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We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
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What It Takes To Be A Top Tier Entertainment Lawyer in 2026
Share I’ve recently run several popular posts breaking down data related to sought after legal jobs. General Counsel Big Law Appellate Attorney Here is another in this series. Two Lawyers, One Elite Market Entertainment law can sound like a single professional category. In practice, the lawyers who reach the top of the Hollywood market often look quite different from one another. Consider two attorneys from the 2025 top-entertainment-law universe. Lesley Freeman represents one route: the company-side entertainment lawyer. She is chief legal officer of AGBO, where she oversees company-wide business and legal affairs across film, television, video game and interactive experiences, and technological innovation, after senior legal roles at MGM, Amazon MGM Studios, HBO, and O’Melveny. Daniel Petrocelli represents another route: the outside-counsel trial lawyer. He is chair of O’Melveny’s trial practice and a vice chair of the firm, with a national litigation practice that includes entertainment, sports, and media disputes. Their careers differ by platform, role, practice area, and professional identity. One sits inside an entertainment company; the other practices from a major law firm. One is associated with corporate and governance work; the other with litigation. Yet both fall within the same publicly recognized top tier of Hollywood lawyers. That contrast points to the article’s central question. If there is no single mold for a top entertainment lawyer, are the paths simply idiosyncratic, or do they follow recurring patterns? The data suggest the latter. The attorneys recognized on The Hollywood Reporter and Variety’s 2025 top-attorney lists do not follow one career template, but their paths are not random. They cluster around several defined routes: entertainment-focused private practice, company-side or operator experience, corporate and finance conversion, litigation conversion, public-service-to-litigation pathways, and smaller specialized lanes in labor, employment, and celebrity family law. Across those routes, the recurring ingredients are platform strength, educational capital or Los Angeles market proximity, long career tenure, specialized practice identity, and entertainment-industry fluency. The article examines five dimensions of the top-attorney sample: route into entertainment law, firm or organizational platform, education pipeline, seniority, and practice specialization. Data and Methodology The dataset includes 103 attorneys drawn from The Hollywood Reporter and Variety’s 2025 lists of top entertainment or Hollywood attorneys. For each attorney, the dataset tracks current organization, law school, J.D. year where available, first-known bar admission year, practice area, prior roles, platform type, and route into entertainment law. The sample is best understood as a recognized-attorney dataset, not a census of all entertainment lawyers. It captures lawyers who reached public top-tier recognition in 2025, rather than every lawyer practicing in the entertainment sector. Multiple but Defined Routes Into Entertainment Law The first question is how these lawyers entered the entertainment-law market. Because every attorney in the dataset is entertainment-related by definition, the key distinction is not whether they practice entertainment law. It is how they got there. The largest group followed what might be called the entertainment private-practice route. These attorneys appear to have built their practices around entertainment, media, talent, music, rights, production, intellectual property, or adjacent industry work relatively early. That route accounts for 40 of the 103 attorneys in the sample, or 38.8%.
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May's top PlayStation games by copies sold
Yesterday’s State of Play gave us an idea of where PlayStation’s heading next. But we’ve had our May estimates for a couple of days now (we always update our data daily for clients), so it’s time to look at what performed best on PlayStation last month. We’ve got a new IP at the top, two evergreens doing their evergreen thing, FC26 smashing it ahead of the World Cup Plus pivot, and a quiet but promising result for Lego Batman. Let’s have a look at the state of Play…Station’s top games for May. 007 takes #001 007 First Light sold 1M copies on PS5 in May, easily making it the month’s top PS5 game by copies sold. Over 80% of those May copies were digital, which is broadly in line with where PlayStation’s digital share has settled for new releases this year. To date, 007 First Light has sold through 2.2M copies across platforms (so no unsold retail copies in that figure). The platform split is 55.1% PS5, 33.1% Steam, and 11.8% Xbox (console, Windows, and cloud combined). In gross revenue terms, 007 First Light has generated $150M. Owing to regional pricing and audience composition differences, the consoles make up a higher share of revenue than they do copies. Of the $150M, 60.5% came via PlayStation, 27.6% via Steam, and 12.9% via Xbox. Part of this is because over two-thirds of 007 First Light‘s PlayStation audience is in North America (43.4%) or Western Europe (23.2%), where local currency means the game generates more revenue per player. On Steam, under half of First Light‘s audience is from those same regions (31.8% North America, 15.1% Western Europe). As we covered in last week’s 007 Steam piece, the Steam version is pulling in higher-than-expected numbers in China, which now accounts for 17.3% of First Light‘s Steam audience. 