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You and I as veterans, it hit me right off the bat because the guy's going,
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well, I've been around since blah, blah, blah, blah, blah happened.
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And LinkedIn, I just went, well, I've been around for 47 of those damn 50 years.
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And I think you're right. I have a different perspective on what's gone on in those 50 years.
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And you've been around for a lot of those 50 years.
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So we should reflect a little since people wanted to do this and we're doing it I thought in a very,
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they were undercutting would be the fair word undercutting where we stand rather
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than empowering us to go further and do better it was undercutting everything
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and that's really the last thing we need in a time of change and challenge.
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Pre-accident investigation podcast. It's me, Todd. How are you?
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This is part two of the David Woods conversation. If you've not heard part one,
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you know, I'm of mixed minds, but it's probably worth going back and listening
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to first because it kind of sets the story.
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It builds the case for what part two talks about.
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But if you're in a hurry and, you know, you got a lot of crap going on and you're
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super busy and important, and many of you are, I realize.
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You're fine jumping in here as well.
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He is a great podcast guest for a bunch of reasons. One, Professor Woods is
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just smart. Every time he talks, I have pages of notes I take down.
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Just the way he phrases things makes me think. I hope you feel the same. I bet you do.
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Secondly, he requires very little feeding and maintenance. I mean,
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he'll take off, baby, and he'll go.
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And I like that because he has lots to say and he's thought a lot about this,
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a bunch about this. So this is kind of a very interesting and very important conversation.
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And I have to tell you, I don't want to ruin the ending because it's good,
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but it really ends in a way that I think it probably must end and should end.
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And it's the right thing to do. You know me.
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My theory is the meaning of life is good work done well for the right reasons.
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I've said that to you guys a million times.
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This kind of builds that case beautifully. And I think you'll appreciate it immensely.
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And it's a great conversation. It's very important. For a part two,
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this is killer good. That's how good it is.
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I'm having a good time here. I hope you're having a good time there.
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There's much for us to share. And I kind of want to jump right into this because
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there's so much information for you just to chew on and think about and enjoy.
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Yes, if you're not enjoying this, we're doing it wrong. It should be pretty fun.
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I mean, that's the whole goal is to learn something and have a good time.
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You know, it's about professional development. And that, my friends,
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that is something that we've been on a journey together for a long, long time.
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So without much further conversation, and I promise you, I don't have a lot more conversation.
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Let's hear part two of the talk that the three of us are going to have,
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Professor Woods, myself, and you.
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And it's going to be on what do we do with this information and how do we move
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forward as a community of people who are directly involved in safe,
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reliable operations. That's our goal.
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Because the other thing that's happened is the world keeps getting more complex.
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So those old things that kind of work some don't work so well anymore or the impact isn't so great.
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And that's why I'm always talking about, especially in patient safety,
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is can you produce an order of magnitude effect?
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I'm looking for 10 times an effect, not a percent. Yes, you could do a study for a percent effect.
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Usually they want us to give them a few percent effect. Right.
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Right. And we're like, no, I'm looking for an order of magnitude of fact,
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given the nature of the systems that change and the potential harm as our systems grow in capability.
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The harm when they break goes up by orders of magnitude, too.
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That's what I've said to you before When things go wrong now,
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The potential for harm When things go wrong Is at least two orders of magnitude
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Bigger than the maximum impact Of our traditional safety initiatives We did our initiative,
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They let us do it And they gave us reasonable funding Within the normal organizational constraints.
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And it was pretty successful It would be
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a percent improvement Not an order
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of magnitude improvement.
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And we're looking at harm that is two orders of magnitude. And as I said to
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you last time, measles is a simple example.
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And by the way, when I talked to you last time, we're now in the seventh month,
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right? And we have set a record, right?
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We are way past the max number.
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We're way on our way to three orders of magnitude. We might hit,
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we're definitely going to hit two and a half orders of magnitude in measles cases.
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As a canary in the coal mine on how the exposure to harm is increasing at the
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same time that our systems grow in capability.
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How will we break that cycle?
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Well, the irony is we can rock the boat with a science base.
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But it is kind of the answer in a way, right? Or it's a vital part of the answer.
