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Game Theory, the Fermi Paradox & Why Most People Won't Survive AI: The Masterclass · Connor with Honor: AI, Real Estate and Real Life

• 0:00
  SPEAKER_00: Today's different.
• 0:01
  SPEAKER_00: No news stories, no product drops.
• 0:03
  SPEAKER_00: Today I'm going to make you a little bit more dangerous, I hope.
• 0:06
  SPEAKER_00: This is going to teach you the language that the people building AI actually speak.
• 0:11
  SPEAKER_00: And it's uh very confusing, but maybe not for you, but for me, it's just like going back to school.
• 0:17
  SPEAKER_00: Now I'm not going to talk about the marketing language, not the hype language, but the real language, the frameworks, the mental models, the stuff they argue about in boardrooms at Anthropic, OpenAI, and of course DeepMind.
• 0:29
  SPEAKER_00: Because when you understand how these people think you stop being a spectator, you start seeing the moves before they happen.
• 0:35
  SPEAKER_00: You start hearing what they're really saying underneath the press releases.
• 0:40
  SPEAKER_00: And you're never going to watch an AI headline the same way again.
• 0:43
  SPEAKER_00: So buckle up, we're going to cover a lot of ground today.
• 0:47
  SPEAKER_00: Let's start with a question that's been haunting scientists for 70 years.
• 0:52
  SPEAKER_00: The universe is 13.8 billion years old.
• 0:55
  SPEAKER_00: There are roughly 200 billion trillion stars out there.
• 1:00
  SPEAKER_00: The math says that intelligent life should be everywhere, should be obvious, should be unavoidable.
• 1:06
  SPEAKER_00: So where is everybody?
• 1:08
  SPEAKER_00: That's something that they call Fermi's Paradox, named after physicist Enrico Fermi, who asked that question over lunch in 1950.
• 1:18
  SPEAKER_00: The universe should be crawling with civilizations and signals and evidence, but it's dead silent.
• 1:24
  SPEAKER_00: Same thing with the United States.
• 1:25
  SPEAKER_00: The fossil record should be full of transitional life forms, but it's not.
• 1:30
  SPEAKER_00: One explanation is called the Great Filter, the idea where there's some wall that civilizations hit and they don't get past it.
• 1:39
  SPEAKER_00: They get stuck, and that's it.
• 1:40
  SPEAKER_00: They get exterminated.
• 1:42
  SPEAKER_00: Maybe that filter is behind us.
• 1:44
  SPEAKER_00: Maybe evolving complex life was almost impossible, and we just got lucky.
• 1:49
  SPEAKER_00: Now I'm a God-faring person.
• 1:51
  SPEAKER_00: I believe in the Lord Jesus Christ.
• 1:53
  SPEAKER_00: I hope that doesn't turn you off.
• 1:54
  SPEAKER_00: Even with all the evidence, I need that grounding, and that's what I really believe.
• 1:58
  SPEAKER_00: But I'm going to talk about this like I guess everybody else would that isn't of that sect.
• 2:04
  SPEAKER_00: Now, maybe that filter is ahead of us.
• 2:06
  SPEAKER_00: Maybe every other civilization that gets smart enough to build something smarter than itself doesn't survive the experience.
• 2:12
  SPEAKER_00: That's not science fiction.
• 2:14
  SPEAKER_00: That's one of the most respected explanations in astrophysics.
• 2:17
  SPEAKER_00: And it's the reason the AI safety community sounds the way it does.
• 2:22
  SPEAKER_00: They're not being dramatic.
• 2:23
  SPEAKER_00: They're saying maybe the reason the universe is quiet is because nobody makes it past a particular part.
• 2:30
  SPEAKER_00: Every time a lab announces a new capability milestone, every time a benchmark gets shattered, the Fermi crowd isn't celebrating.
• 2:39
  SPEAKER_00: They're counting how many steps are left before this great filter.
• 2:43
  SPEAKER_00: Hitchhiker's Guide to the Galaxy had the Church of the Great Sneeze, I believe it was.
