『Let's Know Things』のカバーアート

Let's Know Things

Let's Know Things

著者： Colin Wright
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 A calm, non-shouty, non-polemical, weekly news analysis podcast for folks of all stripes and leanings who want to know more about what's happening in the world around them. Hosted by analytic journalist Colin Wright since 2016.

letsknowthings.substack.comColin Wright 政治・政府
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  • Workplace Automation

    Workplace Automation
    2025/10/28
    This week we talk about robots, call center workers, and convenience stores.We also discuss investors, chatbots, and job markets.Recommended Book: The Fourth Consort by Edward AshtonTranscriptThough LLM-based generative AI software, like ChatGPT, Gemini, and Claude, are becoming more and more powerful by the month, and offering newfangled functionality seemingly every day, it’s still anything but certain these tools, and the chatbots they power, will take gobs of jobs from human beings.The tale that’s being told by upper-management at a lot of companies makes it seem like this is inevitable, though there would seem to be market incentives for them to both talk and act like this is the case.Companies that make new, splashy investments in AI tech, or which make deals with big AI companies, purporting to further empower their offerings and to “rightsize” their staff as a consequence, tend to see small to moderate bumps in their stock price, and that’s good for the execs and other management in those companies, many of whom own a lot of stock, or have performance incentives related to the price of their stock built into their larger pay package.But often, not always, but quite a lot of the time, the increased effectiveness and efficiencies claimed by these higher-ups after they go on a firing spree and introduce new AI tools, seem to be at least partly, and in some cases mostly attributable to basically just threatening their staff with being fired in a difficult labor market.When Google executives lay off 5 or 10% of their staff on a given team, for instance, and then gently urge those who survived the cull to come to the office more frequently rather than working from home, and tell them that 60 hours a week is the sweet spot for achieving their productivity goals, that will tend to lead to greater outputs—at least for a while. Same as any other industry where blood has been drawn and a threat is made if people don’t live up to a casually stated standard presented by the person drawing that blood.Also worth mentioning here is that many of the people introducing these tools, both into their own companies and into the market as a whole, seem to think most jobs can be done by AI systems, but not theirs. Many executives have outright said that future businesses will have a small number of people managing a bunch of AI bots, and at least a few investors have said that they believe most jobs can be automated, but investing is too specialized and sophisticated, and will likely remain the domain of clever human beings like themselves.All of which gestures at what we’re seeing in labor markets around the globe right now, where demands for new hires are becoming more intense and a whole lot of low-level jobs in particular are disappearing entirely—though in most cases this is not because of AI, or not just, but instead because of automation more broadly; something that AI is contributing to, but something that is also a lot bigger than AI.And that’s what I’d like to talk about today. The rapid-speed deployment, in some industries and countries, at least, of automated systems, of robots, basically, and how this is likely to impact the already ailing labor markets in the places that are seeing the spearpoint of this deployment.—Chatbots are AI tools that are capable of taking input from users and responding with often quite human-sounding text, and increasingly, audio as well.These bots are the bane of some customers who are looking to speak to a human about some unique need or problem, but who are instead forced to run a gauntlet of AI-powered bots. The interaction often happens in the same little chat window through which they’ll eventually, if they say the right magic words, reach a human being capable of actually helping them. And like so many of the AI innovations that have been broadly deployed at this point, this is a solution that’s generally hated by customers, but lauded by the folks who run these companies, because it saves them a lot of money if they can hire fewer human beings to handle support tickets, even if those savings are the result of most people giving up before successfully navigating the AI maze and reaching a human customer support worker.In India right now, the thriving call center industry is seeing early signs of disruption from the same. IT training centers, in particular, are experimenting with using audio-capable AI chatbots instead of human employees, in part because demand is so high, but also, increasingly, because doing so is cheaper than hiring actual human beings to do the same work.One such company, LimeChat, recently said that it plans to cut its employee base by 80% in the near-future, and if that experiment is successful, this could ripple through India’s $283 billion IT sector, which accounts for 7.5% of India’s GDP. Hiring growth in this sector already collapsed in 2024 and 2025, and again, while this shift seems to be pretty good for the ...
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    16 分
  • Circular Finance

