.
And reducing that cognitive load sometimes reduces our ability to think and to memorize and then to reason and use that knowledge later on.
If we put the entirety of that cognitive load onto the AI bot rather than us doing it ourselves.
There was a study done, with college students in writing essays.
And some students had access to chatbots.
Some students had limited access, and some had no access.
And their ability to recall what was in those essays varied, depending on whether or not they use the chatbot.
Those who used it to a limited extent learned better than those who'd use the chatbot fully to write their their their essays.
I question that a little bit even because now that's more of a matter of strategy.
How you're using again this technology to learn.
If you're simply telling it to write the the essay for you, of course, you're not going to remember it.
But if you haven't write the essay, then you go through it and have it create some flashcards and then create audios that you can listen to it on your drive, then you probably remember it a lot more.
It's all a matter of the strategies you use with this technology as to whether or not it's helpful or not.
That's excellent.
Kevin did have it's not showing in the chat.
He put it in the q and a section, but also readout is that he Kevin says, are there any therapy chat bots you know of which you would consider ready to start recommending to clients, for that kind of supplemental between sessions, Kim, you were describing?
Or is this more of a future imagining at this point?
I I would be I was already talking just a year and a half ago to a startup who was building this and wanted some advice on how to build it.
So that was a year and a half ago.
So I'm pretty sure they have something in production.
I'm not gonna name any again specifically just because I I couldn't stand behind them.
I will give you a framework for any of these things, whether it's for your clinician's use or even for like Catholic theology stuff.
One of the things that I would do, especially if you're gonna hand some of that over to AI, you have to question their guardrails that they have in place.
What are the the technical term is is evals, but what are the evaluation processes that they use to validate that their bot stays within its bounds.
So that's number one.
Number two is what are the what are the safeguards they have in place when it doesn't?
Because it's not going to stay with within its bounds a 100% of the time.
That's just the nature of AI as it exists today.
If I run a particular query a thousand times, sometimes something will go wrong.
I just can't guarantee it all the time.
And so you just have to understand those particular nuances and you have to question how they're evaluating the correctness of their answers.
The ones that I would go with are the ones who are putting more effort into that because it's more of a it's more of a care around the quality of their answers rather than I created some sort of wrapper to chat GPT, and I just let it go and help people, which is really easy to do.
Yes.
Great question, though.
Great question.
That's excellent question to everyone.
Yes.
Any other last thoughts?
I will put my email in the chat here in case there is any.
It's just simply alumni@divinemercy.edu.
If anybody thinks of anything tonight or tomorrow, you thought, well, something for my personal use or in my clinical or my classroom because, interestingly, we had a few teachers here, which is fantastic.
That's great.
And I I'd love for everybody to take these to to others and for you to join us for May 28 and June 3.
But if there's anything you, are curious about, that you want me to pass along to Jerome, please message me at any point, and, keep an eye on the YouTube, TMU's YouTube.
We'll we'll share this content here, and what an extraordinary, presentation, Jerome.
It's such a gift and a blessing to have you for you to bring your your wisdom, your heart, your passion, just for your your really your your love for for serving here.
It's so evident.
You know, you're really sort of a a a a missionary and mission territory, I think, in a lot of ways.
And it's it's these things are moving fast, but at the same time, it's sort of the early days of this new technology and to have you at the forefront.
I think it gives all of us a little bit more peace of mind, having somebody like you.
No.
Yeah.
I mean, as a voice, with your clarity of thinking and your heart for the gospel, to really be, a leader, and and and thank you for that.
And we're we're we're blessed and honored to call you, an alum of of the university, and it's such a such a gift to have you.
Praise the lord.
Thank you so much, and thank you again for having me.
And everyone, thank you for joining.
I really appreciate your attendance and and attention here.
Thank you.
Yes.
Thanks, everybody.
And, again, write me a note if there's anything else.
And, if not, we'll, we'll wrap it up here.
So God bless everybody, and, see you all again soon.