007 is the equivalent of $44 USD in China, which is roughly 37% cheaper than the US price and about 44% cheaper than Western Europe. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe The crossover data backs up what we’ve seen all year about launch-window cohorts. 11% of PS5 players who played 007 First Light in May also played Lego Batman: Legacy of the Dark Knight, which launched just a few days before. Last month was a great month for Denmark! IO Interactive is Copenhagen-based, and Lego Group is headquartered in Billund (TT Games is UK-based but produces work under Lego Group licence and direction). Speaking of which… A very blocky #2 and #3 Minecraft sold another 788K copies on PlayStation consoles last month. Business as usual, since Minecraft hasn’t sold fewer than 760K copies in a single month all year. With over 350M copies sold across all platforms, Minecraft is the best-selling game in history and one of the strongest brands in the world. Every month, a new cohort of children reaches Minecraft age, which guarantees a constant volume of new sales regardless of what the broader market is up to. The demographic refresh rate is truly impressive, with the audience renewing itself faster than it’s churning. Lego Batman: Legacy of the Dark Knight shifted 757K copies on PS5 last month, bringing its lifetime total on the platform to over 800K. Across all platforms, Legacy of the Dark Knight has now passed 1.5M sold through, so PlayStation accounts for over half of the game’s players. The May crossover data for Legacy of the Dark Knight on PS5 is also useful. 27% of those players also played Fortnite, 16% Roblox, 16% FC 26, and 14% NBA 2K. That’s the household-and-family cohort showing up, plus the launch-window cohort of core gamers who buy practically everything. FC 26 gets players through the door ahead of the World Cup FC 26 sold 411K copies on PlayStation last month (90% via PS5), the fewest copies FC 26 has sold all year and down heavily from April’s 700K. Part of this dropoff is because FC 26 has been available as a PlayStation Plus monthly game since 6 May, cannibalising premium sales. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe The strategic logic is straightforward for EA, which is sacrificing premium unit sales in May to build up the player base ahead of the FIFA World Cup, which kicks off on 11 June. Obviously, a bigger player pool going into the tournament means a bigger pool of potential Ultimate Team spenders during the period when football attention is at its peak. The early returns are around what you’d expect, with 4.4M new players accessing FC 26 via PS Plus last month – a substantial new spender pool. Anecdotally, a few of my mates who were ‘’skipping FIFA and Ultimate Team this year’’, were drawn back in via PS Plus. Lo and behold, one of them is buying packs like it’s going out of fashion. Whether this is all a smart trade for EA depends entirely on the Ultimate Team conversion rate over the next six weeks. Either way, the short-term engagement impact on the game as a whole is evident. FC 26‘s MAUs hit a record 24M on PlayStation in May, up 30% from the previous record set in April. GTA V does what GTA V always does Rounding out the top five is another evergreen title. Grand Theft Auto V shifted another 387K copies on PlayStation last month. No matter what else is happening in the industry, GTA V keeps pulling players in. It’s sold another 1.8M copies on PS5 in the first half of this year alone, helping the franchise pass the 230M-sold milestone across all platforms. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe I have a theory that Minecraft and GTA V are doing the same thing at different demographic levels. Both are functioning as generational gateway games that the audience ages into faster than it ages out of. Minecraft captures kids around age 6-10, GTA V captures much of the same audience around age 12-15 (unofficially, of course). The crossover data suggests this: 40% of GTA V‘s monthly PlayStation players typically play Fortnite in any given month, while 30% play Roblox. Household accounts aside, that’s not the original GTA V audience from 2013. Of course, the under-12 audience would love to get their hands on GTA, too. It’s always been the way of things, and some parents are happy to oblige. Mine did too back in the day, and I turned out just fine. Right? Right!? Want to get your hands on our data for yourself – for free? We’re offering a free trial of our platform for games companies. Send us a message here, or reply to this email, and we’ll set you up. The last word Reply to this email – or reach out here – if you have any feedback for the newsletter – or want to request a game for us to cover. [Alinea Analytics boasts the most accurate PC and console estimates in the business. Game makers use our platform to understand their audience, keep an eye on the competition, monitor sales trends, and spot new opportunities. We equip game studios and financial institutions with accurate data and the confidence to make smarter, data-driven decisions. Want to talk about all things games market data? We’d love to chat!]
