My AI Physical Therapist

~ Sasha ~ 2 Comments

My Instagram feed is basically:

  • The 10 people I follow (including my son’s ceramics account)
  • Dogs / puppies / rescues
  • Tennis / squash tips and highlights
  • Injury prevention / cures for middle-aged athletes

On the last point, my last few years have been marked by a series of minor but chronic injuries. I seem to be in the stage of life of small ligament and tendon strains, injuries that respond well to physical therapy if you can make the time.

The worst has been tennis elbow (lateral epicondylitis). It’s lasted for more than a year, and I’m just now getting better. But I’m finding PT too time-consuming (90-120 minutes so I can do 20 minutes of exercises??) and too much of an insurance hassle.

In a continuation of this trend, a month ago, I got a sharp pain in my hip after a run. After a few dead-end YouTube attempts, I realized I didn’t know what was wrong with me.

Rather than go to the doctor and then back to PT, I turned to ChatGPT. I was amazed with how helpful it was. If you, like me, are still under-using these tools, perhaps this can be an inspiration.

Here’s the original prompt I wrote:

I need you to be an expert physical therapist who can help me diagnose and treat injuries at home. Be thorough in your diagnosis and assume that I am a sophisticated lifetime athlete who can do complex exercises at home as needed. I’m 51 years old. I need to diagnose a pain I have in my right outer hip, just below my hip pointer.

I got the injury after a fast (for me) hilly run after having taken off a few months. This was my 10th run after having taken 3 months off. I had done the same run, 4.3 miles, twice earlier in the week, but my pace in those was 9:30/mile and in this run was 8:20/mile. I felt no pain during the run but after the run it hurt some to stride / step with my right leg, and to go up hills. The pain is greatest when I get up after sitting down for a bit. After a little while it decreases. The pain is sharp and localized to the area just below and above the hip pointer.

From this prompt and a few follow ups, ChatGPT gave me:

  • Its first diagnosis (either a tendinopathy in my gluteus medius / minimus or a TFL overuse injury)
  • A series of diagnostic tests I could do to narrow down the potential injury
  • A full 30 day PT plan that I now have in a Google Sheet that I’m following daily
  • This plan includes descriptions of all the exercises with references.

Since this went so well, I’ve kept talking to ChatGPT about how it’s going: how the exercises, felt; how one of them hurt more than expected and could it give me an alternative; how I feel first thing in the morning and over the course of my day. It’s the conversation I would have with my PT every day if he were available.

With this feedback, ChatGPT both modified the exercise regime to better suit how I’m feeling and has modified the diagnosis.

Here’s the latest that I got back this morning, based on my updated symptoms:

Differential Diagnosis Recap

Condition Why It Fits Why It Doesn’t
Gluteus med/min tendinopathy Pain with heel strike, long stride, compression from sleep, improves with warm-up —
TFL overuse Could be involved, but unlikely primary now; less direct heel-strike involvement Less pain with bridge, more lateral than anterior
Trochanteric bursitis Possible secondary irritant But no diffuse swelling or tenderness reported yet
Labral or joint issues No locking, groin pain, or deep ache Very unlikely
Femoral stress reaction No deep bone pain or night pain Very unlikely

And here’s a visual representation of what I’ve told my AI physical therapist and what that means for my diagnosis—this pretty much blew me away:

I know that for many people, AI is an idea—perhaps even a scary one—and not something that’s part of daily life. And I can understand why many of us might be happier either using none of these tools or waiting for someone to build a “Virtual Physical Therapist” app rather than playing around with ChatGPT or the many other tools available to us today.

I’d encourage you to think about this another way: for $20 / month, an expert in literally any topic you can accurately describe is available to you and to your team.

It’s a shame not to take advantage of that.

Fill in the Blanks

~ Sasha ~ Leave a comment

Any job worth having has blanks. Lots of them.

There may be a set of steps to follow, a standard that’s been written out, a sequence that’s been proven to work.