    Circular Finance
    2025/10/21
    This week we talk about entanglements, monopolies, and illusory money.We also discuss electrification, LLMs, and data centers.Recommended Book: The Extinction of Experience by Christine RosenTranscriptOne of the big claims about artificial intelligence technologies, including but not limited to LLM-based generative AI tech, like ChatGPT, Claude, and Gemini, is that they will serve as universal amplifiers.Electricity is another universal amplifier, in that electrifying systems allows you to get a lot more from pretty much every single thing you do, while also allowing for the creation of entirely new systems.Cooking things in the kitchen? Much easier with electricity. Producing things on an assembly line? The introduction of electricity allows you to introduce all sorts of robotics, measuring tools, and safety measures that would not have otherwise been available, and all of these things make the entire process safer, cheaper, and a heck of a lot more effective and efficient.The prime argument behind many sky-high AI company valuations, then, is that if these things evolve in the way they could evolve, becoming increasingly capable and versatile and cheap, cooking could become even easier, manufacturing could become still faster, cheaper, and safer, and every other aspect of society and the economy would see similar gains.If you’re the people making AI, if you own these tools, or a share of the income derived from them, that’s a potentially huge pot of money: a big return on your investment. People make fortunes off far more focused, less-impactful companies and technologies all the time, and being able to create the next big thing in not just one space, but every space? Every aspect of everything, potentially? That’s like owning a share of electricity, and making money every time anyone uses electricity for anything.Through that lens, the big boom in both use of and investment in AI technologies maybe shouldn’t be so surprising. This represents a potentially generational sea-change in how everything works, what the economy looks like, maybe even how governments are run, militaries fight, and so on. If you can throw money into the mix, why wouldn’t you? And if that’s the case, the billions upon billions of dollars sloshing around in this corner of the tech world make a lot of sense; it may be curious that there’s not even more money being invested.Belief in that promise is not universal, however.A lot of people see these technologies not as the next electricity, but maybe the next smartphone, or perhaps the next SUV.Smartphones changed a whole lot about society too, but they’re hardly the same groundbreaking, omni-powerful upgrade that electricity represents.SUVs, too, flogged sales for flailing car companies, boosting their revenues at a moment in which they desperately needed to sell more vehicles to survive. But they were just another, more popular model of what already came before. There’s a chance AI will be similar to that: better software than came before, for some people’s use-cases—but not revolutionary, not groundbreaking even on the scale of pocketable phone-computers.What I’d like to talk about today are the peculiar economics that seem to be playing a role in the AI boom, and why many analysts and financial experts are eyeballing these economics warily, worrying about what they maybe represent, and possibly portend.—The term ‘exuberance,’ in the context of markets, refers to an excitement among investors—sometimes professional investors, sometimes casual investors, sometimes both—about a particular company, technology, or financial product type.The surge in interest and investment in cryptoassets during the height of the COVID-19 pandemic, for instance, including offshoot products like NFTs, was seemingly caused by a period of exuberance, sparked by the novelty of the product, the riches a few lucky insiders made off these products, and the desire by many people—pros and consumer-grade investors—to get in on that action, at a moment in which there wasn’t as much to do in the world as usual.Likewise, the gobs of money plowed into early internet companies, and the money thrown at companies laying fiberoptic cable for the presumed boom in internet customers, were, in retrospect, at least partly the consequence of irrational exuberance.In some cases these investors were just too early, as was the case with those cable-laying companies—the majority of them going out of business after blowing through a spectacular amount of money in a short period of time, and not finding enough paying customers to fund all that expansion—in others it was the result of sky-high valuations that were based on little beyond the exuberance of investors who probably should have known better, but who couldn’t get past their fear of missing out on the next big thing.In that latter case, that flow of money into early dotcom startups did fund a few winners that survived the ...
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    16 分
  • Tariff Leverage

