Hi Michael, it's great to have you with us today.
Yeah, thanks for having me.
It's wonderful to be here.
If you could tell us a bit about your childhood and go as in-depth as you'd like to about
the past to where you are now.
Yeah.
Where do you begin with childhood?
I think maybe, you know, I tell some people this and maybe it's surprising, maybe it's
not because maybe I like I present a certain way or maybe there's some assumptions of
who I am.
Grew up in sort of this like suburban countryside and sort of a lower income working class family.
So I'd say childhood was really, really great filled with creativity and a lot of time outdoors
and not a lot of time in technology, which I think some people sort of assume.
I might be the kid that's like taking apart radios and try to figure out how to put them
back together the same as like my bike or something else around the garage.
So probably the most impressionable thing is being the first person in my immediate family
to go to university.
And so, you know, education was really important.
It was hard to navigate that as being, you know, kind of that outsider.
My parents kind of, you know, steering me as much as they could, but more things being
unknown than known for them.
And you know, that took me to an incredible path of, you know, everyone says like follow
your passion.
So I started my career in the arts and maybe we could talk a little bit about that.
But where I am today is I ended up going back and doing a master's.
I now work in technology and AI of all things.
And for over a year now, I've been at the Ivy Business School at Western University
now teaching.
So my kind of like full circle moment is being this loved and supported working class kid
to be the first person to go to university to now teach in a university, which I think
is just, you know, if not through education, then it has to be Canada's the only place
where you can make that happen is what I believe.
That's amazing to hear.
So let's go back to your time in high school.
And how did you decide to do a bachelor's in arts and talk to me about your experience
there and then your transition to working for the Toronto Symphony?
Yeah.
Great question.
So I end up becoming sort of this like, you know, kind of now comfortable in crowds and
can sort of speak my mind freely.
But that's not where I started in high school.
I think it was for a good period of time, you know, by sweating through my shirt afraid
of my own shadow a little bit too much.
But at some point in high school, I became kind of the theater kid.
And through, you know, those classes, those opportunities, we had like an improv group
and doing some plays.
I kind of found my voice and being able to talk to people and relate to people and maybe
also being more confident being another character rather than being myself is probably part of
the story.
And so when I was choosing universities, what's interesting is I applied in sort of like a
really eclectic way.
So on one hand, there was like fine arts and sort of bachelor arts programs.
And then on the other hand, were business and technology programs.
And I had actually committed accepted to a different university to do a business and
technology.
I think it was a B.com, but I don't remember.
And on the last day when you can decide or would have you back then, well before email,
I got the acceptance letter from the University of Toronto to do a humanities degree.
And on the very last day, my girlfriend at the time was at the university and I decided
to go to U of T and just sort of pursue the arts and pursue what I love.
I am only able to say this in hindsight.
I don't think I appreciate it at the time.
And there's some brilliant people.
Like I think this quote is loosely based on something that Hal Jackman has said, where
humanities degree or the arts teaches you how to think critically.
It's actually not really about analysis of art in and of itself.
It's about how are you structuring thought?
How can you understand what other people believe, think and value?
And then how do you communicate that?
So that was kind of my takeaway.
And I found myself there by circumstance.
I wish I was probably more intentional at the time, but I did walk away with some skills
and some purpose and some this growth mindset of what I wanted to do in the world.
And what prompted the transition to business and then to AI?
That's a good point.
So I started off at a few different arts organizations as you've noted.
So I worked at a theater company in Branson, Ontario that was just opening up called the
Rose Theater.
I was there for the opening was like one of my first internships, bounced around at like,
you know, a children's theater company, an arts service organization for playwrights.
Found myself at the Toronto Symphony, where the symphony felt like the most professional
place I had ever worked at that point.
I'm like very early 20s.
You know, they've got a board, a CEO, there's hundreds of people, there's lots of revenue
flowing in.
And this is the moment where I start to feel and understand and really experience all the
different, you know, common nodes of business.
So marketing and sales and HR and in our case, fundraising.
And how do they function and how does sort of this corporate structure function?
