The Rip Current with Jacob Ward

It’s a very weird Monday back from the holidays. While most of us were shaking off jet lag and reminding ourselves who we are when we’re not sleeping late and hanging with family, the world woke up to a piece of news this weekend that showed no one in power learned a goddamn thing in history class: the United States has rendered Venezuela’s president to New York, and powerful people are openly fantasizing about “fixing” a broken country by taking control of its oil.This isn’t a defense of Nicolás Maduro. He presided over the destruction of a nation sitting on the world’s largest proven oil reserves. Venezuela’s state now barely functions beyond preserving its own power. The Venezuelans I’ve spoken with have a wide variety of feelings about an incompetent dictator being arrested by the United States.But what’s clear is that anyone who has read anything knows that the history of oil grabs is a history of financial disaster. So when I hear confident talk about oil revenues flowing back to the U.S., I don’t hear a plan. I hear the opening chapter of a time-honored financial tragedy that’s been repeated again and again, even in our lifetimes.Let’s put aside the moral horror of military invasion and colonial brutality, and just focus on whether the money ever actually flows back to the invader. Example after example shows it doesn’t: Iraq was supposed to stabilize energy markets. Instead, it delivered trillions in war costs, higher deficits, and zero leverage over oil prices. Britain’s attempt to hang onto the Suez Canal ended with a humiliating retreat, an IMF bailout, and the end of its time as a superpower. France’s war in Algeria collapsed its government. Dutch oil extraction in Nigeria boomeranged back home as lawsuits, environmental liability, and reputational ruin.Oil empires all make the same mistake: they think they can nationalize the upside while outsourcing the risk. In reality, profits stay local or corporate. Costs always come home. And we’re about to learn it all over again.Read more at TheRipCurrent.com.

Happy New Year! I’ve been off for the holiday — we cranked through a bake-off, a dance party, a family hot tub visit, and a makeshift ball drop in the living room of a snowy cabin — and I’m feeling recharged for (at least some portion of) 2026. So let’s get to it.I woke to reports that “safeguard failures” in Elon Musk’s Grok led to the generation of child sexual exploitative material (Reuters) — a euphemism that barely disguises how awful this is. I was on CBS News to talk about it this morning, but I made the point that the real question isn’t how did this happen? It’s how could it not?AI systems are built by vacuuming up the worst and best of human behavior and recombining it into something that feels intelligent, emotional, and intimate. I explored that dynamic in The Loop — and we’re now seeing it play out in public, at scale.The New York Times threw a question at all of us this morning: Why Do Americans Hate AI? (NYT). One data point surprised me: as recently as 2022, people in many other countries were more optimistic than Americans when it came to the technology. Huh! But the answer to the overall question seems to signal that we’ve all learned something from the social media era and from the recent turn toward a much more realistic assessment of technology companies’ roles in our lives: For most people, the benefits are fuzzy, while the threats — to jobs, dignity, and social stability — are crystal clear.Layer onto that a dated PR playbook (“we’re working on it”), a federal government openly hostile to regulation, and headlines promising mass job displacement, and the distrust makes a lot of sense.Of course, this is why states are stepping in. The rise of social media and the simultaneous correlated crisis in political discord, health misinformation, and depression rates left states holding the bag, and they’re clearly not going to let that happen again. California’s new AI laws — addressing deepfake pornography, AI impersonation of licensed professionals, chatbot safeguards for minors, and transparency in AI-written police reports — are a direct response to the past and the future.But if you think the distaste for AI’s influence is powerful here, I think we haven’t even gotten started in the rest of the world. Here’s a recent episode that has me more convinced of it than ever: a stadium in India became the scene of a violent protest when Indian football fans who’d paid good money for time with Lionel Messi were kept from seeing the soccer star by a crowd of VIPs clustered around him for selfies. The resulting (and utterly understandable) outpouring of anger made me think hard about what happens when millions of outsourced jobs disappear overnight. I think those fans’ rage at being excluded from a promised reward, bought with the money they work so hard for, is a preview.So yes — Americans distrust AI. But the real question is how deep those feelings go, and how much unrest this technology is quietly banking up, worldwide. That’s the problem we’ll be reckoning with all year long.