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Yes. I mean, we have to have a generalizable set of what goes on.
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Because the normal context and pressures and constraints in which we do practical
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safety programs, they're very narrow.
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We get lost in the details of every setting.
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And it's driven very reactively.
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Even the, you know, the, our proactive, we get proactive successes,
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but it's hard to sustain.
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It's hard to have them organically multiply. It's a uphill climb each time we
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pull one off and that doesn't scale.
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And we've seen that when, if you take the long look, you go, yeah.
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So I want to go back to this issue of everything in the human experience pretty
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much is encompassed in the label safety,
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success, failure, reward, harm, fear, blame, responsibility,
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ethics, courage, disaster, heroic saves, the drama of the very near miss, right?
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It covers the C-suite. It covers regulatory policy.
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It goes all the way down to people who have to operate critical systems under
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enormous pressures to do amazing things at the sharp end.
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We cover a new technology that can do more and extend human reach,
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human vision, human action to new scales and distances.
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They have an enormous range of things.
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But in the end, you know, a mantra for proactive
safety that I articulated 26
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years ago, been in print 21 years, is this our fundamental obligation as safety people, right?
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If you're engaged in creating safety, our fundamental obligation is to create
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foresight about the changing shape of risk before harm occurs. Mm-hmm.
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This came out first in the patient safety movement around 2000,
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and then very significantly in the Columbia space shuttle accident.
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And so now those two things, this huge encompassing of human systems issues and this obligation,
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for foresight about the changing shape of risk, means we've got a lot.
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I mean, what scope? I mean, what fun we get to have over the years, right? You and me.
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All the places we get to go, all the things we get to interact,
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all the scary places we've been, right? That's what we talk about over beers.
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Who went to the scariest place and came out alive?
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The so the key is building science base but that science base is about it has
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these funny constraints on it how do you do,
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lab how do you do what science people when people say science they usually think
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of lab experiments and definitive results with laws and you go big laws to hold
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everything up yeah i'm with you,
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and well when safety encompasses so much of human experience you have to look at the real world,
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and how do you and are you understanding human aspirations are you understanding
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why we build technology why we operate in certain ways why we're willing to
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invest in some aspects more automation less people maybe sometimes we should
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grow human expertise and have
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and maybe that's a better investment in the long run sometimes,
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always be one way or the other right.
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The and and and so you end up with this thing of we can't really do what our
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social norm of what science is.
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We have to do something that looks at the real world. So all of those practical
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experiences you and I have been in, we've treated we were just joking about
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it as research opportunities. Right. We're not just helping them.
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Each time we do it, we're going, I'm looking for patterns and understanding,
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whether that's at the sharp end, whether that's about the technology or the
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human technology interaction. whether that's about the organizational beliefs, how do you move them?
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How do you change their models and biases?
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I mean, another one is that makes this hard and different than usual areas of
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science is how do you do science when the people trying to do the science are
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part of the processes the scientists are trying to study?
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If you're trying to understand safety, you're influencing safety.
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You can't study it without being related to the process that's trying to build
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safety or sustain safety.
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You're studying how it breaks, right?
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You're part of the thing you study. You're not an outside objective observer.
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You're in something that's changing all the time.
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So the third thing is creating safety is about all kinds of skills,
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but they're all about balancing competing interests, right? In a changing world,
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not a state, not a category.
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It's about rebalancing how activities need to shift relative to goals,
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how goals need to shift relative to risk, how resources need to shift relative to uncertainty and risk,
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and new technology and new opportunities.
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It's a dynamic balancing And it's very hard To get organizations In today's world,
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That's why I use a lot of military examples Because they have to be good at
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balancing Dynamically Otherwise they lose Even if they start in the best position And they stay there.
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The best position doesn't stay best because there's somebody else adapting to.
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And so that gets us to this current situation we've been talking about of people
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looking back at 50 years and saying,
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yeah, it's just a lot of noise, a lot of labels, not much progress. Sloganeering.
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Pre-scientific sloganeering, right?
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And I think we want to blow away any confusion That there is,
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in fact, fantastic progress And,
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that the world keeps changing And that progress is necessary And needs to be,
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sustained and sped up even,
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And that it's easy, given the pressures Limited resources, huge variety of situations
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And distractions we have to face in safety It's easy not to know a lot about what we know,
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It's hard to keep up.
