What Did You Bring Back?

“What did you bring back?” 

This is one of the questions people ask when someone returns from a trip to another country. And we all know this means things that can be unpacked from a suitcase :)

But what about everything else we bring back? 

I was thinking about this after returning from a trip back home, spending time with family.
I revisited some familiar places and visited some new places, enjoyed familiar food, and picked up conversations with old friends as though no time had passed. 

When I planned this trip, there was no particular outcome I was working towards other than spending quality time with family. There was no checklist to complete and nothing to achieve. Even though I didn't plan for any "specific thing to bring back", the experience gave me quite a lot. And none of it could have fit into a suitcase! 

I went down memory lane and gained some new perspectives on familiar things. I was reminded of what has changed and what hasn't, and I got time to pause and reflect. I realised where I came from and at the same time, I became acutely aware of how much I have changed. 

This travel experience made me think about how often we measure the value of an experience by its output: what we create, complete, achieve, or bring back. But perhaps we sometimes overlook what happens along the way.

Sometimes, the most meaningful product of an experience isn't what we produce. It's what the experience produces in us.

Not every process needs to produce a tangible product. Sometimes, the process itself is the product. I carry with me the conversations, the things I noticed, the things people shared, and the thoughts I am still mulling over. 

And there is learning in that too. Learning that is not always planned, structured or easily measured, but learning that happened simply because I engaged with an experience and allowed it to shape me. 

We often look for evidence of learning in something tangible. We talk about a completed course, acquiring a qualification, some new skills, or something we can demonstrate or produce. But learning can also be much less visible. It can change how we think, what we value, how we understand others and ourselves, and how we approach situations in the future. 

I think some of our most profound learning happens outside any formal structures. Learning happens through experiences, conversations, relationships, unfamiliar situations and moments of reflection. Perhaps we need to pay more attention to these less visible outcomes of learning.

I think that's something worth pondering, not just in our personal lives, but in how we think about experiences and learning more broadly, within communities and organizations. And it is so important that we recognize all of these forms of learning, both for ourselves and for others. Because sometimes, what matters most is not what we bring back from an experience; it is what we carry forward.

A picture of a mural located in the Lodhi Art District
captured by the Author on her recent visit to New Delhi, India

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This post connects to something I explored in an earlier post, When Producing the Thing Is No Longer Proof of Competence, where I questioned our tendency to equate the output with the value of the process. In the August post, I reflected on why producing an artefact isn't necessarily proof of intelligence or competence and how the real value lies in the thinking, judgment and decisions behind it. In this post, I guess I am extending that idea beyond work and learning into life itself. What matters isn't always what we produce or bring back, but what happens along the way, often in ways that no tangible product could capture!

When Everything Is Lit

Rijksmuseum Library - Photo by Taruna Goel

"Do you think museums should completely fill their walls with paintings?" That's the question that Rijksmuseum Instagram handle posted this AM.

The funny thing is, I have been thinking a lot about art galleries and museums. In fact, I was at Rijksmuseum this summer, and it's a beautiful museum.

But I wonder. Can something that is designed to be clear and beautiful actually end up being tiring to look at?

Have you been to art galleries or museums where almost every painting is spotlighted and has its own special corner that takes your attention? I have. Rooms of white walls where I can see everything clearly. But after 30 minutes of walking around and paying attention to every brightly lit part of the room, my eyes get exhausted. I am seeing things, but I can't appreciate the art anymore.

It's what my daughter, a Contemporary Arts grad, likes to call "feeling arted out".

When that happens, she recommends that I sit for some time, away from the art and the bright lights. Perhaps even in a dark(er) area where there are more shadows and where the walls aren't quite as white.

I call it my visual quiet zone. The visual relief where I can simply look without paying any attention.

I am looking for a written quiet zone these days because I am "feeling arted out" after reading post after post of AI-generated content.

I can't deny the clarity of writing. Ideas are packaged as neat, single, short sentences, and the layout of the article is one sentence at a time (but who thinks like that?). It's like a stream of complete, purposeful, independently meaningful series of words (aka punchlines). Yet, as a whole, there is nothing for me to take away. It's a template that feels all too familiar, and is frankly becoming mentally exhausting to process what I am reading. And not because the words or ideas are complicated, but because they are overly consistent and too uniform. 

I am trying to reason why. Why is it crystal clear yet so muddy? I have a take. I think it's because AI-generated content is missing the rhythm and texture of human writing. The light and the dark corners where our eyes can rest, and our brains can shut off.