And, you know, I'll say I was good enough at fundraising and an open an opportunity to
return to U of T where I would work as an administrator in their advancement office
and and I'm spending a decade there grew a lot.
I say it's like, you know, I feel like U of T's played a pivotal role where it's like,
you know, your first university where you're becoming an adult and then kind of where like
I actually grew up by by working there for a decade.
But the transition from all of that into business and technology was very much related to, you
know, first my like my management mindset at the time.
And then the second thing, wow, what an incredible opportunity being at U of T talking about AI
and you know, in the 2010s.
So the first thing is my management mindset before I went back and did my MBA at Ivy Business
School was I always kind of kept the mental note of bad managers and the things that they
would do and we're kind of mentally commit to.
I don't want to do this when I manage.
And I kind of got to a point of like, you know, when you're leading fairly large teams
or you know, really big revenue goals or projects or what have you where I didn't really have
a great skill set, right?
Like this skill set based on I should do things, you know, I should not do the things that
I did not like is not really a strong management philosophy.
And so I felt like, you know, this is a huge part of my career.
I'm not done.
I want to have 10x the impact that I've had thus far.
And if there's if there's one thing I need to learn, I need to learn how to lead.
So that's what took me to Ivy Business School and doing my executive MBA there and kind
of learning and growing.
The transition to technology happened at the same time and it had a lot to do with, you
know, the people and the projects and things I was working at U of T.
I'll just name job for a second.
None of these individuals will remember who I am, but having the opportunity to get assigned
to support or be on projects with some, you know, incredible researchers and then now like
founders like Dr. Raquel Erdison, Dr. Jillian Hadfield and a few others where very early
days like in the 2010s, I'm learning about autonomous vehicles and learning about that,
you know, how did they actually learn?
Why are they learning?
Where is this going and kind of conceptualizing the future or that these systems could be really,
really unsafe if they're not managed or we don't think about the ethics and equity is
really what Dr. Hadfield has contributed to AI and our ecosystem.
And so this planted the seed in me where it's like, you know, we're seeing tech everywhere.
I feel like it's the largest growth industry in the world, but being at U of T in that
moment around, you know, these descendants of Dr. Jeffrey Hinton and where U of T has
kind of led the world.
I had in my gut, but I was probably, you know, just surrounded by some incredible people
where it's like AI is going to be really, really big.
So the transition to business is, you know, MBA, this in depth kind of understanding of
seeing research really at the bleeding edge at U of T and then saying, we got to do more
than just publish papers.
We don't need more citations collecting dust on a bookshelf somewhere.
We have a chance as Canada to really own the podium here and let's figure out how we get
this research out of our really amazing research institutions into companies into everyday life
so that we can, you know, grow economically.
We can create more jobs, but that we can contribute to the world in a meaningful way.
So I joined the Vector Institute and that's been, you know, a wonderful organization that
really grew and groomed me and taught me so much about machine learning.
And now I find myself in healthcare where, you know, we're seeing this every single day
in the way that our clinicians are treating patients.
So along eclectic circus of a journey, but I do relate this a little bit back to, you
think to that 17 or 18 year old humanities kid, a lot of this is based there of how can
I understand what other people value or what they communicate and how can I think critically
about these things.
And AI for me is really about that of we have this massive corpus of information.
How do you take it in?
How do you think critically?
How do you exercise judgment or build systems that are effective or safe?
And so the eye rely on the business skills and, you know, and some of the hustle and
acumen and stuff like that that I've built up.
But a lot of this is that arts background of how do we think critically?
How do we understand what the current context is?
Does the common startup philosophy that says that you should hire slow and fire fast, do
you agree with that?
Oh, that's a great question.
I like the higher slow.
So like I think, you know, we're coming off a period where venture back companies got
incredible valuations.
They hired hundreds, sometimes thousands of people and really did not have the runway
to sustainably support that head count.
The fire fasting, I'd say like, you know, it depends on sort of the context.
I don't know what the definition would be around that, but I find that most individuals
are really learning a job.
You're contributing, but you're learning a job probably for the first year.
The second year is where, you know, you're moving beyond sort of this binary learning
like, oh, I was giving a task, I executed the task.
