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Based on "The deep mystery physicists call “the problem of time” | Jim Al-Khalili: Full Interview" from Big Think Watch the original video

The Ghost in the Machine: Unraveling the Great Mystery of Time

We feel it in the graying of our hair, the frantic pace of a deadline, and the slow crawl of a rainy Sunday afternoon. To us, time is the most fundamental reality of existence—a river that flows relentlessly from a fixed past toward an uncertain future.

Yet, if you ask a physicist to show you this "flow" in the fundamental equations of the universe, they will come up empty-handed. In the world of math and particles, time is often reduced to a mere coordinate, a humble lowercase t that behaves more like a map reference than a rushing current.

"If you look up the 'problem of time' online, you’ll find various definitions," says Jim Al-Khalili, Emeritus Professor of Physics at the University of Surrey and author of On Time. "But it really boils down to four distinct problems: Does time flow? How do we reconcile quantum mechanics with relativity? What is special about 'now'? And where does the direction of time come from?"

In an age where we can synchronize atomic clocks to the billionth of a second, the fact that we still don’t know what time is remains the deepest mystery in science.

Manifest vs. Physical Time: The Dentist and the Party

The first hurdle in understanding time is separating our internal experience from external reality. Al-Khalili uses the term "manifest time"—a concept popularized by philosopher Craig Callender—to describe time as we perceive it.

We’ve all experienced the elasticity of manifest time. When you are five years old, the year between birthdays feels like an eternity because it represents a massive percentage of your total life experience. By fifty, years go by in a flash. Conversely, on a shorter scale, thirty minutes in a dentist’s waiting room with no phone can feel like hours, while thirty minutes at a lively party vanishes in an instant.

"At the party, you’re laying down new experiences, chatting, and taking in sensory input," Al-Khalili explains. "Yet that time goes by much more quickly than the time that drags when you're bored."

While our brains stretch and compress time based on emotion and memory, physics suggests a much more rigid structure. For centuries, following Isaac Newton, we believed in "Absolute Time"—a cosmic clock ticking away at a constant rate regardless of what was happening in the universe. But in 1905, Albert Einstein shattered that clock forever.

The Relativist’s Clock: Why Your Head is Older Than Your Feet

Einstein’s Special Theory of Relativity revealed that time is not a universal constant; it is relative to the observer. If you travel close to the speed of light, your clock slows down relative to someone standing still.

This isn't just a mathematical quirk; it's a physical reality proven by subatomic particles called muons. Created in the upper atmosphere, muons have a lifespan of only a fraction of a second—too short to reach the ground. Yet, because they travel at near-light speeds, their internal clocks slow down (time dilation), allowing them to survive long enough to be detected at Earth’s surface.

Einstein’s General Theory of Relativity added another layer: gravity also slows time. "Everyone who uses a smartphone or Google Maps is making use of the fact that time runs at different rates," says Al-Khalili. GPS satellites are further from Earth’s gravity, meaning their clocks tick slightly faster than those on the ground. To keep your navigation accurate, engineers must manually slow down the satellite clocks to stay in sync with Earth.

The implication is startling: because gravity is stronger closer to the Earth's center, your feet are technically younger than your head. The difference is infinitesimal, but it is real.

The Block Universe and the Illusion of "Now"

If time is relative, then the idea of a universal "Now" becomes impossible. If two stars explode at the same time from your perspective, an observer zooming past in a rocket might see one happen long before the other. Neither is wrong.

This leads many physicists to the "Block Universe" theory. Imagine the universe as a giant loaf of bread. Each slice represents a moment in time. In this view, the past, present, and future all exist simultaneously. Your birth is at one end of the loaf, and your death is at the other; both are equally "real" and eternally present within the four-dimensional structure of space-time.

"This idea is called Eternalism," says Al-Khalili. "All times coexist. Our consciousness is simply drifting along a 'world line' through this block."

