Podcasts about thrasymachus

In this episode I look at the classic text of Western philosophy, Plato's Republic, as detailed by Constance Meinwald in her wide-ranging book Plato. I focus on the early portions of The Republic dealing with the quest for a definition of Justice, including the arguments of Glaucon and Thrasymachus.

Could the principles of musical harmony reflect the nature of the ideal state and the philosopher king? Join us as we explore the philosophical depth of Plato's Republic, where we argue against Thrasymachus's cynical views on justice and journey through the formation of a society in perfect accord with the soul's three elements. We discuss how a just life, guided by wisdom, rather than honor or appetite, is not just more profitable but vastly more fulfilling. The conversation crescendos with the intriguing ways democracy, oligarchy, and tyranny can be heard in Pythagorean scales—each political mode echoing a distinct musical chord that reveals the health of the state.We analyze the potential influence music on the guardians of Plato's Republic, and how it serves as a reminder of their responsibilities and the perils of governance. The episode examines Phrygian music and its philosophical implications, symbolizing the cyclical nature of societies. We contrast the chaotic life of a tyrant, draped in the illusion of power, with the serene existence of the philosopher king, who finds true harmony within. This discussion challenges us to reassess the pursuit of power and the intrinsic value of justice.Wrapping up the symphony, we delve into Plato's philosophy of forms and its crucial role in achieving the ideal republic. As we set the stage for Book 10's further contemplation on the place of artists, we're left to ponder the true meaning of justice and the role of art and poetry in crafting the perfect city-state. This episode is not just a reflection on ancient philosophy but a profound meditation on the essence of wisdom and virtue that continues to resonate through the ages. Tune in for a rich exploration of these timeless ideas that still capture our collective imagination.

In this episode, I recount Socrates and Thrasymachus' debate on Justice from Plato's The Republic. If you want to support me, you can do that with these links: Patreon: https://www.patreon.com/theoryandphilosophy paypal.me/theoryphilosophy Twitter: @DavidGuignion TikTok: @theoryphilosophy IG: @theory_and_philosophy

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: When is Goodhart catastrophic?, published by Drake Thomas on May 9, 2023 on The AI Alignment Forum. Thanks to Aryan Bhatt, Eric Neyman, and Vivek Hebbar for feedback. This post gets more math-heavy over time; we convey some intuitions and overall takeaways first, and then get more detailed. Read for as long as you're getting value out of things! TLDR How much should you optimize for a flawed measurement? If you model optimization as selecting for high values of your goal V plus an independent error X, then the answer ends up being very sensitive to the distribution of the error X: if it's heavy-tailed you shouldn't optimize too hard, but if it's light-tailed you can go full speed ahead. Related work Why the tails come apart by Thrasymachus discusses a sort of "weak Goodhart" effect, where extremal proxy measurements won't have extremal values of your goal (even if they're still pretty good). It implicitly looks at cases similar to a normal distribution. Scott Garrabrant's taxonomy of Goodhart's Law discusses several ways that the law can manifest. This post is about the "Regressional Goodhart" case. Scaling Laws for Reward Model Overoptimization (Gao et al., 2022) considers very similar conditioning dynamics in real-world RLHF reward models. In their Appendix A, they show a special case of this phenomenon for light-tailed error, which we'll prove a generalization of in the next post. Defining and Characterizing Reward Hacking (Skalse et al., 2022) shows that under certain conditions, leaving any terms out of a reward function makes it possible to increase expected proxy return while decreasing expected true return. How much do you believe your results? by Eric Neyman tackles very similar phenomena to the ones discussed here, particularly in section IV; in this post we're interested in characterizing that sort of behavior and when it occurs. We strongly recommend reading it first if you'd like better intuitions behind some of the math presented here - though our post was written independently, it's something of a sequel to Eric's. Motivation/intuition Goodhart's Law says When a measure becomes a target, it ceases to be a good measure. When I (Drake) first heard about Goodhart's Law, I internalized something like "if you have a goal, and you optimize for a proxy that is less than perfectly correlated with the goal, hard enough optimization for the proxy won't get you what you wanted." This was a useful frame to have in my toolbox, but it wasn't very detailed - I mostly had vague intuitions and some idealized fables from real life. Much later, I saw some objections to this frame on Goodhart that actually used math. The objection went something like: Let's try to sketch out an actual formal model here. What's the simplest setup of "two correlated measurements"? We could have a joint normal distribution over two random variables, U and V, with zero mean and positive covariance. You actually value V, but you measure a proxy U. Then we can just do the math: if I optimize really hard for U, and give you a random datapoint with U=1012 or something, how much V do you expect to get? If we look at the joint distribution of U and V, we'll see a distribution with elliptical contour lines, like so: Now, the naïve hope is that expected V as a function of observed U would go along the semi-major axis, shown in red below: But actually we'll get the blue line, passing through the points at which the ellipses are tangent to the V-axis. Importantly, though, we're still getting a line: we get linearly more value V for every additional unit of U we select for! Applying 99th percentile selection on U isn't going to be as good as 99th percentile selection on V, but it's still going to give us more V than any lower percentile selection on U. The proxy is inefficient, but it's not doomed. Late...