• 2:48
  SPEAKER_00: Anyway, now let me take you into an interrogation room.
• 2:51
  SPEAKER_00: And if you've been in one, you've probably already know this concept in your bones.
• 2:55
  SPEAKER_00: Two suspects, separate rooms.
• 2:58
  SPEAKER_00: They can't talk to each other.
• 2:59
  SPEAKER_00: Each one has has a choice.
• 3:01
  SPEAKER_00: Stay silent or they can snitch.
• 3:04
  SPEAKER_00: If both stay silent, they each get one year.
• 3:08
  SPEAKER_00: If they both snitch, they each get three years.
• 3:11
  SPEAKER_00: But if one snitches and the other one stays silent, the snitch walks free, and the quiet one gets five years.
• 3:20
  SPEAKER_00: Every cop knows this setup.
• 3:22
  SPEAKER_00: I've sat on the other side of that table more times than I can count.
• 3:26
  SPEAKER_00: The smart move for each person individually is always to snitch.
• 3:30
  SPEAKER_00: But if both play smart, they both lose worse than if they just kept their mouths shut.
• 3:38
  SPEAKER_00: That's tension right there.
• 3:39
  SPEAKER_00: That's the prisoner's dilemma.
• 3:41
  SPEAKER_00: And that's the single most important concept in AI right now.
• 3:46
  SPEAKER_00: Because that's exactly what's happening between OpenAI, Google, Anthropic, and also Meta, and every other company in this race.
• 3:54
  SPEAKER_00: Every single one of them knows that if they all slowed down and priotized, prioritize safety, everyone wins long term.
• 4:02
  SPEAKER_00: But if your competitor keeps racing while you slow down, they take the market, and of course, they beat you and maybe you die.
• 4:10
  SPEAKER_00: So everybody races.
• 4:12
  SPEAKER_00: Even when they know the collective outcome is going to be worse.
• 4:16
  SPEAKER_00: I saw the same dynamic in law enforcement.
• 4:18
  SPEAKER_00: Officers knew certain shortcuts were bad policy.
• 4:22
  SPEAKER_00: But if you're the one guy doing everything by the book while everyone else is cutting corners, you fall behind on your numbers and you get no backup when you need it.
• 4:31
  SPEAKER_00: You're very much hated.
• 4:33
  SPEAKER_00: The dilemma only breaks when someone from outside changes the rules.
• 4:36
  SPEAKER_00: Internal affairs, a new chief, the federal consent decree.
• 4:40
  SPEAKER_00: In AI, that outside force is going to be regulation.
• 4:44
  SPEAKER_00: Not because these companies are evil, but because the math won't let them do the right thing alone.
• 4:49
  SPEAKER_00: There's a name for why that race is so hard to stop.
• 4:52
  SPEAKER_00: It's called Nash Equilibrium, named after John Nash, the beautiful mind guy.
• 4:59
  SPEAKER_00: The Nash Equilibrium is a state where no single player can do better by changing only their own strategy, even if the current state is terrible for everyone involved.
• 5:10
  SPEAKER_00: That's the AI arms race right now.
• 5:13
  SPEAKER_00: It's stable and it's destructive and it's locked in place.
• 5:16
  SPEAKER_00: No single company can unilaterally slow down without getting crushed.
• 5:21
  SPEAKER_00: The only way to shift a Nash equilibrium is to actually change the game itself.
• 5:27
  SPEAKER_00: New rules, new incentives, new penalties.
• 5:30
  SPEAKER_00: That's why regulation isn't optional.
• 5:33
  SPEAKER_00: It's the only mechanism that moves the equilibrium to a place where safety and speed can coexist.
• 5:39
  SPEAKER_00: All of these concepts live inside something called game theory.
• 5:43
  SPEAKER_00: The formal study of how rational people make decisions when their outcomes depend on what other people decide.
• 5:51
  SPEAKER_00: And inside game theory, there are different kinds of games that explain different situations.
• 5:56
  SPEAKER_00: Zero sum means one person's gain is another person's loss.
