August 13, 2025 • 35 mins
What happens to our ability to think critically when we start outsourcing it to AI?
Professor Scott Anthony is one of the world’s leading experts on innovation and disruption and he believes the way we use AI today will shape the future of our judgment, creativity, and even our careers.
Scott is a professor at the Tuck School of Business, the former managing partner at Innosight (the firm co-founded by the late Clayton Christensen) and author of several books, including his latest, Epic Disruptions.
In this conversation, Scott shares how AI is transforming the way he teaches, consults, and thinks - and why he draws a firm line on where he will never let AI do the work. You’ll learn exactly how to leverage AI as a teammate without letting it hollow out your critical thinking skills, and why protecting your judgment is more important than ever.
If you’ve ever wondered, Am I thinking less deeply than I used to?—this episode might just change the way you work.
Check out Scott’s new book Epic Disruptions.
***
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
What happens to our ability to think critically when we
start outsourcing it to AI all the time? My guest today,
Professor Scott Anthony, is one of the world's leading experts
on innovation and disruption, and he believes that how we
use AI today could shape the future of our judgment,
our creativity, and even our careers. Scott is a professor
(00:25):
at the tuch School of Business. He's also the former
managing partner at Innosite, the firm co founded by the
Lake Clayton Christensen, and the author of several books, including
his latest one, Epic Disruptions. In this conversation, he shares
how AI is transforming the way he teaches, consults and thinks,
and why he draws a very firm line on where
(00:46):
he will never let AI do the work. By the
end of this episode, you'll know exactly how to leverage
AI as a teammate without letting it hollow out your
critical thinking skills. Why protecting your judgment is more important
than ever so if you've ever wondered, am I thinking
less deeply than I used to? This episode might just
(01:10):
change the way you work. Welcome to How I Work,
a show about habits rituals and strategies for optimizing your day.
I'm your host, doctor Amantha Imber. I want to start
(01:34):
by talking about change, because obviously a lot of your
work in the last couple of decades has involved massive
change in helping organizations navigate that, and I dare say
in both our careers, AI is the biggest disruptor that
we have both seen. Is that fair to say? Would
you say the Internet was larger Scott or are we
(01:57):
going with AI? Yeah?
Speaker 2 (01:58):
Time of course will tell on this, but I suspect
time will ultimately judge AI as the biggest disruptor in
our lifetime. And who knows what will come after this,
but at least of what we have seen thus far,
just the pervasive impact of it and really changing the
way that knowledge is created and transmitted and processed. That
has so much ubiquity, it's hard for that not to
(02:19):
have cascading disruptive effects.
Speaker 1 (02:21):
So I want to know, then, what are the biggest
changes that it's made to the way you work? As
a business professor.
Speaker 2 (02:28):
I am in the maybe somewhat advantage position compared to
some of my colleagues. I've only been teaching for three years,
so there's not that much I have to unlearn as
opposed to people who might be my age but have
been teaching for longer than three years.
Speaker 3 (02:42):
But whatever.
Speaker 2 (02:43):
But really you're seeing a change just about everything. Change
the way that you're doing research, change the way you're
putting together courses, change the way that you're running your classes,
change the way that you're assessing students. And we can
go deeper in each of these areas, but I think
that the headline is AI is to a degree changing
everything that's happening in universities, which really isn't a surprise.
(03:05):
I mean, what is a university. It's the creation and
dissemination of knowledge of words.
Speaker 3 (03:11):
And what is AI?
Speaker 2 (03:12):
Generator of AI very good at it's very good at
putting together words in unique ways. So those two things
come together in a kind of predictable sort of way.
Speaker 1 (03:21):
I do want to dig into learning, and we will
go there and also teaching as well. But first, one
of the things that when we last spoke that was
not a recorded conversation, one of the things that intrigued
me most is your latest book, Epic Disruptions. Your clause
with Harvard, who's your publisher, had what I thought was
quite a unique AI clause. Can you tell me about
(03:43):
what they stipulated for your book?
Speaker 2 (03:45):
Absolutely, and in preparation for this, I got the actual
language from it, which I hoped them any trouble with Harvard,
But I'll explain that the why behind it, which I
think will help. The exact clause is authors shall not
generate or use content for the work and collaborate with
or buy artificial intelligence tools SLASH applications without the prior
written consent of publisher. So I called it the thou
(04:08):
shalt not use AI clause again without coordinating with the publisher.
And when you first see that, you're like, oh, that
sounds kind of dragconian. But what's behind that. Well, it's
still unclear if work is generated by AI what that
means for copyright. And if you're a publisher and you
care about copyright, that's a really big deal. So if
you're reporting something to be original work but it's actually
(04:30):
plagiarized or not original work, that could be a real problem.
Speaker 3 (04:33):
So, of course there are.
Speaker 2 (04:34):
Ways that you can and should and do use AI
during the writing process, but the idea here is don't
outsource it, and if you do, please tell us not
Please tell us you must tell us.
Speaker 1 (04:45):
I found that interesting because I'm working on my fifth
book at the moment with Penguin Random House, and there
was no AI clause with them, which, after having that
discussion with you, made me think, hmm, maybe it's in
there now since I signed contracts. Maybe they're making all
their authors do that. But I was intrigued. And so
then in your book writing process, how did you use AI?
Speaker 2 (05:09):
If it all so the research and writing of the
chapters and just brief overview of the book epic disruptions
eleven innovations that.
Speaker 3 (05:16):
Shape our modern world. This is a history book.
Speaker 2 (05:19):
It starts with gunpowder, it goes up to the Apple iPhone,
with then a conclusion looking at disruptions that are in
process today. But there's a lot of research. So the
actual research of the chapters and the writing of the
chapters I did independently. What I used AI for was
to brainstorm, so what are really the epic disruptions that
(05:39):
should make the short list? I had some thoughts I
parried with open AI, chat GPT to come up with
some additional thoughts, kicked around ideas and so on, titling
what's the right way to title and trying to pull
out what are some of the themes that I'm seeing?
Speaker 3 (05:52):
Is it three? Is at five?
Speaker 2 (05:54):
Those kinds of things that are not in the writing,
but really in some of the things that wrap around it.
I found a to be incredibly helpful, not always perfect
at the end, you know, you have to own it yourself,
but if you're trying to expand your thinking, it's a
really useful tool.
Speaker 1 (06:08):
I know you're obviously an early adopter of Jenai, and
I imagine your approach to prompting and getting the best
out of it has evolved. Tell me how you use
it as a brainstorming partner.
Speaker 2 (06:19):
A lot of it is context engineering, you know, making
sure that you put in place the right parameters so
that you are getting a legitimately different perspective on things.
So whether that's taking on a different role, or it's
saying let's be a skeptic or let's be a supporter
or whatever, trying to make sure that you a set
the context where you're going to get something that is
(06:40):
what you're looking for, which might be something that's as
novel as possible or something that's more fine tune as possible,
whatever it is. The second is multiple tools My favorite
at the moment are Claude and chat Shept, So I'll
play them off each other so i'lle be simultaneously brainstorming
a topic. I'd be like, oh, the other one said this,
what do you think?
Speaker 3 (07:00):
Think about that?
Speaker 2 (07:01):
And at some point they converge because all the foundational
stuff will get you to the same place, but they
actually will start sometimes in very different places. And of
course we know if we use the systems, sometimes the
exact same prompts will go in different directions, just depending
on whatever is the magic that's happening underneath the hood.
But those two things are really trying to say, let's
push for the personas and get the context right and
(07:23):
then using different models. Those are the two things that
I found to be the most helpful.
Speaker 1 (07:27):
I will quite often when I'm working on quite a
big project where I want to get different views, I
will quite often have the same prompt in CHETJPT Claude
and Gemini and then finish with ask me you know
any questions so you can be ninety five percent confident
and doing a great job. And it's quite interesting the
different questions that I'll get back when it's a task
(07:49):
that could go in several different directions, So I do
love that as a way and kind of sparring them
against each other I found really useful. One of the
things that I wonder as I think a lot of
people and particularly knowledge workers that you know, whose value
is in their thinking use AI a lot, is I wonder, firstly,
(08:10):
what's going to happen to our ability to think critically?