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It's hard to be part of this. It's hard to synthesize.
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God, that's interesting. You know that's an incredibly interesting thing you
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just said. That's remarkable.
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I mean, so we're getting a little bit to some of the punchlines.
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One is got to put effective and safe, safe and effective up front in order to
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be viable in both the short run and the long run, to be adaptive both in the
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short run and the long run.
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That are put faster, cheaper first assumes a stable world. Right.
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Where it's just a quick race. But when the landscape changes and the rules change
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and the destination changes and the trophy at the end changes, you got to adapt. Yeah.
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So what I want to highlight with you and encourage everybody is to spend some
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more time investigating, arguing, challenging, revising, extending, limiting.
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I'm not even going to say the scope of what we know is more limited than we
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thought, building more.
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But I want to give a couple examples that we have generalizable findings that
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are both concrete to guide how to work in a particular situation.
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Right. One general generalization doesn't apply everywhere.
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But it applies in lots more places. In fact, the reason we know it's a generalization or a law even,
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or a theorem even more that we can prove, is because we see it in many different
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settings play out, even though there are differences because of the unique features
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of those settings or the layer at which we observe it.
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And so I want to give one, right? It's really simple. It's a short paper under 4,000 words.
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It's a synthesis of syntheses.
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It's called the Command-Adapt Paradox Paper And it was written in frustration,
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I admit it Because people kept coming back and saying Well, what about compliance?
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And how much pressure for compliance should we be putting on our subordinate
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managers and personnel To just comply with the policy, to comply with the plans,
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to comply with the rules?
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And I kind of went, oh my God Are we re-litigating this again?
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How many times have we re-litigated this? Why are we doing this?
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This is an example of us We're in the washing machine going around and around
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again I'm tired of getting an ounce in your head off the wall You know,
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And so I reviewed the papers and syntheses To remind people about the basics
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And tried to summarize the synthesis of the syntheses You know, in plain, plain terms,
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compliance says there's plan and conform we often turn the plan into automation
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to try to make sure there's conformance right,
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right and the pressure to plan to behave by plan and conform reduces adaptive
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capacity this is laid out and a variety of things and i went through them in a ways like.
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Here are i had it up but anyway you should go look at it and i'll put the paper
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i'll put the paper in the notes for this.
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You know, it's like one of the findings, one, two, three, four, finding one.
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Okay. Well, the, the modern, right.
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There will always be surprised to challenge your plans. The modern date on that
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is in the 1980s on that finding.
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How far does it go back? It goes back to 1836 in Clausewitz.
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Another one is people outside models of work are miscalibrated.
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Your model of how someone else confronts the world is not the same of the model
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of the person confronting uncertainty, complexity in the world.
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That model confusion really dates back to again, some developments and papers
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and findings in our 50-year history.
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But you know how far it goes back? It goes back to 1890.
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William James, and he called it the psychologist fallacy.
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When the person studying human behavior substitutes their model for the situation,
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for the person's model of the situation, they have to act it.
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And he says, your job is to discover the model the person brings,
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not because it's right, but because they'll behave according,
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that model will influence their behavior.
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And then you can start to see what they're missing, what they're getting right.
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And you'll see that both of your models are wrong.
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Both of your models are incomplete and the risk of miscalibration exists,
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whether the person acting in the world and the person trying to understand the
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person acting in the world.
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And that's in Behind Human Error. That's in the 1983 paper at the Bellagio,
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the first formal official meeting on going behind the label human error in 1983.
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Those were, that fundamental is there. And that comes out in how we deal with
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hindsight bias and the techniques and a whole bunch of different things.
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And we can go on and on in there.
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Very quickly, we see research coming out. And again, we could date it earlier,
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but 1986, Lucy Suchman, plans are resources for action. Plans aren't specifications of action.
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All right. And then we go through how that developed.
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And what that means and what you end up with, oh, and that plans are necessary
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to recognize anomalies and surprise, right?
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If I don't have a model of what's typical, what's supposed to work,
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how things usually work, how we usually handle disruption and variation,
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I can't recognize anomalies, right?