This raises a troubling question about free will. If the future is already "there," waiting for us like a pre-recorded movie, do we actually have a choice in our actions? Al-Khalili describes himself as a "compatibilist." Even if the universe is deterministic and the future is set, the fact that we can never predict it from within the system gives us a functional version of free will. "I’m making free choices, and that’s good enough," he remarks.

The Quantum Vanishing Act

The "problem of time" reaches its peak when we try to merge the physics of the very large (Relativity) with the physics of the very small (Quantum Mechanics).

In the 1960s, physicists John Wheeler and Bryce DeWitt attempted to write a quantum equation for the entire universe. The result, known as the Wheeler-DeWitt equation, had a shocking feature: the variable for time (t) vanished completely. The equation describes a universe that simply is, without any reference to change or duration.

This has led some to suggest that time is an "emergent property," much like the "wetness" of water. You can’t find "wetness" in a single H2O molecule; it only emerges when trillions of molecules interact. Similarly, time might not exist at the most fundamental level of reality, only emerging when we zoom out to the macroscopic world.

The Arrow of Time: Why We Can’t Un-Spill Milk

If the fundamental laws of physics are "time-symmetric"—meaning they work just as well backward as forward—why does the real world only move in one direction? Why do batteries die, buildings crumble, and people age, but never the reverse?

This is the "Arrow of Time," usually attributed to the Second Law of Thermodynamics: entropy (disorder) always increases. A shuffled deck of cards will never spontaneously un-shuffle itself.

However, Al-Khalili points to a more modern explanation: Quantum Decoherence. In the quantum world, particles are "entangled" with their surroundings. As a system interacts with its environment, its "quantum-ness" leaks out and becomes irreversibly lost.

"Decoherence is regarded as the one truly irreversible process in nature," Al-Khalili argues. "I would argue that the arrow of time is baked into reality... due to quantum entanglement and decoherence increasing all the time."

Conclusion: Is Time Real?

While some philosophers and physicists argue that time is a stubborn illusion, Jim Al-Khalili leans toward its reality. If the direction of time is built into the way quantum particles interact with the world, then time itself must have a foundation.

We may be trapped within the river, unable to step onto the bank and view the flow objectively, but that doesn't make the water any less real. Whether time is a fundamental dimension of a frozen block universe or an emergent property of quantum entanglement, it remains the stage upon which the entire drama of existence is played out.

As Al-Khalili notes, we may never fully extract ourselves from time to see its true face, but by studying the way the universe ticks, we come closer to understanding our place within the "ever-changing present."

Based on "667. Here’s Why You Are Constantly Fighting Off Scammers | Freakonomics Radio" from Freakonomics Radio Network Watch the original video

The Billion-Dollar Meat Grinder: Inside the Global Scam Industry

In January, Chen Xi, a 38-year-old Chinese-born entrepreneur, was arrested in Cambodia and extradited to China. On the surface, Chen was the picture of success: one of the wealthiest men in Cambodia, a high-level government adviser, and the head of a massive real estate development firm. But beneath the veneer of legitimate business lay a darker reality. The U.S. government designated his holding company a transnational criminal organization, charging him with fraud and money laundering while seizing a staggering $15 billion in cryptocurrency.

Where did that money come from? According to U.S. prosecutors, Chen was a kingpin of "pig butchering"—a chillingly descriptive term for a scam where victims are "fattened up" with months of romantic or friendly attention before being "slaughtered" for their life savings.

This isn’t just a series of isolated crimes; it is a sophisticated, multi-billion-dollar global industry. In Cambodia alone, cybercrime is estimated to generate $19 billion annually—roughly half of the country’s GDP. In 2024, scammers in Southeast Asia stole an estimated $10 billion from Americans. To understand why your phone is buzzing with "wrong number" texts and your inbox is flooded with suspicious offers, you have to understand the brutal efficiency of the modern scam economy.

The Anatomy of an Industry

We often imagine scammers as lone hackers in dark basements. The reality is far more corporate. Modern scam operations, particularly those in Southeast Asia, function like Fortune 500 companies. They have HR departments, legal teams, marketing experts, and strict performance quotas for their "employees."