And then what's going to happen to our ability to
maintain good judgment? And I want to know for you
with the thinking critically, how do you think about that
for yourself? And do you worry am I going to
lose the ability to think critically if I kind of
crossed that line where I've suddenly outsourced just a little
(08:32):
bit too much to AI?
Speaker 2 (08:33):
Yeah, it is something that I worry about a lot.
I worry even more about for my students and even
more for my children. So as you've got then three
generations there, You've got me nineteen seventy five, my kids
who were born between two thousand and five and twenty sixteen,
and then the students who generally are about thirty years old,
so the average day of birth would be about whatever
(08:53):
that is, nineteen ninety five. It really is being very
clear about the lines. I'm trying to do something that
does rep present original thinking. I just can't outsource that.
I can't ask AI for a first draft of something
I tried, you.
Speaker 3 (09:07):
Know, when it first came out. Of course, I'm going
to play around with it.
Speaker 2 (09:10):
So I'm like, okay, I've got an idea for a
new class, please, is not a curriculum for me? And
A the output was not particularly good, and B my
brain wasn't in it. I hadn't thought about it, I
hadn't processed it, I hadn't struggled, et cetera. So now
when I'm working on a new course, certainly I'll say, okay,
this bit of it, I need to think about some
additional readings, or I want to think about some of
(09:31):
the principles I want to teach here, so I'll get
help to sharpen. But ownership of the integration it has
to be by me or else. That's just a skill
that's going to lapse. So that, to me is the
most important thing. Drawing the line and being really clear
about where you draw that line. There are other tasks
that are less critical where I'm very happy to outsource.
(09:51):
More so as an example, I was facilitating a panel
discussion a couple months ago, and that was pretty much
churn and burn. You know, here are my panel us,
make me smarter about who they are, give me a
few good questions.
Speaker 1 (10:04):
Task.
Speaker 2 (10:04):
Okay, that's great raw material. I can then turn that
into a finished product. But I was totally fine with
first draft being done by AI. But when you really
need to turn on the critical thinking and reasoning, first
draft by AI, I think the research shows is really
really dangerous.
Speaker 1 (10:19):
It's interesting because I it would have been about a
year ago now. I had an executive from Google on
the show and they were talking about how their default
was to use AI or Gemini for the first draft
of everything as a place to start. And I kind
of get that because the blank page in any kind
(10:40):
of work can be a little bit confronting. No One,
particularly writers like us, like a blank page. But then
how do you decide like because I imagine sometimes it
is a fine line. The example that you've given is
quite stark. But are there examples where m you're kind
of on the fence about whether to use A to
(11:00):
help do the thinking versus you sit and struggle with
it and do the hard unpleasant deep work yourself.
Speaker 2 (11:09):
So you know, last term, I had sixty five students
in one of my classes, and there's qualitative feedback that
comes from the sixty five students, and the easy thing
to do is to dump it all in chat shept
and say, tell me the three themes that you see here.
And I did that, except I said, I want the
three themes that you see. I want the biggest outlier
(11:29):
that you see that is negative and that's positive, and
I want something random that you can throw back me.
And then I went and did the same thing over
at Claude. So again tried to have it go through
multiple models, so I didn't fall into the easy trap
of saying, Okay, this is set to warm, so it's
going to tell me that the very nice things my
students had to say, and I'll just be all done
and moved on. So I tried to make sure that
(11:50):
I balanced the big efficiency gains that I got from
not going through every word of everything while also being provoked.
And then I was so interested in the feedback I
did in the end go back and read all of it.
So it didn't end up saving any time at all,
but it was fun to look at it from various angles,
so you know, that is the thing that again back
to the conversation we had about the different ways that
you contact engineering, set perspectives. If you do, put some
(12:14):
things that will force you to critically reason into your
prompts so that what you're getting back is not just
the answer, but is an answer with outliers and as
you said, questions for consideration. Those I think are great
things that can help make sure we don't lose that
is that again, I think it is probably the most
important thing we're going to have to struggle with over
(12:35):
the next decade. And I worry, in a parallel to
what we saw in the book, that many of the
early adopters of AI are going to say, what have
we done? They'll say, at first, this is great, We've
got all these efficiency gains, and then X number of
years in the future they will have hollowed out their
ability to actually do things, and they'll say, we got
something wrong when we did this short term gain but
(12:57):
long term pain.
Speaker 1 (12:58):
Yeah. I really are worry about people's ability to think critically.
I mean, as humans, where we're programmed to go down
the path of least resistance, and that is to outsource
our thinking to AI, and I worry, like I feel
it in myself that it takes willpower to go Okay,
I need to sit here and I need to sit
(13:18):
in discomfort, and I need to do the thinking. And
I do choose to do that because integrity is valued
of mine. But I think it's you know, it's also
like I can see how a lot of people who
are known for their thinking and their quality of their thinking,
it's really easy to go down that path. And you know,
like I kind of look at what LinkedIn has become,
(13:41):
where you know thinkers that I used to follow kind
of like that is not you. You have not generated that.
Why am I even on LinkedIn? How do you feel
now about that as a platform, Like you're very active
on it, but what is your view of what's going
on there and how you're approaching it yourself as someone
who is you know, a great thinker?
Speaker 2 (13:59):
Well, ye, first of all, thanks for calling me a
great thinker sub days better than others. But you know,
a couple of years ago, I was participating in offsite
with a bunch of senior leaders from a large organization
and they said, we want some stimuli, and we want
stimuli not from you, but from younger voices. So I
asked my son Charlie, who was seventeen years old at
the time, to come in and share a perspective about AI,
(14:22):
and he said, look, everyone in my school is using
it all the time, and the thing I really worry
about is that we're going to end up like those
really obese humans in the movie Wally that have completely
lost their capacity to think about anything. None of the
metaphor we were talking about is you know, back in
the day when we were in high school, you could
go to the bathroom and you could buy the answers
(14:42):
to the test. You know, someone at the stall next
to you would have the answer key or whatever. And
people didn't do that because it was just so blatantly
obviously cheating. But now when you go to a large
language model and you ask for a first draft to something,
it doesn't feel like cheating, So, you know, it just
it feels different. And you talked about acting with integrity,
but you could also argue that people are using the
(15:04):
best tools available to be able to get the best
answers they can. So, you know, back to what we
are thinking about on campus, how do you actually go
and design educational experiences that encourage people to learn that
help them sit with the discomfort you talked about, teach
them to be comfortable in that discomfort, and then go
and assess them in a way that goes and says, Yes,
(15:26):
use the best tools that you can, but make sure
we're also developing critically as human beings.
Speaker 3 (15:31):
It's an incredibly hard topic.
Speaker 1 (15:33):
It's really good segue into your work in the business school,
the Taxical of Business, one of the top business schools
in America, Like, how is your approach to teaching what
I'm sure are incredibly smart minds, but who do have
access to AI and who theoretically can outsource their thinking?
(15:53):
How do you design a course and then assess these
students in this new world that we're in with great care?
Speaker 3 (16:00):
That's the short answer.
Speaker 2 (16:02):
That have some advantage in that the courses that I
teach are generally not fined and apply a mathematical formula
or use an off the shelf framework, but more around
critical thinking, really, and how do you deal with uncertainty
and how do you go and act when the data
is telling you not to and hear the voice that
doesn't speak and that stuff isn't regurgitation of frameworks that
(16:24):
you find in books. It's going and puzzling through things together,
very discussion oriented courses and so on, so along some dimensions.
I think it is easier in that context to do
what I do, which is tell students please use AI
to go and go through the case material or to
come up with first answers to questions.
Speaker 3 (16:41):
But we're going to be in a room.
Speaker 2 (16:43):
We're going to put ourselves in the shoes of a
participant or a case protagonist.
Speaker 3 (16:48):
We're going to talk about it, and the laptops.
Speaker 2 (16:49):
Are going to be closed and the cell phones are
going to be off. So you know, whatever you've done
to prepare, that's fine, But fifty percent of your grade,
then it is the discussion quality that we have in class.
So it's pushing on that in class experience and discussion.
That's point number one.
Speaker 3 (17:04):
Point number two.
Speaker 2 (17:05):
I'm thinking, and this is still emergent, thinking about how
do you assess learning in different ways? So I started
a couple terms ago giving people an option for the
final assignment.
Speaker 3 (17:15):
The old final assignment.