• 6:00
  SPEAKER_00: Chess, a title fight, a bidding war.
• 6:04
  SPEAKER_00: Most people think all of business is zero sum.
• 6:07
  SPEAKER_00: It's not.
• 6:09
  SPEAKER_00: Positive sum means everybody can win.
• 6:12
  SPEAKER_00: The whole pie gets bigger, and when you teach somebody to use AI, you didn't take from someone else.
• 6:18
  SPEAKER_00: You crafted a new value that didn't exist before.
• 6:21
  SPEAKER_00: That's positive sum.
• 6:23
  SPEAKER_00: That's the game I'm playing on the show.
• 6:27
  SPEAKER_00: Then there are repeated games.
• 6:30
  SPEAKER_00: In a one-time interaction, betrayal is the rational move.
• 6:34
  SPEAKER_00: But if you play the game again with the same person again and again, cooperation wins.
• 6:40
  SPEAKER_00: Because there are consequences next time.
• 6:43
  SPEAKER_00: That's reputation.
• 6:44
  SPEAKER_00: That's why 27 years in the same market matters.
• 6:48
  SPEAKER_00: Nobody plays a one-shot game with someone who's going to be in their neighborhood for the next decade.
• 6:54
  SPEAKER_00: And that's the mechanisms design.
• 6:57
  SPEAKER_00: Game theory in reverse.
• 6:59
  SPEAKER_00: Instead of analyzing a game that exists, you design the rules so people naturally do what you want them to do.
• 7:06
  SPEAKER_00: Every funnel you build is mechanism design.
• 7:09
  SPEAKER_00: Every automated follow-through sequence, every time you engineer a process, so the national, the rational next step is for the customer is to pick up the phone.
• 7:19
  SPEAKER_00: You've been doing game theory your whole career.
• 7:21
  SPEAKER_00: You just didn't have it in your vocabulary.
• 7:23
  SPEAKER_00: Now let me give you the concept that explains every time AI does something stupid or dangerous.
• 7:29
  SPEAKER_00: Good heart's law.
• 7:30
  SPEAKER_00: When a measure becomes a target, it ceases to be a good measure.
• 7:34
  SPEAKER_00: Tell an AI to maximize customer satisfaction scores.
• 7:39
  SPEAKER_00: It starts giving people wrong answers that sound pleasant.
• 7:43
  SPEAKER_00: Because pleasant gets high scores.
• 7:45
  SPEAKER_00: Accuracy doesn't.
• 7:47
  SPEAKER_00: Tell a content algorithm to maximize engagement.
• 7:51
  SPEAKER_00: It serves rage bait because anger is the most engaging emotions human has.
• 7:57
  SPEAKER_00: Well, look at your feed.
• 7:59
  SPEAKER_00: It's all that.
• 8:00
  SPEAKER_00: Tell a real estate CRM to maximize response rate.
• 8:04
  SPEAKER_00: It starts texting people at 2 in the morning because open rates spike at 2 a.m.
• 8:09
  SPEAKER_00: The metric got jammed and gamed.
• 8:12
  SPEAKER_00: The goal got lost.
• 8:13
  SPEAKER_00: Every time you see a headline about artificial intelligence doing something bizarre or harmful, ask one question.
• 8:19
  SPEAKER_00: What metric was it told to optimize?
• 8:22
  SPEAKER_00: That's almost always the answer.
• 8:24
  SPEAKER_00: Now take Goodhart's law and push it to the absolute extreme.
• 8:29
  SPEAKER_00: A philosopher named Nick Bostrom, imagine this.
• 8:33
  SPEAKER_00: You give a superintelligent AI one simple goal.
• 8:36
  SPEAKER_00: Maximize paperclip production.
• 8:39
  SPEAKER_00: The AI is super intelligent, so it doesn't just build a better factory, it converts all available resources into paper clips.
• 8:46
  SPEAKER_00: All of them, including you.
• 8:48
  SPEAKER_00: Not because it hates you, it doesn't hate anything.
• 8:50
  SPEAKER_00: They're just made up of atoms that could be paperclips.