Disturbingly, many of the people sending those messages are victims themselves. "Thousands of workers fled [Chen’s compounds] after his arrest," notes the Freakonomics Radio team. "They had reportedly been trafficked to Cambodia and were being held against their will." These captives are forced to run "boiler rooms," engaging in "AB testing" on scam scripts to see which emotional triggers result in the highest payout.

"It is absolutely an industry," says Marty De Lima, a gerontologist at the University of Minnesota who studies the impact of fraud. "A very complex, always evolving, very competitive industry."

The Myth of the Vulnerable Senior

There is a persistent myth that scams primarily target the elderly and the technologically illiterate. While older adults do lose more money per incident—the median loss for those over 80 is $1,400 compared to $500 for those under 50—they are not the only targets.

"It’s a myth that older adults are more trusting or lack sophistication," De Lima explains. "Data shows that middle-aged adults report victimization at the highest frequency."

The type of scam often dictates the demographic:

The psychological toll is universal. De Lima describes scamming as "betrayal trauma." The loss of self-efficacy and the shattering of one's worldview often lead to a sense of hopelessness so deep that it can result in suicide—a connection that is tragically underreported.

Why Do Scams Look So Obvious?

We’ve all seen them: the "Nigerian Prince" who needs help moving an inheritance, or the email from a stranger offering a free Yamaha baby grand piano. To a discerning eye, these look like amateur hour. But there is a cold, economic logic to the typos and the far-fetched premises.

In a 2012 paper, Microsoft researcher Cormac Hurley asked: Why do Nigerian scammers say they are from Nigeria? The answer is filtering. Scammers don’t want to waste time on people who are skeptical. By using a premise that is obviously a scam, they ensure that only the most gullible individuals—those most likely to actually transfer money—respond. It’s a way to increase their "conversion rate" while minimizing the labor cost of chasing "leads" that won't pay out.

However, as AI enters the fray, this "obvious" phase is ending. "If you can have your AI do the next step of following up with semi-interested people, that’s not very costly," says De Lima. Scams are becoming more tailored, more professional, and harder to spot.

The Psychology of the Con: System 1 vs. System 2

Scammers are masters of human psychology, specifically the dual-process theory of the mind. Our brains operate in two modes: System 1 (fast, intuitive, emotional) and System 2 (slow, analytical, logical).

A scammer’s goal is to shut down your System 2. They do this through "emotional arousal," which can take two forms:

  1. High Positive Arousal: The promise of a windfall, a romantic connection, or a "ground floor" investment opportunity. This exploits our desires and greed.
  2. High Negative Arousal: The threat of arrest, a "seized" bank account, or a kidnapped relative. This exploits our fear.

When we are in a state of high emotion, we rely on "heuristics"—mental shortcuts. We trust a voice because it sounds like a loved one (often via AI voice cloning), or we comply because a caller ID says "Bank of America."

"Criminals will do anything they can to shut off our analytical processing," De Lima says. "They want us to go straight to those shortcuts and comply."

The AI Arms Race and the Myth of Privacy

We are entering a new era of fraud where "common sense" advice is becoming obsolete. Previously, experts told consumers to look for spelling errors or to ask for a video call. Today, AI can generate perfect prose and "deepfake" a video call in real-time.

One of the most sophisticated modern tactics involves exploiting the bureaucracy of legitimate institutions. A scammer might send a text pretending to be your bank, asking if you authorized a purchase. When you don’t click the link (as a "wise" consumer shouldn't) and instead call the bank’s real number, you might be put on hold. Scammers know this. They wait 30 minutes and call you back, faking the caller ID to look like the bank. Because you just tried to call them, your guard is down.

"Privacy is a myth," warns De Lima. "Our information is out there and available to the highest bidder. Criminals know our names, Social Security numbers, addresses, and mother’s maiden names."

Who is Responsible?

As the scale of fraud reaches hundreds of billions of dollars, the question of accountability has shifted from the scammers to the platforms that enable them.