11,600 Durango homes, businesses lose power
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The cult of objectivity has broken consciousness science
With 22 competing theories and no consensus in sight, the science of consciousness is lost. In this exclusive IAI interview, Berkeley psychedelics researcher and bestselling author of a new book on consciousness Michael Pollan insists that even though consciousness lies beyond traditional forms of scientific investigation, we should resist becoming dualists who see it as something radically different from ordinary stuff in the world. Instead, he makes the case for reimagining science itself: it must stop reaching for objective descriptions of physical reality, and instead embrace subjectivity as the indispensable core of all inquiry. Alasdair Craig: How did your experiences with psychedelics get you interested in consciousness?Michael Pollan: One of the things that happens on psychedelics is that they foreground consciousness. What formerly seemed perfectly transparent and ever present—and yet, non-existent, as water is to fish—suddenly you see it. The metaphor I use in the book is that psychedelics sponge the windscreen. Suddenly you realize: wow, there’s a windscreen, there is this phenomenon that’s mediating my relationship to reality. This is not an unusual realization on psychedelics. I think a lot of people are called to think about consciousness after psychedelic experiences. So that was the proximate inspiration for A World Appears: A Journey Into Consciousness (2026).And then there was a more specific way in which psychedelics influence the book. That was a particular experience I had on psilocybin. I had the sensation that the plants in my garden were conscious and returning my gaze, with their own point of view and agency, and I got curious as to how to evaluate an insight like that. I mean, what’s the truth quotient of insights you have on psychedelics? And I was reading William James—who, of course, wrote beautifully about mystical experience—and he said, we can’t judge the metaphysics here, but we should pay attention to two criteria: (1) How useful is it to think this is true? He was a pragmatist, of course. And (2) can we subject it to other ways of knowing to validate it? Because maybe we should treat these insights as hypotheses. And that’s kind of how I approach psychedelics, as a great generator of hypotheses, but they need to be tested against other ways of knowing. And so that led me down this long path exploring the science of plant intelligence and plant sentience.AC: I love your phrase, “smudging the windowpane of conscious experience.” So do you now start to think, actually, even when I’m not on psychedelics, I’m just seeing a screen all the time, which is not reality, but rather is my conscious experience, behind which reality is hidden?MP: Well, you know, not when I’m brushing my teeth and making breakfast! But yes, in meditation, certainly. I mean, one of the things you realize is that my experience happens to be this way now, but it could be another way. And many things can affect it. My morning coffee changes the screen in various ways, sharpens certain things.___The only tool we have to understand consciousness is consciousness.___There’s this wonderful metaphor in Aldous Huxley’s book, The Doors of Perception, where he thinks we channel consciousness, and that what the brain does is edit it, and there’s a reducing valve. And psychedelics open the reducing valve wider. I don’t know that I’m ready to buy into the idea that consciousness exists outside brains, but I do love that metaphor because there are times when you are more conscious than others. I know I’ve switched from window pane to valve, but you know, a camera aperture can open wider or narrower. And I do have a sense of that. I have a sense of when I’m being less conscious, and when I’m being more conscious, by which I mean, you know, more present, taking in more sensory information. So when you start thinking about consciousness as a matter of degree, that changes things also.I think when we scroll on social media, obviously, we’re conscious. But minimally so, because we don’t have to generate our own thoughts. We’re basically taking these little hits from other people and thinking their thoughts.The process of writing this book made me kind of relativize everyday consciousness as just one type, which is exactly what William James said. Normal consciousness is one type, separated by the flimsiest of screens from the other types.AC: If we stick with the metaphor of the smudge on the window that you get when you take psychedelics, it seems like we’re saying that consciousness has become like an object that you’re looking at, right? You’re looking at the smudge and that just is consciousness. But sometimes we’ll talk about consciousness as a state that you’re in, rather than an object you can perceive. You’re either conscious or you’re not conscious. So it’s difficult to really know what sort of thing we’re talking about when we talk about consciousness, right?MP: Yeah. When you say that consciousness is an object, what’s the subject? Consciousness also? The only tool we have to understand consciousness is consciousness. So we’re in a closed loop and when we get a perspective on consciousness, we’re not achieving any distance from it. That’s one of the problems with studying consciousness. Science is predicated on an objective, God’s eye view of things, and you never get that. There’s no such thing. SUGGESTED VIEWING The brain filters consciousness With Àlex Gómez-Marín But, yeah, there is this sense, I think, that consciousness is something you can approach. Certainly, when you’re writing and trying to recreate a conscious experience, it’s a fiction, but you’re standing back from it, and looking at it. But there’s no real subject-object distinction.AC: That’s so interesting, because when philosophers start talking about consciousness, they often talk about what they call “qualia”, which is their word for the felt experience of, say, the color red. And I think that way of speaking often makes us think of the qualia as an object, which you can see out there: the redness of red. But, as you say, we also want to collapse the subject-object distinction when we talk about consciousness. So there’s something strange going on here…MP: Oh, yeah, there are many strange things going on! *AC: Let’s talk about the varieties of consciousness. Apart from perceptions, there are, pains, emotions, thoughts, and so on. What is it that holds all this diversity together so that they all count as instances of consciousness? What is it that they all have in common?MP: Yeah, that’s a really good question. I mean, there is