But life, and people, are far too complex to fit neatly inside the rubric.

Surprises happen.

Someone goes on holiday, and you need to sub in.

An assumption got made in step 3 and that led to a seemingly-right-but-wrong decision in step 6 and, all of a sudden, we’re in step 8 and we need to decide what to do.

That’s a blank.

 

What Do You Do With a Blank?

The question is: what are we going to do with it? And, more broadly, what is our team going to do with it?

Because blanks appear all the time.

We can’t plan our way around them.

We can’t write a script to deal with all of them.

We can’t wish them away.

A starting point is our organizational values—real ones, that are reinforced every day in both actions and communication, that reinforce the right action. They say,

“Here are the principles and priorities we live by. When all else fails [read: when you come across a blank] behave in this way.”

But, even with great values in place—values that are reinforced regularly and are tangible enough to guide action—they will be insufficient if the people being asked to implement don’t care.

Because when you find yourself saying, “This is a situation I’ve never encountered before. What am I going to do?” you are encountering a situation that requires emotional effort, and emotional effort is neither cheap nor easy.

Every blank is defined by uncertainty, the chance that we might get this wrong. That translates to exposure. And, when faced with exposure, a person who doesn’t care much is more likley to hide or turn their heads the other way. This ultimately leaves the blank as a blank, but it feels safer.

 

Why does caring make all the difference?

Partially because you’ll try harder: you’ll be willing to put in that emotional effort despite the uncertainty and fear.

More because people around you will see you trying harder, and they will be more inclined to pitch in.

And, last but not least, because whoever you are trying to make happy—the person on whose behalf you are filling in this blank— will see how much you care. They will respect that intention and effort even if the outcome isn’t perfect.

This means we’re left with three questions:

  1. Do I understand that the most important parts of my jobs are the ones where I come across a ‘blank’?
  2. Has my organization articulated, and do we daily reinforce, an orientation that will support the best kind of actions we are going to take in these situations?
  3. How do we create and scale ‘giving a damn’ across multiple people in multiple places over long(er) periods of time?

The last one is, in my opinion, the real secret. Because even great values reinforced regularly mean nothing if they land on indifferent ears.

That means that, if you are part of an organization that faces a lots of blanks (and you do), the first question to answer is:

How do I make sure that everyone else cares as much as I do?

 

The Purple Tree

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This spring, on my daily morning dog walk, there was a purple tree in the woods. I think it’s been there every year, but this was the first time I really noticed it.

Each morning when the sun was out, I’d try to capture it: the blooms, its contrast with the trees around it, how the light filtered in and around it. None of my photos did it justice.

I’d look forward to seeing it every morning. Perhaps today was the day when the light would hit it just so.

And then, a few weeks of rainy mornings.

When I finally made my way back to the woods, it was gone.

It wasn’t just that the purple blooms had fallen off. In the midst of the green lushness of early spring, I wasn’t even sure which tree it was.

How impossible that something that was the focal point of my mornings could disappear. It could fade and become just another tree.

Lately there have been things I’ve been carrying with me that I’ve deeply wanted—sentence after sentence that starts with “If only…”

And then some of them come to pass, in part or in full, and the joy I expected to feel fades as quickly as that purple tree.

I’m working on it, though.

Working on letting that thing that was special, that thing that would make all the difference—I’m working on experiencing the joy, or the relief, or ease, that I’d been looking forward to for so long.

Why I don’t have an Apple Watch

~ Sasha ~ 1 Comment

As the weather gets warmer, I start running and swimming more.

I’d love to track my runs and my swims, but I don’t have an Apple Watch or a Garmin.

Having more access to texts, news and Slack notifications—and even knowing more about everything outside my workouts—seems like it would be a bad thing, and I know if I owned the watch I’d wear it all the time.

More features = worse outcomes.

Similarly, I love my Kindle because it only does one thing well.

My favorite restaurants have small menus where everything is great.