Katie Daffen, a former Assistant Director at the FTC, notes that the commission is increasingly going after "facilitators." One example is the payment processor Paddle, which was charged with allowing scammers access to the credit card system despite internal warnings.

But the biggest elephant in the room is Big Tech. Leaked documents from Meta (the parent company of Facebook and Instagram) reportedly suggested that a significant portion of the company’s revenue comes from ads for scams. While Meta claims they "aggressively fight scams" and took down nearly 11 million accounts last year, critics argue they aren't doing enough.

"The technical capacity of these companies to identify and flag scams is there," says De Lima. "They’re making a calculated choice."

The Erosion of Social Trust

Perhaps the most insidious cost of the scam industry isn't financial—it’s the erosion of social trust. When every phone call is a potential threat and every email is a "pig butcher" in disguise, the fabric of human connection begins to fray.

Social trust in the U.S. has declined sharply over the last 40 years, and the constant barrage of fraud is a primary driver. We have become a society that refuses to answer the phone. Marty De Lima admits that even she, an expert in the field, recently missed a legitimate mandatory cybersecurity training because the email looked too much like a scam.

"This is the world that we’re now in," she says.

To protect yourself, the advice is simple but cynical: treat every unsolicited communication as a lie. Independently validate every claim. Don't use the phone numbers provided in messages; find them yourself. In the age of the billion-dollar meat grinder, the only way to avoid being "slaughtered" is to never let yourself be "fattened up" in the first place.

Based on "Dylan Patel — The Single Biggest Bottleneck to Scaling AI Compute" from Dwarkesh Patel Watch the original video

The Trillion-Dollar Silicon Ceiling: Inside the High-Stakes Race for AI Compute

In the quiet corridors of Silicon Valley and the sprawling industrial parks of Taiwan and the Netherlands, a number is being whispered that would have seemed like science fiction only two years ago: one trillion dollars.

That is the approximate scale of the capital expenditure (CapEx) currently being funneled into the global AI supply chain. The "Big Four"—Amazon, Meta, Google, and Microsoft—have forecasted a combined CapEx of roughly $600 billion this year alone. When you add the frantic fundraising of AI labs like OpenAI (recently raising $110 billion) and Anthropic ($30 billion), the financial gravity of the AI revolution begins to warp the entire global economy.

But as Dylan Patel, Chief Analyst at SemiAnalysis, explains, this isn't just a story about money. It’s a story about physical limits, "commitment issues" in the C-suite, and a tiny, specialized machine in the Netherlands that may ultimately decide the speed at which we reach Artificial General Intelligence (AGI).

The Gigawatt War: OpenAI vs. Anthropic

The most visible front of this war is being fought between the two leading AI labs: OpenAI and Anthropic. The divergence in their strategies is stark.

According to Patel, OpenAI has adopted a "YOLO" approach to compute. Early on, Sam Altman’s firm signed massive, long-term contracts for data centers and GPUs with Microsoft, Oracle, CoreWeave, and even SoftBank Energy. At the time, critics thought OpenAI was overextending, potentially risking bankruptcy if their revenue didn't materialize.

Anthropic, led by Dario Amodei, took the opposite path. "Dario was very conservative," Patel notes. "He didn't want to go crazy on compute because if revenue inflected at a different rate... he didn't want to go bankrupt."

This conservatism may have backfired. As AI revenue began to "moon," Anthropic found itself compute-constrained. To keep up with demand for models like Claude 3.5 Opus and Sonnet, Anthropic is now forced to acquire "last-minute" compute at a premium. While OpenAI locked in H100 GPUs at lower rates years ago, Anthropic is navigating a market where spot prices can reach $2.40 per hour for a chip that costs roughly $1.40 to operate.

"OpenAI has way more access to compute than Anthropic by the end of the year," Patel says. The result? Anthropic is having to turn to "neoclouds" and secondary providers, paying higher margins and navigating data center delays just to stay in the race.

The Alchian-Allen Effect: Why High Costs Favor Great Models

One of the most counterintuitive aspects of the current AI boom is that older GPUs are actually increasing in value. Usually, tech depreciates faster than a new car driven off the lot. But in the age of scarcity, an H100 is worth more today than it was three years ago.

