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Aug 18, 2026
010 · TheThe Highest Use of Us
010 · TheThe Highest Use of Us
00:00
19:19
Transcript
0:00
This is Harvest the Signal, where the smallest signals can change the biggest systems. And now, here's your host, Jodi Lynn Owen. What is the system trying to teach us? That's the question behind every field note.
0:16
And this week's is the highest use of us. I'm Jodi Lynn Owen, and this is Harvest the Signal. There is a particular feeling that comes from doing something you are exceptionally well suited to do.
0:32
You are teaching and suddenly know exactly how to help somebody understand. You are caring for a patient and notice a small thing that changes what happens next.
0:43
You are building something and three ideas that had been floating separately suddenly connect. You are leading a team through a problem without a clear answer and find the question that opens the way through.
0:56
Sometimes we call it flow, sometimes creativity, sometimes purpose. Whatever we call it, there is something deeply human about the experience of being fully used. Not used up, used.
1:11
Your judgment, your imagination, your accumulated experience, your creativity, your capacity to connect things that have never been connected before. Your ability to teach, reassure, challenge, invent, notice, or care.
1:28
Dignity lives in the space where we are expressing those capacities, and that is becoming important to me as I think about AI in healthcare, because we are spending an enormous amount of time asking where AI belongs.
1:42
These are necessary questions, but I wonder if we're starting one question too late. Before we decide where AI belongs, perhaps we need to decide why we are bringing it in at all.
1:57
And that's what I want to talk about today, because my answer is increasingly this: to maximize human potential.
2:06
Not productivity, not fewer people, not even efficiency, although efficiency is probably going to be an outcome.
2:13
The purpose is to build infrastructure capable of carrying the work that does not require the highest expression of a human being. So human beings have more capacity for the work that does.
2:25
And that distinction matters because there is a difference between human work and work that is currently being done by humans.
2:33
And this has been true every time we turn a corner with how we work, and it's happened over and over again, and it will continue to happen as we evolve, of course.
2:43
Human work is judgment, discernment, reassurance, teaching, noticing, relationship, creativity, the willingness to carry a moral responsibility for a decision that doesn't have a clean answer.
2:56
Work currently being done by humans is remembering a deadline, finding a document, re-entering the same information a second or a third or a fourth time, reconciling a spreadsheet against a system that doesn't talk to another system, holding a mental map of five disconnected systems so nothing between them gets lost.
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Out of necessity, we have conflated the two, and sometimes that leads us to treat removing the second category as though we are diminishing the first. The opposite may be true.
3:27
When we build systems that absorb administrative burden, we create more room for the best expression of our uniquely human qualities.
3:36
And that makes me think about Frances Perkins, whose work is so meaningful and impacts all of us every single day, but I don't know how well known her story is, so I want to share it here.
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So March twenty-fifth, nineteen eleven, Washington Square, New York City.
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Perkins was across the park when the alarm bells started, and this is a very difficult story to review, but it's really important because of what came out of it. She
4:05
heard these alarms, runs across the park, and goes towards the sound, and then she stops at the edge of the crowd and looks up, and there are flames pouring out of the eighth and ninth floors of the Triangle Shirtwaist Factory.
4:19
There was no fire escape built to effectively evacuate the people on those floors, and the stairwell doors had been locked, which was standard practice at the time to keep workers from slipping out early or walking off with scraps of fabric.
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So the young women trapped on the upper floors had two horrific choices: the fire or the window. Close to fifty of them chose the window.
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By the time it was over, nearly one hundred and forty workers were dead, most of them young immigrant women. Nothing about that day called for more heroism from the workers.
4:56
No amount of individual grit could have unlocked the door. The problem
5:02
wasn't that the people inside the system had failed to perform at a high enough level to escape, but the system had assigned them each responsibility for something no individual should have been responsible for carrying.
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Perkins goes on and spends the next twenty-four years changing that. She helped build laws governing fire safety, building codes, and working hours.
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Later, she was the first woman to serve in a US cabinet, and she became a principal architect of the Social Security Act.
5:33
Ultimately, she built structures that carried things individuals had previously been expected to somehow manage for themselves. And that distinction is important because those structures didn't make people less capable.
5:48
They created conditions in which people could direct more of their capability toward the things that actually required them. And that's the opportunity I see in front of us again.
6:00
This time, the infrastructure we are deciding how to build is intelligent. Picture a supervisor today, not a struggling one, an excellent one. She knows how to develop people.
6:13
She notices when someone is drowning before they say so. She can tell the difference between a mistake that needs a conversation and one that needs a policy. Given the space, she would spend her whole day doing that.