sensory information, right? Which we perceive coming from the world outside ourselves. And then there’s internal information, which is what’s called interoception. And this is very important too. This is where feelings come from—what are sometimes called homeostatic feelings—that are intended to get the brain to keep us in these narrow ranges of temperature and glucose and so on. That’s a very important part of consciousness. And according to some researchers, who I think are probably right, this is where consciousness begins, with these very primal feelings, like hunger and thirst and warmth and itch, and things like that. And then there’s this third thing, which is our thinking about thinking.And what holds all this together is, I think, the sense of self. Consciousness generates a self: it is probably an organizing principle. All this stuff is happening to the self. It’s a construct, I think, but it is very useful. It can connect all these different streams of consciousness to a single being or a place, metaphorically speaking.* AC: The first half of your book is about the science of consciousness. Is consciousness just another thing, like black holes or the origin of life, which we don’t yet understand, but which we should have every hope that science will one day get to the bottom of, or is there something special about consciousness that makes this unlikely?MP: It depends how you define science. As we define science now, it’s going be very difficult. Science since Galileo has had a set of rules or assumptions, which is that the proper remit of science is to deal with the objective, quantifiable, third-person world. And the physical sciences have done amazing work under that set of limitations. Galileo—for tactical reasons, not for philosophical reasons—said science should not deal with the soul, which at the time was what consciousness was considered to be. So what is subjective, what is qualitative, what is first person, we’re going to leave to the church, he said. And this was a good agreement, and it probably kept many scientists from getting burned at the stake. But it leaves science in an awkward spot, now that it wants to venture into that territory of qualities, of first-person experience. And I don’t think it has the proper tools. I think it will have to add to its toolkit in some way, and find a way to bring in phenomenology, or lived experience and introspection, which science is usually dismissive of.The challenge—we alluded to it earlier—is that the only tool you have to study consciousness with is consciousness. And what I mean by that is, the whole scientific enterprise is a manifestation of consciousness. As much as scientists like to flatter themselves with this idea that they attain a godlike perspective on what they study, when it comes to consciousness, there’s no such thing. And it’s fine for all the things you can step outside of and study from that perspective. But two areas it won’t work are consciousness and cosmology.___It could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.___With cosmology, too, you have to study the universe from inside the universe. It’s not that cosmologists haven’t made progress. We know a lot about the age of the universe and expansion and things like that. But we can’t penetrate what happened before the Big Bang. We just don’t have the tools because we can’t stand outside.The fact that there are 22 full-scale theories of consciousness tells you all you need to know: we’re kind of lost. And I was surprised to find that we are more lost than I thought we were when I started this. I thought that there’d be leading theories, or that we had experiments that we could conduct that would nail some of this down. And the fact is, we don’t.So, I don’t know if science can solve it. But, of course, we can change the rules of science. A really influential book for me was a book called The Blind Spot, by two physicists, Marcello Gleiser and Adam Frank, and a philosopher, Evan Thompson. It’s a reminder that science is a social practice. It’s organized in a certain way and it can be organized in a different way. But it has this huge blind spot at the center of it, which is its failure to recognize that it is a form of consciousness itself, and it doesn’t have a good way of taking account of lived experience.AC: On the one hand, I think you want to resist traditional dualism, which would say that consciousness is something magical, something supernatural, right? But on the other hand, you’re accepting that there is this division in reality between the stuff that you can investigate objectively and measure, and so on—the stuff that science has been good at finding out about—and consciousness, which, for some reason, you can’t objectively measure. Some would take this to suggest that the dualism is actually right. Is there a way of reconciling these two strands of your thinking?MP: To call it magical is full of value judgement. I mean, you could just say immaterial. The interesting thing is, I think, that intuitively we’re all dualists. And I don’t know whether that’s because we’re children of Descartes and other cultures are less dualist than we are. Or it may be because that’s how consciousness feels. It feels different than the body. It feels separate from the body. But I don’t think we should trust that intuition.AC: So let’s think about ways that science might be changed to get at consciousness. I suppose the starting point would be the way that you begin the second half of your book. You have this nice line from William James, where he says, “We now begin our study of the mind from within.” Could you give us some sense of the ways of studying the mind from within? What does this involve?MP: I don’t know what that science looks like. But one of the points I’m making is that it depends on the humanities. I found that I learned as much, if not more, about consciousness, from reading novels and poetry. There is a sense of the fullness and complexity of consciousness that you don’t get in any scientific account. I interviewed this stream-of-consciousness writer and I approached her as an expert on consciousness, and she is. So I think that dialogue is really important.I’m reading Ben Lerner’s new novel, Transcription. Just read the first page of this novel: it’s a man falling asleep on a train, going to conduct an interview, and there is the experience of being in the train, facing backwards, there’s the view outside, but there’s a reflection of himself through which he’s seeing outside. There’s the memory of dropping his kids off at school. All this is going on in one moment of consciousness. Scientists aren’t going anywhere near that. But I think it’s useful for them to think about. That’s where we’re trying to go: like, how does such a layered experience happen? You know, it also makes you wonder, could a computer ever do this? And it gives you some doubt.