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Welcome to the Learning Experience Ops Show, where we talk about making learning better
that's future ready.
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I'm Jason Gorman.
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I'm the founder and CEO of Jackrabbit Learning Experience.
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We spend a lot of time as learning professionals designing courses, building programs, and
refining content, which we should.
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That's the work.
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But I keep running into a question out in the world and in my own head that I can't quite
shake, which is,
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As we are doing the work of building courses, are people waiting for us to actually finish
the work that we're doing?
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Because I think increasingly they may not be.
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I think learners, employees, and students are more and more going out and just grabbing AI
tools that they need and building their own solutions to help them learn.
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They are figuring out how to learn what they need when they need it, maybe without us more
increasingly.
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And I don't know that we have
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fully reckoned with what that means for the systems we build and the roles that we have
played as learning professionals and will play into the future.
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And my guest today has been studying exactly this.
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He calls it the shadow curriculum, and his research is surfacing patterns that I think all
of us, every learning professional needs to understand.
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He's asking about what happens to human cognition when AI
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there's more of the thinking for us and what institutions need to become if they want to
stay relevant.
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Adarsh Lathika is a strategy and learning systems practitioner working at the intersection
of AI human behavior and the future of work.
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He has spent over 15 years across higher education, executive learning and consulting, and
is currently building frameworks like Anatomy of Work to understand how learning work and
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performance are being reshaped in an AI first world.
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His work focuses on helping institutions and organizations rethink
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not just what people learn, but how, why, and whether learning translates into real-world
capability.
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Welcome so much to the show, Adarsh.
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Thank so much, Jason.
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Quite excited to be part of this podcast.
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Awesome, so glad to have you here.
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All right, let's jump in with some lightning round questions.
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What is just a 30 second elevator pitch about what you do in your
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So I try to study the misalignment or the growing misalignment between work and human
cognition.
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That's what my focus is.
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So the eventual objective is how do you drive performance and productivity.
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What do love the most about your work?
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think the more I delve deep into it, the more I realize that I don't know much.
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It's a very open canvas.
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In fact, when I started on this journey, I went back to my 10th standard biology text to
understand brain and really go back to the basic concepts to get a sense of what the
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neurotransmitters does, what each part of segments of brain does to human behavior and how
they are related.
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So it's been therefore an exciting part to really relearn a lot of things that I left
behind some 20 years ago and then repurpose to what we are experiencing today so that we
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are a bit more doing better for ourselves in coming future.
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And just to get you know a little bit better just in your day-to-day work, if you are
really in the flow state and you're just kind of time is passing quickly and you're
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totally immersed, what are you most likely to be doing?
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building something.
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So I do have some background of uh programming.
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So I leverage my coding a bit to build.
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So I started building productivity tools for myself so that I can do things oh much
faster.
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I don't really need a team to do it for me.
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From that I started then once I started getting hang of that I started building slightly
more complicated tools as well.
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something that helps me both personally and professionally.
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So that's what I do most.
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That what I do enjoy doing most.
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That's wonderful.
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And I just described a little bit about what you do.
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You just gave your 30 second elevator pitch.
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I'm curious, what was it that inspired you to do what you do?
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So, I mean, a few things that are elicited over a period of time is that, one, humans are
important.
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I think as a species in this planet, we have lot of responsibility to what we do, why we
do, and equally important why we don't do something.
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So a couple of years ago, I decided to take a career break and
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That was the time where AI was coming, this whole charge GPT moment happened.
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And the first thing that came to my mind was the 1984 from George Orwell.
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And the more I was understanding what charge GPT was promising, more I was fearing maybe
to some extent that that obedient world may happen in my lifetime.
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And I was not very happy about it.
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So question was that, how do you then give the power back to the humans?
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So I started thinking about it.
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I had the time to do it.
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I started listening to lot of podcasts around the world.
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I think that's something that internet just allows you to do.
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So I started reading a lot as well.
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And then once I started reflecting back on that or injecting that on top of my
professional experience,
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I felt that maybe oh we need to go back.
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So what could be the gaps that can develop over the next three, four years?
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So my understanding was that knowledge is becoming abundant and instantaneous.
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So when that is happening, what is the role that as a human we will play at workplace?