Atoms shoes are incredible because they’re more comfortable than any other, and they reject design nonsense

In a world in which AI can do most things, being pretty good at a long feature set will be worse than saying “I will do fewer things exceptionally and reject all the rest.”

This requires two things:

  1. Knowing your clients so well that you truly know what matters most to them
  2. The bravery to leave everything but those features on the cutting room floor

Fabian has it right. What more do you really need to know?

6 Points

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My daughter played in a squash tournament last weekend.

In squash, each player has a computer-generated ranking that is reasonably accurate. It’s very easy to think that these numbers tell the whole story.

So, when my daughter lost her match (11-9, 12-10, 12-10 ) to a girl with a 0.10 lower rating, she was very upset.

The next morning, gearing up for day 2 of the tournament, I asked her a question: “If you had won 11-9, 12-10, 12-10 instead of lost, would you have been pretty happy with the result?”

“Yes,” she agreed, she would have.

We did the math together and noticed that the difference between what happened and what might have happened was 6 points.

6 points out of 64 were the difference between “existential crisis” (“Maybe I’m not really improving. Maybe I’ll never improve.”) and “I’m on the right track.”

There are situations in which the difference between winning and losing really matter: if your business runs out of cash but has a fundamentally sound business model, what matters is the cash. And if you “almost” hit your targets every time, then you might have a target-setting or an accountability problem.

But most of the time, we act like my daughter, allowing the space between our narrative of wins and losses to be much bigger than what actually happened.

Drawing the lucky last card feels like our just reward for playing the hand correctly. But the two events are, in fact, unrelated.

 

Trajectory

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We’ve all done compounding math.

Invest $100 today and compound it monthly at 1%, and it will be worth $3,595 (35x return) in 30 years. Compound it annually at 2% and it will be worth $137,740 (1,377x return) in 30 years. And, of course, compound it at 0% and you’ll have $100 forever.

Now, apply this thinking to something you’re working to improve—it can be in your personal life or your organization. And think about getting a tiny bit better each month, say 1% or 2%.

At those rates of improvement, you’d be 30% or 60% better at this thing in two years’ time.  And, let’s be honest, a 1-2% monthly improvement at anything we’re really putting our mind to feels like almost nothing.

So, what do we make of issues that we’re stuck on? Ones that feel like whack-a-mole, where we keep putting in effort and we seem to end up in the same place?

If any meaningful amount of time has passed since we started working on these problems, that means that all our efforts don’t add up to even a 1-2% monthly improvement.

There are only two reasons this could be the case, and they are two sides of the same coin:

  1. The things we’re doing are not effective at addressing the problem
  2. The thing we think is the problem is not really the problem

While this is conceptually easy to understand, coming to terms with it is hard.

If we know that slow progress compounded over time results in massive change, being “stuck” can only happen if all our effort is having almost no yield. When that happens, it’s time to go back to the drawing board.

Compounding math doesn’t leave space for any other conclusions.

How We Learn Algebra Today

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Two weeks ago, I was sitting with my daughter, helping her study for a test on linear equations. She’s in 8th grade, and we’re already getting to the point where my recollection of some of the math she’s studying is rusty. Soon she’ll be in high school and I’ll be of no use at all.

She had a set of problems that stumped both of us, and I told her to use ChatGPT to get an explanation for how to solve them so she could learn and practice the approach before school the next day. She told me she didn’t want to, that she didn’t like using AI, and that she’d just ask her teacher in office hours the next day.

While I have sympathy for her reaction, and a preference for her always talking to her teacher when she wants to go deeper, her approach isn’t going to work. The power and leverage created by AI tools is too much to pass on.

Just last month, a member of our 60 Decibels team created a working prototype to replace a piece of software that we’re paying tens of thousands of dollars for. The prototype took 15 minutes — 15 minutes! — to develop on v0.dev, and we expect it to replace the expensive, paid software we’re using sometime this month.