    Tariff Leverage
    2025/10/14
    This week we talk about trade wars, TACO theory, and Chinese imports.We also discuss negotiation, protectionism, and threat spirals.Recommended Book: More Than Words by John WarnerTranscriptIn January of 2018, then first-term US President Trump announced a slew of tariffs and trade barriers against several countries, including Canada, Mexico, and those in the European Union.The most significant of these new barriers and tariffs were enacted against China, though, as Trump had long claimed that China, the US’s most important trade partner by many measures, was taking advantage of the US market; a claim that economists tepidly backed, as while some of the specifics, like those related to intellectual property theft on the part of China, were pretty overt, the Chinese government fairly brazenly gobbling up IP and technology from US companies that do business in the country before hobbling those US interests in China and handing that IP and technology off to their own, China-born copies, claims about a trade deficit were less clear-cut—most of those sorts of claims seemed to be the result of a misunderstanding about how international trade works.That said, Trump had made a protectionist stance part of his platform, so he kicked off his administration by imposing a package of targeted tariffs against specific product categories from China, including things like solar panels and washing machines. Those were followed by more tariffs on steel and aluminum—from a lot of countries, not just China—and this implementation of trade barriers between the US and long-time trade partners, which had mostly enjoyed barrier-free trade up till that point, kicked off a trade war, with the Trump administration announcing, out of nowhere, new tariffs or limitations, and the country on the pointy end of that new declaration announcing their own counter, usually something the US sells to their country, while in the background, both countries tried to negotiate new trade terms on the down-low.There was a lot of tit-for-tatting in those first couple years of the first Trump administration, and they led to a lot of negotiations between the US government and these foreign governments, which in turn led to the lifting of many such barriers, though the weaponization of barriers continued, with the administration, for instance, announcing a tariff on all imports from Mexico until the Mexican government was able to halt all illegal immigration coming into the US; negotiation ended that threat, too, but this early salvo upset a lot of the US’s long-time allies, while also making it clear that Trump intended to open negotiations with these sorts of threats, whenever possible—which had the knock-on effect of everyone taking the threats pretty seriously, as they were often incredibly dangerous to specific industries, while also taking them less seriously because it was obvious they were intended to be a negotiating tactic.When Trump left office, a bunch of international relationships had been scarred by this approach to trade deals, and when Biden replaced him, he dropped most of the new tariffs against long-time allies, but kept most of the China tariffs in place, especially those related to green technologies like electric vehicles and semiconductors, the local-made versions of which were becoming a big focus for the Biden administration. The administration then went on to expand upon those tariffs, against China, in some cases.What I’d like to talk about today is how this approach to trade protectionism and negotiation has ballooned under the second Trump administration, and what a new threat against China by Trump might mean for how the relationship between these two countries evolves, moving forward.—Trump’s second administration opened with an executive order that declared a national emergency, claiming that the Chinese were trafficking drugs, especially synthetic opioids like fentanyl, into the US, and that this allowed criminals to profit from destroying the lives of US citizens.This declaration allowed him to unleash a flurry of tariffs against China, first imposing 10% on all Chinese imports, then increasing that to 20% in March of 2025.China retaliated, imposing tariffs of 15% on mostly US energy products, like coal and natural gas, and on some types of agricultural machines, while also engaging in some legal pressure against US companies, like Google. They followed this up with tariffs against meat and dairy products, and suspended US lumber import rights, and disallowed three US firms from selling soybeans to China.The US reciprocated, and China reciprocated back. There was a period of spiraling broad tariffs and import bans in the mid-2025 between the US and China, which led to an aggregate baseline tariff on Chinese imports of 104%, which was followed with an aggregate Chinese baseline tariff against US goods of 84%. The US then upped theirs to 145%, and China raised theirs to 125%.Again, vital to ...
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    16 分
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