The second year is when you really understand that context, your internal context, and you
understand the external context where you might be able to be a top contributor or not.
Now, all it's that people don't show up, they're late or quality of work, all that, you know,
aside, but I do take a longer term view, depending if that is a long term view for some people,
on human capital in particular, because it organizations are weird.
Everyone is unique and everyone says that they're unique.
And I don't know that enough leaders reflect on how poor their internal contacts might be
for individuals to succeed.
And so I feel like it's around the year mark, sometimes it's shorter, sometimes it's longer,
but I find that sort of that second year is when people really kind of hit their stride
and you can really see the value that they bring.
Have you ever made a bad hire?
And is there something you could have done in the hiring process that would have stopped
you from hiring them?
Yeah, made a bad hire, for sure, multiple times, did not see it coming.
So I think, you know, interviews are getting to be a little bit more interesting and better,
but something that I really, really reflect on, this does, you know, follow the murder
of George Floyd and Candace efforts and truth and reconciliation is, I do think that as leaders,
managers, people hiring, we need to think about how fraught the hiring process is.
And this has nothing to do with AI suggesting like who we should hire, what resumes we should
read, the process has been fraught to hire the person that went to the best school, had
the best network, had the best reference, it's sort of been coached to do the same.
And I'll say like, you know, we've taken it in quote, a chance on a few people where the
interview was clunky, or you know, there was something where we're like, oh, we're not
too sure, you can't see hustle, you can't see commitment, you can't see drive, and
you're 10 standardized questions, and the one or two assignments you give someone, or
the, you know, one to three references that you check.
So who a person is, you know, you might get that sometimes in an interview process.
And that's something where you're building a relationship together, and that spark may
or may not happen.
But if you find someone that really is aligned with your personal purpose or your corporate
purpose, and they will literally move mountains for you, that's a great hire.
And you know, if they're a bit quirky or late or they've got too many cats, who cares?
As long as they're kind of, you know, really devoted to where both of you can go together.
Yeah, my kids would say you can never have too many cats.
I know my son desperately wants cats and dogs.
We had a dog, and we're now in the like in between phase.
But yes, if we had 16 cats, he would love it.
I think people underscore the importance of references.
And there's a couple of ways to do it, I usually seek references from previous jobs that the
founders don't provide readily, and I let them know that.
Or you can ask for 10 references and say you will randomly call three of them.
Now that's a big ask.
And the job offer or the investment has to reflect that.
But you want references where the founder has had conflict as well.
I think so, and you know, and understanding how people navigate conflict, like sometimes
it really shuts someone down.
And other times, someone can take it on the chin and say, you know, thank you.
I disagree.
But I'm going to think about this or I'm going to learn from this, this opportunity.
So I like how you how you navigate that, I think is, is, is quite important.
I think like, you know, I've seen things where like some companies are doing like mixers or
actually the hiring team is kind of not involved for a certain, you know, round or phase.
It's someone on the team is like messages as a person, hey, are you free for coffee?
That's what I'm interested in.
You know, if this person for an hour or two hours or as coach, the references can put
something together for me, that's fine.
But you know, Karen and Kayla, who you're going to have to work with every single day.
Can you get along?
Like is there some sort of animosity or friction or is there actually, you know, some, some
real bond here for, for whatever reason?
Is there sort of that that spark of opportunity?
What is hard, and I do feel like there's some people talking about this, but what is really,
really hard in AI and in tech is we just have many, many engineers and computer scientists
that are introverted.
And so if you look at the traditional scorecard of, you know, character or leadership, education
experience, whatever, like how we're going to score someone, that individual just might
be really, really nervous to talk to you or to share in that way.
So part of like, you know, do we need to rethink this as some of this just like, would you
be open like we just text over the next like five days of like, you know, I'd love to hear
your thoughts on this big announcement from, from the video, like what do you think the
impact would be on, on our work or health Canada just issued updated regulation on AI's medical
device like what do you thought we can ask that and you know, maybe I've been coached
and trained and have more experience where off the cuff, I'm going to give you something
that's that's eloquent, but maybe for that interview to introverted engineer or computer
scientists, let's just do that over email or do that over Slack or do that over text
messages or something else.