Speaker 2 (17:16):
Was take everything we learned in class, write a paper
about some company, some leader, apply learning from class. The
new option is take everything we learned in class, find
a leader, give me two hundred words about why you
pick this leader. Then design an AI tool to help
them learn something that you learned in class. And the
most critical thing I learned about that is and show
(17:38):
me your work. So the output I kind of care about.
What I really care about is the exact prompts you use,
the back and forth you had with the large language models,
the critical thinking you displayed, blah blah blah blah blah,
because I learned the first run. And sometimes you get
these very very elegant outputs that had a lot of
mess that went into them. I'm like, this is you
(17:58):
didn't do much work and actually did a ton. And
then sometimes you see these things where the output looked
super sophisticated, but the students did basically no work and
had no understanding. So if you don't see the work,
you don't understand that. And then finally, I sample size
the one. But I ran an experiment the last term
where I did a thirty minute interview with the student
at the end of the term and said, we're going
(18:20):
to try this out, just see what it's like. But
pick a situation, let's talk, so you know, just trying
to figure out different ways to assess whether people really
have learned, in some cases leaning into AI, in some
cases going about as old school as you'll go. And
this is an example of one of something that every
educator is thinking about right now.
Speaker 1 (18:37):
Now, I do want to talk about consulting and the
context you worked in the world of management consulting for
I want to say about twenty years Scott nailed it. Yeah, fantastic. Yeah.
And during that time you were managing partner of you know, Site,
which is the firm that the late Clayton Christiansen started,
and that is how we connected when you were you know,
(19:00):
several years ago. So I want to understand, like, if
you were still working in consulting, how do you think
you would be using AI for client work.
Speaker 2 (19:11):
I want to give you a historical example first, then
I'll come answer it. So, you know, fourteen forty Gudenbergen
team comes up with the printing press. We know the
basic story. The world changes. The thing that I just
want to reflect on is who is Gudenberg's first actual customer. Well,
it's the Catholic Church and it makes a lot of
sense dominant organization.
Speaker 3 (19:28):
It's time.
Speaker 2 (19:29):
Not that many Bibles could be created if you have
to hand inscribe them. The printing press makes it much
easier for the Catholic Church to disseminate the Bible that
looks good in the beginning. Martin Luther picks up the
very same technology and the Reformation happens, and the Catholic
Church might ultimately regret the fact that it helped the
fund and innovation that yes, helped u spread the Bible,
(19:50):
but also kind of tore the church apart. And I
tell this story because I think you're going to see
a very similar story for the major consulting companies and
artificial intelligence. Right now, it's a great time for a
lot of the consultancies. But I think you're going to
see two things. I think one, clients are going to say,
we actually don't need a consultancy. There's a lot more
that we're now capable of doing ourselves. A number two,
(20:13):
we have hollowed out the consultancies will say a lot
of our capabilities. So we've got a generation of leaders
that can go and provide eye to eye advice to
top senior leaders and have great judgment and so on.
But the efficiency gains that we got mean that we
don't have another generation that comes after it. I think
we're going to see both those things happen over the
course of the next five to ten years.
Speaker 3 (20:34):
If I were in the field now, I.
Speaker 2 (20:36):
Would be doing all the things that I think smart
people are doing, which is show up to client meetings,
being even smarter, have teams work even faster, have multiple
possibilities being considered in ways that you couldn't do before,
really live up to the full possibility what you can do.
I was at a small company, but now a small
company can look like a big company because you have
(20:56):
all these tools you can take advantage of. That's if
I was still at that company. The thing I also
would be thinking really hard about is is.
Speaker 3 (21:03):
This the right model?
Speaker 2 (21:04):
You know, in a site, like many people in consultancy
got a traditional pyramid model, and people are beginning to say, well,
maybe it's diamonds where you've got you know, a few people.
Maybe it's something that is an inverted pyramid where actually
you have more people at the top who are the
good judgment people that can advise senior clients, and they
don't need to have the people who are doing all
(21:26):
the work at the bottom. I don't know the answer
to that, but I certainly would be thinking really hard
about the new models that are going to be emerging.
Speaker 1 (21:33):
If you were still working with junior consultants, how would
you be teaching them to think critically?
Speaker 2 (21:40):
AI essentially is your new teammate, your new intern, whatever
metaphor you want to use. It's got amazing superpowers. Sometimes
it does some really weird things like make stuff up
or dramatically underperform some things you think it's going to
be good at. The way you figure these things out
is by working very closely with it, never ever outsourced
to it, and recognize life is better in teams and
(22:03):
research shows life is actually sociologically better with AI, as
long as you don't do too much with it and
now source too much to it. But make sure that
you are pushing and using it to augment versus replacing,
because that will be a very short sighted and destructive path.
I mentioned Bobby Hansen before. In his book Leaders Make
the Future that the third edition, he said, you know,
(22:24):
one of the most important things that a future has
to do is be very precise on language, because the
right language will pull you somewhere, the wrong language will
push you away from And he writes in his fifty
years doing this. Artificial intelligence is the worst name for
a new technology he has ever seen, because artificial makes
it sound like it's replaceative, and what you really want
(22:45):
is augmented, where it is something that allows you to
stretch and push and develop further, and that is the
thing I would really be pushing among the young talent
at the organization.
Speaker 3 (22:55):
Don't stop thinking. Once you stop thinking, it's kind of over.
Speaker 1 (22:58):
If you're finding this conversation with Scott Anthony as helpful
as I am, stay with us because in the second half,
Scott reveals why he has started thinking about his life
in five year cycles, and also his advice for improving
your ability to think critically in the age of AI.
(23:19):
If you're looking for more tips to improve the way
you work can live. I write a short weekly newsletter
that contains tactics I've discovered that have helped me personally.
You can sign up for that at Amantha dot com.
That's Amantha dot com. How would you be approaching recruitment
(23:42):
because I feel like I'm seeing a lot of companies
really struggle with this, particularly in those early stages where
you're not having those in depth interviews face to face
because I mean even virtual interviews these days, you know,
I hear all sorts of stories about an AI going
on in the background and putting out answers to questions
that people are being asked. What would you do to
(24:05):
test the ability of someone to think? In this day
and age.
Speaker 2 (24:08):
What I would wish for is a way to be
in a physical location with someone and have a conversation
with them. I think, just the ability to actually have
a conversation with somebody and not ask how many taxi
cabs are there in New York City or whatever, but
just see the way that they approach issues. The approach
I followed what I was interviewing in a sight is
(24:29):
I said, would give people here are ten disruptions that
are in process right now, or ten companies that have
been called disruptive. Pick any one of them and come
up with a point of view, are they actually disruptive?
And if you were caught in a lift with the CEO,
what would you say to them? And I did that
for two reasons.
Speaker 3 (24:47):
One, I want to.
Speaker 2 (24:47):
See what they did with it, and then two, once
we're in a room together that I can push them
and they've had the benefit of being able to think
about it for some period of time.
Speaker 3 (24:55):
And we'd have fun.
Speaker 1 (24:57):
You know.
Speaker 2 (24:57):
Sometimes people would go and produce a PowerPoint tech. I
didn't ask them to do that, but sometimes people would.
Sometimes I get a Microsoft word memos. Sometimes people would
just talk. But it was a really good way just
to get into a conversation where you could see how
someone thinks. I don't know a better way to do it,
you know, I mean you could say psychometric tests or whatever, perhaps,
but you know, I mean, as we know, anything can
(25:17):
be gamed these days.
Speaker 3 (25:18):
It's not easy.
Speaker 1 (25:19):
We talked about critical thinking. I want to talk about
good judgment. How do you help your students develop the
ability to have good judgment? I feel like, and maybe
this is a flawed assumption, but the longer you do something,
the more experience you develop. Generally your judgment becomes better
and better because it's the collection of all the different
(25:40):
experiences that you've had. But how do you think about
the ability to have good judgment and to improve that ability?
Speaker 2 (25:48):
I would like to think that experience makes you better
at having judgment, but I think at least some research
and data would suggest you get some real blind spots.
Speaker 3 (25:57):
Is you're used to.
