Increments

Back to basics baby. We're doing a couple introductory episodes on Popper's philosophy of science, following Chapter 10 of Conjectures and Refutations. We start with Popper's theory of content: what makes a good scientific theory? Can we judge some theories as better than others before we even run any empirical tests? Should we be looking for theories with high probability? Ben and Vaden also return to their roots in another way, and get into a nice little fight about how content relates to Bayesianism. We discuss Vaden's skin care routine If you find your friend's lost watch and proceed to lose it, are you responsible for the watch? Empirical vs logical content Whether and how content can be measured and compared How content relates to probability Quotes My aim in this lecture is to stress the significance of one particular aspect of science—its need to grow, or, if you like, its need to progress. I do not have in mind here the practical or social significance of this need. What I wish to discuss is rather its intellectual significance. I assert that continued growth is essential to the rational and empirical character of scientific knowledge; that if science ceases to grow it must lose that character. It is the way of its growth which makes science rational and empirical; the way, that is, in which scientists discriminate between available theories and choose the better one or (in the absence of a satisfactory theory) the way they give reasons for rejecting all the available theories, thereby suggesting some of the conditions with which a satisfactory theory should comply. You will have noticed from this formulation that it is not the accumulation of observations which I have in mind when I speak of the growth of scientific knowledge, but the repeated overthrow of scien- tific theories and their replacement by better or more satisfactory ones. This, incidentally, is a procedure which might be found worthy of attention even by those who see the most important aspect of the growth of scientific knowledge in new experiments and in new observations. C&R p. 291 Thus it is my first thesis that we can know of a theory, even before it has been tested, that if it passes certain tests it will be better than some other theory. My first thesis implies that we have a criterion of relative potential satisfactoriness, or of potential progressiveness, which can be applied to a theory even before we know whether or not it will turn out, by the passing of some crucial tests, to be satisfactory in fact. This criterion of relative potential satisfactoriness (which I formu- lated some time ago,2 and which, incidentally, allows us to grade the- ories according to their degree of relative potential satisfactoriness) is extremely simple and intuitive. It characterizes as preferable the theory which tells us more; that is to say, the theory which contains the greater amount of empirical information or content; which is logically stronger; which has the greater explanatory and predictive power; and which can therefore be more severely tested by comparing predicted facts with observations. In short, we prefer an interesting, daring, and highly informative theory to a trivial one. C&R p.294 Let a be the statement ‘It will rain on Friday’; b the statement ‘It willbe fine on Saturday’; and ab the statement ‘It will rain on Friday and itwill be fine on Saturday’: it is then obvious that the informative contentof this last statement, the conjunction ab, will exceed that of its com-ponent a and also that of its component b. And it will also be obviousthat the probability of ab (or, what is the same, the probability that abwill be true) will be smaller than that of either of its components. Writing Ct(a) for ‘the content of the statement a’, and Ct(ab) for ‘thecontent of the conjunction a and b’, we have (1) Ct(a) <= Ct(ab) >= Ct(b). This contrasts with the corresponding law of the calculus of probability, (2) p(a) >= p(ab) <= p(b), where the inequality signs of (1) are inverted. Together these two laws, (1) and (2), state that with increasing content, probability decreases, and vice versa; or in other words, that content increases with increasing improbability. (This analysis is of course in full agreement with the general idea of the logical content of a statement as the class of all those statements which are logically entailed by it. We may also say that a statement a is logically stronger than a statement b if its content is greater than that of b—that is to say, if it entails more than b does.) This trivial fact has the following inescapable consequences: if growth of knowledge means that we operate with theories of increasing content, it must also mean that we operate with theories of decreasing probability (in the sense of the calculus of probability). Thus if our aim is the advancement or growth of knowledge, then a high probability (in the sense of the calculus of probability) cannot possibly be our aim as well: these two aims are incompatible. C&R p.295 Socials Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani Come join our discord server! DM us on twitter or send us an email to get a supersecret link Become a patreon subscriber here. Or give us one-time cash donations to help cover our lack of cash donations here. Click dem like buttons on youtube How much content does the theory "dish soap is the ultimate face cleanser" have? Send your order of infinity over to incrementspodcast@gmail.comSupport Increments

We're joined by Jonathan Rauch to discuss what it means to be a radical incrementalist, how to foment revolution on geological timescales, and whether Christianity can be a force for good in politics. Can Jon convince angry-Hitchens-atheist Vaden that Christianity has some benefits? Will both Vaden and Ben be at Sunday prayer? Follow Jonathan on his website, at Brookings, at The Atlantic or on Bluesky. We discuss The constitution of knowledge and whether it's holding Norms vs laws, and whether we should introduce more laws to codify norms Popper's paradox of tolerance How should liberals respond to illiberalism? Which tactics, if any, should democrats adopt from MAGA to fight MAGA? Sharp Christianity and Christian nationalism Rauch's plea to Christians References The Constitution of Knowledge: A Defense of Truth Cross Purposes: Christianity's Broken Bargain with Democracy Errata Jonathan Rauch is the author of nine books, not eight! Socials Follow us on Twitter at @JonRauch, @IncrementsPod, @BennyChugg, @VadenMasrani Come join our discord server! DM us on twitter or send us an email to get a supersecret link Become a patreon subscriber here. Or give us one-time cash donations to help cover our lack of cash donations here. Click dem like buttons on youtube Anyone in Canada have a basement suite Jonathan could rent for a while? Send your address over to incrementspodcast@gmail.comSpecial Guest: Jonathan Rauch.Support Increments

Ben Recht, a professor at UC Berkeley, explores the nuances of statistics and AI. He defends Bayesian approaches while humorously questioning the utility of statistics in daily life. The discussion dives into AI doom, the origins of the term 'robot,' and the contributions of Paul Meehl to science. Recht highlights the philosophical pitfalls of probabilistic reasoning in AI and debates the relevance of traditional statistical methods. Listen in for a thoughtful critique on the intersection of statistics, science, and societal perceptions of technology.