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And therefore, I can't revise models. I can't revise tactics.
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I can't learn new strategies.
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I don't understand and diagnose the anomalies and where they come from.
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So learning and change comes from recognizing anomalies And to do that,
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I need a baseline of typicality that comes from plans So plans help me revise,
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And that's an old finding Eisenhower said that one in the 1950s.
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As well as scientists in the 80s and 90s So that led us to the idea of It's
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not plan and conform, it's plan and revise But revision isn't freelance,
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So then we run through what's the interaction between, right,
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what do we want to achieve? How are we trying to achieve it?
00:18:47.167 --> 00:18:52.826
Variability, surprise, and opportunity will arise outside the boundaries of that scope.
00:18:53.268 --> 00:18:58.132
And how do we revise relative to that? How do we recognize, revise,
00:18:58.319 --> 00:19:03.286
reframe, revitalize, right, head in new directions?
00:19:03.594 --> 00:19:06.544
And we've seen that now that we've lived decades in this.
00:19:06.544 --> 00:19:11.184
We see that over and over again Where safety programs, safety innovations Were
00:19:11.184 --> 00:19:16.884
turned into programs The programs, these were all fights The programs eventually
00:19:16.884 --> 00:19:18.646
were widespread in the industry,
00:19:19.335 --> 00:19:22.630
Even transferred to other industries And then you go and look.
00:19:23.384 --> 00:19:27.820
A while later, and you recognize they're not fit for purpose anymore.
00:19:28.473 --> 00:19:33.781
They're not doing the job. They've lost vitality, right? They need to be revitalized.
00:19:34.182 --> 00:19:38.744
Some of those were the successes in teamwork at crew resource management.
00:19:38.744 --> 00:19:43.782
And then you go into places that have crew resource management or other teamwork programs and you go,
00:19:44.419 --> 00:19:47.604
yeah, but when you actually look at the organization closely,
00:19:47.604 --> 00:19:52.221
you're finding a lot of breakdowns in teamwork, a lot of working across purposes,
00:19:52.581 --> 00:19:57.144
a lack of synchronization over different organizational boundaries within,
00:19:57.144 --> 00:19:58.644
you know, within the organization.
00:19:58.644 --> 00:20:01.416
And you go, there's not great teamwork here, guys.
00:20:01.851 --> 00:20:05.954
You need to revitalize the program and expectations around this.
00:20:05.954 --> 00:20:11.657
And it become routinized and rote and fine and a distraction.
00:20:12.034 --> 00:20:16.376
I get to go off and take my team training, but nothing effective came from it.
00:20:17.022 --> 00:20:21.824
So we have to re-energize the pursuit of safety We have to revitalize That should
00:20:21.824 --> 00:20:27.204
be seen as a basic in safety Not only do you need to You're in a place of.
00:20:28.984 --> 00:20:33.427
Re-energizing, revitalizing safety We want to do this before bad accidents happen
00:20:33.747 --> 00:20:38.324
But down the road, it's not one and done It's a phase And then you're going
00:20:38.324 --> 00:20:43.164
to have to re-energize and revitalize And some of that will be on different aspects,
00:20:44.144 --> 00:20:49.074
That weren't critical before And, you know, were okay to handle With the other
00:20:49.074 --> 00:20:52.934
programs you had But now needed to be more the focus and central thing Because
00:20:52.934 --> 00:20:53.994
the world keeps changing,
00:20:54.693 --> 00:20:59.167
So anyway, so if somebody comes and says to you, it's all noise and it's pre-scientific,
00:20:59.735 --> 00:21:03.024
read the Command-Adapt Paradox paper, right?
00:21:03.024 --> 00:21:06.904
It synthesizes lots of research. It encompasses a broad set of things,
00:21:06.904 --> 00:21:10.904
and it ends up with an actionable strategy, and it's being carried out.
00:21:10.904 --> 00:21:15.524
Guided adaptability is being used by pragmatic people working with everyday
00:21:15.524 --> 00:21:20.344
organizations like Dave Provan and Bethleh and their book coming out on this,
00:21:20.785 --> 00:21:25.713
and they're turning it into practical action so that you can meet those demands.