Speaker 2 (25:59):
Defaulting to certain things and if the situation changes. And
with that, what I really try to do is I
try to essentially give students heuristics and say, what you're
going to do or what you're going to get are
rules of thumbs, mental models, way to think through things
that essentially can help you. So it's not that you
as an individual have judgment. It's you've got a tool
(26:21):
that you can use, and what you have to figure
out is what is the right tool to use in
a context. And this is the thing that I learned
from Clay Christiansen. You know, he used to joke that
his wife Christine would say the famous disruptive line diagram
that's in all of his stuff, it was etched onto
his glasses. Everywhere he looked, he saw disruption. I wear
contact lenses, so the models are like fused under my eyes,
(26:43):
so you know, everywhere I look, I see it. And
that's sometimes maybe a tiny bit of a curse, but
what it really is is a blessing. It allows you
to see things that you wouldn't otherwise see. And whenever
someone asks Clay what's your opinion or your viewpoint about
extra y, Clay would say, I've got no viewpoints or opinions.
The model has a viewpoint, and he was such a
good social scientist. When that didn't happen, he'd say, oh, great,
(27:05):
we found an anomaly, something that didn't fit.
Speaker 3 (27:07):
Therefore the bottle must be wrong in some way. Let's upgrade.
Speaker 2 (27:11):
The vision of our school is to develop wise, decisive
leaders that better the world through business. A wise leader,
in my view, is one who has a whole range
of tools that they can use and knows when to
use them and how to use them.
Speaker 1 (27:24):
I love that, and I guess the follow one question
from that, like, when you yourself are looking at creating a
new model or a framework with which to view the world,
what role does AI play in helping augment your thinking
or does it not play a role there?
Speaker 2 (27:42):
I have an idea that's been bouncing around the back
of my head for a few years now, and this
is what does it really take to be a leader
that can successfully navigate today's world of radical uncertainty? A brand,
the idea, adaptive capacity. And the idea basically is you
need three things. You need metacognition, which means you think
about how you think and have lots.
Speaker 3 (28:03):
Of models at your disposal.
Speaker 2 (28:05):
You need equanimity, the ability to pause so you don't
get overwhelmed with all these models that you have in
your head at a paradox mindset that allows you to
take perceive tensions and turn them into possibilities. As I've
been advancing my thinking about this, AI number one has
been a research partner, so use some of the emerging
research capabilities to say that idea about.
Speaker 3 (28:26):
There not being anything like this, is that true?
Speaker 2 (28:29):
What else do you see out there? What research you
see blah blah blah blah blah. So a research partner.
Number two an experiment designer. So I have been trying
to think about ways to actually go and test this, validated, etc.
Speaker 3 (28:41):
So this will be the sort of thing where I
will idly go and brainstorm. I was thinking about this,
what do you think, etc. Etc. I have a thought
about doing synthetic research.
Speaker 2 (28:50):
I've not done that, but I thought it would be
really cool if you were to actually use AI to
create a simulation to go in test hypotheses. That is
beyond my current capabilities, but something that is on the
list of things to continue to push. Barring from slow
productivity from caw Newport, I work on a five year
timeline for some of these things. So I want to
crack this in the next now four years, since I
(29:10):
set that a year ago, so I'm okay with not
having synthetic research yet, but that's an area that I'm
watching to see if that's something that you actually can't
do with any materiality.
Speaker 1 (29:19):
Tell me more about this five year cycle. I'm curious.
I did not know that about you.
Speaker 2 (29:24):
So caw Newport, who I know. You're a fan of
his book Slow Productivity. I was one of the best
books I read a couple of years ago, and he
had this idea, you know, slow down, slow down. Don't
think necessarily about what you're doing over the next week, month,
or quarter, but really think about what are your aspirations
over a five year time period. As they said, when
you relax the timeline, you're able to just handle things
(29:47):
moving at different paces. So when I did this a
year ago, I said three things that I would like
to do professionally over the next five years. One, I
want to crack this adaptive capacity idea. Two, I want
to do something I've never done before, which is have
my name on a peer reviewed academic article, not the
lead author, but I can be the tenth author. That's fine.
(30:08):
And number three, I'd really like to win a teaching award.
I just validate and demonstrate that I improved my ability
to teach in class.
Speaker 3 (30:15):
So those are the three things I'm saying this on
am I allowed to say the date clus you are
July fourteen, twenty.
Speaker 2 (30:22):
Twenty five, so we can time capsule and check in
on this four years from now.
Speaker 1 (30:26):
Oh wow, I love that. What are some other habits
or rituals or things that you're you've been playing around
with around how you do work? Like? I love the
five year thing, and I always feel like you're someone
that's experimenting with different ways of working and augmenting your productivity.
Speaker 3 (30:42):
I'll call this one Can I watch? And can I watch?
Speaker 1 (30:45):
Is?
Speaker 2 (30:46):
I started teaching three years ago and the school that
I teach at is blessed with a number of really,
really world class teachers. So I've made a regular habit
whenever I'm in a teaching cycle, which tends to be
about a five week cycle, I try to go and
observe at least one and hopefully two other faculty, usually
ones that my students recommend, you know, just who's really
(31:07):
great at running a class. And in those can I
watch moments. I don't care at all about the content.
I'm not going there to learn, you know, what this
teacher is teaching about this topic.
Speaker 3 (31:17):
I'm just absorbing the way that they're running.
Speaker 2 (31:19):
The room, what the students are doing, who's locked in,
who's not locked in, how they're using their physicality, blah
blah blah blah blah, and just trying to get a
sense as to what it takes to really really command
a room of sixty plus very smart NBA students who
again are blessed with a lot of really great teachers.
And I'm sure some of the things they're teaching are
(31:40):
getting into my unconscious as well. But that idea of
being very purposeful in getting stimuli that's different from normal stimuli,
that has been something that has.
Speaker 3 (31:49):
Been one of the more rewarding.
Speaker 2 (31:51):
Routines I've had in the last few years. And I've
made some new friends from doing it too, which is
always nice.
Speaker 1 (31:57):
I love that. Tell me, what are a couple of
things that you've larn from you? Can I watch sessions?
Speaker 2 (32:02):
Is one Joseph Garaco, who teaches in the accounting unit
at talk. I said in one of his sessions, and
you know, I thought, and Joseph, if you're watching this,
I hope you take it in good spirit. I thought
it was going to be the most boring session ever.
I mean, he'd want a teaching a ward, but I'm like,
it's accounting.
Speaker 3 (32:17):
You know. Even though my.
Speaker 2 (32:18):
Grandfather was an accounting teacher, he was not known for
being dynamic. But the thing that Joseph really showed me
is you can find real moments of inspiration by letting
students really go and dwell on seemingly small things. And
what he was really great at doing is opening his
session with what seemed like a really simple question, but
(32:40):
one that just expanded into an hour of really good
discussion where he also could teach about how working capital
works and all that. So the thing I learned from
Joseph is the power of a very very well thought
through opening question when you're in a good class discussion.
Then I sat in the class that Paul Argenti, who
tea in communication and a couple other fields, it talk
(33:03):
a couple months ago, and I noticed he just had
this theme where he was talking about corporate activism and
he used pretty evocative language that I won't repeat to
not get him in trouble, but I just really got
the room. It's like the room like all devices went down.
Everyone was on him and like, how rehearse was that?
He said, I've been doing this for thirty years. It's
(33:24):
just like not quite a scriptive performance, but you know,
just really a way to pull people in. So this
idea that you are, to some degree, for better or worse,
when you're teaching a class, you're a performer, and you
want to think about how you're going to use what
great performers do is the thing I picked up from him.
So great questions and think about, of course teaching, but
a little bit of performance mixed in. Those are a
(33:47):
couple of things I've picked up.
Speaker 1 (33:48):
I love that well, Scott. It's just like it's always
just such a joy to talk. Whether it's on Mike
or off Mike. I always feel like I learn so
many new things and I just love your way of thinking.
Thank you so much for extending your workday on the
East Coast to have this chat with.
Speaker 3 (34:05):
Me, Namantha.
Speaker 2 (34:06):
It is always a pleasure, and thank you for starting
your workday early in Melbourne to have this chat with
me very much.
Speaker 3 (34:11):
Appreciate it. As always.
Speaker 1 (34:14):
I hope you enjoyed this chat with Scott Anthony. For me,
the biggest takeaway is this AI is an incredible partner,
but it should never replace the discomfort of thinking for yourself.
