Podcasts about Expected value

In this episode, we explore what it means to invest in a non-ergodic world—where time, not averages, determines outcomes. We unpack concepts like volatility drag, ensemble vs. time averages, and the implications for portfolio strategy, while also reflecting on how AI and zero-click search are reshaping business and investor behavior.Topics covered include:What is ergodicity and why it mattersHow path dependency and emerging phenomena disrupt the long-termHow podcasting and blogging has changedWhat is the future of Money for the Rest of UsEpisode SponsorsNetSuite LinkedIn Jobs – Use this link to post your job for free on LinkedIn JobsInsiders Guide Email NewsletterGet our free Investors' Checklist when you sign up for the free Money for the Rest of Us email newsletterOur Premium ProductsAsset CampMoney for the Rest of Us PlusShow NotesWayback Machine: jdstein.comProbabilities and Payoffs: The Practicalities and Psychology of Expected Value by Michael J. Mauboussin and Dan Callahan, CFA—Morgan StanleyThe Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb—Penguin Random HouseThe 60% Problem — How AI Search Is Draining Your Traffic by Tor Constantino, MBA—ForbesHollywood Is Cranking Out Original Movies. Audiences Aren't Showing Up. by Ben Fritz—The Wall Street JournalHow Late Night TV Is Downsizing by Alex Weprin and Rick Porter—The Hollywood Reporter‘Severance' Surpasses ‘Ted Lasso' To Become Apple TV+'s Most Watched Series With Season 2 Launch by Nellie Andreeva—DeadlineList of most watched television broadcasts in the United States—WikipediaTao te Ching by Lao Tzu (Author), Marc Mullinax (Translator)—fortress pressWhy AI Might Not Take All Our Jobs—If We Act Quickly by Justin Lahart—The Wall Street JournalElon Musk and the Dangerous Myth of Omnigenius by Gautam Mukunda—BloombergSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

A casino offers you a game. A coin will be tossed. If it comes up heads on the first flip you win $2. If it comes up on the second flip you win $4. If it comes up on the third you win $8, the fourth you win $16, and so on. How much should you be willing to pay to play?The standard way of analysing gambling problems, ‘expected value' — in which you multiply probabilities by the value of each outcome and then sum them up — says your expected earnings are infinite. You have a 50% chance of winning $2, for '0.5 * $2 = $1' in expected earnings. A 25% chance of winning $4, for '0.25 * $4 = $1' in expected earnings, and on and on. A never-ending series of $1s added together comes to infinity. And that's despite the fact that you know with certainty you can only ever win a finite amount!Today's guest — philosopher Alan Hájek of the Australian National University — thinks of much of philosophy as “the demolition of common sense followed by damage control” and is an expert on paradoxes related to probability and decision-making rules like “maximise expected value.”Rebroadcast: this episode was originally released in October 2022.Links to learn more, highlights, and full transcript.The problem described above, known as the St. Petersburg paradox, has been a staple of the field since the 18th century, with many proposed solutions. In the interview, Alan explains how very natural attempts to resolve the paradox — such as factoring in the low likelihood that the casino can pay out very large sums, or the fact that money becomes less and less valuable the more of it you already have — fail to work as hoped.We might reject the setup as a hypothetical that could never exist in the real world, and therefore of mere intellectual curiosity. But Alan doesn't find that objection persuasive. If expected value fails in extreme cases, that should make us worry that something could be rotten at the heart of the standard procedure we use to make decisions in government, business, and nonprofits.These issues regularly show up in 80,000 Hours' efforts to try to find the best ways to improve the world, as the best approach will arguably involve long-shot attempts to do very large amounts of good.Consider which is better: saving one life for sure, or three lives with 50% probability? Expected value says the second, which will probably strike you as reasonable enough. But what if we repeat this process and evaluate the chance to save nine lives with 25% probability, or 27 lives with 12.5% probability, or after 17 more iterations, 3,486,784,401 lives with a 0.00000009% chance. Expected value says this final offer is better than the others — 1,000 times better, in fact.Ultimately Alan leans towards the view that our best choice is to “bite the bullet” and stick with expected value, even with its sometimes counterintuitive implications. Where we want to do damage control, we're better off looking for ways our probability estimates might be wrong.In this conversation, originally released in October 2022, Alan and Rob explore these issues and many others:Simple rules of thumb for having philosophical insightsA key flaw that hid in Pascal's wager from the very beginningWhether we have to simply ignore infinities because they mess everything upWhat fundamentally is 'probability'?Some of the many reasons 'frequentism' doesn't work as an account of probabilityWhy the standard account of counterfactuals in philosophy is deeply flawedAnd why counterfactuals present a fatal problem for one sort of consequentialismChapters:Cold open (00:00:00)Rob's intro (00:01:05)The interview begins (00:05:28)Philosophical methodology (00:06:35)Theories of probability (00:40:58)Everyday Bayesianism (00:49:42)Frequentism (01:08:37)Ranges of probabilities (01:20:05)Implications for how to live (01:25:05)Expected value (01:30:39)The St. Petersburg paradox (01:35:21)Pascal's wager (01:53:25)Using expected value in everyday life (02:07:34)Counterfactuals (02:20:19)Most counterfactuals are false (02:56:06)Relevance to objective consequentialism (03:13:28)Alan's best conference story (03:37:18)Rob's outro (03:40:22)Producer: Keiran HarrisAudio mastering: Ben Cordell and Ryan KesslerTranscriptions: Katy Moore

Welcome back, to The Corner of Story and Game. In this episode we chat about game design philosophy with Lauren Bond, Senior Narrative Game Designer at Wizards of the Coast. We explore two fascinating lenses from Jesse Schell's The Art of Game Design: the Lens of Expected Value and the Lens of Chance. Lauren shares how these lenses influence her approach to worldbuilding, how randomness can enhance gameplay, and how to create meaningful player interactions through thoughtful design. From balancing skill and luck in RPGs to building immersive narratives in card games, this episode is a treasure trove of insights for creators and players alike.

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David Glidden (@dglid), co-founder of the Forecasting Meetup Network, provides a step-by-step how-to guide to organizing a forecasting meetup. Timestamps 1:08: Review of September forecasting meetup 2:08: Polymarket's commitment to community-building 3:03: October forecasting meetup 7:03: Interview with Glidden begins 8:29: Working with a partner 9:42: Sensitivity to rejection 12:48: Nate Silver's community of elites 14:25: Big visions 15:25: Shayne Coplan's vision 18:28: Scratch your own itch 19:52: Prediction market newsletters 21:39: Polymarket's The Oracle 22:32: How to begin 23:03: Finding a venue 26:17: Focus on n of 1 26:38: Fundraising 27:28: Manifund 32:39: Value for sponsors 37:17: Getting RSVPs 38:56: How to get involved 41:54: Expanding beyond Washington 43:26: Grassroots activism 44:46: Opponents of election betting 47:53: Why companies don't invest in grassroots activism Join us for a pre-election forecasting & prediction markets meetup/party this Tuesday! Details and RSVP for free here: https://partiful.com/e/ITHDAcznT1DppUXD2p9x Trade on Polymarket.com, the world's largest prediction market. Follow Star Spangled Gamblers on Twitter @ssgamblers

A Note from James:"Are you a member of the river or the village? That's the question we're diving into today. Nate Silver—yes, the Nate Silver from 538—joins us with Maria Konnikova, a master of poker and decision-making. Members of the 'river,' as Nate describes, are rational thinkers. They make decisions based on probabilities and data, not emotions. So, are you in the river or the village? Because today, we're talking about how to think differently about risk—whether it's betting on an election, making an investment, or even figuring out how to navigate life. Here's what you need to know."Episode Description:In this episode, James Altucher brings together two brilliant minds: Nate Silver, known for his predictive prowess, and Maria Konnikova, a renowned psychologist and poker player. The trio delves into how they make calculated decisions when the stakes are high. With examples from poker, elections, and everyday life, they discuss how we can all navigate a world full of uncertainty. What does it mean to be a rational thinker? And how can understanding probabilities make you a better decision-maker? Join them as they explore strategies for improving your risk assessment, leveraging data, and making choices that keep you in the game longer.What You'll Learn:Risk Assessment Tools: How to analyze risk effectively using concepts from poker and data science.The River vs. The Village: Are you making rational decisions, or are you just playing it safe? Find out how to challenge your instincts.Understanding Probabilities: How to apply probabilistic thinking to everyday situations, from career moves to investments.Avoiding Cognitive Traps: Learn about common mental biases that can lead to poor decisions and how to overcome them.Betting on Your Choices: Practical advice on evaluating your options to maximize the chances of success.Timestamped Chapters:[01:30] – Are You a Member of the River or the Village?[03:21] – Meet the Guests: Nate Silver and Maria Konnikova[10:09] – Maria's Journey into Poker and Game Theory[14:59] – Understanding Risk and Decision Making[27:55] – The Challenge of Trust and Information in the Digital Age[31:04] – Nate's Transition from Poker to Election Forecasting[42:37] – The Evolution of Poker Strategy[54:15] – Betting Markets and Inefficiencies[1:00:58] – Decision Making and Risk in Poker and LifeAdditional Resources:Maria Konnikova's Book: The Biggest BluffNate Silver's Newsletter: The Silver BulletinMaria Konnikova's Newsletter: The LeapNate Silver's Book: On the EdgePodcast: Risky Business with Maria Konnikova and Nate Silver ------------What do YOU think of the show? Head to JamesAltucherShow.com/listeners and fill out a short survey that will help us better tailor the podcast to our audience!Are you interested in getting direct answers from James about your question on a podcast? Go to JamesAltucherShow.com/AskAltucher and send in your questions to be answered on the air!------------Visit Notepd.com to read our idea lists & sign up to create your own!My new book, Skip the Line, is out! Make sure you get a copy wherever books are sold!Join the You Should Run for President 2.0 Facebook Group, where we discuss why you should run for President.I write about all my podcasts! Check out the full post and learn what I learned at jamesaltuchershow.com------------Thank you so much for listening! If you like this episode, please rate, review, and subscribe to “The James Altucher Show” wherever you get your podcasts: Apple PodcastsiHeart RadioSpotifyFollow me on social media:YouTubeTwitterFacebookLinkedIn

To truly understand cricket, or life for that matter, we need to learn from poker. We need to understand the concept of Expected Value. We also need to learn from economics, and understand Opportunity Cost. Welcome to Episode 19 of Everything is Everything, a weekly podcast hosted by Amit Varma and Ajay Shah. In this episode, Amit shares what he learnt about cricket from being a professional poker player and understanding economics. Amit and Ajay then apply those concepts to life itself. Never again will you be results-oriented. Never again will you be judgemental and insufferable. Welcome to the new humble you. This episode was first published on YouTube on November 3, 2023. For magnificent, detailed, juicy show notes, click here.