There’s a reason the Shopify CEO’s leaked memo — in which Step 1 reads “Hire an AI before you hire a human” — went viral. If we’re not retooling how we are running our organizations, we are already falling behind. Whereas if we’re diving in, we have the opportunity for unparalleled leverage.

Our job, then, is to keep on talking to the human—in my daughter’s case, her math teacher. But we need to go into that meeting having practiced and learned and honed our skill with the free tutor who now lives in each of our browsers. We need to take every repetitive task, every task that can be easily described, every part of the work that’s not uniquely leveraging our specific skills, relationships and insights, and find a way to have an AI tool improve or take over that part of the work.

 

Who, What, When

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Organizational complexity grows faster than the growth of organizations.

One of the drivers of this is the math of large groups: the number of relationships in a group grows much faster than the number of people in a group.*

For example, in a nuclear family of 4 people, there are 6 pairs of relationships. That number grows to 10 in a family of 5 and, if each of the 3 kids in this family has three kids, it grows to 136.**

Similarly, when a company grows from 10 people to 100, the number of pairs grows from 45 to 4,950. That number excludes all external relationships and all other configurations of people.

In this context, it’s easy to see why seemingly simple concepts like prioritization and hitting deadlines can become difficult to maintain as an organization grows. Suddenly, everyone has a list of 100 things, and everyone is doing their best to get most of them done.

While this is true, it also allows us to get into bad habits.

One of these bad habits is vagueness around who will get what will get done by when. It’s the difference between:

  • (Easy, natural) We talk about things, agree (in principle) about the decision, someone says they’ll run point. Meetings end with inconsistent documentation and summary around next steps.
  • (Rigorous, learned) We decide things, agree with clarity about the decision, and we always have a point person who signs up to action something and gives clarity about the deadline. All meetings have consistent written prep and consistent summaries and documentation of next steps.

In the “Rigorous, Learned” culture, for each and every decision, there is a Who, What and When. No exceptions.  (The only wrinkle is that the “When” can either be the due date or the date by which a due date will be decided upon.)

The difference between “nearly clear” and “clear” here is huge: there’s no 80/20. As in:

  • “We (mostly) decided this” v. “everyone knows and could repeat back what the decision was”
  • “I’m pretty sure Alexis is in charge” v. “Alexis is in charge”
  • “She’ll give us an update next week” v. “She’ll get it done by April 21st”

No one person can make this happen alone.

We must decide as a group to change how we show up for each other; and we must reinforce a new set of habits—particularly during meetings—that support these new behaviors.

When we build up these habits, we weave something new into our cultural fabric.

We become a group of people who keep our promises to one another, who know we can count on each other, and who know what’s most important.

This new culture will persist no matter how big we get.

 

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Math notes

* I wanted to describe this as an “exponential” relationship but, strictly speaking, it is quadratic. The easy way to describe this is that the number of relationships grows proportionally to the square of the number of people in the group.

** 2 grandparents, their kids (3 + 3 spouses), and their grandkids (3 x 3) makes a 17-person family. The number of pairs in a group of 17 is (17 x 16)/2 = 136.

 

 

The Structure of an Apology

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It’s not as hard as it looks if we ground our apology in facts.

We say the following:

It is a fact that this happened.

I understand that this happened.

I apologize to you for my role in making this happen / not stopping it from happening. 

I feel genuine remorse about the fact that it happened.

Owning our mistakes is one of the bravest, most empathetic things we can do. No fooling.

Pain in the….Arm

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The time I’d normally have spent, yesterday, finalizing today’s post was after the plasma injection I got in my arm for persistent (last 10 months) tennis elbow.

The doctor told me not to use my right arm (includes typing) for the week.

So, that post will go live next week. In the meantime…

I remind myself that I am More than the Broken Parts.

And, for further reading that may not have crossed your desk: here’s the memo about what is happening to U.S. foreign aid in the aftermath of the dismantling of USAID.

Hopefully what emerges will be some semblance of what is described.