And maybe that's the way that we're going to build trust in that relationship.
Maybe that's the way that I should be evaluating you.
So that's a long way of me sort of saying that like, the world has changed, you know,
like we're working remotely, very, very often, have our hiring practices changed as as radically
probably not.
And we probably need to rethink it.
What are your thoughts in remote work?
And you have a similar culture remotely, because a lot of us, a lot of companies are
mandating back in office.
Where do you fall on that spectrum?
So it's like a working parent hybrid is an incredible benefit.
And I can't say that it's that it's not you mentioned you have kids.
They're sick.
All these crazy things that happen with with kids schedules.
I know a lot of us also have like elder care responsibilities.
So it makes it challenging to be in office and present as much as maybe you would like
to be.
There's the there's the old adage, right?
Culture eats strategy for breakfast.
So are we really fixated on our corporate strategy?
Or are we really fixated on our corporate culture?
And I think you can build this remotely.
It is hard.
It might actually be more expensive than what people think.
Like I hope that founders are not choosing hybrid or remote because it's the cheap thing
to do, but that it actually does resonate with the team or individuals or what it is
that that you need to build or why you're building.
You get a lot more accomplished in person, so I do see sort of, you know, community building
this kind of like this culture building happens just a little bit more seamlessly and in person
than it does virtually, but it doesn't mean that it's impossible.
On my experience and kind of our team right now is you have to put effort on both sides.
So we are hybrid, but we have a lot of people that are committed to like, when are we all
going skating in a few weeks together as a team over lunch?
This isn't dictated by the leadership team to say like, you know, 28th of the month is
you know, skating day and we expect you like, no, like it's a real group of friends and
community within the team saying there's literally a skating rink across the street.
Who wants to go on this day?
Yes.
Do this as a team activity.
So there's real effort on that side to build relationships, build trust, build friendships,
get to know one another beyond the code or the deliverable or the tactic that you're
working on.
In the same time, you know, we've also grown remotely.
We have people that are not working within 30 minutes or an hour of downtown Toronto.
How do we maintain that same friendship bond culture virtually?
So you know, there's there's stuff that randomly pops up.
You got to be creative with how you're using Slack.
And I'd say the team does a fairly good job of it, but you need to put effort in into
both sides for sure.
It's something I will actually just share about our team.
We I don't actually know where the name came from, but for whatever reason, on a monthly
basis, they created just a really quick internal application called Timbits.
I don't want any kind of issues with the Tim Horns Corporation.
It's spelled differently.
It just sounds the same.
But on a monthly basis, we just get an email of like, Hey, Mike, you're going to have coffee,
your virtual coffee with Rashad, and you're not allowed to talk about work.
There's some suggestions of things that you could talk about.
And it randomly kind of assigns people on every month.
So this isn't leadership being dictated.
This isn't, you know, the standing meeting.
This isn't, but it does fork force us to break the mold to say, you know what, I haven't
talked to this ETL developer in six months.
We never cross paths.
They're not on, you know, my immediate team.
This is great.
What are you doing as a person?
Did you enjoy the holidays or, you know, how are things going?
So we're using tech and investing sort of both sides of like in person and virtual to
really maintain our team culture.
If you could wave a magic wand and change one thing about Canadian healthcare, what
would you change?
Working in healthcare at times, it feels like, it feels sometimes a little bit like everyone's
at odds.
So, you know, we read a lot of the media and it feels like it's sort of accusatory of
physicians or providers are so slow or something like wait times are egregious because they're
so slow.
If I could wave a magic wand, the one thing I would change is I hope that we come to understanding
that providers and patients actually want the same thing.
We want to take care of our patients and as a patient, you know, I want to get the best
care possible.
What probably your average person doesn't know is all the constraints that are in the
way to deliver, you know, max amount of coverage or the type of quality of care that all of
us want.
And a lot of this is regulatory, a lot of this is data access.
Some of it is human capital.
So I'd hope that I can't change all those things with this wand wand, but the one thing
I would change is just that current, what I feel mindset of that we're at odds like
providers and patients are sort of antagonistic with one another.