*AC: Before we get to computers, perhaps we could talk briefly about plants. How did you come to feel that they are sentient?MP: Well, it was a psychedelic experience, and it’s not unusual on psychedelics. In fact, there’ve been studies about how people become animists during psychedelic experience. Their belief in animism arises after a single psychedelic experience.You know, most scientists would say this is all a myth. But we have only 400 years of the age of enlightenment and science. Before that, we were animists, and if you go around the world, most indigenous cultures are still animists, and children are animists, by and large, until they go to school. So it could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.As I said, I wanted to test this idea, and see whether there was conventional scientific evidence for it. And there’s fascinating work going on in a field that calls itself—in a rather cheeky way—plant neurobiology. These are people who fully realize there are no neurons in plants, but they’re trolling conventional botanists! And they’re doing experiments that are demonstrating that plants can learn and remember, which is kind of amazing: how do you store a memory without neurons? They’re finding plants that can solve problems, that can hear and see. In fact, they have 20 senses to our five or six. For example, a bean plant looking for something to twine, and given a pole within eight inches or so of it, knows where that pole is and will aim its spiraling reach at that pole. What is that about? Is it bouncing signals off of it?One of the spookiest things is the fact that the same anesthetics that put us out put plants out. You might think that plants are already out, but they’re not. They’re just slow. If you take a plant with a fast behavior, like a Venus flytrap, and give it an anesthetic, it will stop reacting. So you have to ask yourself, what is lost when the plant is anaesthetized? Some state of alertness, of awareness, of its environment, of reactivity. I’m not prepared to call that consciousness, but maybe it’s sentience—which is a simpler form of consciousness, and involves the ability to sense what’s going on in your environment and assess what’s good and bad for you and act appropriately. That may be a universal quality of life.AC: Let’s turn from plants to AI. You point out that LLMs are trained on the internet rather than direct interactions with reality. You put this really nicely when you say the internet is not the world so much as a shadow cast by the world. So LLMs are living in this kind of shadow world, or in Plato’s cave, as you put it. What’s the significance of this for AI consciousness and moral consideration? And, to recall the beginning of our conversation, if we’re stuck behind a veil or screen of consciousness, are we also stuck in a kind of shadow world?MP: I don’t think they’re the same shadow worlds because our world includes nature and other people. And even if it’s mediated in some ways... There is a reality out there, and we are in relation to it, through consciousness. There’s friction with it. What’s missing from the LLMs is that friction with the real world. There’s more to the world than human representation, which is what they’re dealing with. And that means that so far, AI is a cultural technology for combining thoughts we’ve already had. SUGGESTED VIEWING Cracking the code for thought With Roger Penrose, Sabrina Gonzalez Pasterski, Max Tegmark, Güneş Taylor Genuine creativity is more than collage. A lot of what AI does now is tantamount to collage, putting this with that and you know, that’s part of art, certainly. But there are also genuinely new ideas that come into the world that don’t come in through manipulating the representations we already have. So it remains to be seen whether AIs can be truly creative in that more radical sense.But my arguments against AI becoming conscious have to do with the fact that the idea of AI consciousness is based on this faulty metaphor that the brain is a computer. There are dimensions in which the brain is like a computer—it certainly does its share of computation. But computers have this sharp distinction between hardware and software, and brains don’t. In a brain, hardware and software are identical. Every memory is a physical change to the brain. Brains are not interchangeable in the way computers are. So this idea that you could take the consciousness out and somehow run it on another substrate, a silicon substrate, seems foolhardy.Anyway, it’s a more extended argument, and I may be wrong. And when we move to computers that aren’t based on silicon—neuromorphic computers and things like that—all bets may be off.AC: Regarding your point about LLMs being stuck in the world of our representations—the internet or whatever—and not being able to interact with reality, are these representations, the world of the internet, themselves part of reality? We’ve created the internet, but it’s still a real thing that exists. And so while the LLMs may be trapped within that part of reality, they’re nevertheless within reality and interacting with it and so on. So it’s not obvious that there’s a barrier there to them becoming conscious and being creative.MP: Yeah, I mean, if our consciousness is built out of human culture, which is what we’re talking about with all those representations. But I tend to think consciousness comes a bit more out of nature and friction with the natural world, but...AC: So there’s a fundamental divide between the natural world and human artefacts?MP: And we lose track of that, and especially people in this computer world. You know, the people who are creating these AI systems, my guess is they’ve been into video games since the age of three, and they didn’t go outside a lot. And their own contact with nature is somewhat limited. I could be wrong, it’d be a very interesting thing to ask, all the wizards of AI, whether they like to go fishing and hiking and do things like that. Or were they on computers from a very early age? I interviewed Blake Lemoine, the Google engineer who came to believe that LaMDA, the Google LLM out at the time, was conscious and deserved personhood. It was very clear that he didn’t see a distinction between this bubble in which he lived and the real world. And I think we’ve all been distanced from the natural world, and this is taking us even further away. But it’s still there, you know, and we still have bodies, and we’re still mortal, and we don’t live in a simulation.AC: I think that’s a great place to finish. Michael Pollan, thank you very much!