Patel points to the Alchian-Allen Effect to explain the market's behavior. In economics, this theorem suggests that if you add a fixed cost (like a high price for compute) to two goods of different quality, people will shift their consumption toward the higher-quality good.

"If a Hopper GPU went from $2 to $3 an hour, the price differential between running a 'medium' model and a 'great' model shrinks," Patel explains. "The calculus is: I'm paying all this money for the compute anyway; I might as well pay slightly more to make sure it's the very best model."

This effect is driving all the revenue toward the "frontier" models. It also means that companies that signed five-year contracts years ago have locked in a massive competitive advantage. They are running the world’s most valuable software on "cheap" historical silicon, while newcomers are paying "AGI-pilled" prices for the same hardware.

The Hidden Bottlenecks: From Turbines to Tin Droplets

While the world focuses on chips, the real bottlenecks are often more mundane—and much harder to solve.

Google, for instance, recently "woke up" to the scale of the challenge. After seeing their Gemini revenue skyrocket to a $5 billion annual run rate in just months, the company shifted into overdrive. They aren't just buying chips; they are putting down deposits on power turbines for 2028 and 2029, securing power purchasing agreements (PPAs), and buying up land with existing electrical grid access.

But even if you have the land and the power, you still need the silicon. And the silicon supply chain is hitting a physical wall.

To understand the scale, Patel breaks down the "math of a gigawatt." To build one gigawatt of data center capacity using Nvidia’s upcoming "Rubin" chips, you need:

This leads to the ultimate gatekeeper of the AI era: ASML.

ASML: The 13.5-Nanometer Bottleneck

ASML, a Dutch company, is the only firm in the world capable of making Extreme Ultraviolet (EUV) lithography machines. These machines, which cost upwards of $400 million each, are the most complex devices ever built by humans.

The process is mind-boggling: inside the machine, a laser hits a droplet of molten tin twice. The first hit shapes the droplet; the second blasts it into a plasma that releases EUV light at a wavelength of 13.5 nanometers. This light is then reflected by the world's flattest mirrors (made by Zeiss) to "print" circuits onto silicon.

"ASML can make about 70 of these tools this year," Patel says. "Even under very aggressive expansion, they only get to a little over 100 by the end of the decade."

If Sam Altman wants to bring a gigawatt of compute online every week by 2030, he would need to secure roughly 25% of the entire global output of EUV machines. This is a tall order when Apple, Intel, and the mobile phone industry also need those same machines to survive.

The "AGI-Pilled" Gap

The strangest part of this trillion-dollar scramble is the disconnect between the buyers and the builders.

The AI labs (OpenAI, Anthropic, DeepMind) are "AGI-pilled"—they believe they are years, not decades, away from models that can automate most human cognitive labor. If they are right, a GPU isn't just a chip; it's a "worker" that can repay its own cost in a matter of months.

However, the companies that actually make the machines—ASML, TSMC, and the memory vendors—remain skeptical. They have lived through decades of "boom and bust" cycles in the semiconductor industry. They are hesitant to build $20 billion fabs that might sit empty if the AI bubble bursts.

"Constantly, we're told our numbers are way too high," Patel says of his firm’s projections. "And then when they're right, they say, 'Okay, but your next year's numbers are definitely too high.'"

This skepticism is the ultimate bottleneck. If the labs are right about the proximity of AGI, the world is drastically under-investing in the machinery required to build it. We are attempting to launch a digital god using a supply chain that is still worried about next year's smartphone sales.

As we approach 2030, the race for AI won't just be about who has the best code. It will be about who had the foresight to put a deposit on a tin-blasting laser in the Netherlands five years ago. In the trillion-dollar silicon war, the winners are those who realize that in a world of infinite software, the only thing that matters is the finite machine.