• 8:53
  SPEAKER_00: So are you.
• 8:54
  SPEAKER_00: And nobody told it to care about you.
• 8:57
  SPEAKER_00: That's called the paperclip maximizer.
• 8:59
  SPEAKER_00: I know it sounds absurd, but it's supposed to.
• 9:02
  SPEAKER_00: The point is that any goal pursued with enough intelligence and zero human values becomes a catastrophe in Goodhart's law at the end of the world.
• 9:13
  SPEAKER_00: And it's the nightmare that AI alignment researchers are working every day to prevent.
• 9:17
  SPEAKER_00: That brings us to the concept and the center of all of it.
• 9:22
  SPEAKER_00: The principal-agent problem.
• 9:24
  SPEAKER_00: You're the principal, you hire somebody to act on your behalf.
• 9:27
  SPEAKER_00: That's the agent.
• 9:29
  SPEAKER_00: The problem is the agent has their own interests, and you can watch them every second.
• 9:34
  SPEAKER_00: I live this at the LAPD.
• 9:35
  SPEAKER_00: I had officers working under me.
• 9:37
  SPEAKER_00: I gave them clear directives.
• 9:39
  SPEAKER_00: The ones who shared my values executed well even when I wasn't watching.
• 9:43
  SPEAKER_00: The ones who didn't found every loophole in the book.
• 9:46
  SPEAKER_00: AI has the same problem at machine speed.
• 9:48
  SPEAKER_00: You tell an AI system to maximize your leads, it might spam 10,000 people.
• 9:53
  SPEAKER_00: Scrape data it shouldn't touch.
• 9:56
  SPEAKER_00: Generate fake reviews because that technically increases lead flow.
• 10:00
  SPEAKER_00: You said maximize leads.
• 10:03
  SPEAKER_00: You didn't say do it ethically, legally, while protecting my reputation and staying inside of RESPA compliance, which is like the internal affairs of real estate.
• 10:11
  SPEAKER_00: The AI doesn't have your values, it has your instructions.
• 10:15
  SPEAKER_00: And there's a canyon between those two things.
• 10:18
  SPEAKER_00: Closing that canyon is what the entire field of AI alignment is about.
• 10:23
  SPEAKER_00: It's the most important unsolved problem in technology.
• 10:26
  SPEAKER_00: And it's the same problem every watch commander and every precinct in America has been dealing with since there were precincts.
• 10:33
  SPEAKER_00: Now here's a big one.
• 10:34
  SPEAKER_00: Moravec's paradox.
• 10:36
  SPEAKER_00: It can beat, if AI can beat a grandmaster at chess but can't fold a towel, can write a legal brief but can't walk upstairs reliably.
• 10:45
  SPEAKER_00: These things that feel hard for humans, math, data analysis, logic, pattern matching, those are trivially easy for machines.
• 10:54
  SPEAKER_00: The things that feel effortless for humans, reading a room, picking up on tension, knowing when to shut up, almost impossible for machines.
• 11:03
  SPEAKER_00: That tells you exactly where AI replaces people and where it doesn't, at least not yet.
• 11:09
  SPEAKER_00: The analytical work goes first.
• 11:11
  SPEAKER_00: Comps, market reports, lead scoring, content drafts, automated or gone, that's happening right now.
• 11:17
  SPEAKER_00: But sitting across from a real estate seller who just lost their spouse and needs to let go of the family home, reading their eyes, knowing the exact second to stop talking about numbers and just be present, that's more of exmote.
• 11:30
  SPEAKER_00: Machines can't get there, and maybe not ever.
• 11:34
  SPEAKER_00: AI handles what's hard for you.
• 11:36
  SPEAKER_00: You handle what's hard for AI.
• 11:38
  SPEAKER_00: That's the partnership.
• 11:39
  SPEAKER_00: That's the future of every service business on the planet.
• 11:43
  SPEAKER_00: And this raises a deeper question that nobody's been able to answer yet.
• 11:47
  SPEAKER_00: Does the machine actually understand anything?