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How Science Works
The 2nd Weather and Climate Livestream is now underway. It is organized by a group of early-career researchers concerned about declining funding for the field and eager to demonstrate how weather and climate research makes a difference in our lives. Last year’s event was a great success, drawing terrific press coverage including a piece in the NY Times. This year features a strong lineup of talks aimed at a general audience — I highly recommend tuning in. Share I gave a talk yesterday about How Science Works in Three Steps. You can see the short presentation here (I’ve appended a transcript below): And please tune into the livestream here. It runs through tomorrow at 6 pm ET. Thanks for reading The Climate Brink! Subscribe for free to receive new posts and support our work. Subscribe Cleaned up transcript: Thank you, and thanks to everyone tuning in. I want to talk about something I think a lot of people don’t really understand: how science actually works. Arguments over any scientific topic — climate change, vaccines, you name it — revolve around competing claims. For climate change, the claims are: Is the Earth warming? Are humans to blame? What will the impacts be? Over the last 150 years, the scientific community has developed a remarkably robust method for sorting out which claims are true and which aren’t. That method is what I want to walk through. So how does science generate knowledge? If you ask a high schooler, they’ll give you the version they learned in ninth grade: an individual scientist forms a hypothesis, runs an experiment, and draws a conclusion. That’s more or less what happens at the individual level, though in practice it’s more iterative — you design, test, and refine all at once, landing on a slightly different idea each time until you reach a conclusion about whatever hypothesis you’ve ended up with. But this isn’t science. It’s only step one. Any individual scientist can make mistakes — scientists are human. Maybe there’s a bug in the code, maybe there’s an error in the experiment. Just because someone ran an experiment and reached a conclusion doesn’t mean it’s right, and scientists don’t treat a single result as settled truth. Step two is peer review, the first layer of quality control. The scientist writes up what they did and submits it to a journal, which sends the paper to other experts in the field. Those experts judge whether the methods are sound, whether it properly references prior work, and whether the conclusions actually follow from the data. Ask any scientist and they’ll tell you peer review is miserable — the comments come back brutal, often harsh, and you have to revise and resubmit, sometimes multiple times, before an editor finally accepts the paper. Peer review catches an immense amount of bad science, but it can’t catch all of it. Reviewers get sloppy or overworked, they miss obvious mistakes, and they can’t catch hidden errors — a bug in the code, a misread instrument. So a peer-reviewed paper making it into a journal doesn’t mean the paper is right. Nobody treats a single paper as the final word. That’s where step three comes in: the crucible of science. Important results get retested by the broader community. If you publish something interesting, it gets dissected. Sometimes people try to reproduce your work directly but more often they test its implications. If someone claims X is true, and that implies that Y is also true, then scientists will go check Y. If a claim survives this gauntlet long enough, it becomes accepted. That’s how we generate knowledge. Let me give an example: the ozone hole. In 1985 — and I doubt many people watching were around then, but I remember it well — Joe Farman and his colleagues published observations from Antarctica showing that a huge chunk of ozone was disappearing every year. This was shocking because most atmospheric chemists had expected ozone loss to occur at mid-latitudes and high altitudes, not over the South Pole. When scientists see something they don’t understand, they rush to explain it, and several competing hypotheses quickly appeared in the peer-reviewed literature. One pointed to chlorine chemistry from chlorofluorocarbons. A second blamed nitrogen chemistry, possibly driven by solar proton events — meaning the sun was responsible. A third argued it wasn’t chemistry at all but dynamics: winds were carrying naturally low-ozone air from the lower atmosphere up into the stratosphere. Then the community went to work testing which theory could survive the crucible. Aircraft flew into the ozone hole and found no nitrogen, ruling out the nitrogen theory. Measurements showed the air in the polar vortex was descending, not rising — which would bring high-ozone air down, eliminating the dynamics theory. Meanwhile, those same flights measured enormous amounts of chlorine, strongly correlated with exactly the regions where ozone was being destroyed. That became known as the “smoking gun” paper, and it established that chlorine chemistry was the cause. Through this process, a consensus emerged. And it’s worth being clear that this consensus is organic. There’s no vote, no poll, no meeting where it gets decided. Scientists go to conferences, talk to one another, and independently arrived at the same answer. It’s the ultimate free market of ideas. After the consensus was established, the peer-reviewed literature doesn’t even mention the rival theories — it simply takes chlorine chemistry as given. That’s what a consensus looks like. It doesn’t mean every single scientist agrees, but it does mean there’s no longer any legitimate debate. So where can you see what scientists actually think? It’s all in the peer-reviewed literature, which contains the entire historical record of the argument: the discovery, the