And if this episode gave you a new way to
think about your own work, please share it with a
friend or a colleague and make sure to follow How
I Work so you don't miss future conversations like this.
(34:37):
Thank you so much for listening, and here's to working
smarter with our brains fully switched on. If you like
today's Joe, make sure you g'd follow on your podcast
app to be alerted when new episodes drop. How I
Work was recorded on the traditional land of the Warrangery People,
part of the Cooler Nation.
What happens to our ability to think critically when we
start outsourcing it to AI all the time? My guest today,
Professor Scott Anthony, is one of the world's leading experts
on innovation and disruption, and he believes that how we
use AI today could shape the future of our judgment,
our creativity, and even our careers. Scott is a professor
(00:25):
at the tuch School of Business. He's also the former
managing partner at Innosite, the firm co founded by the
Lake Clayton Christensen, and the author of several books, including
his latest one, Epic Disruptions. In this conversation, he shares
how AI is transforming the way he teaches, consults and thinks,
and why he draws a very firm line on where
(00:46):
he will never let AI do the work. By the
end of this episode, you'll know exactly how to leverage
AI as a teammate without letting it hollow out your
critical thinking skills. Why protecting your judgment is more important
than ever so if you've ever wondered, am I thinking
less deeply than I used to? This episode might just
(01:10):
change the way you work. Welcome to How I Work,
a show about habits rituals and strategies for optimizing your day.
I'm your host, doctor Amantha Imber. I want to start
(01:34):
by talking about change, because obviously a lot of your
work in the last couple of decades has involved massive
change in helping organizations navigate that, and I dare say
in both our careers, AI is the biggest disruptor that
we have both seen. Is that fair to say? Would
you say the Internet was larger Scott or are we
(01:57):
going with AI? Yeah?
Speaker 2 (01:58):
Time of course will tell on this, but I suspect
time will ultimately judge AI as the biggest disruptor in
our lifetime. And who knows what will come after this,
but at least of what we have seen thus far,
just the pervasive impact of it and really changing the
way that knowledge is created and transmitted and processed. That
has so much ubiquity, it's hard for that not to
(02:19):
have cascading disruptive effects.
Speaker 1 (02:21):
So I want to know, then, what are the biggest
changes that it's made to the way you work? As
a business professor.
Speaker 2 (02:28):
I am in the maybe somewhat advantage position compared to
some of my colleagues. I've only been teaching for three years,
so there's not that much I have to unlearn as
opposed to people who might be my age but have
been teaching for longer than three years.
Speaker 3 (02:42):
But whatever.
Speaker 2 (02:43):
But really you're seeing a change just about everything. Change
the way that you're doing research, change the way you're
putting together courses, change the way that you're running your classes,
change the way that you're assessing students. And we can
go deeper in each of these areas, but I think
that the headline is AI is to a degree changing
everything that's happening in universities, which really isn't a surprise.
(03:05):
I mean, what is a university. It's the creation and
dissemination of knowledge of words.
Speaker 3 (03:11):
And what is AI?
Speaker 2 (03:12):
Generator of AI very good at it's very good at
putting together words in unique ways. So those two things
come together in a kind of predictable sort of way.
Speaker 1 (03:21):
I do want to dig into learning, and we will
go there and also teaching as well. But first, one
of the things that when we last spoke that was
not a recorded conversation, one of the things that intrigued
me most is your latest book, Epic Disruptions. Your clause
with Harvard, who's your publisher, had what I thought was
quite a unique AI clause. Can you tell me about
(03:43):
what they stipulated for your book?
Speaker 2 (03:45):
Absolutely, and in preparation for this, I got the actual
language from it, which I hoped them any trouble with Harvard,
But I'll explain that the why behind it, which I
think will help. The exact clause is authors shall not
generate or use content for the work and collaborate with
or buy artificial intelligence tools SLASH applications without the prior
written consent of publisher. So I called it the thou
(04:08):
shalt not use AI clause again without coordinating with the publisher.
And when you first see that, you're like, oh, that
sounds kind of dragconian. But what's behind that. Well, it's
still unclear if work is generated by AI what that
means for copyright. And if you're a publisher and you
care about copyright, that's a really big deal. So if
you're reporting something to be original work but it's actually
(04:30):
plagiarized or not original work, that could be a real problem.
Speaker 3 (04:33):
So, of course there are.
Speaker 2 (04:34):
Ways that you can and should and do use AI
during the writing process, but the idea here is don't
outsource it, and if you do, please tell us not
Please tell us you must tell us.
Speaker 1 (04:45):
I found that interesting because I'm working on my fifth
book at the moment with Penguin Random House, and there
was no AI clause with them, which, after having that
discussion with you, made me think, hmm, maybe it's in
there now since I signed contracts. Maybe they're making all
their authors do that. But I was intrigued. And so
then in your book writing process, how did you use AI?
Speaker 2 (05:09):
If it all so the research and writing of the
chapters and just brief overview of the book epic disruptions
eleven innovations that.
Speaker 3 (05:16):
Shape our modern world. This is a history book.
Speaker 2 (05:19):
It starts with gunpowder, it goes up to the Apple iPhone,
with then a conclusion looking at disruptions that are in
process today. But there's a lot of research. So the
actual research of the chapters and the writing of the
chapters I did independently. What I used AI for was
to brainstorm, so what are really the epic disruptions that
(05:39):
should make the short list? I had some thoughts I
parried with open AI, chat GPT to come up with
some additional thoughts, kicked around ideas and so on, titling
what's the right way to title and trying to pull
out what are some of the themes that I'm seeing?
Speaker 3 (05:52):
Is it three? Is at five?
Speaker 2 (05:54):
Those kinds of things that are not in the writing,
but really in some of the things that wrap around it.
I found a to be incredibly helpful, not always perfect
at the end, you know, you have to own it yourself,
but if you're trying to expand your thinking, it's a
really useful tool.
Speaker 1 (06:08):
I know you're obviously an early adopter of Jenai, and
I imagine your approach to prompting and getting the best
out of it has evolved. Tell me how you use
it as a brainstorming partner.
Speaker 2 (06:19):
A lot of it is context engineering, you know, making
sure that you put in place the right parameters so
that you are getting a legitimately different perspective on things.
So whether that's taking on a different role, or it's
saying let's be a skeptic or let's be a supporter
or whatever, trying to make sure that you a set
the context where you're going to get something that is
(06:40):
what you're looking for, which might be something that's as
novel as possible or something that's more fine tune as possible,
whatever it is. The second is multiple tools My favorite
at the moment are Claude and chat Shept, So I'll
play them off each other so i'lle be simultaneously brainstorming
a topic. I'd be like, oh, the other one said this,
what do you think?
Speaker 3 (07:00):
Think about that?
Speaker 2 (07:01):
And at some point they converge because all the foundational
stuff will get you to the same place, but they
actually will start sometimes in very different places. And of
course we know if we use the systems, sometimes the
exact same prompts will go in different directions, just depending
on whatever is the magic that's happening underneath the hood.
But those two things are really trying to say, let's
push for the personas and get the context right and
(07:23):
then using different models. Those are the two things that
I found to be the most helpful.
Speaker 1 (07:27):
I will quite often when I'm working on quite a
big project where I want to get different views, I
will quite often have the same prompt in CHETJPT Claude
and Gemini and then finish with ask me you know
any questions so you can be ninety five percent confident
and doing a great job. And it's quite interesting the
different questions that I'll get back when it's a task
(07:49):
that could go in several different directions, So I do
love that as a way and kind of sparring them
against each other I found really useful. One of the
things that I wonder as I think a lot of
people and particularly knowledge workers that you know, whose value
is in their thinking use AI a lot, is I wonder, firstly,
(08:10):
what's going to happen to our ability to think critically?
And then what's going to happen to our ability to
maintain good judgment? And I want to know for you
with the thinking critically, how do you think about that
for yourself? And do you worry am I going to
lose the ability to think critically if I kind of
crossed that line where I've suddenly outsourced just a little
(08:32):
bit too much to AI?
Speaker 2 (08:33):
Yeah, it is something that I worry about a lot.