6:27
Instead, she spends a large part of it tracking who's due for what certification renewal, chasing a form a vendor portal lost, reconciling spreadsheets against systems that don't talk to each other, recreating evidence of something she already knows happened, but the software that was supposed to record it did not.
6:46
Checking, checking, and checking again that nothing has fallen through a gap that exists only because no one built a floor there. She's not overwhelmed because she's weak. She is overwhelmed because she is the floor.
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We have this brilliant mind in our midst, but what isn't she noticing? Who isn't she mentoring? What problem isn't she solving? What idea never gets enough uninterrupted attention to become an idea at all?
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That is the cost we underestimate when we talk about administrative burden. We measure the hours lost to mechanics for sure, but we rarely measure the human capacity that never had the room to emerge.
7:26
So there's an old engineering idea called mistake proofing that we're all grateful for, even if we don't know that it's operating in our homes right now. The premise is almost embarrassingly simple.
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Human beings will make errors. So instead of demanding endless vigilance, you design the process so some errors become harder or even impossible to make. Best example, a microwave will not start while the door is open.
7:50
It does not need you to remember. The system remembers for you. Thank goodness. That isn't about removing people from work.
7:58
It's about refusing to spend human attention on a job the system can do so that attention remains available for the work only a person can do.
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Noticing what no sensor would catch, solving a problem no one has seen before, making a judgment when the answer is not obvious. Healthcare is not an engineered process, at least not entirely, nor should it be.
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But we make an engineering decision every time we decide what a person has to hold in her head and what the system will hold for her.
8:31
And in a lot of healthcare organizations, the answer is still that people hold almost all of it.
8:37
We have called that a lot of names, dedication, I don't know, but some of it is just infrastructure we never built or couldn't build. Good infrastructure doesn't make responsibility smaller.
8:49
It makes responsibility more human. We can let the system remember, connect, prompt, document, detect, and coordinate, and that frees the person to interpret, decide, teach, comfort, challenge, create, and lead.
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That is not a demotion. It's an opportunity to spend more of our working lives closer to the edge of what we are capable of.
9:13
For most of my career, that kind of infrastructure was a nice idea and a really hard engineering problem.
9:20
Connecting what happens across all of the disconnected systems a clinic runs on required either a lot of people or a person who can do a lot doing it by hand or software that was often too rigid to survive contact with how care actually happens.
9:37
But something has changed. And I don't think the most interesting thing about AI is how impressive the technology has become, although it's incredibly impressive.
9:49
The interesting thing is that now we have infrastructure capable of taking on more of what has been consuming human attention because there was nowhere else to put it.
10:00
This isn't a claim about what AI can do in healthcare. It's an answer to why it belongs there at all. Not because it is efficient, because it can create the conditions for more human potential to be expressed.
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And I wonder what all of the humans in healthcare will create when we are free from the administrative burdens that tie us to the system as we know it today.
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Infrastructure should carry the non-negotiables so leaders can carry the humans.
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We describe a good leader as someone who gives feedback, develops people, catches problems early, builds accountability, and helps an organization learn.
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But a leader can only do the human part of that job with whatever capacity is left after she finishes administering the mechanics of it. Give the mechanics to infrastructure and you don't just save her time.
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You give her back to the humans that she leads. And perhaps you give back even more.
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The space to think beyond the immediate task, to connect ideas, to teach and invent and innovate, to become better at the work and make the work better instead of just trying to keep up with it all the time.
11:14
The same is true in the exam room. So if clinicians and staff are spending real cognitive and emotional capacity compensating for operational fragmentation, that cost does not evaporate. It goes somewhere.
11:26
Some of what patients experience as rushed or inconsistent care or a clinician who seems distracted might not begin in the exam room at all.
11:35
It might begin several steps upstream in a system that never built anywhere else for four things to live except a capable person's head, leaving less of her available for the fifth thing, the person in front of her.
11:51
When we give some of that capacity back, the opportunity is larger than a calmer visit.
11:58
In talking with a lot of physicians over the last few months I have heard over and over and over again how much this means to them because we create room for clinicians to notice, teach, connect, wonder, and think with their patients.
12:15
And it feels different as a clinician to go home after a day of that versus a day of trying to chart 30 visits and complete all of the referrals manually. These are not soft benefits around the perimeter of healthcare.
12:30
They are where learning happens and where better care gets imagined and ultimately where organizations can evolve. So here's the idea. Maybe dignity
12:42
is not only measurable by what a system does not require a person to carry. I propose it is also visible in what that person becomes capable of doing when the unnecessary weight is gone.