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: When is Goodhart catastrophic?, published by Drake Thomas on May 9, 2023 on LessWrong. Thanks to Aryan Bhatt, Eric Neyman, and Vivek Hebbar for feedback. This post gets more math-heavy over time; we convey some intuitions and overall takeaways first, and then get more detailed. Read for as long as you're getting value out of things! TLDR How much should you optimize for a flawed measurement? If you model optimization as selecting for high values of your goal V plus an independent error X, then the answer ends up being very sensitive to the distribution of the error X: if it's heavy-tailed you shouldn't optimize too hard, but if it's light-tailed you can go full speed ahead. Related work Why the tails come apart by Thrasymachus discusses a sort of "weak Goodhart" effect, where extremal proxy measurements won't have extremal values of your goal (even if they're still pretty good). It implicitly looks at cases similar to a normal distribution. Scott Garrabrant's taxonomy of Goodhart's Law discusses several ways that the law can manifest. This post is about the "Regressional Goodhart" case. Scaling Laws for Reward Model Overoptimization (Gao et al., 2022) considers very similar conditioning dynamics in real-world RLHF reward models. In their Appendix A, they show a special case of this phenomenon for light-tailed error, which we'll prove a generalization of in the next post. Defining and Characterizing Reward Hacking (Skalse et al., 2022) shows that under certain conditions, leaving any terms out of a reward function makes it possible to increase expected proxy return while decreasing expected true return. How much do you believe your results? by Eric Neyman tackles very similar phenomena to the ones discussed here, particularly in section IV; in this post we're interested in characterizing that sort of behavior and when it occurs. We strongly recommend reading it first if you'd like better intuitions behind some of the math presented here - though our post was written independently, it's something of a sequel to Eric's. Motivation/intuition Goodhart's Law says When a measure becomes a target, it ceases to be a good measure. When I (Drake) first heard about Goodhart's Law, I internalized something like "if you have a goal, and you optimize for a proxy that is less than perfectly correlated with the goal, hard enough optimization for the proxy won't get you what you wanted." This was a useful frame to have in my toolbox, but it wasn't very detailed - I mostly had vague intuitions and some idealized fables from real life. Much later, I saw some objections to this frame on Goodhart that actually used math. The objection went something like: Let's try to sketch out an actual formal model here. What's the simplest setup of "two correlated measurements"? We could have a joint normal distribution over two random variables, U and V, with zero mean and positive covariance. You actually value V, but you measure a proxy U. Then we can just do the math: if I optimize really hard for U, and give you a random datapoint with U=1012 or something, how much V do you expect to get? If we look at the joint distribution of U and V, we'll see a distribution with elliptical contour lines, like so: Now, the naïve hope is that expected V as a function of observed U would go along the semi-major axis, shown in red below: But actually we'll get the blue line, passing through the points at which the ellipses are tangent to the V-axis. Importantly, though, we're still getting a line: we get linearly more value V for every additional unit of U we select for! Applying 99th percentile selection on U isn't going to be as good as 99th percentile selection on V, but it's still going to give us more V than any lower percentile selection on U. The proxy is inefficient, but it's not doomed. Lately, however, ...