I worry even more about for my students and even
more for my children. So as you've got then three
generations there, You've got me nineteen seventy five, my kids
who were born between two thousand and five and twenty sixteen,
and then the students who generally are about thirty years old,
so the average day of birth would be about whatever
(08:53):
that is, nineteen ninety five. It really is being very
clear about the lines. I'm trying to do something that
does rep present original thinking. I just can't outsource that.
I can't ask AI for a first draft of something
I tried, you.
Speaker 3 (09:07):
Know, when it first came out. Of course, I'm going
to play around with it.
Speaker 2 (09:10):
So I'm like, okay, I've got an idea for a
new class, please, is not a curriculum for me? And
A the output was not particularly good, and B my
brain wasn't in it. I hadn't thought about it, I
hadn't processed it, I hadn't struggled, et cetera. So now
when I'm working on a new course, certainly I'll say, okay,
this bit of it, I need to think about some
additional readings, or I want to think about some of
(09:31):
the principles I want to teach here, so I'll get
help to sharpen. But ownership of the integration it has
to be by me or else. That's just a skill
that's going to lapse. So that, to me is the
most important thing. Drawing the line and being really clear
about where you draw that line. There are other tasks
that are less critical where I'm very happy to outsource.
(09:51):
More so as an example, I was facilitating a panel
discussion a couple months ago, and that was pretty much
churn and burn. You know, here are my panel us,
make me smarter about who they are, give me a
few good questions.
Speaker 1 (10:04):
Task.
Speaker 2 (10:04):
Okay, that's great raw material. I can then turn that
into a finished product. But I was totally fine with
first draft being done by AI. But when you really
need to turn on the critical thinking and reasoning, first
draft by AI, I think the research shows is really
really dangerous.
Speaker 1 (10:19):
It's interesting because I it would have been about a
year ago now. I had an executive from Google on
the show and they were talking about how their default
was to use AI or Gemini for the first draft
of everything as a place to start. And I kind
of get that because the blank page in any kind
(10:40):
of work can be a little bit confronting. No One,
particularly writers like us, like a blank page. But then
how do you decide like because I imagine sometimes it
is a fine line. The example that you've given is
quite stark. But are there examples where m you're kind
of on the fence about whether to use A to
(11:00):
help do the thinking versus you sit and struggle with
it and do the hard unpleasant deep work yourself.
Speaker 2 (11:09):
So you know, last term, I had sixty five students
in one of my classes, and there's qualitative feedback that
comes from the sixty five students, and the easy thing
to do is to dump it all in chat shept
and say, tell me the three themes that you see here.
And I did that, except I said, I want the
three themes that you see. I want the biggest outlier
(11:29):
that you see that is negative and that's positive, and
I want something random that you can throw back me.
And then I went and did the same thing over
at Claude. So again tried to have it go through
multiple models, so I didn't fall into the easy trap
of saying, Okay, this is set to warm, so it's
going to tell me that the very nice things my
students had to say, and I'll just be all done
and moved on. So I tried to make sure that
(11:50):
I balanced the big efficiency gains that I got from
not going through every word of everything while also being provoked.
And then I was so interested in the feedback I
did in the end go back and read all of it.
So it didn't end up saving any time at all,
but it was fun to look at it from various angles,
so you know, that is the thing that again back
to the conversation we had about the different ways that
you contact engineering, set perspectives. If you do, put some
(12:14):
things that will force you to critically reason into your
prompts so that what you're getting back is not just
the answer, but is an answer with outliers and as
you said, questions for consideration. Those I think are great
things that can help make sure we don't lose that
is that again, I think it is probably the most
important thing we're going to have to struggle with over
(12:35):
the next decade. And I worry, in a parallel to
what we saw in the book, that many of the
early adopters of AI are going to say, what have
we done? They'll say, at first, this is great, We've
got all these efficiency gains, and then X number of
years in the future they will have hollowed out their
ability to actually do things, and they'll say, we got
something wrong when we did this short term gain but
(12:57):
long term pain.
Speaker 1 (12:58):
Yeah. I really are worry about people's ability to think critically.
I mean, as humans, where we're programmed to go down
the path of least resistance, and that is to outsource
our thinking to AI, and I worry, like I feel
it in myself that it takes willpower to go Okay,
I need to sit here and I need to sit
(13:18):
in discomfort, and I need to do the thinking. And
I do choose to do that because integrity is valued
of mine. But I think it's you know, it's also
like I can see how a lot of people who
are known for their thinking and their quality of their thinking,
it's really easy to go down that path. And you know,
like I kind of look at what LinkedIn has become,
(13:41):
where you know thinkers that I used to follow kind
of like that is not you. You have not generated that.
Why am I even on LinkedIn? How do you feel
now about that as a platform, Like you're very active
on it, but what is your view of what's going
on there and how you're approaching it yourself as someone
who is you know, a great thinker?
Speaker 2 (13:59):
Well, ye, first of all, thanks for calling me a
great thinker sub days better than others. But you know,
a couple of years ago, I was participating in offsite
with a bunch of senior leaders from a large organization
and they said, we want some stimuli, and we want
stimuli not from you, but from younger voices. So I
asked my son Charlie, who was seventeen years old at
the time, to come in and share a perspective about AI,
(14:22):
and he said, look, everyone in my school is using
it all the time, and the thing I really worry
about is that we're going to end up like those
really obese humans in the movie Wally that have completely
lost their capacity to think about anything. None of the
metaphor we were talking about is you know, back in
the day when we were in high school, you could
go to the bathroom and you could buy the answers
(14:42):
to the test. You know, someone at the stall next
to you would have the answer key or whatever. And
people didn't do that because it was just so blatantly
obviously cheating. But now when you go to a large
language model and you ask for a first draft to something,
it doesn't feel like cheating, So, you know, it just
it feels different. And you talked about acting with integrity,
but you could also argue that people are using the
(15:04):
best tools available to be able to get the best
answers they can. So, you know, back to what we
are thinking about on campus, how do you actually go
and design educational experiences that encourage people to learn that
help them sit with the discomfort you talked about, teach
them to be comfortable in that discomfort, and then go
and assess them in a way that goes and says, Yes,
(15:26):
use the best tools that you can, but make sure
we're also developing critically as human beings.
Speaker 3 (15:31):
It's an incredibly hard topic.
Speaker 1 (15:33):
It's really good segue into your work in the business school,
the Taxical of Business, one of the top business schools
in America, Like, how is your approach to teaching what
I'm sure are incredibly smart minds, but who do have
access to AI and who theoretically can outsource their thinking?
(15:53):
How do you design a course and then assess these
students in this new world that we're in with great care?
Speaker 3 (16:00):
That's the short answer.
Speaker 2 (16:02):
That have some advantage in that the courses that I
teach are generally not fined and apply a mathematical formula
or use an off the shelf framework, but more around
critical thinking, really, and how do you deal with uncertainty
and how do you go and act when the data
is telling you not to and hear the voice that
doesn't speak and that stuff isn't regurgitation of frameworks that
(16:24):
you find in books. It's going and puzzling through things together,
very discussion oriented courses and so on, so along some dimensions.
I think it is easier in that context to do
what I do, which is tell students please use AI
to go and go through the case material or to
come up with first answers to questions.
Speaker 3 (16:41):
But we're going to be in a room.
Speaker 2 (16:43):
We're going to put ourselves in the shoes of a
participant or a case protagonist.
Speaker 3 (16:48):
We're going to talk about it, and the laptops.
Speaker 2 (16:49):
Are going to be closed and the cell phones are
going to be off. So you know, whatever you've done
to prepare, that's fine, But fifty percent of your grade,
then it is the discussion quality that we have in class.
So it's pushing on that in class experience and discussion.
That's point number one.
Speaker 3 (17:04):
Point number two.
Speaker 2 (17:05):
I'm thinking, and this is still emergent, thinking about how
do you assess learning in different ways? So I started
a couple terms ago giving people an option for the
final assignment.
Speaker 3 (17:15):
The old final assignment.
Speaker 2 (17:16):
Was take everything we learned in class, write a paper
about some company, some leader, apply learning from class. The
new option is take everything we learned in class, find
a leader, give me two hundred words about why you
pick this leader. Then design an AI tool to help
them learn something that you learned in class. And the
most critical thing I learned about that is and show
(17:38):
me your work. So the output I kind of care about.