I read from expected value to expeditious.     "Expected Value" goes by a number of aliases.  https://en.wikipedia.org/wiki/Expected_value     The word of the episode is "expectorate".     Theme music from Tom Maslowski https://zestysol.com/     Merchandising! https://www.teepublic.com/user/spejampar     "The Dictionary - Letter A" on YouTube   "The Dictionary - Letter B" on YouTube   "The Dictionary - Letter C" on YouTube   "The Dictionary - Letter D" on YouTube   "The Dictionary - Letter E" on YouTube     Featured in a Top 10 Dictionary Podcasts list! https://blog.feedspot.com/dictionary_podcasts/     Backwards Talking on YouTube: https://www.youtube.com/playlist?list=PLmIujMwEDbgZUexyR90jaTEEVmAYcCzuq     https://linktr.ee/spejampar dictionarypod@gmail.com https://www.facebook.com/thedictionarypod/ https://www.threads.net/@dictionarypod https://twitter.com/dictionarypod https://www.instagram.com/dictionarypod/ https://www.patreon.com/spejampar https://www.tiktok.com/@spejampar 917-727-5757

Throughout this episode, our experts will discuss the intricacies of merging and acquiring businesses and the importance of the Integration Triangle, a framework we have developed to ensure successful outcomes. Host Cristina Barquero is joined by Phil Roux, a partner with 20 years of experience in M&A, and Tom Marshall, a principal in L.E.K. Consulting's Organization and Performance practice, who share their expertise in creating sustainable value for clients and driving synergy value realization. The discussion explores the criticality of taking a pragmatic stance in mergers, the elements of the Integration Triangle, potential issues if those elements are not well integrated and best practices to follow.Key points/topics covered:The critical need for a pragmatic stance in M&A to ensure value creationOverview of the Integration Triangle framework, encompassing value creation, the combined operating model and integration strategyChallenges and risks that arise when there is a lack of alignment between value creation objectives, the combined operating model and integration strategyBest practices for leveraging the Integration Triangle, including early planning, continuous refinement and comprehensive ownership of all three elementsThe expected outcomes of adopting an effective approach to integrating the elements of the Integration Triangle, such as increased value creation, broader buy-in and improved negotiation stanceConnect with our experts on LinkedIn:Phil Roux, Partner, L.E.K. Consulting: https://www.linkedin.com/in/pgdroux/Tom Marshall, Partner, L.E.K. Consulting: https://www.linkedin.com/in/tom-marshall-1078671b/Cristina Barquero, Practice Manager (O&P), L.E.K. Consulting: https://www.linkedin.com/in/cristina-barquero3108/ Visit L.E.K. Consulting at https://www.lek.com/

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: D&D.Sci: The Mad Tyrant's Pet Turtles, published by abstractapplic on March 30, 2024 on LessWrong. This is a D&D.Sci scenario: a puzzle where players are given a dataset to analyze and an objective to pursue using information from that dataset. You steel your nerves as the Mad Tyrant[1] peers at you from his throne. In theory, you have nothing to worry about: since the Ninety Degree Revolution last year, His Malevolence[2] has had his power sharply curtailed, and his bizarre and capricious behavior has shifted from homicidally vicious to merely annoying. So while everyone agrees he's still getting the hang of this whole "Constitutional Despotism"[3] thing, and while he did drag you before him in irons when he heard a Data Scientist was traveling through his territory, you're still reasonably confident you'll be leaving with all your limbs attached (probably even to the same parts of your torso). Your voice wavering only slightly, you politely inquire as to why you were summoned. He tells you that he needs help with a scientific problem: he's recently acquired several pet turtles (by picking at random from a nearby magic swamp), and wants to know how heavy each of them is, without putting his Precious Beasts[4] to the trouble of weighing them. To encourage you to bring your best, he will be penalizing you 10gp for each pound you overestimate by (An advisor with robes like noontime in summer rushes to the Tyrant's side and whispers something urgent in his ear before scuttling away.) which will be deducted from the 2000gp stipend he will of course be awarding you for undertaking this task, because compelling unpaid labor from foreign nationals is no longer the done thing. (The bright-robed advisor visibly sighs in relief.) However, he snarls with a sudden ferocity, if you dare to insult his turtles by underestimating their weight, he will have you executed (An advisor with robes like the space between stars rushes to the Tyrant's other side and whispers something urgent in his other ear before scuttling away.) that is, he'll have you maimed (The Tyrant looks briefly to the dark-robed advisor, who shakes their head sadly.) lightly tortured (Another sad head-shake.) he'll deduct 80gp (An encouraging gesture.) for each pound you underestimate by (An approving nod.) and he'll also commission an unflattering portrait of you to hang in his throne room. (The dark-robed advisor gives the Tyrant a big smile and two thumbs up.) The meeting apparently having been concluded to his satisfaction, the guards see you out. Some time, some help, some adverse reactions to ambient magic[5], and several waterlogged sets of clothes later, you have a dataset representing a random sample[6] of the other turtles in that swamp. You also convince some palace officials to give reliable testimony on some characteristics of the Tyrant's pets, though no-one is willing to provide any actual measurements[7]. What numbers will you give the Tyrant? I'll post an interactive you can use to test your choices, along with an explanation of how I generated the dataset, sometime on Monday 8th April. I'm giving you nine days, but the task shouldn't take more than an evening or two; use Excel, R, Python, Tiger Instincts, or whatever other tools you think are appropriate. Let me know in the comments if you have any questions about the scenario. If you want to investigate collaboratively and/or call your choices in advance, feel free to do so in the comments; however, please use spoiler blocks or rot13 when sharing inferences/strategies/decisions, so people intending to fly solo can look for clarifications without being spoiled. Notes: You may assume that you are wealthy and courageous enough to prioritize maximizing Expected Value, though the value you assign to providing honest estimates and to the possibility of...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: D&D.Sci: The Mad Tyrant's Pet Turtles, published by abstractapplic on March 30, 2024 on LessWrong. This is a D&D.Sci scenario: a puzzle where players are given a dataset to analyze and an objective to pursue using information from that dataset. You steel your nerves as the Mad Tyrant[1] peers at you from his throne. In theory, you have nothing to worry about: since the Ninety Degree Revolution last year, His Malevolence[2] has had his power sharply curtailed, and his bizarre and capricious behavior has shifted from homicidally vicious to merely annoying. So while everyone agrees he's still getting the hang of this whole "Constitutional Despotism"[3] thing, and while he did drag you before him in irons when he heard a Data Scientist was traveling through his territory, you're still reasonably confident you'll be leaving with all your limbs attached (probably even to the same parts of your torso). Your voice wavering only slightly, you politely inquire as to why you were summoned. He tells you that he needs help with a scientific problem: he's recently acquired several pet turtles (by picking at random from a nearby magic swamp), and wants to know how heavy each of them is, without putting his Precious Beasts[4] to the trouble of weighing them. To encourage you to bring your best, he will be penalizing you 10gp for each pound you overestimate by (An advisor with robes like noontime in summer rushes to the Tyrant's side and whispers something urgent in his ear before scuttling away.) which will be deducted from the 2000gp stipend he will of course be awarding you for undertaking this task, because compelling unpaid labor from foreign nationals is no longer the done thing. (The bright-robed advisor visibly sighs in relief.) However, he snarls with a sudden ferocity, if you dare to insult his turtles by underestimating their weight, he will have you executed (An advisor with robes like the space between stars rushes to the Tyrant's other side and whispers something urgent in his other ear before scuttling away.) that is, he'll have you maimed (The Tyrant looks briefly to the dark-robed advisor, who shakes their head sadly.) lightly tortured (Another sad head-shake.) he'll deduct 80gp (An encouraging gesture.) for each pound you underestimate by (An approving nod.) and he'll also commission an unflattering portrait of you to hang in his throne room. (The dark-robed advisor gives the Tyrant a big smile and two thumbs up.) The meeting apparently having been concluded to his satisfaction, the guards see you out. Some time, some help, some adverse reactions to ambient magic[5], and several waterlogged sets of clothes later, you have a dataset representing a random sample[6] of the other turtles in that swamp. You also convince some palace officials to give reliable testimony on some characteristics of the Tyrant's pets, though no-one is willing to provide any actual measurements[7]. What numbers will you give the Tyrant? I'll post an interactive you can use to test your choices, along with an explanation of how I generated the dataset, sometime on Monday 8th April. I'm giving you nine days, but the task shouldn't take more than an evening or two; use Excel, R, Python, Tiger Instincts, or whatever other tools you think are appropriate. Let me know in the comments if you have any questions about the scenario. If you want to investigate collaboratively and/or call your choices in advance, feel free to do so in the comments; however, please use spoiler blocks or rot13 when sharing inferences/strategies/decisions, so people intending to fly solo can look for clarifications without being spoiled. Notes: You may assume that you are wealthy and courageous enough to prioritize maximizing Expected Value, though the value you assign to providing honest estimates and to the possibility of...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Comparing Alignment to other AGI interventions: Extensions and analysis, published by Martín Soto on March 21, 2024 on The AI Alignment Forum. In the last post I presented the basic, bare-bones model, used to assess the Expected Value of different interventions, and especially those related to Cooperative AI (as distinct from value Alignment). Here I briefly discuss important enhancements, and our strategy with regards to all-things-considered estimates. I describe first an easy but meaningful addition to the details of our model (which you can also toy with in Guesstimate). Adding Evidential Cooperation in Large worlds Due to evidential considerations, our decision to forward this or that action might provide evidence about what other civilizations (or sub-groups inside a civilization similar to us) have done. So for example us forwarding a higher aC|V should give us evidence about other civilizations doing the same, and this should alter the AGI landscape. But there's a problem: we have only modelled singletons themselves (AGIs), not their predecessors (civilizations). We have, for example, the fraction FV of AGIs with our values. But what is the fraction cV of civilizations with our values? Should it be higher (due to our values being more easily evolved than trained), or lower (due to our values being an attractor in mind-space)? While a more complicated model could deal directly with these issues by explicitly modelling civilizations (and indeed this is explored in later extensions), for now we can pull a neat trick that gets us most of what we want without enlarging the ontology of the model further, nor the amount of input estimates. Assume for simplicity alignment is approximately as hard for all civilizations (both in cV and cV=1cV), so that they each have pV of aligning their AGI (just like we do). Then, pV of the civilizations in cV will increase FV, by creating an AGI with our values. And the rest 1pV will increase FV. What about cV? pV of them will increase FV. But the misalignment case is trickier, because it might be a few of their misaligned AGIs randomly have our values. Let's assume for simplicity (since FV and cV are usually small enough) that the probability with which a random misaligned (to its creators) AGI has our values is the same fraction that our values have in the universe, after all AGIs have been created: FV.[1] Then, cV(1pV)FV goes to increase FV, and cV(1pV)(1FV) goes to increase (1FV). This all defines a system of equations in which the only unknown is cV, so we can deduce its value! With this estimate, and with some guesses αV and αV for how correlated we are with civilizations with and without our values[2], and again simplistically assuming that the tractabilities of the different interventions are approximately the same for all civilizations, we can compute a good proxy for evidential effects. As an example, to our previous expression for dFC|VdaC|V we will add cVαVdpC|VdaC|V(1pV)+cVαVdpC|VdaC|V(1pV)(1FV) This is because our working on cooperativeness for misalignment provides evidence cV also do (having an effect if their AI is indeed misaligned), but it also provides evidence for cV doing so, which only affects the fraction of cooperative misaligned AIs if their AI is indeed misaligned (to their creators), and additionally it doesn't randomly land on our values. We similarly derive the expressions for all other corrections. Negative evidence In fact, there's a further complication: our taking a marginal action not only gives us evidence for other civilizations taking that action, but also for them not taking the other available actions. To see why this should be the case in our setting, notice the following. If our estimates of the intermediate variables like FV had been "against the baseline of our correlated agents not taking...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Comparing Alignment to other AGI interventions: Basic model, published by Martín Soto on March 20, 2024 on The AI Alignment Forum. Interventions that increase the probability of Aligned AGI aren't the only kind of AGI-related work that could importantly increase the Expected Value of the future. Here I present a very basic quantitative model (which you can run yourself here) to start thinking about these issues. In a follow-up post I give a brief overview of extensions and analysis. A main motivation of this enterprise is to assess whether interventions in the realm of Cooperative AI, that increase collaboration or reduce costly conflict, can seem like an optimal marginal allocation of resources. More concretely, in a utility framework, we compare Alignment interventions (aV): increasing the probability that one or more agents have our values. Cooperation interventions given alignment (aC|V): increasing the gains from trade and reducing the cost from conflict for agents with our values. Cooperation interventions given misalignment (aC|V): increasing the gains from trade and reducing the cost from conflict for agents without our values. We used a model-based approach (see here for a discussion of its benefits) paired with qualitative analysis. While these two posts don't constitute an exhaustive analysis (more exhaustive versions are less polished), feel free to reach out if you're interested in this question and want to hear more about this work. Most of this post is a replication of previous work by Hjalmar Wijk and Tristan Cook (unpublished). The basic modelling idea we're building upon is to define how different variables affect our utility, and then incrementally compute or estimate partial derivatives to assess the value of marginal work on this or that kind of intervention. Setup We model a multi-agentic situation. We classify each agent as either having (approximately) our values (V) or any other values (V). We also classify them as either cooperative (C) or non-cooperative (C).[1] These classifications are binary. We are also (for now) agnostic about what these agents represent. Indeed, this basic multi-agentic model will be applicable (with differently informed estimates) to any scenario with multiple singletons, including the following: Different AGIs (or other kinds of singletons, like AI-augmented nation-states) interacting causally on Earth Singletons arising from different planets interacting causally in the lightcone Singletons from across the multi-verse interacting acausally The variable we care about is total utility (U). As a simplifying assumption, our way to compute it will be as a weighted interpolation of two binary extremes: one in which bargaining goes (for agents with our values) as well as possible (B), and another one in which it goes as badly as possible (B). The interpolation coefficient (b) could be interpreted as "percentage of interactions that result in minimally cooperative bargaining settlements". We also consider all our interventions are on only a single one of the agents (which controls a fraction FI of total resources), which usually represents our AGI or our civilization.[2] And these interventions are coarsely grouped into alignment work (aV), cooperation work targeted at worlds with high alignment power (aC|V), and cooperation work targeted at worlds with low alignment power (aC|V). The overall structure looks like this: Full list of variables This section safely skippable. The first 4 variables model expected outcomes: UBR: Utility attained in the possible world where our bargaining goes as well as possible. UBR: Utility attained in the possible world where our bargaining goes as badly as possible. b[0,1]: Baseline (expected) success of bargaining (for agents with our values), used to interpolate between UB and UB. Can be i...