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: When is Goodhart catastrophic?, published by Drake Thomas on May 9, 2023 on LessWrong. Thanks to Aryan Bhatt, Eric Neyman, and Vivek Hebbar for feedback. This post gets more math-heavy over time; we convey some intuitions and overall takeaways first, and then get more detailed. Read for as long as you're getting value out of things! TLDR How much should you optimize for a flawed measurement? If you model optimization as selecting for high values of your goal V plus an independent error X, then the answer ends up being very sensitive to the distribution of the error X: if it's heavy-tailed you shouldn't optimize too hard, but if it's light-tailed you can go full speed ahead. Related work Why the tails come apart by Thrasymachus discusses a sort of "weak Goodhart" effect, where extremal proxy measurements won't have extremal values of your goal (even if they're still pretty good). It implicitly looks at cases similar to a normal distribution. Scott Garrabrant's taxonomy of Goodhart's Law discusses several ways that the law can manifest. This post is about the "Regressional Goodhart" case. Scaling Laws for Reward Model Overoptimization (Gao et al., 2022) considers very similar conditioning dynamics in real-world RLHF reward models. In their Appendix A, they show a special case of this phenomenon for light-tailed error, which we'll prove a generalization of in the next post. Defining and Characterizing Reward Hacking (Skalse et al., 2022) shows that under certain conditions, leaving any terms out of a reward function makes it possible to increase expected proxy return while decreasing expected true return. How much do you believe your results? by Eric Neyman tackles very similar phenomena to the ones discussed here, particularly in section IV; in this post we're interested in characterizing that sort of behavior and when it occurs. We strongly recommend reading it first if you'd like better intuitions behind some of the math presented here - though our post was written independently, it's something of a sequel to Eric's. Motivation/intuition Goodhart's Law says When a measure becomes a target, it ceases to be a good measure. When I (Drake) first heard about Goodhart's Law, I internalized something like "if you have a goal, and you optimize for a proxy that is less than perfectly correlated with the goal, hard enough optimization for the proxy won't get you what you wanted." This was a useful frame to have in my toolbox, but it wasn't very detailed - I mostly had vague intuitions and some idealized fables from real life. Much later, I saw some objections to this frame on Goodhart that actually used math. The objection went something like: Let's try to sketch out an actual formal model here. What's the simplest setup of "two correlated measurements"? We could have a joint normal distribution over two random variables, U and V, with zero mean and positive covariance. You actually value V, but you measure a proxy U. Then we can just do the math: if I optimize really hard for U, and give you a random datapoint with U=1012 or something, how much V do you expect to get? If we look at the joint distribution of U and V, we'll see a distribution with elliptical contour lines, like so: Now, the naïve hope is that expected V as a function of observed U would go along the semi-major axis, shown in red below: But actually we'll get the blue line, passing through the points at which the ellipses are tangent to the V-axis. Importantly, though, we're still getting a line: we get linearly more value V for every additional unit of U we select for! Applying 99th percentile selection on U isn't going to be as good as 99th percentile selection on V, but it's still going to give us more V than any lower percentile selection on U. The proxy is inefficient, but it's not doomed. Lately, however, ...

This is a free preview of a paid episode. To hear more, visit andrewsullivan.substack.comSusan is a philosopher and writer focusing on the Enlightenment, moral philosophy, metaphysics and politics. She was professor of philosophy at Yale and Tel Aviv University, and in 2000 assumed her current position as director of the Einstein Forum in Potsdam. She's the author of nine books, including Evil in Modern Thought, Moral Clarity and Learning from the Germans. Her new book is Left Is Not Woke. We hit it off from the get-go.For two clips of our convo — on why being an “ally” is misguided, and the Nazi philosopher who influenced woke thought — pop over to our YouTube page. Other topics: the tension between universalism and tribalism in her Jewish upbringing in Atlanta; her mom's work desegregating schools amid night calls from the Klan; Susan joining a commie commune; making it to Harvard as a high-school dropout; the legacy of Kant; Montaigne on how the West could learn from other cultures; the views of Voltaire, Rousseau, Wittgenstein and Rawls; the dialogue between Socrates and Thrasymachus on justice and power; the cynical faux-sophistication of postmodernists; the impact of Foucault and Carl Schmitt on wokeness; truth and reason as mere instruments of power; the woke impulse to deny progress; evolutionary psychology; Jesus rejecting tribalism; the Enlightenment rebuking clerical authority but respecting religion; Anthony Appiah and universalism within African and Indian cultures; anti-colonialism; the Iraq War and the hypocrisy of a liberal democracy using torture; the transition from Obama to Trump; and the Afropessimism of Ta-Nehisi Coates and others.Browse the Dishcast archive for another discussion you might enjoy (the first 102 episodes are free in their entirety). Upcoming guests include Mark Lilla on liberalism, Nigel Biggar defending colonialism, Tabia Lee on her firing as a DEI director, Chris Stirewalt on Fox News, Ben Smith on going viral, and John Oberg on veganism.

Everyone's favorite philosopher who gives no specifics on how to achieve his utopia: Karl Marx! And Plato, too! In this episode, we look at two of Plato's political (or antipolitical) dialogues: Gorgias and Republic. We look at the varying definitions of justice, whether it's just to act according to your power, and how Plato's ideal society was structured. We look at all this with a critical eye, but we do appreciate many of the opinions on justice and the faults with lying politicians.  Follow us on Twitter! @UlmtdOpinions