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So then that's when the whole idea about judgment and context came to my mind.
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since then, I've been focusing on
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You kind of touched on this a little bit already, but what are you the most anxious about
for the future?
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Personally, I don't like somebody else taking decisions for me.
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I'm not a big fan of that.
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So, and I think when it is AI to make that happen at a large population scale, then I
think we, especially as a, at the context of India, we take a lot of pride of being the
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youngest nation or youngest nation for the next say 20 years.
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But imagine a case where in which we have a huge population of youthful, high energetic
population, but nothing to do.
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And I think that can become very negative, very fast that we can't really control.
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So that is what I'm a bit worried about because there's a journey that as a country we are
going through since independence and we had the time.
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to course correct because time allowed us to do it.
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But now AI is making everything redundant.
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I'm not so sure whether we are responding correctly to what AI is today and what AI
promises to be tomorrow.
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So that is something that makes me anxious.
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But at the same time, it also is a great opportunity that can unlock if you're using it
the
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right way.
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So I am trying to focus more on the latter.
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Good.
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And last lightning round question.
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What is a skill?
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Can be related to your work, not related to your work, but what's a skill you're trying to
learn right now?
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So, one thing which I am trying to learn is how do I sell better because I am a
solopreneur.
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So, I love building and I could afford to be a builder maybe 10-15 years ago.
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Not so much in AI first world.
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I can't afford to do it.
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So, I believe that everything and anything related to selling as a skill, right from
public speaking to story, narrating a story.
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to being in front of a crowd and speaking those, these are the skills that I'm working on
and I use AI for that as well.
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Good, yeah, wherever we can get that advantage, let's get that advantage.
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All right, well, we'll move to the kind of longer form questions here.
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I mentioned that you came into this field of learning through operations, things like
building and scaling systems across university campuses, online initiative, executive
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education, corporate settings.
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And you have said elsewhere that the pattern you have seen
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is that we typically optimize for delivering learning, but not translating it into human
capability.
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And so I'm curious if you can give me just a specific moment or project that you were on
where you really saw that gap clearly, just to illustrate.
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So the background to that is that I have a habit of going through P &S.
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And something that was very stark and became very strongly apparent to me was that human
resources are always on the expense side of the balance sheet.
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And it's just OK.
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Maybe in early.
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2010s it was okay, but with automation data science now AI coming to picture I think We
need to start valuing human for the Contextual understanding Yoshi has and that is with
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the current gap that AI has because Like if you had to come compare US and India and I
want to start
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I want to open a restaurant say in San Francisco and I want to start a restaurant in
Bangalore.
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Now I will give the same prompt for both cases.
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I am more likely to rely on the response that AI gives me for opening a restaurant in San
Francisco because India as a country we contribute to less than 5 % of internet data.
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So that means AI doesn't have the context in which a city like Bangalore operates.
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Of course, there might be some aspects that we can definitely apply, but the finer things
will still be amiss.
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So that can only be brought in by a human.
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So therefore, human is valuable.
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So where I realized this was when data science started becoming very popular.
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We started a data science school way back in 2014-15.
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Now, so I think at that time, we were probably the second most prominent education
provider in the country to launch a data science course.
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And what I felt was that I asked the best question, why is a learner who's done a bachelor
or a master's going to again come to my campus to sit through a 9 month course, a diploma
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course, what is that he or she is going to achieve or what is the aspiring to achieve?
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We might think that it is the skill of neuroscience, but the fact is that he or she wants
a job.
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So what I did at that point of time is that even when we had
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Launching the pilot batch I created a system.
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So we partnered with IBM big data at that point of time We partnered with a couple of
there is this company so that they can not only bring in their own faculty for doing guest
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lectures, but also Give them internship and then final placement jobs as well.
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So because I was able to create the ecosystem that program
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became successful and this is time when I was monitoring it, it was one of the largest, oh
most successful program within the company.
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I think in a three year period, it graduated close to 670 people.
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So it was, so that really worked for me.
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So what I'm trying to say is that I put the learner as the focus and I put all the
business metrics around it.
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Because I was able to do that,
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we were able to create a business which was sustainable.
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Sustainable because learners wanted it.
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We were not trying to push a product.
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It was actually pulling learners to our product.