Always the uncool kids at the table, Ben and Vaden push back against the AGI hype domininating every second episode of every second podcast. We react to "We're not ready for superintelligence" by 80,000 Hours - a bleak portrayal of the pre and post AGI world. Can Ben keep Vaden's sass in check? Can the 80,000 hours team find enough cubes for AGI? Is Agent-5 listening to you RIGHT NOW? Listener Note: We strongly recommend watching the video for this one, available both on youtube and spotify: - https://www.youtube.com/@incrementspod - https://open.spotify.com/show/1gKKSP5HKT4Nk3i0y4UseB We discuss The incentives of superforecasters Arguments by authority Whether superintelligence is right around the corner The difference between model size and data Are we running out of high quality data? Does training on synthetic data work? The assumptions behind the AGI claims The pitfalls of reasoning from trends References Michael I Jordan Neil Lawrence [Important technical paper from Jordan pushing back on Doomerism](A Collectivist, Economic Perspective on AI) Jordan article talking about dangers of using AlphaFold data Nature paper showing you can't use synthetic data to train bigger models Paper estimating of when training data will run out (Coincidentally enough, sometime between 2027-2028) Socials Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani Come join our discord server! DM us on twitter or send us an email to get a supersecret link Become a patreon subscriber here. Or give us one-time cash donations to help cover our lack of cash donations here. Click dem like buttons on youtube But how many cubes until we get to AGI though? Send a few of your cubes over to incrementspodcast@gmail.com Episode header image from here. Support Increments

Dive into the philosophical showdown between Berkeley and Newton as they battle over the nature of gravity. Explore the educational implications of AI tools like ChatGPT in writing, and ponder whether we can learn from historical figures like Stalin in addressing plagiarism. Uncover the distinctions between instrumentalism and essentialism, and laugh as Berkeley grapples with Newton's concepts of force. Finally, witness the ongoing debate about observability in science and discover the fascinating legacy of these influential thinkers.

This week we take a break from our regularly scheduled programming to listen to Ben, Rich, and Cam loutishly pontificate on one of the oldest poems in history. That's right, three fiction noobs take on Homer. Ladies, have you ever wondered what your fella is doing when you're out for the evening? Look no further. The podcast you're listening to is Do You Even Lit? which you can find on any podcast platform and on youtube. The hosts are Richard Meadows, Cam Peters, and some third guy. Back to increments in a couple weeks! In the meantime: find us on twitter at @BennyChugg, @VadenMasrani, and @Incrementspod come join our discord channel! Send us a message or an email to get a supersecret link hit those like buttons on youtube to show off your virtuosity Should we switch out Vaden for Rich and Cam? Tell us at incrementspodcast@gmail.com.Special Guest: Richard Meadows.Support Increments

Join research director Hugo Mercier as he dives into the fascinating world of belief and conformity. He critiques the dual process theory of cognition, identifying how our biases often lead us astray. Mercier explores the mechanics of propaganda, particularly how social media has reshaped its influence. He also examines why advertising often fails despite hefty budgets and shares insights on social signaling in belief systems. With discussions on flat earthers and the importance of dialogue, this conversation unpacks the nuances of how we trust and believe.

Brett Hall and Peter Boghossian dive into the intricacies of confidence and evidence. Hall, a speaker in street epistemology, presents a fallibilist view on knowledge while Boghossian discusses rational decision-making and trust. They explore how confidence is interwoven with personal beliefs and scientific inquiry, emphasizing that confidence doesn't equal truth. The conversation also touches on moral reasoning, the challenges of defining knowledge, and the implicit knowledge conveyed through emotions. Expect thought-provoking insights and lively discourse!

Peter Boghossian, a philosopher renowned for his work in street epistemology, joins Brett Hall, a critical rationalist thinker, to dissect the interplay between confidence and evidence. They explore how historical moments in science, like Eddington's solar eclipse experiment, reveal the complexities of validating theories. The duo emphasizes the subjective nature of confidence, weighing Bayesianism against critical rationalism, and highlights the dangers of overconfidence in decision-making. Their conversation is a refreshing deep dive into epistemology and its real-world implications.

Explore the intriguing idea that humans might not be as gullible as we think, with insights from Hugo Mercier's work. Listen in as the hosts dissect the evolution of communication and how it impacts social interactions. They question when people change their minds and delve into the balance between motivated reasoning and social conformity. Get ready for playful debates about stubbornness and belief formation, all peppered with fascinating animal examples that highlight the nuances of reliable communication.