What is Justice?  What do we owe to each other? The theme of justice is core issue of all human societies and pervades myth and philosophy.  Plato's Republic and Gorgias are reflections on justice and the right ordering of the soul and society. So is Aristotle's Politics.  The Hebrew Bible, the Tao Te Ching, the Analects of Confucius, the writings of Buddhism, and the Stoics all contain reflections on justice.  C.S. Lewis notes in his appendix to the Abolition of Man that in every land and every culture there is a “Tao,” a way of being in the world that affirms what is good and condemns what is bad.  Despite the universal hungering for justice, injustice seems to be the way of man.  Against Plato stands Thrasymachus and Callicles, the tyrant and the sophist who want to reduce justice to power.   In this episode I speak with Marcel Gaurnizo about the nature of justice. We discuss the definition of justice — giving each what is due.  We discuss how justice is not simply a social or political condition but a human virtue that requires a consistent act of the will. Marcel explains how the shift from metaphysical view of justice to political justice opens the door to the dictatorship and tyranny of the majority or injustice through procedural methods. We discuss the Plato's story of the ring of Gyges which makes the wearer invisible just like Bilbo and Frodo in the Lord of the Rings — and thus free from any punishment. Would we have strength to do the right thing even if we would never get in trouble for doing what is wrong? As Marcel notes, the ring of Gyges is all around us.  There are many things that are legal—that we will not be punished for — but which are evil and unjust. Marcel also walks us through different species of justice — commutative (exchange) and distributive.  He explains how many of the errors we make about legal, economic, and social justice —both on the right and the left — often come from a misunderstanding of the difference between commutative and distributive justice, e.g. we apply commutative justice to the family. Marcel argues that one of the problems we have today on the right and left is that we are not formed in correct thinking about justice is that In this conversation there are some detailed discussions, but in a time where there the word “justice” is used so frequently and where there is so much confusion, I think it is very worthwhile. Some of the themes and thinkers we discuss include:  Justice as a virtue Economic justice of exchange Social Justice Family vs. Market Gary Becker and the error of applying commutative justice to the family John Rawls and the shift to political and procedural justice Socialist view of justice Marxism Philosophical Materialism Aristotle's Politics  Plato's Republic  St. Thomas Aquinas Treatise on Justice  Friedrich Nietzsche Monasteries Catholic Social Teaching John Rawls and the transformation of justice into political justice. Relativism Post-Modernism Human Nature — what kind of thing we are Individualism, the market, and the state Poverty and Distribution Biography Marcel Gaurnizo is a philosopher and theologian. He spent many years in Europe and has founded a number of institutions including an academy in Austria to teach philosophy, ethics, and politics, and was president of Aid to the Church in Russia after the fall of the Soviet Union. Resources Whittaker Chambers: Big Sister is Watching You The Second Coming, Poem by William Butler Yeats

Hello good people, In todays episode I cover Socrates in the first book of Plato's Republic, in which he goes through tremendous trials and tribulations in order to define 'justice.' I hope you lot enjoy this weeks episode. If you did, be sure to join me using the links below. (oh and download audible using this link) Audible: https://www.audible.com/ Join us: The Website: https://www.podpage.com/a-social-experiment/ Youtube: https://www.youtube.com/channel/UCkw9k2H2CDhDxCxSrJjAfUw Instagram: https://www.instagram.com/asocialexperiment._/ Spotify: https://open.spotify.com/show/13wYI8AEohRihpR9WrBLWx?si=595e5e625c26479e Apple: https://podcasts.apple.com/us/podcast/a-social-experiment/id1612177000 Amazon Music: https://music.amazon.com/podcasts/6560a7b2-98f3-49db-b603-73d969d2864c/a-social-experiment Audible: https://www.audible.com/pd/A-Social-Experiment-Podcast/B09W7PFBG8 --- Send in a voice message: https://anchor.fm/asocialexperiment/message Support this podcast: https://anchor.fm/asocialexperiment/support

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: Why the tails come apart, published by Thrasymachus on LessWrong. [I'm unsure how much this rehashes things 'everyone knows already' - if old hat, feel free to downvote into oblivion. My other motivation for the cross-post is the hope it might catch the interest of someone with a stronger mathematical background who could make this line of argument more robust] [Edit 2014/11/14: mainly adjustments and rewording in light of the many helpful comments below (thanks!). I've also added a geometric explanation.] Many outcomes of interest have pretty good predictors. It seems that height correlates to performance in basketball (the average height in the NBA is around 6'7"). Faster serves in tennis improve one's likelihood of winning. IQ scores are known to predict a slew of factors, from income, to chance of being imprisoned, to lifespan. What's interesting is what happens to these relationships 'out on the tail': extreme outliers of a given predictor are seldom similarly extreme outliers on the outcome it predicts, and vice versa. Although 6'7" is very tall, it lies within a couple of standard deviations of the median US adult male height - there are many thousands of US men taller than the average NBA player, yet are not in the NBA. Although elite tennis players have very fast serves, if you look at the players serving the fastest serves ever recorded, they aren't the very best players of their time. It is harder to look at the IQ case due to test ceilings, but again there seems to be some divergence near the top: the very highest earners tend to be very smart, but their intelligence is not in step with their income (their cognitive ability is around +3 to +4 SD above the mean, yet their wealth is much higher than this) (1). The trend seems to be that even when two factors are correlated, their tails diverge: the fastest servers are good tennis players, but not the very best (and the very best players serve fast, but not the very fastest); the very richest tend to be smart, but not the very smartest (and vice versa). Why? Too much of a good thing? One candidate explanation would be that more isn't always better, and the correlations one gets looking at the whole population doesn't capture a reversal at the right tail. Maybe being taller at basketball is good up to a point, but being really tall leads to greater costs in terms of things like agility. Maybe although having a faster serve is better all things being equal, but focusing too heavily on one's serve counterproductively neglects other areas of one's game. Maybe a high IQ is good for earning money, but a stratospherically high IQ has an increased risk of productivity-reducing mental illness. Or something along those lines. I would guess that these sorts of 'hidden trade-offs' are common. But, the 'divergence of tails' seems pretty ubiquitous (the tallest aren't the heaviest, the smartest parents don't have the smartest children, the fastest runners aren't the best footballers, etc. etc.), and it would be weird if there was always a 'too much of a good thing' story to be told for all of these associations. I think there is a more general explanation. The simple graphical explanation [Inspired by this essay from Grady Towers] Suppose you make a scatter plot of two correlated variables. Here's one I grabbed off google, comparing the speed of a ball out of a baseball pitchers hand compared to its speed crossing crossing the plate: It is unsurprising to see these are correlated (I'd guess the R-square is > 0.8). But if one looks at the extreme end of the graph, the very fastest balls out of the hand aren't the very fastest balls crossing the plate, and vice versa. This feature is general. Look at this data (again convenience sampled from googling 'scatter plot') of this: Or this: Or this: Given a correlation, the envelo...