Okay, honest admission here: I don’t fully know what I think about this topic yet. A podcast producer (thanks Nancy!) once told me “let them watch you think out loud,” and I’m taking her to heart — because the thing I’m worried about is already happening to me.Lately, I’ve been leaning hard on AI tools, God help me. Not to write for me — a little, sure, but for the most part I still do that myself — but to help me quickly get acclimated to unfamiliar worlds. The latest unfamiliar world is online marketing, which I do not understand AT ALL but now need to master to survive as an independent journalist. And here’s the problem: the advice these systems give isn’t neutral, because first of all it’s not really “advice,” it’s just statistically relevant language regurgitated as advice, and second, because it just vacuums up the language wherever it can find it, its suggestions come with online values baked in. I know this — I wrote a whole fucking book about it — but I lose track of it in my desperation to learn quickly.I’m currently trying to analyze who it is that follows me on TikTok, and why, so I can try to port some of those people (or at least those types of people) over to Substack and YouTube, where one can actually make a living filing analysis like this. One of the metrics I was told to prioritize? Disagreement in the comments. Not understanding, learning, clarity, the stuff I’m after in my everyday work. Fighting. Comments in which people want to argue with me are “good,” according to ChatGPT. Thoughtful consensus? Statistically irrelevant.Here’s the added trouble. It’s one thing to read that and filter out what’s unhelpful. It’s another thing to do so in a world where all of us are supposed to pretend we had this thought ourselves. AI isn’t just helping us work faster. It’s quietly training us to behave differently — and to hide how that training happens. We’re all pretending this output is “ours,” because the unspoken promise of AI right now is that you can get help and still take the credit. (I believe this is a fundamental piece of the marketing that no one’s saying out loud, but everyone is implying.) And the danger isn’t just dishonesty toward others. It’s that we start believing our own act. There’s a huge canon of scientific literature showing that lying about a thing causes us to internalize the lie over time. The Harvard psychologist Daniel Schachter wrote a sweeping review of the science in 1999 entitled “The Seven Sins of Memory,” in which he synthesized a range of studies that showed that memory is us building a belief on the prior belief, not drawing on a perfect replay of reality, and that repetition and suggestion can implant or strengthen false beliefs that feel subjectively true. Throw us enough ideas and culturally condition us to hide where we got them, and eventually we’ll come to believe they were our own. (And to be clear, I knew a little about the reconstructive nature of memory, but ChatGPT brought me Schachter’s paper. So there you go.) What am I suggesting here? I know we’re creating a culture where machine advice is passed off as human judgment. I don’t know whether the answer is transparency, labeling, norms, regulation, or something else entirely. So I guess I’m starting with transparency.In any event, I do know this: lying about how we did or learned something makes us less discerning thinkers. And AI’s current role in our lives is built on that lie.Thinking out loud. Feedback welcome. Thanks!

Here’s one I truly didn’t see coming: the Trump administration just made the most scientifically meaningful shift in U.S. marijuana policy in years.No, weed isn’t suddenly legal everywhere. But moving marijuana from Schedule I — alongside heroin — to Schedule III is a very big deal. That single bureaucratic change cracks open something that’s been locked shut for half a century: real research.For years, I’ve covered the strange absurdities of marijuana science in America. If you were a federally funded researcher — which almost every serious scientist is — you weren’t allowed to study the weed people actually use. Instead, you had to rely on a single government-approved grow operation producing products that didn’t resemble what’s sold in dispensaries. As a result, commercialization raced ahead while our understanding lagged far behind.That’s how we ended up with confident opinions, big business, and weak data. We know marijuana can trigger severe psychological effects in a meaningful number of people. We know it can cause real physical distress for others. What we don’t know — because we’ve blocked ourselves from knowing — is who’s at risk, why, and how to use it safely at scale.Meanwhile, the argument that weed belongs in the same category as drugs linked to violence and mass death has always collapsed under scrutiny. Alcohol, linked to more than 178,000 deaths per year in the United States alone, does far more damage, both socially and physically, yet sits comfortably in legal daylight.If this reclassification sticks, the excuse phase is over. States making billions from legal cannabis now need to fund serious, independent research. I didn’t expect this administration to make a science-forward move like this — but here we are. Here’s hoping we can finish the job and finally understand what we’ve been pretending to regulate for decades.Covering earlier regulatory changes for Al Jazeera in 2016...

The United States has a split personality when it comes to AI data centers. On the one side, tech leaders (and the White House) celebrate artificial intelligence as a symbol of national power and economic growth. But politicians from Bernie Sanders to Ron DeSantis point out that when it shows up in our towns, it drains water, drives up electricity prices, and demands round-the-clock power like an always-awake city.Every AI prompt—whether it’s wedding vows or a goofy image—fires up racks of servers that require enormous amounts of electricity and water to stay cool. The result is rising pressure on local water supplies and power grids, and a wave of protests and political resistance across the country. I’m covering that in today’s episode, and you can read the whole report over at Hard Reset.