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Dorothy succumbs to peer pressure, Atlas enjoys drugs, Quinten discovers the evils of democracy, and James tries to strategize killing a monster. “Portions of the materials are the copyrights and trademarks of Paradox Interactive AB, and are used with permission. All rights reserved. For more information please visit worldofdarkness.com.”

In this week's episode, Pace and Shane discuss expected value as it relates to the world of sports betting - what it means, how the books intentionally don't tell you about it, the fact that most bets you see in advertisements have a negative expected value, and more. You'll also hear about Apple Sports, and Kenny's Vision Pro experience. If you want to join our community - use coupon code BEHINDTHELINES for a discount here:https://courses.inplaylive.com/p/plansFor some Free Sports Investing Training (from one of the world's top live sports wagering experts), click here:https://event.webinarjam.com/register...And start your Free Trial of OddsJam's Premium Betting Tools Here (15% off forever code = inplaylive15 ; 35% off 1st month code = inplaylive):https://oddsjam.com/?ref=yjjkytkIf you want to join our community - use coupon code BEHINDTHELINES for a discount here:https://courses.inplaylive.com/p/plansFor some Free Sports Investing Training (from one of the world's top live sports wagering experts), click here:https://event.webinarjam.com/register...And start your Free Trial of OddsJam's Premium Betting Tools Here (15% off forever code = inplaylive15 ; 35% off 1st month code = inplaylive):If you want to join our community - use coupon code BEHINDTHELINES for a discount here:If you want to join our community - use coupon code BEHINDTHELINES for a discount here:https://courses.inplaylive.com/p/plansFor some Free Sports Investing Training (from one of the world's top live sports wagering experts), click here: https://event.webinarjam.com/register...And start your Free Trial of OddsJam's Premium Betting Tools Here (15% off forever code = inplaylive15 ; 35% off 1st month code = inplaylive): ...

Lairdinho and psufans2 discuss how they evaluate expected value in Sorare, and how that changes with the upcoming new in-season cash competitions. Intro and outro music: My Way by NEFF

Welcome back to another thrilling episode of "Gambling with Good JuJu"! This week, the dynamic crew is joined by the one and only Golden Pants of The Risk Takers Podcast, a seasoned sports bettor with a knack for finding value in the unpredictable world of gambling.In this episode, we delve deep into the realm of +EV betting (Expected Value) with Golden Pants as he shares his expert insights on how to identify and capitalize on value bets. Whether you're a seasoned pro or just getting started, you won't want to miss the valuable tips he dishes out on building bankrolls effortlessly.Our conversation takes an exciting turn as Golden Pants sheds light on the often-overlooked golf betting market. Discover the nuances of betting on the greens, and learn how to navigate this unique landscape for potentially lucrative outcomes.As we explore the intricacies of sports betting, we touch upon the concept of evolving as a bettor. Golden Pants shares personal anecdotes and lessons learned throughout his journey, offering a glimpse into the mindset required for long-term success in the world of gambling.So, grab your favorite beverage, settle in, and join us for a lively discussion on all things sports betting. Whether you're a casual enthusiast or a seasoned gambler, this episode is sure to provide valuable insights and entertainment. Let's talk about gambling with Good JuJu!Follow along on Twitter or Instagram @goodjujubets.