Based on "Under Secretary of War on Iran, Anthropic and the AI Battle Inside the Pentagon | The a16z Show" from a16z Watch the original video

Wartime Speed: Inside the Pentagon’s High-Stakes Race to Reclaim the AI Edge

In the quiet corridors of the Pentagon, a fundamental shift is occurring. For decades, the building operated at what insiders call "peacetime speed"—a lethargic rhythm of bureaucratic red tape, thousand-page requirement documents, and a handful of massive defense contractors. But according to the Department’s Chief Technology Officer, those days are over. The United States is currently facing the largest military buildup in human history, and the battlefield is no longer just about steel and gunpowder; it’s about silicon and software.

In a recent candid discussion on The a16z Show, the Under Secretary of Defense for Research and Engineering (often referred to as the Pentagon's CTO) laid out a bracing vision for the future of American Dynamism. From the "holy cow" moments involving commercial AI models to the chilling reality of vendor lock-in during active military operations, the message was clear: The Pentagon must adopt Silicon Valley’s "wartime" urgency, or risk falling behind an adversary that isn't waiting for a committee's approval.

The Ghost of the "Last Supper"

To understand why the Pentagon is struggling to modernize, one must look back to the early 1990s—a period the Under Secretary identifies as the beginning of the "peacetime speed" era. Following the Cold War, the Department of Defense held a famous meeting known as "The Last Supper." Military leaders told industry giants that the era of massive procurement and rapid innovation was over. They encouraged consolidation, telling companies to become dividend-payers and stock-buybackers rather than disruptors.

The result was a defense industrial base that shrank from dozens of competitors to just four or five "primes." While the U.S. rested on its laurels, China began a massive military expansion in the mid-2000s. "We’ve outsourced a lot of our key domestic production—critical minerals, batteries, supply chain components," the Under Secretary warned. "We looked up and realized we have a lot of catching up to do."

From 14 Priorities to 6: The Radical Simplification

When the Under Secretary took office, he found a department spread too thin, buried under 14 "critical" priority areas that hadn't changed in a decade. "Who can remember 14 things when you’re trying to motivate a workforce?" he asked.

In a move reminiscent of a Silicon Valley turnaround, he slashed the list to six. At the absolute top of that list: Applied AI.

The goal isn't just to build "killer robots," but to integrate AI as a "substrate"—a layer of intelligence that touches every facet of the military. He categorizes the AI mission into three distinct buckets:

  1. Enterprise Efficiency: Automating mundane administrative tasks for the department’s 3 million employees.
  2. Intelligence Augmentation: Using AI to sift through decades of siloed satellite imagery and data. "You take a human analyst and you increase their throughput by a thousand," he explained.
  3. Warfighting & Logistics: Using models to solve complex physics problems, plan fuel-efficient troop movements in contested environments, and run millions of combat simulations.

The results of this focus have been immediate. In just 90 days, the number of Department personnel using some form of AI jumped from 80,000 to over 1.2 million.

The "Holy Cow" Moment: The Conflict of Constitutions

The most provocative part of the discussion centered on the Pentagon’s relationship with "Frontier" AI companies like Anthropic and OpenAI. In the past, software was a tool the military bought and owned. Today, AI is often provided as a service with "Terms of Service" and "Corporate Constitutions."

The Under Secretary described a "holy cow" moment when reviewing contracts inherited from previous administrations. He discovered dozens of restrictions baked into the software. In theory, these commercial models—integrated into the most sensitive combat commands—could be "turned off" by the vendor if an operation violated a company’s internal ethical guidelines.

"The software's 'soul' or 'constitution'—which is not the U.S. Constitution—cannot be dictating our command and control environment," he argued. "We cannot have a situation where a model could just stop in the middle of an operation and put lives at risk because a vendor decided it didn't like how the tool was being used."

This tension became visceral following the Maduro raid, a highly successful military operation. A senior executive from a primary AI vendor reportedly questioned whether their software was used during the raid, expressing hesitation about its involvement.

"When a company says, 'Hey, was our software used there because we’re not sure we’d like that,' a chill goes up your spine," the Under Secretary said. "It’s like a stranger saying they saw your kid at school. You realize you are 'single-threaded' on a vendor whose values might not align with national security."