00:21:25.992 --> 00:21:28.889
Do it now, do it fast, and don't cost me money. That's right.
00:21:29.624 --> 00:21:31.095
And make it better, make it better.
00:21:31.904 --> 00:21:36.134
What a great conversation. Thank you, my friend. Well,
the other ones,
00:21:36.134 --> 00:21:41.244
I mean, there's other ones I want to mention quickly to remind people of this
00:21:41.244 --> 00:21:42.829
before we bring it to a close.
00:21:43.724 --> 00:21:48.164
Just to highlight to people, I already mentioned the fluency law and now that
00:21:48.164 --> 00:21:50.440
goes back to the psychologist fallacy.
00:21:51.349 --> 00:21:56.028
But the fluency law and all that stuff is critical to our analysis of how things
00:21:56.028 --> 00:21:58.048
go right and how things can go wrong.
00:21:58.645 --> 00:22:02.388
You have to go in and understand how people are adapting. And to do that,
00:22:02.388 --> 00:22:06.134
that's where in resilience engineering, we said study how things go right. Why?
00:22:06.511 --> 00:22:10.198
Because people are doing fluent adaptations to make things go right.
00:22:10.198 --> 00:22:12.129
So go study how things go right.
00:22:12.558 --> 00:22:17.088
So make sure you understand the fluency law. It's critical out there in the
00:22:17.088 --> 00:22:19.780
last 25 years of how we pursue safety.
00:22:20.308 --> 00:22:24.858
And forget the big labels and arguments over this And putting numbers on it,
00:22:24.858 --> 00:22:28.980
whatever There's a fundamental law, right?
00:22:29.236 --> 00:22:34.958
Now, it's an empirical law But we can derive this from some first principles
00:22:34.958 --> 00:22:39.545
That gives it extra strength It's not just empirical that we see it a lot It
00:22:39.777 --> 00:22:41.676
kind of has to work this way Right.
00:22:42.958 --> 00:22:46.808
And so then when you understand it You can make use of it in a variety of settings
00:22:46.808 --> 00:22:50.628
To help understand and direct your action and also understand how sometimes
00:22:50.628 --> 00:22:52.045
people get on the wrong track.
00:22:52.702 --> 00:22:56.468
The other one is, this one came, there were some things anticipating it,
00:22:56.468 --> 00:23:00.911
but it was first, the label was first used in 98, it's the law of stretch systems.
00:23:01.513 --> 00:23:05.621
Every system is stretched to operate at its capacity as soon as there is some improvement.
00:23:06.638 --> 00:23:10.318
When a new form of technology comes along, the capabilities will be exploited
00:23:10.718 --> 00:23:13.291
to achieve a new intensity and tempo of activity.
00:23:13.925 --> 00:23:20.029
The statement of the law is actually a paraphrase of an after-action report from a U.S.
00:23:20.319 --> 00:23:27.708
Military operation that was Kordsman, Anthony Kordsman, summarized the use of
00:23:27.708 --> 00:23:30.682
new modern military technology in the Gulfs.
00:23:31.618 --> 00:23:35.454
To do more, do it faster in more complex ways. It didn't make the work on the,
00:23:36.054 --> 00:23:37.580
sharp end operator easier.
00:23:38.160 --> 00:23:41.364
It enabled them to do more, do it faster in more complex ways.
00:23:41.364 --> 00:23:45.811
What did that mean? You could do more. It was good. A
capability also meant it was riskier.
00:23:46.578 --> 00:23:49.132
Things could go wrong. When they went wrong, harm was bigger.
00:23:49.312 --> 00:23:52.533
Right. And some of that were friendly fire incidents.
00:23:53.642 --> 00:23:58.994
So notice this highlights how everybody's adapting and how when people say we're
00:23:58.994 --> 00:24:05.324
going to improve the system in this way, I'm sorry, but that's not what's going to happen.
00:24:06.008 --> 00:24:09.824
Do I know what's going to happen? No. What I know is what we think is going
00:24:09.824 --> 00:24:11.774
to happen is not what's going to happen.