In my life, I've stumbled upon 10 concepts that have changed my life for the better. While they're not directly tied to financial advisor marketing, these 10 concepts have created more success, wealth, and happiness in my life. And they will do the same for you.  In today's show, I reveal the remaining 5 life-changing concepts that every financial advisor who wants more success, wealth, and happiness should know.  And you know what?  Who couldn't use more success, wealth, and happiness?  Listen now.  Show highlights include: The weird way studying the best scams of the past 100 years might be the best financial decision you make (2:47)  Warren Buffet's #1 rule for getting stinkin', filthy rich (4:26)  The “Expected Value” marketing and sales trick that turns even the most skeptical prospect into cold, hard cash (4:46)  How having a well-defined niche lets you break all the marketing “rules” while you laugh your way to the bank (10:28)  Why knowing the 2 distinct types of happiness lets you systematically, intentionally, and purposefully increase your joy (16:26)  Go to https://TheAdvisorCoach.com/Coaching and pick up your free 90 minute download called “5 Keys to Success for Financial Advisors” when you join The James Pollard Inner Circle.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: 1/E(X) is not E(1/X), published by EdoArad on November 9, 2023 on The Effective Altruism Forum. When modeling with uncertainty we often care about the expected value of our result. In CEAs, in particular, we often try to estimate E[effectcost]. This is different from both E[costeffect]1 and E[effect]E[cost] (which are also different from each other). [1] The goal of this post is to make this clear. One way to simplify this is to assume that the cost is constant. So we only have uncertainty about the effect. We will also assume at first that the effect can only be one of two values, say either 1 QALY or 10 QALYs with equal probability. Expected Value is defined as the weighted average of all possible values, where the weights are the probabilities associated with these values. In math notation, for a random variable X, where x are all of the possible values of X.[2] For non-discrete distributions, like a normal distribution, we'll change the sum with an integral. Coming back to the example above, we seek the expected value of effect over cost. As the cost is constant, say C dollars, we only have two possible values: In this case we do have E[effectcost]=E[effect]E[cost], but as we'll soon see that's only because the cost is constant. What about E[costeffect]? which is not 1E[effectcost]=C211$QALY, a smaller amount. The point is that generally 1E[X]E[1X]. In fact, we always have 1E[X]E[1X] with equality if and only if X is constant.[3] Another common and useful example is when X is lognormally distributed with parameters μ,σ2. That means, by definition, that lnX is normally distributed with expected value and variance μ,σ2 respectively. The expected value of X itself is a slightly more complicated expression: Now the fun part: 1X is also lognormally distributed! That's because ln1X=lnX. Its parameters are μ,σ2 (why?) and so we get In fact, we see that the ratio between these values is ^ See Probability distributions of Cost-Effectiveness can be misleading for relevant discussion. There are arguably reasons to care about the two alternatives E[costeffect]1 or E[effect]E[cost] rather than E[effectcost], which are left for a future post. ^ One way to imagine this is that if we sample X many times we will observe each possible value x roughly P(X=x) of the times. So the expected value would indeed generally be approximately the average value of many independent samples. ^ Due to Jensen's Inequality. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the Fort Collins real estate investor podcast? Book a free consultation to discuss.

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the Jacksonville real estate investor podcast? Book a free consultation to discuss.

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the Las Vegas real estate investor podcast? Book a free consultation to discuss.

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the McAllen real estate investor podcast? Book a free consultation to discuss.

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the Kenosha real estate investor podcast? Book a free consultation to discuss.

In the last few years, we've seen equity explode. Property prices have been growing like a weed in a spring. And, lower mortgage interest rates mean loan paydown has been more like the Mississippi than a backyard creek. Many real estate investors who owned property during that period will be tempted to tap into that equity to invest in more properties... leverage up. But, leveraging up is not without risk. In this special class, James demonstrates how risk changes as you leverage up and much more using the concept of expected value and his new spreadsheet: Expected Value - Risk and Reward Calculator. Free Real Estate Deal Analysis Spreadsheet: Download a copy of the newest version of The World's Greatest Real Estate Deal Analysis Spreadsheet™ by going to:https://RealEstateFinancialPlanner.com/spreadsheetImprove Cash Flow: Book a consultation to improve cash flow using our proprietary 88 cash flow improving strategies.Real Estate Agent & Lender Collaborators: Interested in collaborating with us on the Denver real estate investor podcast? Book a free consultation to discuss.

Figure 1  (see full caption below)This post is a part of Rethink Priorities' Worldview Investigations Team's CURVE Sequence: "Causes and Uncertainty: Rethinking Value in Expectation." The aim of this sequence is twofold: first, to consider alternatives to expected value maximisation for cause prioritisation; second, to evaluate the claim that a commitment to expected value maximisation robustly supports the conclusion that we ought to prioritise existential risk mitigation over all else.Executive SummaryBackgroundThis report builds on the model originally introduced by Toby Ord on how to estimate the value of existential risk mitigation. The previous framework has several limitations, including:The inability to model anything requiring shorter time units than centuries, like AI timelines.A very limited range of scenarios considered. In the previous model, risk and value growth can take different forms, and each combination represents one scenarioNo explicit treatment of persistence –– how long the mitigation efforts' effects last for ––as a variable of interest.No easy way [...] ---Outline:(00:38) Executive Summary(05:26) Abridged Report(11:20) Generalised Model: Arbitrary Risk Profile(13:37) Value(19:00) Great Filters and the Time of Perils Hypothesis(21:06) Decaying Risk(21:55) Results(21:58) Convergence(25:35) The Expected Value of Mitigating Risk Visualised(31:59) Concluding Remarks(35:00) AcknowledgementsThe original text contained 24 footnotes which were omitted from this narration. --- First published: October 23rd, 2023 Source: https://forum.effectivealtruism.org/posts/S9H86osFKhfFBCday/how-bad-would-human-extinction-be --- Narrated by TYPE III AUDIO.

A thought-provoking conversation about Effective Altruism (EA) with technologist Ben Goldhaber, as we explore its intersections with utilitarianism and transaction costs. We'll try to navigate the tricky terrains of libertarianism and the more "directed" world of EA, balancing directional and destinationist solutions, and the role of strong leadership and community dynamics in maintaining this equilibrium. We'll question the limits of utility maximization as a framework and ponder over the potential dangers it could pose if unchecked. Our discussion investigates how EA, rational thinking, and global development has influenced the field of AI alignment. And my favorite new TWEJ, from @dtarias. In the first monthly edition of TAITC.Some resources:The Reddit source for the TWEJSunday Brunch, for $195, at the BreakersEconTalk: Peter SingerEconTalk: Will McCaskill and LongtermismEconTalk: Eric Hoel and the Repugnant ConclusionKevin Munger--Everything Was Rational and Nothing VibedConsequentialism: IEPEffective Altruism ForumSB-F on SB-F (New York Times)If you have questions or comments, or want to suggest a future topic, email the show at taitc.email@gmail.com ! You can follow Mike Munger on Twitter at @mungowitz

In today's episode of BB+ from One Week Season, Mike Johnson breaks down several key topics, including: Drafters $20 Contest Expected Value and ROI Positional Silos Value of Team Stacks 2022 Champ and Top-10 Review QB trends Positional point allocations Takeaways for 2023

Paul Hembekides, aka Hembo, is a Content Producer for ESPN and got his start in the Stats & Information department, working with Expected Value host Paul Carr in the ESPN research room. Currently, Hembo works on Get Up and #Greeny, Mike Greenberg's daily ESPN Radio show. He also partnered with Greenberg to co-author “Got Your Number”, a New York Times Bestseller that explores sports history through the lens of who “owns” each number in sports. In this conversation, Hembo talks about…The origin of “Got Your Number” and he and Greenberg's process for choosing the numbers.How he put together the stats and facts for each athlete.How he balances stats and words in the book.Biggest surprise when researching and writing the book.His path and how he got to his current ESPN role.What he had to learn to adapt his sports passion and knowledge to TV & Radio.A look inside a researchers mindset & how he approaches the “give me the best stat” question.Tips & advice for getting into sports research.Then, TruMedia's Sergio De La Espriella joins the show to discuss Paul's conversation with Hembo.Show LinksTo purchase “Got Your Number”, click here.Follow Hembo on Twitter: @PaulHembo.Follow @TruMediaSports on Twitter.Listen here or wherever you get your podcasts: Apple, Spotify, Google, Stitcher, TuneIn.

In this episode we talk about what EV is and what return on investment is. We also have a short day of playing cards and slot machines. --- Support this podcast: https://podcasters.spotify.com/pod/show/mw-usa/support

Replaying an episode on EVBet DFS style games using Player Props with ThriveFantasy.com and use Promo Code: SBD (100% deposit match up to $100)Want to support the show AND bet vig-free? Sign up at BettorEdge.com and use Promo Code: SBD (free $20)