I don't feel like it's real and I'd love to wave a wand and just remove that.
Or we all are like, oh yeah, no, they actually want to take care of me and they chose this
profession or you know, you know what, it's fair that this person's really frustrated.
They couldn't get into my family practice for three weeks or four weeks because I'm so
overbooked and now they have pneumonia or they just sat in my emergency department for
12 or 16 hours before they saw me.
And of course, they're really, really frustrated.
So I'd love to sort of remove the animosity so that we could really build back a system
that is reflective of who we are.
If Sequoia or A16Z or General Catalyst sent you an email tomorrow said, Michael, here's
$50 million.
We want you to build something in healthcare.
What would you build?
All right, great.
Well, 50 is not enough money if you're A16Z listening to this.
$500 million, whatever the number is.
So I think, you know, we are starting to see this.
We see some of the potential and the type of quality of data that the Nordic countries
have captured.
And where we're really excited at Unity Health and St. Mike's is yes, AI is everywhere and
this is another AI talk.
I get it.
We're done with that.
We are just at the beginning.
If we're just seeing the tip of the iceberg, we don't see what's below the water.
And the thing that I would build is a real robust multimodal AI company.
Our leader, my boss, Dr. Muhammad Nani, has been talking about this for years.
But imagine a system that can not only read, which is what we have now, right?
A lot of the systems are based on reading text data out of your electronic medical record.
Imagine a future AI that can not only read, but can see because we've built in video feeds.
Imagine a future AI system that can read, see, and hear because we're using auditory
inputs from our emergency department or our surgical bays.
Imagine that it's a system that can feel because it's getting sensor feedback or instrument
feedback from any of the diagnostic machines we're using or any of the surgical devices
that we're using.
That's the type of AI that really feels science fiction and far-fetched, but where I'm getting
excited because we are seeing things like Alpha Fold and the team getting a Nobel Prize
just a few weeks ago.
And that is really, yes, a big, massive data set and a huge feat, but we've really not
tapped into all the data possible.
And if we can get a team like the next DeepMind access to that type of information, and I
think you would be aligned with this, imagine that we can start helping people before they
arrive in clinic that you knew, based on your aura ring and your feedback, I got to actually
get on medication or I need to go to St. Mike's because this is actually pretty severe.
And so the thing I would build is something around multimodal AI.
And I think it's bigger than one medical discipline, one clinical area.
I think it's widespread because medicine is interdisciplinary.
It's going to take in data and data types and feeds from across the care spectrum.
You know, lately we've been hearing that AI, in some circles that AI is getting dumber,
and which is attributed to the phenomenon called drift from what I understand AI just
goes wonky.
How do you control for that?
How do you fix that?
Yeah, I think we are seeing that drift is not a guarantee from at least my reading and
understanding.
So it may or may not occur.
And that's sort of the interesting phenomena to me of like, why is this or when is this
not happening?
Some of our models which are not LMS are just the R machine learning and some rules based
systems, they're not getting dumber.
The accuracy is staying the same.
But the part that I think maybe we need to keep in mind is our current context does change.
So I'll give you an example.
We've got a tool that predicts volumes into our emergency department at St. Mike's and
St. Joe's.
It's 48 to 72 hours in advance and it's very, very accurate, over 90% accurate, I think
over 95% accurate.
The part that we've done that's different than some other areas is we're able to predict
severity of cases and some key areas for us.
So we'll know, okay, you know, on Monday morning, we are going to have 30 cases, 28 of them are
going to be pretty easy, two of them are going to be difficult and five of them are going
to be mental health cases.
What is this tool trained on or where is it getting its data from just in general?
Yeah, so this is, it's a time series model.
And so we're doing inputs of sort of our historical data at our emergency departments of the types
of visits.
And there's a lot of literature, I think going back to the 70s of that, emergency department
visits are very predictable and there's seasonality associated with it.
As Canadians, we should understand that there's cold and flu season for, for a reason.
For our hospital too, there's also trauma care season.
So please wear your helmets when you're riding your bike or going skating.
So we see these natural spikes and occurrences and they do repeat themselves on an annual
basis.