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So if you have to now put in the context of what AI is doing.
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As I said earlier, I'm trying to learn public speaking, improve my public speaking skills.
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How am I doing it?
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I record one.
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I raise my hand for every opportunity that I can get.
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Second, when I do land up that opportunity, I record the conversation.
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Then I have a custom GPT created.
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I feed that according to the custom GPT.
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Then there is a rubric that I created based on my secondary research that I've done on how
a public speaking should be done.
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The intonation, the vocabulary, the fillers that you use.
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There are eight, nine parameters that are there.
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So I keep, I have created a feedback structure wherein I get a report saying, you are
done.
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good in these five things, you are okay in other two things and these are definitely two
things that you need to improve upon.
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that becomes very important because as I said earlier, the employees are learning and
everything is still an expensive item for an organization.
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They are seeing a world where in which more and more people are getting laid off.
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So employees today are not seeing that commitment from the organization for their career
path.
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So the question comes back from an employee perspective is that if the employer is not
promising me a five years or 10 years with them, why should I then commit another five
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years?
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So my company may want to learn, say for example, Python.
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But I as an individual may feel, okay, I don't want to learn Python because now coding is
as easy as just picking two system and generating code.
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Then why should I bother about it?
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Let me learn storytelling.
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So the company may be investing a lot on
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getting the person to learn coding.
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But I may use in ChatGP to your Gemini or some other coding instance to improve my public
skills or storyboarding skills.
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So that is going to be dichotomy, which will the gap is going to continue to widen, widen
and widen.
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Mm-hmm.
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You have described what you call a shadow learning system.
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And you've kind of just went into that a little bit just now.
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But the idea, basically, as I understand it, is that learners are using AI to build their
own tools in parallel to any kind of formal education that they're getting.
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And they're doing this in part because institutions, employers or universities aren't
actually keeping up with what's possible.
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And so I'm curious, can you walk me through how you think this is happening now, how this
shadow learning is happening?
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Just what does that look like for a student or an employee?
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So the scenarios are different for both parties.
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For the student, institution is still important because you still need a degree to get a
job.
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At least from where I come from, that's a basic qualification that it does not matter what
degree it is, but you need to have a graduate degree to get your first job.
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Therefore, institution is still important.
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That scenario is slightly different for somebody who is a working professional.
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largely because one, you keep hearing this news about people getting laid off almost on a
every third day you get a news assembly or there's a mass layoff happening in a globally
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repeated company and you don't know whether it's going to be you next or when is your turn
and historically what I experienced is that the while we talk about it in the vision
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mission or the
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company statements, we are not really very transparent when it comes to employee
communication.
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So that gap also adds to this anxiety that the employees can have.
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So that means it's a dogged out world.
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I feel that the employer is not committed to my career growth, my professional growth.
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Therefore, I do what I believe is the right thing.
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So if somebody comes to you today and tell me you learn
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Google AI Studio because that is the most important tool today, I go and learn that.
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Tomorrow, Anthropic might launch a better coding agent than that.
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So I learned that tomorrow.
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what internally it indirectly does is that it just, gives me as an employee, it gives me a
sense that I'm actually learning and doing the right thing.
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But what it internally does is it's creating a lot of anxiety inside my subconscious mind.
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that I am always hyper which means that I not focused at work I am not giving 100 % at
work so the company starts suffering and over a period of time I also start suffering so
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it's a loss loss game that both of us are playing so in that way what I feel is that even
if it hurts be transparent with the employees say be very clear that these are the five
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things which is going to happen in the next one month
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because it's difficult to predict what's going to happen after that.
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therefore, explain your decision very detailed to the employees.
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I think employees today are very smart to understand when somebody's been genuine and
being honest in their communication.
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And I'm sure that people will rally behind that.
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And even if they end up being laid off, they have a very better understanding of why that
happened and why they don't really fit into that plan.
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I think that becomes very important.
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It seems like there's this kind of necessary degree of trust here between the employee and
the institution.
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And it seems like with this shadow learning system, if an employee or a student is using
tools to...
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to do their own learning, why do they need the institution for that?
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Yeah, why would they depend on the institution at all?
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So if you look at student as a cert, you still need a degree, therefore institution
becomes important.