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: SBF, extreme risk-taking, expected value, and effective altruism, published by vipulnaik on November 13, 2022 on The Effective Altruism Forum. NOTE: I have some indirect associations with SBF and his companies, though probably less so than many of the others who've been posting and commenting on the forum. I don't expect anything I write here to meaningfully affect how things play out in the future for me, so I don't think this creates a conflict of interest, but feel free to discount what I say. NOTE 2: I'm publishing this post without having spent the level of effort polishing and refining it that I normally try to spend. This is due to the time-sensitive nature of the subject matter and because I expect to get more value from being corrected in the comments on the post than from refining the post myself. If errors are pointed out, I will try to correct them, but may not always be able to make timely corrections, so if you're reading the post, please also check the comments to check for flaws identified by comments. The collapse of Sam Bankman-Fried (SBF) and his companies FTX and Alameda Research is the topic du jour on the Effective Altruism Forum, and there have been several posts on the Forum discussing what happened and what we can learn from it. The post FTX FAQ provides a good summary of what we know as of the time I'm writing this post. I'm also funding work on a timeline of FTX collapse (still a work in progress, but with enough coverage already to be useful if you are starting with very little knowledge). Based on information so far, fraud and deception on the part of SBF (and/or others in FTX and/or Alameda Research) likely happened and were likely key to the way things played out and the extent of damage caused. The trigger seems to be the big loan that FTX provided to Alameda Research to bail it out, using customer funds for the purpose. If FTX hadn't bailed out Alameda, it's quite likely that the spectacular death of FTX we saw (with depositors losing all their money as well) wouldn't have happened. But it's also plausible that without the loan, the situation with Alameda Research was dire enough that Alameda Research, and then FTX, would have died due to the lack of funds. Hopefully that would have been a more graceful death with less pain to depositors. That is a very important difference. Nonetheless, I suspect that by the time of the bailout, we were already at a kind of endgame. In this post, I try to step back a bit from the endgame, and even get away from the specifics of FTX and Alameda Research (that I know very little about) and in fact even get away from the specifics of SBF's business practices (where again I know very little). Rather, I talk about SBF's overall philosophy around risk and expected value, as he has articulated himself, and has been approvingly amplified by several EA websites and groups. I think the philosophy was key to the overall way things played out. And I also discuss the relationship between the philosophy and the ideas of effective altruism, both in the abstract and as specifically championed by many leaders in effective altruism (including the team at 80,000 Hours). My goal is to encourage people to reassess the philosophy and make appropriate updates. I make two claims: Claim 1: SBF engages in extreme risk-taking that is a crude approximation to the idea of expected value maximization as perceived by him. Claim 2: At least part of the motivation for SBF's risk-taking comes from ideas in effective altruism, and in particular specific points made by EA leaders including people affiliated with 80,000 Hours. While personality probably accounts for a lot of SBF's decisions, the role of EA ideas as a catalyst cannot be dismissed based on the evidence. Here are a few things I am not claiming (some of these are discussed ...

Would you rather get paid $2MM today or $100,000 a year for 30 years?! Both sound great, but there is no correct answer… It all depends on your Discount Rate! This thought experiment depicts one of the fundamental tenants of investing: The Time Value of Money Today, J Scott, shows us how to use this simple idea to gain a competitive advantage… J Scott is a 5-time best-selling BiggerPockets author who just released his incredible new book: REAL ESTATE BY THE NUMBERS! Over 47 chapters, he digs into the 47 formulas that INVESTORS NEED TO UNDERSTAND.   In today's episode, we discuss… What we each learned from our backgrounds in professional poker How to structure any deal to optimize ROI Strategies for making deals pencil in this low DSCR market I know you want to realize the EXPECTED VALUE of this incredible interview, so do not wait to invest your Valuable Time into this making Money with this content!!! Take Control, Hunter Thompson Resources mentioned in the podcast: 1. J. Scott Website Book Interested in investing in ATMs? Check out our webinar.   Please note that investing in private placement securities entails a high degree of risk, including illiquidity of the investment and loss of principal. Please refer to the subscription agreement for a discussion of risk factors. Tired of scrambling for capital?  Check out our new FREE webinar -  How to Ensure You Never Scramble for Capital Again (The 3 Capital-Raising Secrets). Click Here to register.   CFC Podcast Facebook Group

This week, we're doing things a bit differently on Expected Value. Producer Sergio De La Espriella has taken over Expected Value and conducted an interview in Spanish, as a way of expanding accessibility to data and analytics information to the Spanish-speaking public. Our Spanish-speaking guest is Cristian Perez. Cristian is coming off a four year stint with the Cincinnati Reds where he served as an Assistant Bullpen & Advances Scouting Coach. He also played college baseball at Duke University & the University of Southern California. In this conversation, Julio talks about…How he ended up getting into baseballHis earliest experience with baseball analyticsWhy forming relationships is such an important part of coachingHow much access Latin American players have to analyticsWhat can be done to make analytics more digestable to Latin American playersHis favorite moments from his playing career and his time as a MLB coachHis favorite place to eat in South FloridaShow LinksFollow Cristian on Twitter: @Cris_Perez18Follow @TruMediaSports on Twitter.Listen here or wherever you get your podcasts: Apple, Spotify, Google, Stitcher, TuneIn.

A casino offers you a game. A coin will be tossed. If it comes up heads on the first flip you win $2. If it comes up on the second flip you win $4. If it comes up on the third you win $8, the fourth you win $16, and so on. How much should you be willing to pay to play? The standard way of analysing gambling problems, ‘expected value' — in which you multiply probabilities by the value of each outcome and then sum them up — says your expected earnings are infinite. You have a 50% chance of winning $2, for '0.5 * $2 = $1' in expected earnings. A 25% chance of winning $4, for '0.25 * $4 = $1' in expected earnings, and on and on. A never-ending series of $1s added together comes to infinity. And that's despite the fact that you know with certainty you can only ever win a finite amount! Today's guest — philosopher Alan Hájek of the Australian National University — thinks of much of philosophy as “the demolition of common sense followed by damage control” and is an expert on paradoxes related to probability and decision-making rules like “maximise expected value.” Links to learn more, summary and full transcript. The problem described above, known as the St. Petersburg paradox, has been a staple of the field since the 18th century, with many proposed solutions. In the interview, Alan explains how very natural attempts to resolve the paradox — such as factoring in the low likelihood that the casino can pay out very large sums, or the fact that money becomes less and less valuable the more of it you already have — fail to work as hoped. We might reject the setup as a hypothetical that could never exist in the real world, and therefore of mere intellectual curiosity. But Alan doesn't find that objection persuasive. If expected value fails in extreme cases, that should make us worry that something could be rotten at the heart of the standard procedure we use to make decisions in government, business, and nonprofits. These issues regularly show up in 80,000 Hours' efforts to try to find the best ways to improve the world, as the best approach will arguably involve long-shot attempts to do very large amounts of good. Consider which is better: saving one life for sure, or three lives with 50% probability? Expected value says the second, which will probably strike you as reasonable enough. But what if we repeat this process and evaluate the chance to save nine lives with 25% probability, or 27 lives with 12.5% probability, or after 17 more iterations, 3,486,784,401 lives with a 0.00000009% chance. Expected value says this final offer is better than the others — 1,000 times better, in fact. Ultimately Alan leans towards the view that our best choice is to “bite the bullet” and stick with expected value, even with its sometimes counterintuitive implications. Where we want to do damage control, we're better off looking for ways our probability estimates might be wrong. In today's conversation, Alan and Rob explore these issues and many others: • Simple rules of thumb for having philosophical insights • A key flaw that hid in Pascal's wager from the very beginning • Whether we have to simply ignore infinities because they mess everything up • What fundamentally is 'probability'? • Some of the many reasons 'frequentism' doesn't work as an account of probability • Why the standard account of counterfactuals in philosophy is deeply flawed • And why counterfactuals present a fatal problem for one sort of consequentialism Get this episode by subscribing to our podcast on the world's most pressing problems and how to solve them: type ‘80,000 Hours' into your podcasting app. Producer: Keiran Harris Audio mastering: Ben Cordell and Ryan Kessler Transcriptions: Katy Moore

Read the full transcriptAre ambition and altruism compatible? How ambitious should we be if we want to do as much good in the world as possible? How should we handle expected values when the probabilities become very small and/or the values of the outcomes become very large? What's a reasonable probability of success for most entrepreneurs to aim for? Are there non-consequentialist justifications for longtermism?Habiba Islam is an advisor at 80,000 Hours where she talks to people one-on-one, helping them to pursue high impact careers. She previously served as the Senior Administrator for the Future of Humanity Institute and the Global Priorities Institute at Oxford. Before that she qualified as a barrister and worked in management consulting at PwC specialising in operations for public and third sector clients. Follow her on Twitter at @FreshMangoLassi or learn more about her work at 80,000 Hours at 80000hours.org.

Read the full transcript here. Are ambition and altruism compatible? How ambitious should we be if we want to do as much good in the world as possible? How should we handle expected values when the probabilities become very small and/or the values of the outcomes become very large? What's a reasonable probability of success for most entrepreneurs to aim for? Are there non-consequentialist justifications for longtermism?Habiba Islam is an advisor at 80,000 Hours where she talks to people one-on-one, helping them to pursue high impact careers. She previously served as the Senior Administrator for the Future of Humanity Institute and the Global Priorities Institute at Oxford. Before that she qualified as a barrister and worked in management consulting at PwC specialising in operations for public and third sector clients. Follow her on Twitter at @FreshMangoLassi or learn more about her work at 80,000 Hours at 80000hours.org. [Read more]

Are ambition and altruism compatible? How ambitious should we be if we want to do as much good in the world as possible? How should we handle expected values when the probabilities become very small and/or the values of the outcomes become very large? What's a reasonable probability of success for most entrepreneurs to aim for? Are there non-consequentialist justifications for longtermism?Habiba Islam is an advisor at 80,000 Hours where she talks to people one-on-one, helping them to pursue high impact careers. She previously served as the Senior Administrator for the Future of Humanity Institute and the Global Priorities Institute at Oxford. Before that she qualified as a barrister and worked in management consulting at PwC specialising in operations for public and third sector clients. Follow her on Twitter at @FreshMangoLassi or learn more about her work at 80,000 Hours at 80000hours.org.