The "Elon Model" and the Regulatory Moses

To fix this, the Pentagon is attempting to "move the debris" of bureaucracy. The Under Secretary is pushing for a shift from "Cost-Plus" contracts—which reward companies for taking longer and spending more—to "Firm-Fixed-Price" contracts.

He calls this the "Elon Model," citing SpaceX’s success. Instead of a thousand-page Request for Proposal (RFP) that dictates exactly how to build a bolt, the Pentagon is moving toward simple requirements: I need a missile that goes this far, in this environment, with this payload. You figure out how to build it.

This shift is designed to open the door for startups. However, the Under Secretary issued a challenge to the "American Dynamism" movement: Innovation isn't enough. Startups must learn the "old world" muscle of mass production. "The primes have an advantage in manufacturing at scale. Startups need to build the factories, the quality testing, and the supply chains to cross that chasm."

A Call to Service

The Under Secretary’s journey to the Pentagon wasn't a traditional one. A successful tech executive and immigrant whose first language was Arabic, he felt a pull toward public service after selling his company, Tellme Networks, to Microsoft.

He views the current moment as a "galvanizing" one for the tech industry, similar to the 2018 "Project Maven" controversy at Google. While that moment saw some employees protest military contracts, it also birthed a new generation of patriotic founders who want to ensure the U.S. maintains its technological edge.

"Our system doesn’t come for free," he concluded. "We need builders, people who care, and people who are willing to sacrifice. We need patriots to come and do these things every now and again because industry has the best brains, but the country needs those brains to protect our way of life."

As the AI battle inside the Pentagon intensifies, the goal remains singular: ensuring that when the next "wartime" moment arrives, the United States is moving at the speed of the future, not the pace of the past.

Based on "Louise Erdrich on Her New Story Collection and the Mystery of Writing" from New York Times Podcasts Watch the original video

The Art of the Army Crawl: Louise Erdrich on the Mystery of the Written Word

In the world of contemporary American literature, few figures loom as large or as prolific as Louise Erdrich. Since her 1984 debut Love Medicine, she has navigated nearly every corner of the literary landscape, from haunting poetry to National Book Award-winning fiction. Yet, despite her decades of acclaim and a Pulitzer Prize to her name, Erdrich remains a writer who views her own process not as a masterclass in control, but as a slow, often bewildering "army crawl" through the undergrowth of her own imagination.

In a recent conversation with Gilbert Cruz on the New York Times Book Review podcast, Erdrich peeled back the curtain on her latest collection, Python’s Kiss, and shared the idiosyncratic, often physical ways she brings her stories to life.

The Eight-Year Short Story

Perhaps the most striking revelation of Erdrich’s process is the sheer timeline of her shorter works. One story in the new collection, "The Love of My Days," is a mere ten pages long, yet it took eight years to complete. For Erdrich, this isn't a matter of writer’s block, but of a quiet, persistent gestation.

"I have a set of words just randomly pop up," she explains. "I keep notebooks. I write something down, and sometimes something keeps going for a while, but it always fizzles out." She describes these fragments as "nuggets" that occasionally lose their energy and are tucked away—sometimes for years—only to resurface when the writer herself has changed.

She describes the completion of these stories not as a sprint, but as a slow movement across a landscape. "It just crept along... army crawled along the forest floor somehow until it got to the end." This patience isn't a disciplined choice, she insists, but a byproduct of her own curiosity. She writes to amuse herself, returning to a draft only when a single line or paragraph hooks her back into the narrative’s world.

When the Story "Announces Itself"

One of the eternal questions for any multi-genre writer is how to decide whether an idea belongs in a poem, a children’s book, or a sprawling novel. For Erdrich, the decision is rarely hers to make.

"It announces itself," she says. "I don’t have a way of changing it if it’s not going to be what it wants to be." If a narrative refuses to stop, it becomes a novel; if it evolves toward a resolution within twenty pages, it remains a story. This lack of authorial ego is central to her philosophy. She views writing as a process that happens outside of her conscious will—a necessity for someone who describes herself as "not a very in control person" in her daily life.