00:24:12.554 --> 00:24:17.144
Because people are adaptive. And what they'll see as an advantage is different
00:24:17.144 --> 00:24:19.013
than what we thought it would be.
00:24:19.517 --> 00:24:24.234
We'll think more narrowly and linearly. They'll see it relative to their goals.
00:24:24.234 --> 00:24:26.124
Remember that psychologist fallacy.
00:24:26.443 --> 00:24:31.464
They'll see it in a new light. And they'll go, look what this will do for me.
00:24:32.156 --> 00:24:37.104
And that means maybe it won't do something so good for a different role at a
00:24:37.104 --> 00:24:40.103
different layer of the operation or organization.
00:24:40.798 --> 00:24:44.694
And we see this in the adaptations around AI coding.
00:24:46.414 --> 00:24:51.144
We just see it all the time in all of this. one that is really,
00:24:51.144 --> 00:24:56.054
really important and has been there since 19.
00:24:56.054 --> 00:25:01.230
I first said it in 83 at the Bellagio meeting, and then it's in the 94 Behind Human Error, is how,
00:25:01.843 --> 00:25:05.934
hindsight, knowledge of outcome changes your perspective and changes your ability
00:25:05.934 --> 00:25:11.224
to understand what happens when people confront situations with uncertainty and risk.
00:25:11.912 --> 00:25:15.499
And so I gave it a new name a few years ago, the novelty inequality.
00:25:16.109 --> 00:25:20.994
I think this is a mathematically provable situation. I have not found a partner
00:25:20.994 --> 00:25:23.644
to help me pull off a mathematical Bayesian proof.
00:25:24.997 --> 00:25:30.001
Well, you know, I've always argued with Bayes. Now I want to use Bayes to help me.
00:25:30.334 --> 00:25:33.820
I haven't quite found a way to do this. Bayes is kind of intransigent.
00:25:33.820 --> 00:25:37.460
You know, I'm not sure I'm on your side, Dave. You've criticized me so much.
00:25:38.990 --> 00:25:44.610
But the novelty inequality, when you're in a situation facing uncertainty and
00:25:44.610 --> 00:25:51.662
risk, the potential novelty in front of you is much, much greater than the known novelty,
00:25:52.179 --> 00:25:54.379
that's determined after the fact.
00:25:55.182 --> 00:25:59.472
Right. Afterwards, we can hone in on this is exactly what was different.
00:26:00.064 --> 00:26:04.520
This is exactly where the rules didn't apply. This is exactly the surprising
00:26:04.520 --> 00:26:08.951
nature. This is exactly what needed to be adapted relative to normal practice.
00:26:09.578 --> 00:26:14.400
But beforehand, you're not sure There's multiple forms This was shown in the
00:26:14.400 --> 00:26:18.120
hindsight cartoon That Richard Cook came up with And we used in the patient
00:26:18.120 --> 00:26:23.840
safety movement In the 90s Based on the Behind Human Error book Trying to explain what this,
00:26:24.666 --> 00:26:30.691
meant And literally the cartoon used It's in the 2010 book You can see,
00:26:31.418 --> 00:26:36.810
The range of uncertainty factors And trade-offs that the Sharp end person confronts
00:26:36.810 --> 00:26:43.620
In the face of uncertainty and risk versus the after-the-fact analysis can hone in on only a few.
00:26:44.007 --> 00:26:47.860
And as I always joked about Three Mile Island, they had 10 minutes to make a
00:26:47.860 --> 00:26:53.684
decision for a situation they had not been trained for and didn't know even could exist. Right.
00:26:54.950 --> 00:27:03.120
When the after-action analysis took six months and $6 million of the best engineers
00:27:03.120 --> 00:27:08.060
in the field and $60 million in 1980 terms is a hell of a lot of money.
00:27:08.060 --> 00:27:09.337
Yeah, yeah, that's some big jack.
00:27:09.686 --> 00:27:13.100
And I think a lot of us would make decisions better with $60 million,
00:27:13.900 --> 00:27:18.980
even in today's dollars, and access to the best engineers or analysts on that
00:27:18.980 --> 00:27:20.726
particular topic, right?
00:27:22.102 --> 00:27:26.110
And stuff. So we have lots and lots of stuff.