In this episode I discuss expected value, actual value and variance in more detail. I also discuss my session at a casino about 4 hours from home using advantage play, card counting and advantage slots to make money. --- Support this podcast: https://podcasters.spotify.com/pod/show/mw-usa/support

This week, we're doing things a bit differently on Expected Value. Producer Sergio De La Espriella has taken over Expected Value and conducted an interview in Spanish, as a way of expanding accessibility to data and analytics information to the Spanish-speaking public. Our first Spanish-speaking guest is Julio Costa, data scientist for Fulham F.C. in the Premier League. Julio has an unorthodox background that includes studying in the United States, running his own analytics blog, and a history of coaching. In this conversation, Julio talks about…His day to day duties as a data scientist.His interaction with the players and coaching staff.How data is prioritized at Fulham vs at other places he has been.His journey to arriving at Fulham.What he learned from his time at the University of Texas at Austin.The Analysts Eye and how that impacted his career.What he looks for when watching a match.Tips for those looking to become a soccer data scientist.His soccer fandom history coming from Portugal.His favorite place to eat in London.Show LinksFollow Julio on Twitter: @juliocosta_lisb.Follow The Analyst Eye on Twitter: @theanalysteye.To check out The Analyst Eye, click here.Follow @TruMediaSports on Twitter.Listen here or wherever you get your podcasts: Apple, Spotify, Google, Stitcher, TuneIn.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Prioritisation should consider potential for ongoing evaluation alongside expected value and evidence quality, published by freedomandutility on August 13, 2022 on The Effective Altruism Forum. One argument in favour of funding deworming, despite uncertain effects, is that the expected value is high because the estimated effect size is slightly positive and the direct costs of deworming are low the quality of evidence is high (RCTs) (compared to many other initiatives which get funded by EA) I think this excludes a third key consideration in prioritising causes, which is the potential for ongoing evaluation, both in terms of quality of evaluation and timescales for evaluation. Imagine that we have 2 interventions, intervention A and intervention B. Both have the same estimated effect size where the central estimate is positive, but there's a chance the effect is negative: +0.05 (95% Confidence Interval from -0.25 to +0.35) Both have the same quality of evidence: Effect size estimated from a meta-analysis of 5 RCTs But Intervention A has marginally greater expected value because it's cheaper to implement and Intervention B would be much cheaper to evaluate through ongoing observational studies In this case, I think we should fund Intervention B because of the value of being able to course-correct and update our estimated expected value based on more cheaply accessible new evidence. If EA continues to fund deworming in the long-term, but further testing of effects via RCTs or monitoring of effects via observational studies doesn't occur, there's a risk that millions could be spent sub-optimally. I think EA should either: also fund further evaluation of deworming, or prioritise interventions with better expected value or better quality of evidence or potential for cheaper, higher quality or faster further evaluation, over deworming Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Sarah Rudd is one of the early pioneers of modern soccer analytics, being heavily involved in the evolution of soccer analytics over the last 10-15 years. Rudd recently joined Blue Crow Sports Group after spending time with Arsenal in the Premier League. Sarah is half of the “First Family” of soccer analytics, being married to Ravi Ramineni, another top soccer analytics mind who previously worked as the Director of Analytics for the Seattle Sounders. Ravi was on Expected Value a couple of years ago, making them the first wife-and-husband combo to appear on the podcast. In this conversation, Sarah talks about…Her academic background and early professional path before transitioning into soccerThe 2011 presentation that put her on the soccer analytics mapWhat she did at StatDNA (the company Arsenal bought to be their in-house analytics group)How the acceptance of analytics changed during her decade with ArsenalBridging the stereotypical gap between scouting and analyticsWorking on the private side of soccer analyticsAdvantages and disadvantages of a club doing everything in-houseHer new company Blue Crow Sport Group and what they're up toHow she and her husband Ravi watch soccer gamesWhat she's done to track her excitement level during World Cup matchesThen, TruMedia's Sergio De La Espriella joins the show to discuss Paul's conversation with Sarah.Show LinksFollow Sarah on Twitter: @srudd_ok.To check out Sarah on LinkedIn, click here.To check out Sarah's 2011 NESSIS presentation, click here.To take a look at a Guardian piece on StatDNA being bought by Arsenal, click here.To check out a NY Times article on Arsenal and soccer analytics, click here.For more on Blue Crow Sports Group, click here.For more on Blue Crow Sports Group's recent purchase of C.D. Leganes, click here.Follow @TruMediaSports on Twitter.Listen here or wherever you get your podcasts: Apple, Spotify, Google, Stitcher, TuneIn.

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-How to calculate Expected Value and why EV is so importantBet DFS style games using Player Props with ThriveFantasy.com and use Promo Code: SBD (100% deposit match up to $100)Want to support the show AND bet vig-free? Sign up at BettorEdge.com and use Promo Code: SBD (free $20)

“Whenever you say ‘I can't find ideas,' what you're really saying is, ‘the world is perfect and it needs nothing.'”-MJ DeMarco, HEx Podcast #57—There's a lot of terrible advice out there. Maybe you've noticed this the last time you were outside. People will say things like, “Just follow your passion!” or, “Money doesn't matter!” or, perhaps even worse, “Only 40 more years until retirement, and then you'll be a millionaire!”Some of the people that proffer this advice actually do want the best for you, and they're honestly trying to help. The problem is that they've never learned how money actually works, how wealth is actually created, and how entrepreneurs can solve the problems that are pervasive in society and reap a financial windfall by doing so. Our guest on the podcast today, author MJ DeMarco, has taken aim at all the bad advice out there and has consistently proven the truth of his principles in the process of building out his own businesses and helping tens of thousands of entrepreneurs achieve their financial goals - including me. He reveals the fallacy behind the idea that following your passion will pay your bills; he shows how, in some contexts, money can buy happiness, and how it can also remove some of the sources of unhappiness; and this whole thing about retirement? What people don't tell you is that in 40 years, you'll be 40 years older, and unable to enjoy your money to the degree that you would have been able to while you're young. As he says, wheelchairs, don't fit inside the trunks of Lamborghinis. But his wisdom goes deeper than that. Much deeper. Business can be an incredible source of personal fulfillment, and if you're willing to put your heart and soul (and brain and hands) into something for 10 years, you can win the financial game. You can have it when you're relatively young, and you'll never have to wonder, “What would have happened if I really went for it?”—What We Cover:How the level of access to knowledge is unprecedented right now, and how tapping into it can change the trajectory of your lifeMJ's “C-E-N-T-S” framework for coming up with high-velocity business ideas (featuring the Commandments of Control, Entry, Need, Time, and Scale)How to increase the magnitude of your contribution and accelerate your profitsThe timelessness of great books and podcastsNassim Taleb's concept of “antifragility” and how it can help prepare you for any external event that could threaten your safety and securityThe Great Rat Race Escape, MJ's newest book, a business book/novel hybrid that follows one couple's personal journey from financial slavery to financial freedom”Value skews” and how you can develop them in order to walk over your competition”Superior Unexpected Customer Service” (SUCS) and why it's so much easier today for your business to stand out”Expected Value” and why you should always aim for “Excellent” instead of just “Good”The latest redefinition of “financial freedom” and why it's just financial slavery in a different formWhy investing in your health will improve your life in every other areaWhen you should begin your child's financial education and how to avoid the mediocrity narrativePlease leave a review if you enjoy The HighExistence podcast. 

The OTM boys are back for another strategy show to talk everything you need to know about the concept of Expected Value. -What is EV? -What is the EV of the challenges? -What is the EV of the upcoming base packs? -How can I use the concepts of EV in my Top Shot decision making Website: www.otmnft.com/ Twitter: twitter.com/OwnTheMomentNFT YouTube: www.youtube.com/c/OwnTheMoment Discord Signup: bit.ly/OwnTheMomentDiscordSignup