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looking ahead, I think institution can actually transform into a place where students
build their cognitive and behavioral skills, which I believe are two important segments of
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00:18:12,040
skills which are going to keep them employable in the next 5, 10, 15 years.
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So that transition needs to happen.
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But from an employee perspective, that's a very pertinent question and it's not very easy
one to answer.
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Largely because I'll again go back to the fact that uh all the employees and employer
related investments are still expense in the balance sheet and not really a detailed
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00:18:31,011
investment.
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00:18:38,174
So historically, what has happened is learning and development teams tried to optimize the
training intervention.
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So as long as you are the
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either the in-house team or the external vendors are able to meet a minimum level of
quality they always go for the cheaper option because at some point of time the EBITDA or
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00:19:03,103
the PAT is going to come into picture and they try to always protect that so when you
start doing it, it becomes very difficult to make the transition to something because you
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00:19:08,596
are trying to meet a short-term objective but not really building a company for
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next 5-10 years.
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So that becomes very challenging for the L &D team.
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00:19:25,211
And that means that they need to work very closely with finance and the purchase for most
part to ensure that to convince them that why this investment at this rate is important.
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00:19:32,951
Because even when for example, I have seen cases where in which you are trying to deliver
an AI training to a set of people.
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So the CHRO may approve it, the L &D head may approve it.
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but then again it goes to the purchase and the finance what they do is that they just look
at the proposal as excel items they just do a comparison with what is available in the
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market and they look at high level keywords say you know I can get you 10 % cheaper, 20 %
cheaper and then the question becomes what is cheaper to be delivered and I don't think HR
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or L &D fights beyond a point and then you always end up extending or giving a substandard
training program to the employees
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which means that employees are not happy.
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Again, the loop just continues.
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So we need a very confident and assertive NND team to actually make this work.
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00:20:26,521
You've also written about this notion of cognitive debt, which is that AI is reducing
engagement and pushing people away from thinking and more towards just verifying the
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output that the AI produces.
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And so if you're a person who is responsible for making courses,
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a learning designer, instructional designer, how do we address this?
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How do we address this pattern to help people engage more deeply, not just verify, to stay
kind of in the moment with the things they're engaged with?
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00:20:57,413
So I'm not an ID person, so I don't know how the courses eventually get built.
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But I will explain my thought process here.
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If you are somebody who has been working in a specific field with significant experience,
then it is OK that you get AI to do the work and you play the role of a verifier.
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That means that you are doing your work much more faster and much more efficient manner.
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You are not sure you are playing
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the role of a team lead to say 15 team members or 15 AI agents, which is alright.
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00:21:36,534
But if the objective of the training department is also to create a funnel of leaders who
are going to take up the mantle say in next 2-3 years and currently you are given a team
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00:21:47,430
of say junior resources or people with say less than 2 years of work experience, how do
they build the domain understanding or enough of
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00:21:57,014
domain understanding that they are building their expertise, they are building that level
of intuition so that they can then therefore review the output given by AI.
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00:21:58,635
That is the challenge.
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00:22:09,874
so what historically used to happen is that you join a company as a junior resource and
you had the sufficient amount of time where in which you start by doing the repetitive
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00:22:16,297
task for say six months, one year, and then you start doing more of a repetitive task.
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And at the end of a 12 month, 15 month period, you get to understand why that repetitive
task makes sense.
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00:22:30,477
And therefore, what that task contributes to the business objective of the company or the
segment that you are part of.
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00:22:39,757
But what AI does today is that because AI can do or shortchange that 12 month of learning
into a few seconds or a few prompts, right?
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00:22:47,517
Junior resource then becomes just copy pasting the AI response and feeding into the next
step or next stage.
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00:22:58,197
So he or she is not really developing an intuition and therefore not building on the
ability to judge AI output on a long-term basis.
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00:23:09,484
So if as an L &D professional or as a CXO who is looking to build a culture, we build a
long-term business which is going to sustain for the next 10, 15, 20 years.
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00:23:21,270
You are not really doing good by having the same old approach what you followed say 10-15
years ago for learners who are coming in system today.
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00:23:23,331
What is the right solution towards it?
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00:23:30,455
Now I can only hypothesize, like for example you can probably give more projects to them
so that they understand the why behind what they are doing.