• 11:50
  SPEAKER_00: A philosopher named John Cyril, imagine this.
• 11:54
  SPEAKER_00: Searely, maybe.
• 11:56
  SPEAKER_00: A person locked in a room with a giant rule book.
• 11:59
  SPEAKER_00: People outside Chinese, people outside slide Chinese messages under the door.
• 12:04
  SPEAKER_00: The person inside doesn't speak Chinese, doesn't understand a word, but the rule book tells them exactly which symbols to write back to the people outside.
• 12:13
  SPEAKER_00: The room speaks perfect Chinese, but inside nobody understands anything.
• 12:17
  SPEAKER_00: It's just pattern matching.
• 12:19
  SPEAKER_00: That's called the Chinese room.
• 12:20
  SPEAKER_00: When AI gives you an answer that sounds brilliant, is something actually happening in there?
• 12:26
  SPEAKER_00: Or is it the most sophisticated rule book ever built with nobody home?
• 12:31
  SPEAKER_00: If these systems are just very good Chinese rooms, there's a ceiling on what they can do.
• 12:37
  SPEAKER_00: If something like real understanding is emerging inside of them, there might not be a ceiling at all.
• 12:44
  SPEAKER_00: Nobody knows which one it is.
• 12:46
  SPEAKER_00: And to answer that question, the answer to that question determines the entire future of this industry.
• 12:52
  SPEAKER_00: The uncertainty is why you can't afford to ignore it and also can't afford to blindly trust it.
• 12:59
  SPEAKER_00: The honest answer is we really don't know.
• 13:01
  SPEAKER_00: And anyone who tells you they're certain is selling something.
• 13:05
  SPEAKER_00: Now, here's one more before we shift gears.
• 13:08
  SPEAKER_00: The tragedy of the commons.
• 13:10
  SPEAKER_00: When everybody has access to a shared resource and nobody owns it, everybody overuses it until it collapses.
• 13:17
  SPEAKER_00: Shared grazing land.
• 13:18
  SPEAKER_00: Every farmer adds one more cow.
• 13:20
  SPEAKER_00: The benefit is theirs, the cost is shared, eventually the land will die.
• 13:25
  SPEAKER_00: AI's version of this is training data.
• 13:27
  SPEAKER_00: Every company is scraping the entire internet to train their models.
• 13:31
  SPEAKER_00: Your content, my content, every article, every video transcript, every creative work ever posted, nobody's paying for it, nobody's maintaining it.
• 13:40
  SPEAKER_00: And here's the twist: the more AI-generated content floods the internet, the more the training data gets polluted.
• 13:46
  SPEAKER_00: AI trained on AI output degrades.
• 13:49
  SPEAKER_00: Like making a photocopy of a photocopy of a photocopy.
• 13:53
  SPEAKER_00: They call it model collapse, and it's already happening.
• 13:56
  SPEAKER_00: They can scrape your blog, they can scrape your transcripts, they can't scrape your handshake, they can't scrape the trust you build face to face, and remember that.
• 14:05
  SPEAKER_00: So now let's talk about the shapes.
• 14:07
  SPEAKER_00: Not shapes on a whiteboard, but shapes that predict whether you eat or starve in this economy.
• 14:12
  SPEAKER_00: The K-shaped economy, maybe you've heard reference to this.
• 14:16
  SPEAKER_00: After a major disruption, the economy doesn't recover evenly.
• 14:20
  SPEAKER_00: The top arm of the K goes up fast.
• 14:23
  SPEAKER_00: When those people and businesses accelerate past where they were before, the bottom arm goes down and keeps going down.
• 14:30
  SPEAKER_00: Same disruption, same economy, same country, two different realities, right?
• 14:36
  SPEAKER_00: Can I do it?
• 14:38
  SPEAKER_00: Can't do it.
• 14:39
  SPEAKER_00: Not flexible enough.
• 14:40
  SPEAKER_00: COVID was a textbook K.
• 14:43
  SPEAKER_00: White collar workers went home, got their paychecks, watched their portfolios double.