About Lucky MaverickAbout Jonathan BalesAt one point in my life, I thought that in Pizza Hut's “Makin' it great” ad campaign, they were actually saying “Brickin' a brick.”I mean I was a toddler, but still. Brickin' a brick. I believed this for years, even when I was old enough to logically understand “brickin' a brick” doesn't make any f*****g sense.I always thought it would be funny if a big company ran a huge ad campaign with a slogan that was totally meaningless just to see how it would perform. That's what I'd do if I were in charge. “McDonald's: Ready for the lightning?” Then we'd spend millions of dollars on it, maybe changing the classic ‘M' logo to add in lightning bolts, and then I'd get fired.It didn't matter that I believed Pizza Hut's slogan was “Brickin' a brick.” I got by. Even if I believed it today, it probably wouldn't change much for me. It's okay to have beliefs that are wrong. Most thoughts—and even actions—don't matter.The majority of what you think you know is probably wrong, and most of what's right doesn't mean s**t anyway. Sometimes, though, you come across an idea that's truly impactful to your life. It might still be wrong, but at least it's useful for you, which is better than being wrong and useless I suppose.I think the value of knowledge probably grows exponentially such that most of it is basically worthless but a small percentage is overwhelmingly valuable. This has been my experience, anyway, as a few basic ideas capable of shifting my worldview have been more valuable than everything else I know combined, so I've tried to prioritize finding this rare knowledge that actually makes a difference, blocking out almost everything in search of the truly scarce stuff.With that said, I thought it might be cool to talk about the most impactful ideas that have changed my life thus far. The main criteria I used for selecting these is that each idea is something with which I at some point either disagreed or didn't even really comprehend. It's really important to get adequate sleep, but everyone knows that. These are all ideas that at some point I didn't grasp, but ones that made profound impacts to my life once I did.The Big ConceptsConvexityErrors, randomness, and “the unexpected” should help you, not harm you.If you've read my articles for more than 10 minutes, you probably know I've learned so much from Nassim Nicholas Taleb. From black swans to antifragility to being a giant dick to anyone who disagrees with you on Twitter, I'd say I owe more of my success to Taleb than anyone else I've read.The main idea that's changed my worldview is convexity, and specifically the concept of acquiring more benefits than harm from chaotic events. Whereas most people focus on improving prediction accuracy—and sometimes in areas in which that's nearly impossible—few properly focus on the payoffs, which are more easily controllable and offer a larger usable edge in terms of competition.I applied this to DFS by focusing on ownership and lineup composition instead of projection accuracy. That is, maybe this player or team that everyone thinks will do well actually will, but maybe they won't, and if they don't, how can I benefit to the greatest degree?One way to apply convexity to your life is to mimic evolution:Don't suppress chaos.Natural selection is what Taleb would term “antifragile”—the opposite of fragile—because not only is it not harmed by chaos, it benefits from it. A species can change for the better fairly quickly in evolutionary terms from a single random genetic mutation.Even natural disasters are positives for most species as a whole, assuming they're not entirely killed off, because they end up coming back stronger and more prepared than before. Humans, too, are hopefully more prepared for the next pandemic; COVID has been devastatingly brutal, but “good” and “bad” are designations that often change based on your time horizon. What's bad in a static environment can often be one of the most beneficial things when viewed long-term.“Failure saves lives. In the airline industry, every time a plane crashes the probability of the next crash is lowered by that. So these people died, but we have effectively improved the safety of the system, and nothing failed in vain.”By embracing chaos in all aspects of life, you're set up for more sustainable long-term success. That's one reason I tweeted this:Not all jobs are the same and every person is different; there's no one-size-fits-all plan for everyone. In fact, most people are probably best off in the employee role.Generally speaking, though, one of the biggest misconceptions about being a salaried employee is that it's safer than something like an independent contractor. Being a contractor isn't always a great solution—it's not feasible in some areas and takes a long time to build a customer base—but who do you think is more susceptible to a sharp change in income: someone making $70,000 a year from one employer or someone earning the same amount from eight clients in two different niches? The latter is more volatile, but the former is riskier.Evolution embraces chaos, and in exchange eventually delivers the best results. Without that volatility, there could be no progress.“Nature builds things that are antifragile. In the case of evolution, nature uses disorder to grow stronger. Occasional starvation or going to the gym also makes you stronger, because you subject your body to stressors and gain from them.”Don't deprive yourself of life's shocks; they're what allow for your personal evolution.Think long.Evolution needs time to operate. This is a characteristic of things that like chaos; they love time. The more time, the better, which runs in opposition to most things, which eventually break down over time.Many people are doing things—whether professionally or personally—that, unbeknownst to them, will not survive over time; they're eventually going to go busto, as we say in the gambling world.If we're being honest, most people can't even calculate expected value in static environments. A much smaller percentage know how to do it over time, choosing what's optimal in arenas in which the first order of business should be eliminating risk of ruin, i.e. “not dying.”Natural selection does this better than any business in the world; it's built into the system. Species maximize their chances of survival as a whole above all else. Survive, then optimize.Build systems that embrace volatility and are meant to survive and improve with time.Via negativaAddition by subtractionThis is a simple concept, which is that to improve basically anything in life, first look at what you can take away before adding anything. Unhealthy? What are some things you can remove from your diet or lifestyle before adding something like supplements? Unhappy? What can you remove from your life before taking antidepressants?The ‘via negativa' concept is related to an approach I've discussed when it comes to winning games, which is to reverse-engineer a strategy by starting with what success looks like, then working backwards by removing the paths that don't lead to winning.Think of how a sculptor creates a statue from a slab of concrete; the “truth” of the statue is already there, hidden and waiting to be realized, but only after removing that which isn't necessary.LeverageBig wins require big leverage.I used to make the majority of my money as a freelance writer. I liked it and hated it at the same time. I liked that I was in control of how much money I made (sort of), and I disliked that I was broke and forced to write all day long to get by. Still, I can write pretty quickly, so once I got rolling and had some companies paying me, it was a decent income.But in terms of making short-term money, I had no ability to apply leverage. What I mean by that was I got paid for what I produced, and that's it. I was paid for my time, which can become quite tempting if you can quickly create things of value.However, I almost always tried to write evergreen articles I thought could live for a long time. I wasn't sure why I wanted to do that; it just felt right for some reason. It was one of the best decisions I made because writing in that way was a form of leverage. That's actually the idea behind what I'm doing right now with this newsletter—building up long-term equity (in the form of trust) that can be cashed in at a later date. I'm not charging for it and I don't have immediate plans to do so, but my guess is that writing things that (hopefully) help people will always be a valuable use of my time.Traders are of course familiar with leverage, which can make smart men very rich and dumb ones very poor. The same is true outside of markets. I recently wrote about leverage in Sam Hinkie, Leverage & Dynamic Decision-Making. The key to finding real success is to figure out what works and apply leverage. Fundamental to this idea is understanding and accepting today's wealth is not created by how hard someone works.You'll have a difficult time becoming wealthy by getting paid for your time. You have to get paid for the value you provide others through your unique knowledge, multiplied by the leverage you place on it. The returns from this sort of work—amplified by the internet—are compounding. This increases the importance of logical decision-making. When the results of your decisions are non-linear, it amplifies their impact.If you consider yourself a sharp decision-maker and you have unique knowledge or skills, there's never been a better time to get rich. The theoretical bounds of the value you can extract are nearly limitless.Acquire specific knowledge or develop a unique skill. This is a form of permissionless leverage—meaning no one can stop you from acquiring it—and it's easy to unlock with the internet. You probably already have a lot of specific knowledge in areas of interest to you. The intersection of those areas is likely where you have the most unique knowledge.Apply leverage to your distinct knowledge through media or code, i.e. leverage your knowledge to create online content or software. You can use labor and money, too, but they're no longer required.Focus on “evergreen” work; put time into things that have no theoretical limit for how much they can earn and require no additional work from you—things for which the cost of replication is zero or near-zero. And “earn” can mean money, but it can also mean trust or respect or some other output that can be monetized at a later date. I'm not currently making money from this newsletter, but it's still providing leverage.In the age of near-infinite leverage, you don't get rich based on how hard you work. You get rich by having specific knowledge, creating something of value to others, and applying leverage to it.This is a great synopsis of the age of infinite leverage. Expected Value (EV)How to calculate the value of a decision over timeI talk a lot about Expected Value, which is Probability multiplied by Payoffs. It's a fairly straightforward concept with a wide array of uses, yet I don't regularly see non-gamblers making decisions in terms of EV.You don't need to make perfect EV calculations to get use out of this way of thinking. Here's the key to letting EV thinking change your life: measure decisions based on the amount of EV you can generate and not the outcome of the decision. Your job is done at the moment of the choice; what happens after that is effectively irrelevant. From the About section of Lucky Maverick:Payoffs change the name of the game. If I bet on the roll of a die and get paid only when a ‘six' comes up, it might be an awful gamble if I'm betting straight up or the bet of a lifetime if I'm getting paid, say, 10-to-1 (meaning for every $1 I bet, I get $10 when a ‘six' is rolled). The EV in the latter scenario is 16.7% x $10) + (83.3% x -$1) = 0.837, meaning if I were to make this bet 1 million times, I'd earn around 84 cents per roll for every $1 bet.The EV before and after the roll of the die is 84 cents. Most people think of the value of the roll after the fact as either +$10 or -$1. You have to avoid this trap. The value is 84 cents no matter what happens. The result doesn't change the EV. It has zero impact on the quality of your decision to make that bet.This isn't just academics. In reality, many situations—the most lucrative of life's opportunities, in my opinion—possess way more luck than people realize, meaning they're closer to a coin flip or roll of the dice than it naturally seems. As such, you see the equivalent of intense analysis of a coin's properties and how weighted it is toward heads and what the air conditions are at the time of the flip—all in an effort to improve prediction accuracy of a coin toss to 50.1%—with little regard given to the payoffs.Utilizing EV as a tool to quickly calculate payoffs is also a great way to build convexity. And once you're comfortable calculating EV, you can move to what I call “dynamic EV,” or decision-making over time. As Taleb has said, “Your grandmother viewed smoking as an activity, not an event.”Risk-taking is an activity completed repeatedly over time, not a singular event. When assessing risk and calculating dynamic EV, you should (usually) act as though you'd need to make the same decision repeatedly and let it play out millions of times.When you think in terms of EV, results don't really matter (in the short-term), which can be sort of freeing in a way.Opportunity costThink about something's value not just in terms of what is gained, but also what is lost.I order delivery food all the time. I used to order almost every single meal through GrubHub. Now I've grown up, though. So I use DoorDash. When people have questioned me in the past, I just repeatedly mentioned ‘opportunity cost' until they left me alone. Basically, this was me… The most important things to understand about opportunity cost are that 1) discussing it while referencing the value of your time is a surefire way to get people to leave you alone, and 2) it's an awesome way to justify laziness. “Oh yeah, no, I didn't complete even the most basic of life tasks today because of opportunity cost, definitely not because I'm lazy as s**t.” The math on getting delivery, for me, includes what I give up: the need to cook. A lot of people love to cook. I kind of wish I did because it seems like an awesome lifelong hobby, but I don't. I hate to cook and I hate to clean up. Ordering delivery can be expensive, but I don't need to pay for groceries (with a hidden spoilage cost that many underestimate), nor do I waste time cooking/cleaning. The delivery life ain't for everyone, but for me, it's very clearly +EV. I don't need to use my extra time to make money to justify the cost; just being able to have more free time to do something I enjoy is worth it long-term. I did this when I was broke, too; there are plenty of good lunch deals out there and you can just stock up at those times.Every decision you make to do one thing means not doing many other things, and you should have at least a surface level idea of what you're giving up with each choice. Usually, what you give up is time. To determine if something is worth your time, ask yourself what you'd need to be paid per hour to complete a task you don't enjoy. It should really be an aspirational rate—where you want to be financially rather than where you are—but let's say it's $100. Now let's say you see an item at a supermarket that costs $25 that you know is $15 at another place across town. Should you go get the cheaper one? Well, not unless you can do it in six minutes or less (assuming you don't need to go there anyway). As much as you possibly can, you should pay to get your time back; even if it's small to start and you can't always afford to put time ahead of money, this general mindset will unlock max long-term freedom.They say you always need to do things you don't want to do. Maybe, but I'd at least prefer to be able to choose my points of pain rather than having them forced upon me.Pareto principle80% of results come from 20% of causes.The Pareto principle (or 80-20 rule) is seen throughout the world in both natural and man-made systems; the top quintile of causes produce four-fifths of the effects.As a thought experiment, applying the Pareto principle to itself leads to this sort of Russian doll situation in which, to generate the greatest rewards, you should work in the tails. I wrote about this concept in How to Get Better at Anything ASAP in relation to how to learn things as quickly as possible:But why would we stop at 80/20? Why not apply the 80/20 rule to the top 20%? That's 64% of effects from just 4% of causes. And how about again? 51.2% of effects from just 0.8% of causes. And again, again, and again? Just over one-quarter of effects from over 1-in-15,000 causes.Okay, you get the idea. Regardless of the exact numbers, if most of the benefits of something come from a much smaller percentage of your efforts, as long as you can properly identify which efforts are “working,” you can acquire incredible leverage by continuing to apply the 80/20 rule—by taking your beliefs and hypotheses to their logical end, then working back from there.Basically, it's much simpler and more effective to start at logical extremes and work inward than to be general and move toward the tails. This applies to everything from starting a business to learning a new subject to finding a romantic partner.Truth filtersThere are various lenses through which to view the world—and find truth—and we should use as many as possible to assess reality.Author Scott Adams is an awesome example, for me, of why it's important not to dismiss information simply because of the source. I believe Adams is wrong about a whole lot—and he's borderline insane—but there are some insights in his book How to Fail at Almost Anything and Still Win Big that I think are outstanding.Side note: when reading, it doesn't matter how much an author is “right.” I've read lots of books that are probably highly accurate but don't really provide me with anything uniquely valuable to live my life. When reading, I'm searching for rare bits of knowledge that can help shift my worldview. In that way, the frequency of informative nuggets is far less important than the profundity of the few truly useful parts. I don't really care to acquire knowledge for the sake of it; I'm seeking scarce wisdom, in which case you have to read people who go out on a limb to be both right and non-consensus.In his book, Adams lays out six filters for truth, or how we typically go about figuring out what's fact and what's fiction—personal experience, experiences of people you know, experts, scientific studies, common sense, and pattern recognition. I'd add two more filters for truth to the list: logic/math and “what works.” No matter the exact filters proposed, the idea is there are various ways to go about determining what is true.As an example, let's broadly apply these filters to betting a sporting event. How do you know which side of game to bet? Well, you could build a model (science). You could poll smart people and take the average (wisdom of crowd, or experience of people you know). You could get information from pros (experts). You could search for historical trends that might be of use (pattern recognition). You could trust your gut (personal experience).You get the idea. There are many ways to go about searching for what is true. We should be open to using any and all of them at any given time. If my model is the only thing pointing toward playing a particular guy in DFS, my assessment of reality is probably not as likely to be accurate as if he's high in the model and other pros in my circle like the same guy and there are historical predictors of his success and my gut is telling me he's a smart high-leverage play.One of the strongest skills you can develop is this ability to cultivate different lenses and utilize specific ones as needed. Sometimes you should trust in data, but sometimes your gut and natural pattern recognition will lead to better results. Most people view the world in one or two very specific ways and can't really move outside of that way of thinking. At the very least, you should be open to the idea that other people see a fundamentally different world than you, and their experience is real and shouldn't be dismissed. Developing a cold rationality is vital to this, as it will always feel as though what you believe is right; logically, though, you should accept that not only do people see the world differently from you, but many times, their view will be more accurate (or more useful) than yours. The easiest way to come to grips with your fallibility is to look back on what you used to believe to be true that you no longer do, which I presume is a whole lot. If our past selves have been so consistently wrong, why would we think our present selves are anything more than slightly better?In previously newsletters, I've mentioned the book The 5 Love Languages. The main thesis is that there are various ways in which partners give and receive love: words of affirmation, physical touch, quality time, gifts, and acts of service. When I realized the power of recognizing my own and others' love languages (and not just in romantic relationships) as fundamentally different lenses to view the world, it was life-changing.The more lenses you can develop, the better you'll be at both assessing reality (and thus making quality decisions) and seeing others' viewpoints.Hidden rulesThe game within the game If you haven't yet read it, check out my first Lucky Maverick post How to Win Games: Find the Hidden Rules.Basically, you'll start to find success when you approach life as a game and find the “hidden” edges others are overlooking—when you begin playing a different sort of game than what your competitors realize you're playing.When you become a true long-term winner, you'll know exactly which hidden rules you're exploiting and you'll see others overlooking the real game you're playing.More Important Ideas I'd Tell My Younger SelfDownside works to motivate more than upside. If you want to improve in a certain area, create a situation in which failure leads to negative consequences.You won't know what people really think until they bet on it. You won't know what you really think until you bet on it.First find specific and unique knowledge. Then become indispensable. Then apply leverage. Once you have leverage, the most important skill to possess is good judgement.Accuracy matters the same as payoffs in theory, but much less in practice because the former is what everyone else focuses on and the latter is easier to directionally predict.You have to be okay being wrong and being thought a moron. If you're not okay with people thinking you're an idiot—sometimes because you make giant mistakes and sometimes because they're the morons not seeing what's obvious to you—you can't achieve unconventional success.Your starting point matters, but making quick choices and continually iterating matters more. Work to speed up your trial-and-error cycle.Be early. If you're first, you don't need to be that good. The easiest way to win is to limit competition, and the easiest way to limit competition is to be first.Good negotiations don't meet in the middle. Obtain things “outside” the negotiation that are more important to you than to the other party.When a measure becomes a target, it loses its quality of being a good measure (Goodhart's Law). If you want to lose 10 pounds in an effort to become healthier, focus on what leads to good health rather than setting a goal weight.Process > results short-term, results > process long-term. If after a little while you still suck at something, it's you, not variance.Almost everyone else is faking it. Overconfidence wins and wins and wins…until it doesn't. It's a house of cards. Put yourself in position to benefit when the cards topple.When you don't know something, say “I don't know.” Pretty simple, but you'll end up doing it a lot. Few actually admit when they don't know something, and it erodes others' trust in them when they feign knowledge. You can't possibly know a lot about more than a few topics, so don't pretend.Making firm decisions is important. Maintaining optionality is important. Doing both at the same time is an incredibly rare skill you should cultivate. Make decisions with conviction but be willing to change your stance at any point that it's warranted.Don't let your high-energy self write checks your low-energy self needs to cash, i.e. don't let your best self create future obligations you won't live up to. Being data-driven is incredibly important, but most high-consequence decisions are a combination of art and science. Let data inform your gut.Turn anything you want to learn into a game and solve it the same way you'd go about winning Checkers or Monopoly or poker.The most stable possible life will stem from being able to withstand and even root for chaos. Accept worst-case scenarios to become free.It's better to be sometimes wrong on your own than right with everyone else because occasionally you'll be right on your own, which is the most rewarding (and fun).The best leaders lead without anyone knowing it.Set up meritocracies. Don't submit to hierarchies and avoid interacting with people worried about status or power.Avoid ruin first, then worry about EV.Use emotions as a trigger for logic. You'll always be emotional, but recognize when and why it's happening, then jump right into rational thinking.Work for free.Short-term balance is overrated.Don't plan much and change course often. Traveling is the most effective way to foster creativity.Great writing is the most obvious sign of a clear mind. Writing isn't solely a way to communicate what you think; it's also a way to figure out and crystalize what you think.Other people see the world in a fundamentally different way than you do. Their experience is just as authentic as yours, even when it seems like you're right.What people say is irrelevant. The only thing that matters is what they do.Many of life's truths seem paradoxical, or at least counterintuitive. Tao Te Ching is one of my favorite books and it simultaneously says nothing and everything at once. When you take core truths to their logical end, even concepts like time or the ‘self' become paradoxical. Never stop searching for life's paradoxes.Luck isn't real. But some people keep getting luckier than others. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit luckymaverick.substack.com