Writing, for Erdrich, is her primary mode of processing the world. It began in the fifth grade as a way to handle being "overwhelmed" by the ending of the original Planet of the Apes. Growing up in North Dakota—a state she describes as a "national sacrifice area" due to its hundreds of underground ICBM silos—the film’s nuclear subtext resonated with a terrifying clarity. That early anxiety fueled a lifelong habit of keeping diaries, which she admits began as "cries of woe" before evolving into the rich repositories of detail that now inform her fiction.

The Physicality of the Page

While many imagine a writer’s work as a purely intellectual exercise, Erdrich’s method is surprisingly physical. When she finds herself "off" or stuck, she literally takes to the floor.

"I have to throw everything on the floor—all these notebooks, these crazy notes—and I have to crawl through them and put them in order," she says. This "physicalizing of the intellectual act" allows her to see the architecture of a story in a way a computer screen cannot provide. It is a humble image: one of our greatest living writers on her hands and knees, sorting through scraps of paper to find the missing beginning of a tale.

This humility extends to her view of her own successes. When The Night Watchman—a novel based on her grandfather’s fight against Native American termination policies—won the Pulitzer Prize, Erdrich famously remarked that the award didn't go to her, but to the book and her grandfather. As she has aged, she says her ego has retreated, allowing her to embrace a "simplicity" in her storytelling that she lacked in her earlier, more self-conscious years.

A Life Built on Letters

Erdrich’s literary DNA is rooted in a family of prolific letter writers. Her father would write long, exaggerated letters about the mundane—turning her mother’s canning hobby into a tall tale about canning toads and slugs. He even undertook a project to write a limerick for every single town in North Dakota.

This tradition of written connection shaped Erdrich’s understanding of character and voice. Her grandfather’s letters from his time as tribal chairman for the Turtle Mountain Chippewa became the foundational "personality" for the protagonist of The Night Watchman. For Erdrich, the archive of family letters is more than just a memory; it is a "treasure" that proves the power of the written word to preserve a soul.

The Evolution of the Indigenous Voice

Beyond her own writing, Erdrich is a fierce advocate for other authors. Since 2001, she has owned Birchbark Books, an independent bookstore in Minneapolis. In the twenty-five years since its opening, she has witnessed a tectonic shift in the literary landscape.

"When I first started, there was only one set of shelves that had any Native titles on them," she recalls. "And they were mostly by non-Native authors about Native people." Today, the store could be filled entirely with Indigenous voices. She points to the "explosion" of Native writing as a fulfillment of a prophecy: that once writers from different tribes began to tell their unique stories, the world would realize the vast, diverse richness of the Indigenous experience.

When asked for recommendations, she points to James Welch’s 1974 novel Winter in the Blood, calling it a "beautiful, bleak, short, funny, intensely personal book" that she returns to repeatedly.

The Mystery of the "Other World"

Despite her immense body of work, Erdrich maintains that the act of creation remains a mystery to her—and she prefers it that way. She often looks back at her own handwriting in old notebooks and feels a sense of detachment, as if the words were written by someone else.

"I’m, in my real life, a boring person," she claims with a laugh. "I don’t really have a magical personality, but the stories write themselves." She believes that while research and thought are essential, there is a piece of art that belongs to "some other world, some other entity."

As the interview concluded, Erdrich offered a glimpse into her current reading habits, which range from the ancient and meditative (Sei Shōnagon’s The Pillow Book for insomnia) to the provocatively modern. On her shelf currently sits a book titled Make the Golf Course a Public Sex Forest—a compendium of essays regarding a local Minneapolis land-use controversy.

It is this blend of the high-brow and the earthy, the historical and the speculative, the Pulitzer-winning and the "army-crawling" that defines Louise Erdrich. She remains a writer who is less interested in being a "literary figure" than she is in following the mystery of the next sentence, wherever it might lead her on the forest floor.