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: The Tails Coming Apart As Metaphor For Life , published by Scott Alexander on the AI Alignment Forum. [Epistemic status: Pretty good, but I make no claim this is original] A neglected gem from Less Wrong: Why The Tails Come Apart, by commenter Thrasymachus. It explains why even when two variables are strongly correlated, the most extreme value of one will rarely be the most extreme value of the other. Take these graphs of grip strength vs. arm strength and reading score vs. writing score: In a pinch, the second graph can also serve as a rough map of Afghanistan Grip strength is strongly correlated with arm strength. But the person with the strongest arm doesn't have the strongest grip. He's up there, but a couple of people clearly beat him. Reading and writing scores are even less correlated, and some of the people with the best reading scores aren't even close to being best at writing. Thrasymachus gives an intuitive geometric explanation of why this should be; I can't beat it, so I'll just copy it outright: I thought about this last week when I read this article on happiness research. The summary: if you ask people to “value their lives today on a 0 to 10 scale, with the worst possible life as a 0 and the best possible life as a 10”, you will find that Scandinavian countries are the happiest in the world. But if you ask people “how much positive emotion do you experience?”, you will find that Latin American countries are the happiest in the world. If you check where people are the least depressed, you will find Australia starts looking very good. And if you ask “how meaningful would you rate your life?” you find that African countries are the happiest in the world. It's tempting to completely dismiss “happiness” as a concept at all, but that's not right either. Who's happier: a millionaire with a loving family who lives in a beautiful mansion in the forest and spends all his time hiking and surfing and playing with his kids? Or a prisoner in a maximum security jail with chronic pain? If we can all agree on the millionaire – and who wouldn't? – happiness has to at least sort of be a real concept. The solution is to understand words as hidden inferences – they refer to a multidimensional correlation rather than to a single cohesive property. So for example, we have the word “strength”, which combines grip strength and arm strength (and many other things). These variables really are heavily correlated (see the graph above), so it's almost always worthwhile to just refer to people as being strong or weak. I can say “Mike Tyson is stronger than an 80 year old woman”, and this is better than having to say “Mike Tyson has higher grip strength, arm strength, leg strength, torso strength, and ten other different kinds of strength than an 80 year old woman.” This is necessary to communicate anything at all and given how nicely all forms of strength correlate there's no reason not to do it. But the tails still come apart. If we ask whether Mike Tyson is stronger than some other very impressive strong person, the answer might very well be “He has better arm strength, but worse grip strength”. Happiness must be the same way. It's an amalgam between a bunch of correlated properties like your subjective well-being at any given moment, and the amount of positive emotions you feel, and how meaningful your life is, et cetera. And each of those correlated is also an amalgam, and so on to infinity. And crucially, it's not an amalgam in the sense of “add subjective well-being, amount of positive emotions, and meaningfulness and divide by three”. It's an unprincipled conflation of these that just denies they're different at all. Think of the way children learn what happiness is. I don't actually know how children learn things, but I imagine something like this. The child sees the millio...

Eddie and Aneesh discuss the "might makes right" argument of Thrasymachus.