12:57
The question of where we bring AI into healthcare has to be addressed. But applying the question of why we bring AI into healthcare gives us context, framing, and purpose for what we decide to do.
13:11
It is about what we think a person is for and whether we are building these new systems to protect and expand the fullest expression of that or spend it down.
13:22
The workers who came after Perkins' reforms, all of us, didn't have to be braver than the ones who died in 1911. They didn't have to become better at reading buildings for danger.
13:35
They got to work inside a floor someone else had already built. Codes that make doors open from the inside. Inspections that make fire escapes real. The system carried what no individual should have had to carry alone.
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And that left the person to carry what was actually hers. The skill, the judgment, the work, and the life she went home to at the end of the shift.
14:00
We have another chance now to decide what belongs in the infrastructure and what we want to preserve for people.
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If we get that decision right, the measure of good AI in healthcare will not be how much human work it replaces. It will be how much human potential it releases. So here's the question I want to leave you with.
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How much of what you carried today needed you? And what might become possible if more of you is available for the work that does? One more signal. And that's your cue I'm about to drop something extra for the listener.
14:42
Now, when I was thinking of stories that help illustrate this, I thought of the Industrial Revolution, of course, but I really like to highlight female stories.
14:51
And Perkins' story in its entirety is remarkable and moving for so many reasons. But I started to try to think of other little stories that might ring true. And I thought of several, including spellcheck.
15:05
When spellcheck came along, everybody said, oh, it's going to make people terrible spellers.
15:09
But what it did was free up writers to be able to write beautiful sentences without worrying how to spell the word recommend or necessary. And I thought of a few other examples. And then I thought, what about GPS?
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GPS changed spatial awareness.
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And if you take somebody who grew up unfolding maps and getting around in cars and somebody who grew up only with GPS, I think you may have some differences in how they know how to navigate the physical world we're in.
15:36
So not every example is a perfect example. Some things change us, but it's not bad. It's just different. And the one thing I thought of that really held true was passwords.
15:52
Obviously, because I'm old as rock, I was alive when the internet came on board and we all adapted to it. So we treated passwords as a memory problem in the beginning.
16:04
And there was all this advice about writing down your password and putting it in your purse or your wallet so it would stay safe. And then every website needed us to pick a new password.
16:15
So remembering the growing pile of passwords became our responsibility. And people did what people do when a system asks something incredibly unreasonable of them, which is that we adapt it. We use the same passwords.
16:29
We actually made them simpler and we wrote them down and then we put them on our fridge or, you know, tack them on the board in front of our computer. Then you forget the password. Then you get locked out entirely.
16:40
So for a while, the response was essentially people need to be better at passwords. And then somebody asked a better question, which was why are we asking people to remember all of this in the first place?
16:52
At the time, we were all memorizing seven digit phone numbers to really good effect. But now we're layering on something that is a really different kind of thing to remember.
17:02
So password managers became the memory keepers of our passwords. And we started to get programs for that.
17:10
Now we're moving towards pass keys, you know, our finger, our face, our eyeball, which go one step further and begin removing the password itself.
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And if you notice what happened there, we did not make human memory better at any point along the way. We just stopped designing a system that depended on human memory for something a machine could hold perfectly well.
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And nobody lost dignity because a browser remembered a password. Nobody became less capable because a system carried something that they used to have to carry themselves. We just put the weight where it belonged.
17:46
And that's what Harvest the Signal is all about. As we decide what AI should and shouldn't do next, we don't need to only ask, can the technology do this? Can we create the coding to get this to happen?
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We also want to ask, or maybe we want to ask ahead of time, why are we leveraging AI and how can its use elevate us into the most full expression of our potential as humans?
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So this is where I encourage you to noodle through these ideas while you're walking the dog or driving home.
18:22
If today's field note changed the way you might contextualize and frame the use of AI in your organization or in your life, please let me know. I read every reply.
18:33
In fact, the next Harvest the Signal may begin with something you've stopped accepting but haven't yet put into words. You can find me on LinkedIn under my name or on threads at Harvest the Signal.
18:44
And if you'd like me to be the voice in your ear while you get where you're going, hit subscribe and we'll keep exploring patterns hiding in plain sight together. I'm Jodi Lynn Owen.
18:55
Until next time, keep looking for the signal. This has been Harvest the Signal with Jodi Lynn Owen. The smallest signals can change the biggest systems.
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Be sure to like, follow, and share so you never miss an episode or the opportunity to compare your field notes with your colleagues.
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