The other key input for us too, actually, is we input weather and we input cultural events
in the city.
So really, really high likelihood, but we know, you know, if there's a hockey game and
freezing rain and it's a Saturday night during cold and flu season, it's probably going to
be a bad night in our emergency department.
And when you say you input cultural events, like what is actually happening?
Yeah, so we have basically like a listening type bot that there's a few different sites
that's looking for posted dates.
So hockey games is, it's one of the big ones basketball games.
We you know, if there's parades and stuff like that, there's just more slips, trips,
bumps and falls.
And so therefore, where do they arrive?
They arrive at downtown hospitals.
And it's able to kind of say a hockey game will have one extra patient, whereas a Taylor
Swift concert might have 100 extra patients or.
Yeah, I don't know the volumes and how that, how those two sort of things equate.
I will tell you the thing that we missed.
I don't know if the listening tool didn't have this, but the thing where we had many
more people in the emergency department than what we were expecting was when our world
championship Toronto Raptors had their parade.
And we, you know, I don't think the city was ready for that celebration.
But the emergency department, it was like we weren't ready, but we saw many more people
than what we were anticipating that day.
So that's one of the, one of the misses.
But the, yeah, I don't know that we take into account the volume of the event, but just
certain events like, you know, marathons and stuff like that, the people do get hurt and
they do end up in our emergency department.
Do you think we should mandate explainability for AI as some of our medical societies have
come out with and said, you know, if you're using an AI, you need to understand at some
level how it works, but AI, you know, is a black box for the most part.
Yeah.
So I think explainability has caught on somewhat unfortunately.
And so there's a few things to be the backup and say about this.
So no, I don't think that we should mandate explainability and feel like also that we've
solved the problem.
I feel like explainability is caught on as a surrogate for trust and safety.
So if we can understand something is kind of the argument, oh, then therefore it is trustworthy
or then therefore it is safe.
And that's actually not true.
You can understand something and it could still not be trustworthy and it could still
not be safe.
The other example, you know, I've heard many people sort of say, you know, there's actually
a lot of really common medications that all of us use regularly that we don't understand
that we can't explain.
You can ask your average physician or nurse, what is the mechanism of action for a CETA
medifin and they're probably going to get it wrong.
But yet it's, you know, one of the most widely used pharmaceuticals in the world.
We all drive cars or get on trains and buses, but we don't necessarily understand, you know,
how does a V8 or V12 engine works anymore?
What is the difference between combustion or electric engines?
So I don't think that explainability takes us to the place that we want to go.
I think it just sort of caught on of like, oh, you know, if I understand more, I'm going
to feel safer.
And the reality with AI is you might not understand something, but still it might be really, really
unsafe.
So the part where I'm interested is what are the monitors and evaluations that are in place.
And I don't know how we necessarily regulate that.
That's not my space to dictate.
But what I would want to see is for critical systems that have an impact in hurting someone,
that they're monitored, and that there's some type of regular evaluation in place.
That's what would make me feel safer and that we're in a better spot.
Throughout history, we have been the smartest being on earth as far as we know.
And now we're creating something which is more creative and smarter than us.
And I think this scares us.
And I think this is where this rise of explainability comes from is, okay, if I can explain it,
I'm smarter than it.
And I think that that's what's driving these rules and regulations.
You sit at an intersection of industry and healthcare.
What advice would you give to hospitals who are looking to be more innovative and incorporate
more AI and startups into their ecosystem?
And what are some things they do wrong?
So I think it really comes down to identifying the problem and picking the right problem.
And there's many different ways that you can go about that.
What I see, whether you're building or you're buying something, like you're going to partner
with a startup or what have you, innovation is this big, sexy thing.
And a lot of people on the leadership team get involved in these meetings and issue the
RFP, what have you.
And I'll just be honest, I don't know many nurses directly.
I'm not funded or supported by any sort of nursing union or federation.
But you go through these processes and typically nurses are not included whatsoever.
And it's such a huge miss for acute care.
I can't speak to clinical practice specifically.
But for acute care, where it's like something 80% or like 70% of bedside care is delivered
by nurses, but they're not part of the innovation RFP process.