In this episode, Trishul and Aaron provide a quick primer on common and useful statistical methods. Mean, median, mode, standard deviation, bell curves, and so on. With a normal distribution, the mean should equal the median, and the law of large numbers allows you to make inferences between a sufficiently large sample and the overall population. Unfortunately, most things don't behave as "normally" as we would like. And this is where things can get tricky. Even so, maybe Warren Buffett is just a beneficiary of the Wyatt Earp Effect, which is a great reason why you need to understand the fundamentals of statistics before you put your hard-earned money to work in the financial markets.Episode ReferencesMMS #21. Why the VIX is useless.Investing Forever - Risk Management 101Investing Forever - Intro to VolInvesting Forever - Intro to HistogramsInvesting Forever - Nothing Is PerfectThe Wyatt Earp EffectRandom VariableSample SizePopulation HeatmapsRandom Stock PickingDifference Between Mean and MedianSkewnessKurtosisWarren Buffett says Index Funds are the Best InvestmentPodcast DescriptionWelcome to The Mind Money Spectrum Podcast where your hosts Aaron Agte and Trishul Patel go beyond traditional finance questions to help you explore how to use your money to achieve the freedom you want in life. Aaron is a Financial Planner from the Bay Area, and Trishul is a Wealth Manager on the East Coast. For more information about Aaron, check out GraystoneAdvisor.com. And for more information on Trishul check out InvestingForever.com. We thank you all for listening, and stay tuned for our latest episode on our website, MindMoneySpectrum.com.

Dr. Trogdon and Brett sit down to discuss calculating the expected value of chasing your dreams. The emotional relationship that we all have with our most personal goals can be hard to navigate. Whether trying to make it as a professional athlete at the highest level, a successful artist, or skillfully climbing the corporate ladder towards your dream job, it can be hard to review your progress over time without laying out your plan at the beginning. Trog discusses examples from formal economic studies to help tailor your goal setting, progress review, and even goal reassessment while you are on your path to success. Brett also shares examples from his and his peers lives chasing their dreams and navigating second careers on the other side of the dreams. Enjoy the episode! Thanks for listening - have a great day!! **Please subscribe, rate, and leave a review to let us know what you think of the episode!**