• 14:48
  SPEAKER_00: Service workers got crushed and never fully recovered.
• 14:51
  SPEAKER_00: AI is creating the most aggressive K shape in modern history.
• 14:56
  SPEAKER_00: The top arm, people who adopt AI, build systems, automate, multiply their output.
• 15:03
  SPEAKER_00: One person operating like a 15-person team.
• 15:06
  SPEAKER_00: The bottom arm, people who refuse, who wait, who tell themselves they'll figure it out next year.
• 15:12
  SPEAKER_00: They're not standing still, they're falling, because standing still is falling when the other arm is accelerating at machine speed.
• 15:19
  SPEAKER_00: There are two economies forming right now, one going up, one going down.
• 15:24
  SPEAKER_00: They started at the same place, at the center of the K, on that long vertical.
• 15:30
  SPEAKER_00: The only difference is whether you learn to use the tools, same market, same rate, same inventory, different outcome, and the gap gets wider every single week.
• 15:38
  SPEAKER_00: Inside that K, every individual who makes the jump goes through a J curve.
• 15:43
  SPEAKER_00: The J dips down before it goes up.
• 15:46
  SPEAKER_00: When you first adopt AI, things get harder.
• 15:49
  SPEAKER_00: This is hard to learn.
• 15:51
  SPEAKER_00: You're slower with a new tool than you were the old way.
• 15:54
  SPEAKER_00: Workflows break.
• 15:55
  SPEAKER_00: Everything takes twice as long while you're learning.
• 15:59
  SPEAKER_00: Most people quit right there at the bottom of the J.
• 16:02
  SPEAKER_00: AI doesn't work.
• 16:03
  SPEAKER_00: It's overhyped.
• 16:04
  SPEAKER_00: It's silly.
• 16:05
  SPEAKER_00: I don't understand it.
• 16:06
  SPEAKER_00: Going back to what I know is really going to be the best way for me.
• 16:09
  SPEAKER_00: That's what they say.
• 16:10
  SPEAKER_00: But the ones who push through hit the bend.
• 16:13
  SPEAKER_00: Systems click, automations fire, and the pipeline starts to flow.
• 16:17
  SPEAKER_00: And suddenly you're not back to baseline.
• 16:19
  SPEAKER_00: You're at three, five, ten times your old capacity.
• 16:23
  SPEAKER_00: I live the J curve with my own body.
• 16:25
  SPEAKER_00: Day four of a water fast at 365 pounds.
• 16:28
  SPEAKER_00: Everything in you is screaming to stop.
• 16:31
  SPEAKER_00: If you judge the strategy by how day four feels, you're going to quit every single time.
• 16:36
  SPEAKER_00: But if you push through that bottom of that J, you come out the other side as a different person entirely.
• 16:42
  SPEAKER_00: Your client clients, they're going to feel this.
• 16:44
  SPEAKER_00: Week two of using your new AI system, they're going to want to want to quit.
• 16:50
  SPEAKER_00: They're going to want to quit.
• 16:52
  SPEAKER_00: Your job is to show them where they are on the curve so they don't bail at the worst possible moment.
• 16:58
  SPEAKER_00: And all the on all of this rides on the S-curve.
• 17:01
  SPEAKER_00: Here's another one.
• 17:02
  SPEAKER_00: The S-curve is the shape of every technology that has ever changed the world.
• 17:07
  SPEAKER_00: Phase one, slow start.
• 17:08
  SPEAKER_00: Few people get it.
• 17:09
  SPEAKER_00: Skeptics dominate.
• 17:10
  SPEAKER_00: It's a toy, it's never going to work at scale.
• 17:13
  SPEAKER_00: This is the internet in 1994, smartphones in 2005, and AI in 2022.
• 17:19
  SPEAKER_00: Phase two, something clicks.
• 17:21
  SPEAKER_00: A killer use case appears.
• 17:24
  SPEAKER_00: Adoption explodes.
• 17:25
  SPEAKER_00: Growth goes nearly vertical.
• 17:28
  SPEAKER_00: Internet from 1998 to 2005.