Or they don't have a mechanism to share their challenges or pain points.
So that for me is like a big miss of not including everyone within that practice as part of the
journey, identifying the right end users as well.
So we're still seeing very much a top down model.
And I think we need to be honest, our innovation record in healthcare, but across industries
in Canada is one of the worst in the world.
So we have the lowest corporate R&D expenditure on technology in the G8.
So we find ourselves below Italy.
So that's not something that we might kind of like really conceptualize and think about.
This isn't healthcare being less than average at its ability to innovate.
We're seeing this in financial services, in manufacturing, in forestry, in education,
in any industry in Canada, we find ourselves in the last place of the G8.
So there's kind of this thing, like if you do something wrong once, do you repeat that
pattern or do you actually change it?
We find ourselves decades into this journey of we keep repeating the same pattern.
And what I would say is we need to break the model.
We need to try new things.
Probably the same model doesn't work for each organization or each individual, but not including
your people in that process, in that journey is a huge, huge miss.
My second thing that probably we'll get some hate mail for this one, but I've said it before,
so it's okay.
The second fallacy that I think organizations fall into is a very long, protracted, expensive
governance process.
Okay, so we are going to innovate XYZ.
So we need to talk to privacy, we need to talk to legal, and we need to talk to IT security,
we need to talk to ethics, and we probably need to hire a consultant and, you know, met
with one of my colleagues and they're frustrated, but they're into two plus years of working
on an AI governance framework for their organization.
It's the most beautiful framework you will ever see.
I hope they get it framed, but where we stand today after the tens of thousands of hours
that have been invested into that thing is the organization has not deployed any AI solutions.
So we're now in 2025 and they're not using AI after all that money.
So I wouldn't get hung up.
Yes, you need governance, but you need to be lean, smart, and action oriented of how you're
going through that process.
And yes, leadership needs to be engaged.
We would have that as part of like our strategy framework or our diamondy.
Yes, leadership needs to be aligned, but leadership doesn't need to lead and be the only decision
maker in an innovation process.
We need to keep our people and our end users engaged and part of that process as well.
Yeah, I think hospitals need to have an innovation department which has control over a few beds
in a marriage or in a floor and has full and has a budget and has the ability to deploy
that budget without any oversight from leadership.
I think there needs to be a distinct department which is separate from hospital governance,
legal leadership that can, you know, incorporate these projects.
Yeah, I completely agree.
And I mean, like your audience is mostly in healthcare, so they will get this, but we
see this in other areas as well.
So I spent some time in academia as I mentioned.
If we look at our org chart, how come we don't have a chief innovation officer or a chief
technology officer?
Like, isn't that strange that like some of these networks and systems are multi-million,
sometimes billion dollar organizations and we don't have a chief innovation or chief
technology officer?
We also sometimes don't have a chief marketing officer or chief revenue officer either.
And this goes for major academic health science networks.
This goes for many of the universities and colleges in the country.
So, you know, wearing my like business school hat of like, why do we find ourselves in the
position that we are?
Yeah, you know, we can tweak some things and we can blame economic policy or hate on whatever
political party we want or individual, but structurally, we've made some really weird
decisions, right?
Like, if we want to see more innovation commercialized out of our universities and academic hospitals,
how come there's not a chief commercialization officer at every university and hospital?
If we want our hospitals to, you know, be global brands like the MIT, the Harford, the
Stanford, the Oxford, it came from U of T and Ivy that have great brands.
But how come we don't have a chief marketing and revenue officer at every university and
hospital?
So, there's things where structurally, we find ourselves where we are because we've made
the decision, we've made the bed that we're lying in.
And that's things that could change, you know, to your point, can you appoint someone?
Can you give them a mandate money and people to go and change the way that care is delivered?
Absolutely.
There's nothing that's holding us back except our own ambition.
Last question, Michael.
If you could go back and talk to yourself 20 years ago, what advice would you give him?
You have no idea what's coming, but take a breath, it's all going to be okay.
Awesome.
Thank you, Michael.
Yeah, great to speak with you.
Thank you.