In the second part of Republic, Book 1, Socrates agrees with Thrasymachus that in the precise sense of the word "ruler," a ruler never makes mistakes. But he points out that in the precise sense, a ruler also rules for the benefit of others not for his own benefit. The argument shifts to the question whether it is more profitable to be unjust than just, with Thrasymachus defending the former and Socrates arguing for the latter. Although Socrates appears to win the argument, Thrasymachus leaves the room and Socrates admits that he knows no more about the concept of justice than he did at the beginning of the discussion.

It is in Book 1 of Plato's dialogue Republic that political philosophy begins. The character Socrates begins by asking a pivotal question "What is justice?" He receives and disposes of two weak definitions but is quickly confronted by Thrasymachus who ties the concept of justice to whatever is to the advantage of the ruler. Socrates attempts to refute this definition but believes that his refutation is weak. He says, at the end of the chapter, that "the result of the discussion, as far as I am concerned, is that I know nothing [about justice]."

Plato's Republic is arguably THE foundational text of the Western tradition in philosophy. Book One introduces the theme, Justice, in the form of a Socratic dialogue attempting to define it, as well as a consideration of its practical effects for human life, both individually and corporately. Note Plato's (in the form of Socrates) profound opposition to the ethical relativism of Thrasymachus, a Sophist, who claims that power and oppression always go hand-in-hand, as many claim today. This is the fourth installment of Book I. Enjoy! If you'd like to support us, donate through Paypal at Romanschapter5@comcast.net https://www.youtube.com/c/TheChristianAtheist/featured https://www.facebook.com/JnJWiseWords https://wisewordsforyouroccasion.wordpress.com   #plato, #socrates, #platoandsocrates, #socratesandplato, #republik, #republic, #westerntradition, #philosophy, #rationality, #drjohndwise, #philosopher, #philosophical, #philosophicalauthor #westerntraditionphilosophy, #traditionalphilosophy, #foundations, #foundationalphilosopher, #foundationaltext, #platosrepublic, #philosophy, #dialogue, #dialogues, #greekphilosophy, #ancientgreekphilosophy, #athens, #platonicdialogue, #platonic, #ancientgreeks, #ancientgreece,#hellen, #hellenistic, #athenian, #atheniantradition, #greekcivilization, #greeksociety, #greekhistory

Plato's Republic is arguably THE foundational text of the Western tradition in philosophy. Book One introduces the theme, Justice, in the form of a Socratic dialogue attempting to define it, as well as a consideration of its practical effects for human life, both individually and corporately. Note Plato's (in the form of Socrates) profound opposition to the ethical relativism of Thrasymachus, a Sophist, who claims that power and oppression always go hand-in-hand, as many claim today. This is the third installment of Book I. Enjoy! If you'd like to support us, donate through Paypal at Romanschapter5@comcast.net https://www.youtube.com/c/TheChristianAtheist/featured https://www.facebook.com/JnJWiseWords https://wisewordsforyouroccasion.wordpress.com   #plato, #socrates, #platoandsocrates, #socratesandplato, #republik, #republic, #westerntradition, #philosophy, #rationality, #drjohndwise, #philosopher, #philosophical, #philosophicalauthor #westerntraditionphilosophy, #traditionalphilosophy, #foundations, #foundationalphilosopher, #foundationaltext, #platosrepublic, #philosophy, #dialogue, #dialogues, #greekphilosophy, #ancientgreekphilosophy, #athens, #platonicdialogue, #platonic, #ancientgreeks, #ancientgreece,#hellen, #hellenistic, #athenian, #atheniantradition, #greekcivilization, #greeksociety, #greekhistory

Plato's Republic is arguably THE foundational text of the Western tradition in philosophy. Book One introduces the theme, Justice, in the form of a Socratic dialogue attempting to define it, as well as a consideration of its practical effects for human life, both individually and corporately. Note Plato's (in the form of Socrates) profound opposition to the ethical relativism of Thrasymachus, a Sophist, who claims that power and oppression always go hand-in-hand, as many claim today. This is the second installment of Book I. Enjoy! If you'd like to support us, donate through Paypal at Romanschapter5@comcast.net https://www.youtube.com/c/TheChristianAtheist/featured https://www.facebook.com/JnJWiseWords https://wisewordsforyouroccasion.wordpress.com   #plato, #socrates, #platoandsocrates, #socratesandplato, #republik, #republic, #westerntradition, #philosophy, #rationality, #drjohndwise, #philosopher, #philosophical, #philosophicalauthor #westerntraditionphilosophy, #traditionalphilosophy, #foundations, #foundationalphilosopher, #foundationaltext, #platosrepublic, #philosophy, #dialogue, #dialogues, #greekphilosophy, #ancientgreekphilosophy, #athens, #platonicdialogue, #platonic, #ancientgreeks, #ancientgreece,#hellen, #hellenistic, #athenian, #atheniantradition, #greekcivilization, #greeksociety, #greekhistory