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But I think
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You need to experiment a lot at this point of time to figure it out for you.
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00:23:43,707
Because I think the answer depends on a lot of things, including what part of the world
you're coming from, what industry you are in, what is the business objective of the
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00:23:44,627
organization.
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00:23:52,174
So probably you can factor in all those things and then find the answer that works for you
at that particular stage of the company or the face of the company.
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00:23:53,114
That's great.
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00:24:02,335
you have asked the question, what gets lost for us when speed and output become the
primary measure of success?
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00:24:04,308
So I'm going ask you that question.
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What's your answer to that question?
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00:24:10,074
What does get lost when speed and output become the primary measure of success?
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00:24:17,110
So when speed and output becomes primary measure, I think you lose out on people who are
foundationally strong.
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00:24:27,037
And that foundational skills are important on a long-term basis, especially because unless
your foundational knowledge, foundational understanding of your business, your industry,
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00:24:30,250
your segment that you're part of, you are never able to...
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00:24:37,726
catch the problems in the air response or the variations in air response.
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00:24:46,293
But habitually, over a period of last many years, we are used to rewarding people for
speed and agility in the way they work.
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00:24:52,041
But what we should also realize is that, is it really creating a learning beyond what is
supervision?
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00:24:53,915
And I believe in most of the cases,
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00:25:01,560
It might be just building skills at a superficial level and not allowing for the skills to
have the depth that it requires.
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So I think that is going to be the fundamental challenge going forward.
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00:25:15,987
it also becomes that you are not only redesigning and relooking your L &D plan, but you
are also relooking your performance metrics and your reward system so that you are
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enabling the right learning culture and therefore the overall
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the public culture.
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00:25:30,680
This takes us a little bit back to what you something you said before about human biology,
that you went back, you studied some things that maybe you had looked at years ago, but
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00:25:35,803
you looped back to it because you felt it was so relevant to where we are right now.
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um This intersection of, yeah.
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um
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was COVID, the first phase of COVID.
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00:25:50,430
So at that point of time, I was in Bangalore, my wife was in Perth in UK.
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00:26:00,430
And she was telling us that there was this young chap in her team who was probably one of
the best developer that she has seen.
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00:26:06,262
And he had one of the first casualty in the first phase of COVID.
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00:26:15,867
Now one interesting point that she told us while she said he was brilliant in coding, he
did not actually pass away because of COVID.
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00:26:20,387
He actually passed away because he had not eaten for many days.
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00:26:27,527
This is despite the fact that there were couple of ready to eat meals packets available in
his house.
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00:26:31,467
So what happened was that he was staying in apartment with his colleagues.
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00:26:35,804
So before the COVID lockdown happened, his colleagues moved to the hometown and he was
left alone.
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00:26:36,697
He did not know how to.
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00:26:41,828
because he did not know how to cook, he had the raw materials but he starved himself to
death.
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00:26:45,419
I think he also had some health conditions which complicated things for him.
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00:26:47,461
Also that actually got me thinking.
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00:26:55,485
even if I am the best at what I do, if I don't have the supporting competencies, am I
going to be productive at a long-term basis?
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00:27:00,106
And I think we can see good enough analogies in sports.
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00:27:02,468
Now I don't know enough personalities in...
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00:27:14,639
basketball or soccer that you may relate to but from a cricket there are characters,
individuals who have come shown so much of promise but they just fizzled out because they
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00:27:25,398
did not have the right character, they did not show the right attitude, they did not show
the right discipline for them to be selected after the first few matches or first few
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00:27:27,109
series to represent the country.
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00:27:28,402
So now if you have to
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consider that in an employment scenario.
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00:27:46,442
Earlier you are probably the best salesperson in your company but you were rude with your
colleagues, you would not cooperate with anybody else, were more like a bully to your team
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00:27:47,282
members.
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00:27:51,762
And the company probably would close its to because you were bringing in the revenue.
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00:27:56,458
But now what AI has done is that AI can do a lot of things that you are doing.
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00:28:04,369
The question is that what is that you need to be doing to ensure that you are still
relevant in the overall scope of things.
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00:28:14,551
That means that you are not only a good person or at least good working professional but
the collateral aspects of who you are.