00:27:26.812 --> 00:27:30.992
So we wanted to come back. You asked me, well, and this is going to go back
00:27:30.992 --> 00:27:34.181
to, we're trying to stimulate our friends.
00:27:34.663 --> 00:27:40.592
Yeah. That, you know, in a time of turbulence and change where the value of
00:27:40.592 --> 00:27:47.372
pursuing safety is in decline, the attention and willingness to invest in efforts to improve safety.
00:27:47.372 --> 00:27:51.506
In fact, it's the opposite, are faster, cheaper.
00:27:52.197 --> 00:27:55.820
Who gives a damn about what consequences play out along the way?
00:27:56.174 --> 00:27:58.524
We have to move fast and we have to move cheaper.
00:27:59.186 --> 00:28:03.268
And so how do we stand up for safety in this period of turbulence?
00:28:03.859 --> 00:28:05.212
We all need to pull together.
00:28:05.929 --> 00:28:10.660
And as you asked at the beginning, how do I deal with it and how do I personally get frustrated?
00:28:11.275 --> 00:28:16.284
Well, Voltaire said it for me in the 1700s.
00:28:17.018 --> 00:28:24.268
Mon Dieu, gardez-moi de mes amis. Quand à mes ennemis, je m'en charge.
00:28:25.132 --> 00:28:31.548
Dear, dear God, protect me from my friends. I can contend with my adversaries on my own.
00:28:32.888 --> 00:28:36.730
Beautiful. Thank you, my friend. We all need to pull together.
00:28:37.822 --> 00:28:42.466
And that is synthesize. Put safely and effective first.
00:28:43.802 --> 00:28:51.579
Build the momentum for continuous energy investment, re-energizing, revitalization.
00:28:51.933 --> 00:28:54.722
We are in a period of desperate need for revitalization.
00:28:55.323 --> 00:28:59.596
That requires innovation, that can draw on the science base.
00:28:59.926 --> 00:29:04.310
That's going to change the science base. It's going to expand the science base.
00:29:04.692 --> 00:29:08.750
We need to do it together because we are like the sharp end operator.
00:29:09.017 --> 00:29:12.892
We got to pull off something when we're under constraints. They're tying one
00:29:12.892 --> 00:29:17.121
arm behind our back, and they're trying to cut us off at the knees at the same time.
00:29:17.759 --> 00:29:22.990
We got to show a way, get some tools in there to show we can still dance,
00:29:23.204 --> 00:29:24.905
and we can help them dance too.
00:29:25.265 --> 00:29:30.992
Because we all are part of the balancing act that creates and sustains safety
00:29:30.992 --> 00:29:32.879
while we do things effectively.
00:29:33.355 --> 00:29:36.422
And that's always been the case, and it will always be the case. Thank you.
00:29:40.947 --> 00:29:45.629
And there you have it. Part two, finito, complete, terminar.
00:29:45.629 --> 00:29:47.627
It's over. We've done it.
00:29:48.178 --> 00:29:50.589
And thanks for hanging in there and listening to both parts.
00:29:50.589 --> 00:29:54.053
I know it's made a difference. It's a very interesting conversation.
00:29:54.308 --> 00:29:58.755
And I kind of hope it does rock a boat. I'll be good with it rocking a boat.
00:29:59.196 --> 00:30:02.759
But more importantly, I hope it builds a pretty strong case for we're better
00:30:02.759 --> 00:30:05.819
collectively together than we are separate.
00:30:06.486 --> 00:30:10.381
And I think that's a really important message. And that's not coming from me, baby.
00:30:10.770 --> 00:30:15.066
That's coming from Professor David Woods, the Ohio State University, the man.
00:30:15.664 --> 00:30:19.599
He's been around along 47 of the 50 years. That's a long time,
00:30:19.599 --> 00:30:21.010
dude. That is a long time.
00:30:21.428 --> 00:30:24.439
Learn something new every single day. Have as much fun as you possibly can.
00:30:24.439 --> 00:30:26.789
Be good to each other. Be kind to each other. Take care of each other,
00:30:26.789 --> 00:30:29.993
even the least among us. And for goodness sakes, be safe.