competing theories, the debate, the testing, and finally the community coalescing around one answer. But there’s a lot of room for misrepresentation. You can dig up an old paper claiming the ozone hole was caused by dynamics and wave it around as if there still was a debate about the cause of the ozone hole — without mentioning that the idea was disproven long ago and that even its own authors no longer believe it. There’s a bigger problem, though: the peer-reviewed literature is written in a language I call “nerd.” It’s extremely hard to read — honestly, some of it is hard for me to follow. It takes graduate students years to work through the literature in a single field, so we can’t expect policymakers or ordinary people to do it. This is where scientific assessments come in. The most famous is the IPCC — the Intergovernmental Panel on Climate Change. The job of an assessment is to read and summarize the peer-reviewed literature, synthesizing what’s settled, what’s been disproven, and what remains genuinely debated. To ensure the assessments accurately summarize the peer-reviewed literature, assessments are written by large teams, which are far less prone to bias than individuals and which dilute the influence of any one scientist with an axe to grind. The teams are deliberately assembled to avoid stacking the deck, and the reports themselves go through multiple rounds of peer review. That rigorous process is exactly why you can trust them and why people consider the IPCC to be the gold standard of what we know about the climate system. An assessment produced through a different process may well not be credible. You can even watch the consensus evolve across assessments. Take the attribution of warming. The 1990 IPCC report said the observed warming was broadly consistent with model predictions but also comparable to natural variability — in other words, we don’t know whether humans are responsible. By 1995, it concluded that the balance of evidence suggested a discernible human influence — a sentence only a committee could write, and one that barely commits to anything. By 2001, most of the warming over the previous 50 years was judged “likely” due to greenhouse gases; by 2007, “very likely”; by 2013, “extremely likely.” The 2023 report says essentially the same as 2013 — there’s not much stronger language available. So, to wrap up: science is our ultimate tool for deciphering the universe — the most successful method we’ve ever developed for determining what’s true and what isn’t. Our understanding is written into the peer-reviewed literature, so if you want to know what scientists think, that’s where to look. And for those of us who don’t speak nerd, scientific assessments are the Rosetta Stone — they translate nerd into English. Let me open the floor to questions. Thank you.
Global Live Entertainment Market Size/Share Worth USD 859 Billion by 2034 at a 5.4% CAGR: Custom Market Insights (Analysis, Outlook, Leaders, Report, Trends, Forecast, Segmentation, Growth, Growth Rate, Value)
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The work you can't always see: Beer is political, part 2
Recently I published a piece about beer, politics, and the question of who speaks up and who doesn’t. I meant every word of it. I still do. And then my inbox opened up. Cleveland Prost is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe I’ve been writing about beer since 2014. For most of that time, I kept things deliberately light — taproom profiles, new releases, the people behind the pints. Gradually, over years of building this thing, you gave me something I didn’t expect: permission. Permission to go deeper. To say what I actually saw in this industry and what I actually believed about it. That trust isn’t something I take lightly. It’s why that piece existed at all, and it’s why this one does too. I’m not walking anything back. But I want to go further. In that piece, I wrote that beer has never existed outside the system. That immigration policy affects who staffs breweries and harvests ingredients. That labor policy affects taproom workers. That civil rights policy affects who feels safe walking into a taproom. That “beer does not exist in a vacuum. The idea that it does is comforting. It is also false.” I believe that as much now as I did when I wrote it. But one idea came back at me, in different forms, over and over (from reader emails, comments, and conversations): that beer itself isn’t political — that it only becomes political when someone decides to make it that way. That what we’re really seeing is a choice by individuals to inject division into something that doesn’t inherently require it. It’s a comforting idea. It’s also wrong — and I think it’s worth being precise about why. That framing assumes that breweries operate outside the conditions shaping everything else. That politics is something you choose to bring into a room that was, until then, clean and neutral. That if you stay quiet, you stay clear of it. But the room was never neutral. It was never clean. Politics is already in the room. It’s in who walks through the door comfortably and who hesitates. It’s in whether a space can be used for organizing without fear. It’s in whether helping someone quietly might carry consequences you have to think carefully about in advance. It’s in who staffed the brewery, who harvested the grain, who can afford to be a regular. The idea that you opt out of all that by staying quiet is an illusion. You only change how visible your response to it is. This is, I realize, a hard thing to hear if you came to a beer newsletter for something lighter. I wrote recently that “beer, for me, has always felt like a refuge — a third place in an increasingly fractured world.” I meant that. I still do. But a refuge is not an escape from reality. It’s a place to gather strength to face it. Here’s what I actually missed — and what I want to correct. Multiple people in the industry reached out to me. I’m not naming them and I’m not identifying their businesses, because that’s not my call. If and when they want to be loud about what they’re doing, that agency belongs to them. What I can share is the substance of what they said, because it complicated something I presented too cleanly. The overall message: *You don’t know what we all are doing.