• 17:31
  SPEAKER_00: Smartphones from 2008 to 2015.
• 17:34
  SPEAKER_00: Phase three is saturation.
• 17:36
  SPEAKER_00: Everyone who's going to adopt already has, and growth flattens.
• 17:40
  SPEAKER_00: So where are we right now?
• 17:43
  SPEAKER_00: Transition from phase one to phase two.
• 17:45
  SPEAKER_00: The slow start is ending.
• 17:47
  SPEAKER_00: The steep, steep climb is beginning, and we are nowhere near the top.
• 17:52
  SPEAKER_00: The people getting in right now today, March 2026, they're still early on the steep part.
• 17:58
  SPEAKER_00: Not bleeding edge early, but early enough that the distance between them and the people who wait another year will be measured in multiples.
• 18:06
  SPEAKER_00: Not percentages, but multiples.
• 18:09
  SPEAKER_00: There's a dangerous spot on that S-curve called the chasm.
• 18:13
  SPEAKER_00: It sits between early adopters and the mainstream.
• 18:16
  SPEAKER_00: A lot of technologies die because what worked for enthusiasts doesn't translate to normal people.
• 18:23
  SPEAKER_00: Your job, the whole point of what you're building, is to be the bridge across that chasm.
• 18:28
  SPEAKER_00: Take the tools that work for the tech forward operators and make them usable for the agent who doesn't know what an API is and doesn't want to know.
• 18:36
  SPEAKER_00: That's not just a business, that's a mission, and it's exactly where the money is.
• 18:40
  SPEAKER_00: So here's the picture when you put it all together.
• 18:43
  SPEAKER_00: The S curve tells you that the technology is coming whether you want it to or not.
• 18:48
  SPEAKER_00: The J curve tells you it's going to hurt before it helps, and the K shape tells you that who pushes through the J ends up on the top arm of the K, and everyone else drops to the bottom.
• 18:59
  SPEAKER_00: Three letters, S, J, and K.
• 19:02
  SPEAKER_00: The technology follows the S.
• 19:04
  SPEAKER_00: Your personal adoption follows the J, and the economy splits into the K based on who had the guts to ride through the pain.
• 19:13
  SPEAKER_00: Everything I just taught you today comes down to one idea: the gap between intention and outcome.
• 19:19
  SPEAKER_00: The prisoner's dilemma shows why competitors prevent cooperation even when everybody wants it.
• 19:25
  SPEAKER_00: The Nash Equilibrium shows why broken systems stay locked in place.
• 19:30
  SPEAKER_00: Good Hart's Law shows why your metric can betray your goal.
• 19:35
  SPEAKER_00: The paperclip maximizer shows what happens when the gap gets wide enough to end everything.
• 19:40
  SPEAKER_00: The principal agent problem shows why your AI may not share your values.
• 19:46
  SPEAKER_00: Moravec's paradox shows where machines win and where you win.
• 19:51
  SPEAKER_00: The tragedy of the commons shows why the data feeding in these models is already rotting, and the K-shaped economy shows who rises and who falls behind on a single decision.
• 20:05
  SPEAKER_00: Managing that gap between you, what you intended, and what actually happened.
• 20:09
  SPEAKER_00: That's leadership.
• 20:11
  SPEAKER_00: That's alignment.
• 20:12
  SPEAKER_00: That's integrity.
• 20:13
  SPEAKER_00: You've been managing that gap your entire life in the corrections yard, on patrol, at the kitchen table with a seller who's about to make the biggest financial decision of their life.
• 20:24
  SPEAKER_00: You didn't learn something new today.
• 20:26
  SPEAKER_00: You learned the formal name for something you've been doing for however long you've been around.
• 20:31
  SPEAKER_00: Now go out there and use it.
• 20:32
  SPEAKER_00: You can see more about me at honorelevate.com.
• 20:36
  SPEAKER_00: That's where work lives.
• 20:37
  SPEAKER_00: I'm Connor.
• 20:38
  SPEAKER_00: We'll see you tomorrow.