What I really care about is the exact prompts you use,
the back and forth you had with the large language models,
the critical thinking you displayed, blah blah blah blah blah,
because I learned the first run. And sometimes you get
these very very elegant outputs that had a lot of
mess that went into them. I'm like, this is you
(17:58):
didn't do much work and actually did a ton. And
then sometimes you see these things where the output looked
super sophisticated, but the students did basically no work and
had no understanding. So if you don't see the work,
you don't understand that. And then finally, I sample size
the one. But I ran an experiment the last term
where I did a thirty minute interview with the student
at the end of the term and said, we're going
(18:20):
to try this out, just see what it's like. But
pick a situation, let's talk, so you know, just trying
to figure out different ways to assess whether people really
have learned, in some cases leaning into AI, in some
cases going about as old school as you'll go. And
this is an example of one of something that every
educator is thinking about right now.
Speaker 1 (18:37):
Now, I do want to talk about consulting and the
context you worked in the world of management consulting for
I want to say about twenty years Scott nailed it. Yeah, fantastic. Yeah.
And during that time you were managing partner of you know, Site,
which is the firm that the late Clayton Christiansen started,
and that is how we connected when you were you know,
(19:00):
several years ago. So I want to understand, like, if
you were still working in consulting, how do you think
you would be using AI for client work.
Speaker 2 (19:11):
I want to give you a historical example first, then
I'll come answer it. So, you know, fourteen forty Gudenbergen
team comes up with the printing press. We know the
basic story. The world changes. The thing that I just
want to reflect on is who is Gudenberg's first actual customer. Well,
it's the Catholic Church and it makes a lot of
sense dominant organization.
Speaker 3 (19:28):
It's time.
Speaker 2 (19:29):
Not that many Bibles could be created if you have
to hand inscribe them. The printing press makes it much
easier for the Catholic Church to disseminate the Bible that
looks good in the beginning. Martin Luther picks up the
very same technology and the Reformation happens, and the Catholic
Church might ultimately regret the fact that it helped the
fund and innovation that yes, helped u spread the Bible,
(19:50):
but also kind of tore the church apart. And I
tell this story because I think you're going to see
a very similar story for the major consulting companies and
artificial intelligence. Right now, it's a great time for a
lot of the consultancies. But I think you're going to
see two things. I think one, clients are going to say,
we actually don't need a consultancy. There's a lot more
that we're now capable of doing ourselves. A number two,
(20:13):
we have hollowed out the consultancies will say a lot
of our capabilities. So we've got a generation of leaders
that can go and provide eye to eye advice to
top senior leaders and have great judgment and so on.
But the efficiency gains that we got mean that we
don't have another generation that comes after it. I think
we're going to see both those things happen over the
course of the next five to ten years.
Speaker 3 (20:34):
If I were in the field now, I.
Speaker 2 (20:36):
Would be doing all the things that I think smart
people are doing, which is show up to client meetings,
being even smarter, have teams work even faster, have multiple
possibilities being considered in ways that you couldn't do before,
really live up to the full possibility what you can do.
I was at a small company, but now a small
company can look like a big company because you have
(20:56):
all these tools you can take advantage of. That's if
I was still at that company. The thing I also
would be thinking really hard about is is.
Speaker 3 (21:03):
This the right model?
Speaker 2 (21:04):
You know, in a site, like many people in consultancy
got a traditional pyramid model, and people are beginning to say, well,
maybe it's diamonds where you've got you know, a few people.
Maybe it's something that is an inverted pyramid where actually
you have more people at the top who are the
good judgment people that can advise senior clients, and they
don't need to have the people who are doing all
(21:26):
the work at the bottom. I don't know the answer
to that, but I certainly would be thinking really hard
about the new models that are going to be emerging.
Speaker 1 (21:33):
If you were still working with junior consultants, how would
you be teaching them to think critically?
Speaker 2 (21:40):
AI essentially is your new teammate, your new intern, whatever
metaphor you want to use. It's got amazing superpowers. Sometimes
it does some really weird things like make stuff up
or dramatically underperform some things you think it's going to
be good at. The way you figure these things out
is by working very closely with it, never ever outsourced
to it, and recognize life is better in teams and
(22:03):
research shows life is actually sociologically better with AI, as
long as you don't do too much with it and
now source too much to it. But make sure that
you are pushing and using it to augment versus replacing,
because that will be a very short sighted and destructive path.
I mentioned Bobby Hansen before. In his book Leaders Make
the Future that the third edition, he said, you know,
(22:24):
one of the most important things that a future has
to do is be very precise on language, because the
right language will pull you somewhere, the wrong language will
push you away from And he writes in his fifty
years doing this. Artificial intelligence is the worst name for
a new technology he has ever seen, because artificial makes
it sound like it's replaceative, and what you really want
(22:45):
is augmented, where it is something that allows you to
stretch and push and develop further, and that is the
thing I would really be pushing among the young talent
at the organization.
Speaker 3 (22:55):
Don't stop thinking. Once you stop thinking, it's kind of over.
Speaker 1 (22:58):
If you're finding this conversation with Scott Anthony as helpful
as I am, stay with us because in the second half,
Scott reveals why he has started thinking about his life
in five year cycles, and also his advice for improving
your ability to think critically in the age of AI.
(23:19):
If you're looking for more tips to improve the way
you work can live. I write a short weekly newsletter
that contains tactics I've discovered that have helped me personally.
You can sign up for that at Amantha dot com.
That's Amantha dot com. How would you be approaching recruitment
(23:42):
because I feel like I'm seeing a lot of companies
really struggle with this, particularly in those early stages where
you're not having those in depth interviews face to face
because I mean even virtual interviews these days, you know,
I hear all sorts of stories about an AI going
on in the background and putting out answers to questions
that people are being asked. What would you do to
(24:05):
test the ability of someone to think? In this day
and age.
Speaker 2 (24:08):
What I would wish for is a way to be
in a physical location with someone and have a conversation
with them. I think, just the ability to actually have
a conversation with somebody and not ask how many taxi
cabs are there in New York City or whatever, but
just see the way that they approach issues. The approach
I followed what I was interviewing in a sight is
(24:29):
I said, would give people here are ten disruptions that
are in process right now, or ten companies that have
been called disruptive. Pick any one of them and come
up with a point of view, are they actually disruptive?
And if you were caught in a lift with the CEO,
what would you say to them? And I did that
for two reasons.
Speaker 3 (24:47):
One, I want to.
Speaker 2 (24:47):
See what they did with it, and then two, once
we're in a room together that I can push them
and they've had the benefit of being able to think
about it for some period of time.
Speaker 3 (24:55):
And we'd have fun.
Speaker 1 (24:57):
You know.
Speaker 2 (24:57):
Sometimes people would go and produce a PowerPoint tech. I
didn't ask them to do that, but sometimes people would.
Sometimes I get a Microsoft word memos. Sometimes people would
just talk. But it was a really good way just
to get into a conversation where you could see how
someone thinks. I don't know a better way to do it,
you know, I mean you could say psychometric tests or whatever, perhaps,
but you know, I mean, as we know, anything can
(25:17):
be gamed these days.
Speaker 3 (25:18):
It's not easy.
Speaker 1 (25:19):
We talked about critical thinking. I want to talk about
good judgment. How do you help your students develop the
ability to have good judgment? I feel like, and maybe
this is a flawed assumption, but the longer you do something,
the more experience you develop. Generally your judgment becomes better
and better because it's the collection of all the different
(25:40):
experiences that you've had. But how do you think about
the ability to have good judgment and to improve that ability?
Speaker 2 (25:48):
I would like to think that experience makes you better
at having judgment, but I think at least some research
and data would suggest you get some real blind spots.
Speaker 3 (25:57):
Is you're used to.
Speaker 2 (25:59):
Defaulting to certain things and if the situation changes. And
with that, what I really try to do is I
try to essentially give students heuristics and say, what you're
going to do or what you're going to get are
rules of thumbs, mental models, way to think through things
that essentially can help you. So it's not that you
as an individual have judgment. It's you've got a tool
(26:21):
that you can use, and what you have to figure
out is what is the right tool to use in
a context. And this is the thing that I learned
from Clay Christiansen. You know, he used to joke that
his wife Christine would say the famous disruptive line diagram
that's in all of his stuff, it was etched onto
his glasses. Everywhere he looked, he saw disruption. I wear
contact lenses, so the models are like fused under my eyes,
(26:43):
so you know, everywhere I look, I see it. And
that's sometimes maybe a tiny bit of a curse, but
what it really is is a blessing. It allows you
to see things that you wouldn't otherwise see. And whenever
someone asks Clay what's your opinion or your viewpoint about
extra y, Clay would say, I've got no viewpoints or opinions.