We are messy in the ways we think and write. When I write, some ideas are powerful, and hopefully, those sentences stick with you, but most other sentences are like fillers. They don't give any new ideas or say anything too dramatic, but simply build on the main ideas. There is an interplay of good writing combined with not-so-good writing (even if unintentional). It adds to the contrast and the variation that I expect when reading or listening to another human. Part of the human charm, I think. I should mention that I am not a fan of mistakes in human writing. So, I don't advocate adding imperfections to writing just to sound human. But I do appreciate the evidence of human thinking behind what's written or being read.

But with AI-generated content, where everything reads so perfectly, and every sentence is a main idea, it reminds me of the struggle of reading a page of text, all formatted in bold. 

Or walking around museums that completely fill their walls with paintings.

I need a written quiet zone.

When Producing the Thing Is No Longer Proof of Competence

Harvard psychologist and education professor Howard Gardner recently shared his view on how AI could change education. He believes cognitive tasks will become optional for humans, freeing people to pursue their interests. The actual interview between Rick Hess and Howard Gardner is certainly more nuanced than just the statement and makes for an interesting read. 

https://www.edweek.org/technology/opinion-howard-gardner-how-ai-will-force-us-to-rethink-education/2026/08

While I can't say I agree with his bold statement of cognitive tasks becoming optional for humans, what is true is that when all our lives, humans have defined their intelligence based on cognitive tasks, and then, AI takes over some of those cognitive tasks, we are suddenly left thinking more deeply about what we thought was exclusive to us... our intelligence!

But I think the real leap in this discussion is to stop making these lists of "things human can do that AI can't" (because, realistically, that list is shrinking by the hour). The more important task is to start questioning systems that were designed with the assumption that producing something is the way to demonstrate intelligence. I mean systems of education, training, assessment in school and at work that rely on writing an essay, submitting a portfolio, completing a presentation slide deck, making a report, etc. 

In L&D, we have always done this. We use course completion, knowledge tests, work samples and portfolios as evidence that learning has occurred or that someone is ready to perform. But we know all too well that completing training isn't the same as being able to perform at work, just like producing the right answer isn't necessarily evidence of understanding. 

The artefact was never the actual competency yet we believed for so long that it was. But when the artefact can be produced by AI, it becomes an even weaker proxy for learning, intelligence, and competence.

Having worked in the areas of competency development and assessment for close to 3 decades, I know too well that competence is messy. It involves recognizing what is happening, deciding what matters, and applying information in various contexts. Then there is exercising judgment, adapting when circumstances change and taking responsibility for the outcome. The artifact may provide useful evidence of those things, but it isn't 'the thing' itself. 

The artefact as the evidence of intelligence is losing ground quickly. Especially given the recent development of AI watermarking, where Anthropic has begun watermarking text generated by Claude so that the content can be machine-identified as AI-generated.

So, where does the value of expertise sit when AI can produce so much of the work we have traditionally been paid to produce? We are all realizing what was always true but hidden in plain sight that expertise is beyond outputs and is generally more upstream. 

In my field of instructional design, this is becoming increasingly obvious. AI can produce storyboards, graphics, video, narration, activities and assessments. It can turn a reasonably well-defined brief into a fairly complete learning product very quickly. 

What is the value of an instructional designer? I don't think the answer is simply "in knowing how to use AI." I think it is increasingly in everything that happens before we ask AI to produce something.

I am glad I work with clients and teams who get this. I am currently working on an organization-wide performance improvement initiative where we are taking an end-to-end approach to needs analysis, looking carefully at the system rather than responding to a request for training. We are examining the work, people, processes, tools, expectations, resources and environment, and working through the findings collaboratively. We are so focused on not hurrying towards the output and it is taking some discipline and intention to do it this way. I mean, when we can produce learning in minutes, it is rather tempting to start producing! But the more capable the tool, the more important is the role of the human to spend time figuring out what actually needs to be produced.

Because AI makes the “doing” easier, the value of human capability is more upstream in knowing what to ask, what to pursue and why it matters.

Perhaps we need to get much better at assessing the things that are harder to produce on demand and are certainly harder to outsource to AI. 

Perhaps we have to redefine what now constitutes human intelligence and what makes us competent. 

Perhaps it is about things like understanding the context, tapping into the lived experience, human judgment, and being responsible and accountable for our choices and actions. 

This binary view of AI vs. Human just won't cut it anymore. This isn't as simple as AI on one side and human expertise on the other. The opportunity staring at us is in knowing how to combine the two. The shift from producing answers to identifying what problems to solve is the real discussion. Not the how but the why. 

But it was always about the why, wasn't it?