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00:28:16,313
That means you need to have a good health.
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00:28:19,214
We are picking up, you need to have good discipline.
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00:28:24,115
We are picking up lot of the bad habits of
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00:28:27,094
workplace which have impact on workplace.
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00:28:30,369
For example, the amount of screen time that you all have.
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00:28:37,643
It's very stupid to expect that just because I'm not using mobile at workplace means that
I'm more attentive at workplace.
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00:28:38,453
No.
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00:28:49,462
You are using a lot of screen time when you're doing commute at home which is already
impact your ability to focus which extends to your performance at work as well.
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00:28:50,374
Or the
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00:28:51,675
there's a mobile app feature, right?
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00:28:58,841
When you make a payment, the message comes to you, the OTP get generated and the app is
automatically reads.
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00:29:06,148
Now from a user point of view, you may think it's faster, it's convenient, but what it
does is that it is impact your short-term memory.
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00:29:14,236
Over a period of say two, three years, your ability to retain facts for a short-term is
get compromised and that also access to your workplace.
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00:29:16,952
So when AI is doing all these things,
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00:29:25,509
What remains with you as the biggest competitive advantage is your ability to review and
judge, judgment, critical thinking.
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00:29:33,277
And that, if you are in a meeting and you need to respond fast, you cannot always then
Google or use AI for the facts.
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00:29:38,703
Then you take your sweet time to apply your mind, your logic to come to a response.
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00:29:42,867
You should be able to give that response at an instant level.
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00:29:43,877
So that...
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00:29:50,756
ability to get again compromised because you are doing so much of other things outside of
work which is impacting your performance at work.
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00:30:00,240
that's the so all these things when I start realizing for myself I of course there were
enough research out in the the public space about this but in some cases I started doing
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00:30:02,048
it experimenting on myself as well.
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00:30:05,632
Okay if I do these things I'm able to see some visible
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00:30:09,608
qualitative in my own way of judging it, I may improving it there.
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00:30:15,048
So once I start seeing some slight positives, I started doing more and more research.
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00:30:21,488
That's how the entire narration of work and life outside work came to picture.
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00:30:28,968
your human biology becomes important, human thinking becomes important, our ability to,
our cognitive thinking becomes important.
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00:30:34,779
So I started to see all this together so that as humans we are more productive.
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00:30:47,619
This actually dovetails perfectly with my last question here, which is you've identified
three big shifts that we're in right now.
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00:30:51,219
I'm kind of curious to hear your take on all three of these.
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00:30:54,279
One is from institutions to individuals.
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00:30:56,979
The second is from courses to systems.
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00:31:01,539
And the third is from knowledge to judgment, which you've just talked about here for a
second.
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00:31:16,794
um Some of these feel difficult for us to redesign our organizations for, to teach people
how to think in terms of systems or to apply judgment over just accessing knowledge.
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00:31:23,938
And from this dependency on institutions to more of a self-reliance, self-reliance as an
individual.
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00:31:29,970
But I'm curious if you could kind of unpack the three of those a little bit more, because
those shifts are interesting.
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00:31:40,517
Okay, I think before I start, I think it's important to understand or question the
definition of organization or company to start with.
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00:31:50,561
The moment you are asked a question of defined organization, it's most likely that at some
point of the definition, we will write that it's a huge company with employing hundreds of
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00:31:58,224
thousands of people, making billion dollars of revenue, working in say, 10 different large
markets of the world.
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00:32:02,726
But that reality is true only for few people.
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00:32:07,637
As organization, I might still be a billion dollar company, but employ only two people.
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00:32:09,714
Now the question of
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00:32:21,798
what is the role of learning and development or skill in that such a company, verse-versus
a traditional company which is running for last 50-60 years, is already a billion dollar
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00:32:26,639
but is it going to be there for the next 5 years, 10 years, 50 years, I don't know.
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00:32:34,022
So we need to ask those questions and contextualize the definition of organization for
yourself and then look at these shifts.
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00:32:35,872
So when I'm looking at moving
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00:32:39,224
from institutions to individuals, the learning.
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00:32:51,411
With this amount of layoffs happening and also the biggest impact I feel that AI is having
on workforce is not the layoffs that is created.
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00:32:52,523
I think that is the...