Plato's Republic is arguably THE foundational text of the Western tradition in philosophy. Book One introduces the theme, Justice, in the form of a Socratic dialogue attempting to define it, as well as a consideration of its practical effects for human life, both individually and corporately. Note Plato's (in the form of Socrates) profound opposition to the ethical relativism of Thrasymachus, a Sophist, who claims that power and oppression always go hand-in-hand, as many claim today. This is the first installment of Book I. Enjoy! If you'd like to support us, donate through Paypal at Romanschapter5@comcast.net https://www.youtube.com/c/TheChristianAtheist/featured https://www.facebook.com/JnJWiseWords https://wisewordsforyouroccasion.wordpress.com   #plato, #socrates, #platoandsocrates, #socratesandplato, #republik, #republic, #westerntradition, #philosophy, #rationality, #drjohndwise, #philosopher, #philosophical, #philosophicalauthor #westerntraditionphilosophy, #traditionalphilosophy, #foundations, #foundationalphilosopher, #foundationaltext, #platosrepublic, #philosophy, #dialogue, #dialogues, #greekphilosophy, #ancientgreekphilosophy, #athens, #platonicdialogue, #platonic, #ancientgreeks, #ancientgreece,#hellen, #hellenistic, #athenian, #atheniantradition, #greekcivilization, #greeksociety, #greekhistory

The second installment in our 11-part series on Plato's Republic. Use the following timestamps for easier navigation: 0:22 Introduction: virtues vs values 7:10 The beginning of the Republic 13:50 Cephalus’ “definition” of justice 15:10 Polemarchus tries to define justice 29:30 Thrasymachus challenges Socrates 34:20 Thrasymachus tries to define justice 42:25 Thrasymachus praises injustice 54:45 Epilogue I: Is this good philosophy? 1:08:10 Epilogue II: Is this good literature? ------------------ Support Ancient Greece Declassified on Patreon: patreon.com/grecepodcast Or make a one-time donation: paypal.me/greecepodcast

The Left is laying the rhetorical groundwork for a domestic war on Trump supporters, as red state governments start planning how to respond. Florida Governor Ron DeSantis announced plans to push back on the Big Tech Cartel—will they work? Our editors, joined for the first time by new managing editor Seth Barron, discuss the desperation and discreditation of the mainstream media.

Man is the measure of all things - Protagoras This is our third episode in a series of four (we recently decided to make Book Two into two episodes) where we will be taking a look at Plato's best-known work, The Republic. We discuss Book Two specifically in this episode, looking at the continued argument for justice, beginning in Book One with Thrasymachus. We start off briefly by discussing the divided line, and knowledge, before moving into The Ring of Gyges - or the ring of invisibility. We discuss how that influences the just and unjust person, and whether or not the just or unjust is happier. We also talk about how this information is applicable in looking back, as well as looking forward. Always feel free to let us know what you think, or any episode requests. We would love to hear from you!

Instances out of Plato's Republic. Thrasymachus and Socrates discuss Justice and what a ruler does. Arguments and attitudes about this including what a doctor is.

Discussion of Thrasymachus’ challenge to justice and Socrates answer. What is wrong with the idea that "might makes right"? How is the definition of Justice as "the advantage of the strong" a flawed definition? How, moreover, is it a spiritual poison that causes death to the soul? How could Socrates, Plato, defeat such a seemingly damnable vision of the world?

(covers the second half of book 1 of Plato's Republic) In this episode, Socrates goes up against his most formidable opponent yet: the sophist Thrasymachus. Thrasymachus leaps at Socrates “like a wild beast” and yells at him for playing dirty. Then, he tells the boys that morality is a lie and that they should do as much injustice as they can get away with. Socrates responds by winning the argument in the least persuasive way possible. Pod Art: Marijke BouchierTheme music: David Zikotivz, Clayton Tapp Ancient lyre music: Michael Levy Editing, episode art and social: SepidehThrasymachus: Paul Sagarhttps://twitter.com/goodintheorypodhttps://www.instagram.com/goodintheorypod/https://www.facebook.com/goodintheorypodSupport the show (https://www.patreon.com/user?u=35146517&fan_landing=true)

Paul Sagar is a lecturer in political theory at King's College London and the guy who played Thrasymachus in book 1. He actually doesn't like reading Plato very much. I ask him why. Support the show (https://www.patreon.com/user?u=35146517&fan_landing=true)

Ever wanted to learn philosophy from drunk people? Us, neither. Here's a collection of mini-episodes as Connor and the "Two Joes" attempt to teach some of the fundamental ideas and thinkers in the history of philosophy, from the Ancient Greeks to the Enlightenment and beyond. These conversations are some of the earliest we had, back when we were trying to be professorial and educational. Originally improvised audio tests, after recovering them from an old hard drive, they are lost no more. Hopefully you'll share in our passion and interest as you follow us from insightful dialogue to drunken mishaps. The conversations featured in this episode are: 0:25 - A Very Brief Introduction to René Descartes' Meditations. Topics covered: "I think therefore I am", Cartesian doubt, Cartesian dualism. 6:15- Thomas Kuhn: The Structure of Scientific Revolutions & Paradigm Theory. Topics covered: Paradigm shifts, Scientism, The Copernican Revolution, Normal science v. revolutionary science, (We're not scientists). 30:40 - Plato's Republic & Why We Read it. Topics covered: Socratic dialogues, Thrasymachus, The Cave, the Forms, Contextual reading and why philosophy is important to read.