The model has a viewpoint, and he was such a
good social scientist. When that didn't happen, he'd say, oh, great,
(27:05):
we found an anomaly, something that didn't fit.
Speaker 3 (27:07):
Therefore the bottle must be wrong in some way. Let's upgrade.
Speaker 2 (27:11):
The vision of our school is to develop wise, decisive
leaders that better the world through business. A wise leader,
in my view, is one who has a whole range
of tools that they can use and knows when to
use them and how to use them.
Speaker 1 (27:24):
I love that, and I guess the follow one question
from that, like, when you yourself are looking at creating a
new model or a framework with which to view the world,
what role does AI play in helping augment your thinking
or does it not play a role there?
Speaker 2 (27:42):
I have an idea that's been bouncing around the back
of my head for a few years now, and this
is what does it really take to be a leader
that can successfully navigate today's world of radical uncertainty? A brand,
the idea, adaptive capacity. And the idea basically is you
need three things. You need metacognition, which means you think
about how you think and have lots.
Speaker 3 (28:03):
Of models at your disposal.
Speaker 2 (28:05):
You need equanimity, the ability to pause so you don't
get overwhelmed with all these models that you have in
your head at a paradox mindset that allows you to
take perceive tensions and turn them into possibilities. As I've
been advancing my thinking about this, AI number one has
been a research partner, so use some of the emerging
research capabilities to say that idea about.
Speaker 3 (28:26):
There not being anything like this, is that true?
Speaker 2 (28:29):
What else do you see out there? What research you
see blah blah blah blah blah. So a research partner.
Number two an experiment designer. So I have been trying
to think about ways to actually go and test this, validated, etc.
Speaker 3 (28:41):
So this will be the sort of thing where I
will idly go and brainstorm. I was thinking about this,
what do you think, etc. Etc. I have a thought
about doing synthetic research.
Speaker 2 (28:50):
I've not done that, but I thought it would be
really cool if you were to actually use AI to
create a simulation to go in test hypotheses. That is
beyond my current capabilities, but something that is on the
list of things to continue to push. Barring from slow
productivity from caw Newport, I work on a five year
timeline for some of these things. So I want to
crack this in the next now four years, since I
(29:10):
set that a year ago, so I'm okay with not
having synthetic research yet, but that's an area that I'm
watching to see if that's something that you actually can't
do with any materiality.
Speaker 1 (29:19):
Tell me more about this five year cycle. I'm curious.
I did not know that about you.
Speaker 2 (29:24):
So caw Newport, who I know. You're a fan of
his book Slow Productivity. I was one of the best
books I read a couple of years ago, and he
had this idea, you know, slow down, slow down. Don't
think necessarily about what you're doing over the next week, month,
or quarter, but really think about what are your aspirations
over a five year time period. As they said, when
you relax the timeline, you're able to just handle things
(29:47):
moving at different paces. So when I did this a
year ago, I said three things that I would like
to do professionally over the next five years. One, I
want to crack this adaptive capacity idea. Two, I want
to do something I've never done before, which is have
my name on a peer reviewed academic article, not the
lead author, but I can be the tenth author. That's fine.
(30:08):
And number three, I'd really like to win a teaching award.
I just validate and demonstrate that I improved my ability
to teach in class.
Speaker 3 (30:15):
So those are the three things I'm saying this on
am I allowed to say the date clus you are
July fourteen, twenty.
Speaker 2 (30:22):
Twenty five, so we can time capsule and check in
on this four years from now.
Speaker 1 (30:26):
Oh wow, I love that. What are some other habits
or rituals or things that you're you've been playing around
with around how you do work? Like? I love the
five year thing, and I always feel like you're someone
that's experimenting with different ways of working and augmenting your productivity.
Speaker 3 (30:42):
I'll call this one Can I watch? And can I watch?
Speaker 1 (30:45):
Is?
Speaker 2 (30:46):
I started teaching three years ago and the school that
I teach at is blessed with a number of really,
really world class teachers. So I've made a regular habit
whenever I'm in a teaching cycle, which tends to be
about a five week cycle, I try to go and
observe at least one and hopefully two other faculty, usually
ones that my students recommend, you know, just who's really
(31:07):
great at running a class. And in those can I
watch moments. I don't care at all about the content.
I'm not going there to learn, you know, what this
teacher is teaching about this topic.
Speaker 3 (31:17):
I'm just absorbing the way that they're running.
Speaker 2 (31:19):
The room, what the students are doing, who's locked in,
who's not locked in, how they're using their physicality, blah
blah blah blah blah, and just trying to get a
sense as to what it takes to really really command
a room of sixty plus very smart NBA students who
again are blessed with a lot of really great teachers.
And I'm sure some of the things they're teaching are
(31:40):
getting into my unconscious as well. But that idea of
being very purposeful in getting stimuli that's different from normal stimuli,
that has been something that has.
Speaker 3 (31:49):
Been one of the more rewarding.
Speaker 2 (31:51):
Routines I've had in the last few years. And I've
made some new friends from doing it too, which is
always nice.
Speaker 1 (31:57):
I love that. Tell me, what are a couple of
things that you've larn from you? Can I watch sessions?
Speaker 2 (32:02):
Is one Joseph Garaco, who teaches in the accounting unit
at talk. I said in one of his sessions, and
you know, I thought, and Joseph, if you're watching this,
I hope you take it in good spirit. I thought
it was going to be the most boring session ever.
I mean, he'd want a teaching a ward, but I'm like,
it's accounting.
Speaker 3 (32:17):
You know. Even though my.
Speaker 2 (32:18):
Grandfather was an accounting teacher, he was not known for
being dynamic. But the thing that Joseph really showed me
is you can find real moments of inspiration by letting
students really go and dwell on seemingly small things. And
what he was really great at doing is opening his
session with what seemed like a really simple question, but
(32:40):
one that just expanded into an hour of really good
discussion where he also could teach about how working capital
works and all that. So the thing I learned from
Joseph is the power of a very very well thought
through opening question when you're in a good class discussion.
Then I sat in the class that Paul Argenti, who
tea in communication and a couple other fields, it talk
(33:03):
a couple months ago, and I noticed he just had
this theme where he was talking about corporate activism and
he used pretty evocative language that I won't repeat to
not get him in trouble, but I just really got
the room. It's like the room like all devices went down.
Everyone was on him and like, how rehearse was that?
He said, I've been doing this for thirty years. It's
(33:24):
just like not quite a scriptive performance, but you know,
just really a way to pull people in. So this
idea that you are, to some degree, for better or worse,
when you're teaching a class, you're a performer, and you
want to think about how you're going to use what
great performers do is the thing I picked up from him.
So great questions and think about, of course teaching, but
a little bit of performance mixed in. Those are a
(33:47):
couple of things I've picked up.
Speaker 1 (33:48):
I love that well, Scott. It's just like it's always
just such a joy to talk. Whether it's on Mike
or off Mike. I always feel like I learn so
many new things and I just love your way of thinking.
Thank you so much for extending your workday on the
East Coast to have this chat with.
Speaker 3 (34:05):
Me, Namantha.
Speaker 2 (34:06):
It is always a pleasure, and thank you for starting
your workday early in Melbourne to have this chat with
me very much.
Speaker 3 (34:11):
Appreciate it. As always.
Speaker 1 (34:14):
I hope you enjoyed this chat with Scott Anthony. For me,
the biggest takeaway is this AI is an incredible partner,
but it should never replace the discomfort of thinking for yourself.
And if this episode gave you a new way to
think about your own work, please share it with a
friend or a colleague and make sure to follow How
I Work so you don't miss future conversations like this.
(34:37):
Thank you so much for listening, and here's to working
smarter with our brains fully switched on. If you like
today's Joe, make sure you g'd follow on your podcast
app to be alerted when new episodes drop. How I
Work was recorded on the traditional land of the Warrangery People,
part of the Cooler Nation.
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