* And they’re right. I don’t. One example involved a collaboration brewed quietly to support another business facing serious challenges in a whole different region, with proceeds directed toward solidarity, community, and keeping operations afloat. No announcement. It could have been broadcast widely. The point was never publicity. Another example involved logistical support for community efforts: organizing safe transportation, providing space for meetings on otherwise closed days, facilitating gatherings under difficult conditions. All of it happening while balancing real financial pressure and genuine concern for personal safety. None of what they described is a brewer “deciding to make beer political.” It’s people responding to the conditions around them — conditions that are already shaping who feels safe, who has access, who can gather, who needs help, and who has the capacity to offer it. Politics, again, already in the room. Already shaping choices. Whether anyone announced it or not. I’ve spent decades in taprooms, at barrel releases, at festivals, in back offices and brewing floors, talking to the people who built this industry from nothing. I know how much happens that never makes it onto social media. I know the owner who quietly comp’d a tab for someone having a crisis. The brewer who drove an hour to pick up a stranger who needed a safe ride. The taproom that stayed dark on a Tuesday so a community group could use the space without it becoming A Whole Thing. None of that gets a post. Most of it never will. So when I wrote recently about silence — when I said that “silence right now doesn’t feel neutral, it feels like complicity” — I was writing about what I could see. And I was right about what I saw. The public silence of breweries that have the platform, the stability, and frankly the safety to say something and choose not to? That still troubles me. I’m not softening that. But some of what I read as silence is actually something else entirely. It’s people doing the work with their hands instead of their phones. It’s people who are genuinely afraid — not of being canceled, but of real consequences for their families, their employees, their ability to keep the doors open at all. That deserves more than a footnote. It deserves to be named clearly. Here’s the tension I want to sit with honestly: public statements matter. They matter because people can’t rally around something they can’t see. Visibility creates awareness and solidarity. It helps people find each other. It tells someone standing outside your taproom door, uncertain whether they’ll be welcomed inside, something they need to know — or whether it’s even safe for them to be in public at all. That’s not performative. I wrote recently that the craft beer movement “was built on collective defiance. It was built on rejecting consolidation. On pushing back against homogeneity.” I believe that too. And I’ll extend it: breweries should be at least as loud about their values as they are when they drop a new seasonal. Your hazy IPA gets a full rollout — the label art, the tap handle photo, the countdown post. Human dignity deserves the same energy. Be as loud about human rights as you are about your beer. There is no reason those two things should require different levels of courage from you. But visibility isn’t the only form of courage. And not everyone can be visible right now without real consequences — financial, personal, sometimes physical. There are people in this industry doing hard, unglamorous, sometimes risky work in the background, and announcing it would compromise it or paint a target on someone who’s already stretched thin. That’s not silence as complicity. That’s operational discipline under pressure. What I want to push back on — clearly, not gently — is the idea that behind-the-scenes action and public visibility are in competition with each other. The person organizing quietly in the back room and the person posting a statement of solidarity on a Tuesday morning are both doing something real. We need both. We need the quiet infrastructure and we need the visible signal. We need people to know that this industry — at its best, at its most independent, and human — gives a fuck. I closed that piece with a question: “Reactive and fearful? Or clear and values-driven?” That question still stands. But having heard from you, I’d add a corollary: the values-driven path isn’t always the loudest one. Sometimes it’s a phone call and a recipe. Sometimes it’s a room made available on a closed Tuesday. Sometimes it’s a drive across town for someone who needed a safe ride home. All of it is political. All of it was always political. You don’t get to opt out of that — you only get to decide what you do with it. I’ve spent more than a decade writing about this industry because I believe it can be exactly that. I’ve been lucky enough to build an audience that lets me say so plainly. That’s a privilege I intend to use. The work is happening. Some of it you’ll see. Some of it you won’t. Support it either way. Cleveland Prost is a reader-supported publication covering beer and brewing across New York state. To receive new posts and support this work, consider becoming a free or paid subscriber. Cleveland Prost is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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