This is the first in a three-part series focusing on strategic communication: what is it, how does it work, what are its strengths and limitations, is it morally defensible, and is it even avoidable? In today’s episode, we examine the Socratic Method in practice: a rambunctious debate on the nature of justice between Socrates and Thrasymachus in Plato’s Republic. In theory, the Socratic Method is an open, transparent dialectical process of uncovering truth. But in practice, the method trespasses into the territory of strategy. Did Socrates’ commitment belong to the truth, or to winning at Thrasymachus’ expense? What can leaders in the modern world learn from this hilarious exchange? What are some real life situations in which a Socratic strategy pays dividends? Jason and Juan Pablo discuss, laying the groundwork for our most heated debate yet. We recommend listening to each part in chronological order. The views expressed on this podcast are our own. If you enjoy what you're hearing, please follow/support us through any of the below media: Twitter: https://twitter.com/Panopticpod Patreon: https://www.patreon.com/panopticpod Website: https://www.panopticpod.com/ Apple: https://podcasts.apple.com/us/podcast/pan-optic-podcast/id1475726450 Spotify: https://open.spotify.com/show/0edBN0huV1GkMFxSXErZIx

Having fun is awesome! Having fun and learning at high Bloom’s cognitive levels is even better. Use your students innate sense of humor to hook them into your content AND improve your classroom culture! Thrasymakos.wordpress.com @Thrasymachus

Being a “perfect” teacher doesn’t come from knowing your content perfectly, it comes from building more perfect relationships with your kiddos! Then the content is easier to address. @Thrasymachus on Twitter and Thrasymakos.wordpress.com blog “Humor” blog can be accessed there.

A neglected gem from Less Wrong: Why The Tails Come Apart, by commenter Thrasymachus. It explains why even when two variables are strongly correlated, the most extreme value of one will rarely be the most extreme value of the other. Take these graphs of grip strength vs. arm strength and reading score vs. writing score:     In a pinch, the second graph can also serve as a rough map of Afghanistan   Grip strength is strongly correlated with arm strength. But the person with the strongest arm doesn’t have the strongest grip. He’s up there, but a couple of people clearly beat him. Reading and writing scores are even less correlated, and some of the people with the best reading scores aren’t even close to being best at writing. Thrasymachus gives an intuitive geometric explanation of why this should be; I can’t beat it, so I’ll just copy it outright:     I thought about this last week when I read this article on happiness research. The summary: if you ask people to “value their lives today on a 0 to 10 scale, with the worst possible life as a 0 and the best possible life as a 10”, you will find that Scandinavian countries are the happiest in the world. But if you ask people “how much positive emotion do you experience?”, you will find that Latin American countries are the happiest in the world. If you check where people are the least depressed, you will find Australia starts looking very good. And if you ask “how meaningful would you rate your life?” you find that African countries are the happiest in the world. It’s tempting to completely dismiss “happiness” as a concept at all, but that’s not right either. Who’s happier: a millionaire with a loving family who lives in a beautiful mansion in the forest and spends all his time hiking and surfing and playing with his kids? Or a prisoner in a maximum security jail with chronic pain? If we can all agree on the millionaire – and who wouldn’t? – happiness has to at least sort of be a real concept. The solution is to understand words as hidden inferences – they refer to a multidimensional correlation rather than to a single cohesive property. So for example, we have the word “strength”, which combines grip strength and arm strength (and many other things). These variables really are heavily correlated (see the graph above), so it’s almost always worthwhile to just refer to people as being strong or weak. I can say “Mike Tyson is stronger than an 80 year old woman”, and this is better than having to say “Mike Tyson has higher grip strength, arm strength, leg strength, torso strength, and ten other different kinds of strength than an 80 year old woman.” This is necessary to communicate anything at all and given how nicely all forms of strength correlate there’s no reason not to do it.

Humor can be a big asset in the classroom when don't right. On the other hand... Follow: @donwettrick @Thrasymachus @bamradionetwork #edtechchat #edchat #edtech Charles Cooper is a life long educator interested in merging humor, technology and learning. He was the 2012 Humanities Texas Teacher of the Year and is currently on step 9 of 1,500 to take over the world. Charles Cooper is a life long educator interested in merging humor, technology and learning. www.thrasymakos,wordpress.com